WorldWideScience

Sample records for biomedical image retrieval

  1. Biomedical image retrieval using microscopic configuration with ...

    Indian Academy of Sciences (India)

    G DEEP

    2018-03-10

    Mar 10, 2018 ... The selection of feature descriptors affects the image .... Example of obtaining LBP for 3 9 3 neighbourhoods (adopted from Ojala et al [9]). 20 Page 2 of 13 ...... Directional binary wavelet patterns for biomedical image indexing ...

  2. A robust pointer segmentation in biomedical images toward building a visual ontology for biomedical article retrieval

    Science.gov (United States)

    You, Daekeun; Simpson, Matthew; Antani, Sameer; Demner-Fushman, Dina; Thoma, George R.

    2013-01-01

    Pointers (arrows and symbols) are frequently used in biomedical images to highlight specific image regions of interest (ROIs) that are mentioned in figure captions and/or text discussion. Detection of pointers is the first step toward extracting relevant visual features from ROIs and combining them with textual descriptions for a multimodal (text and image) biomedical article retrieval system. Recently we developed a pointer recognition algorithm based on an edge-based pointer segmentation method, and subsequently reported improvements made on our initial approach involving the use of Active Shape Models (ASM) for pointer recognition and region growing-based method for pointer segmentation. These methods contributed to improving the recall of pointer recognition but not much to the precision. The method discussed in this article is our recent effort to improve the precision rate. Evaluation performed on two datasets and compared with other pointer segmentation methods show significantly improved precision and the highest F1 score.

  3. A novel biomedical image indexing and retrieval system via deep preference learning.

    Science.gov (United States)

    Pang, Shuchao; Orgun, Mehmet A; Yu, Zhezhou

    2018-05-01

    The traditional biomedical image retrieval methods as well as content-based image retrieval (CBIR) methods originally designed for non-biomedical images either only consider using pixel and low-level features to describe an image or use deep features to describe images but still leave a lot of room for improving both accuracy and efficiency. In this work, we propose a new approach, which exploits deep learning technology to extract the high-level and compact features from biomedical images. The deep feature extraction process leverages multiple hidden layers to capture substantial feature structures of high-resolution images and represent them at different levels of abstraction, leading to an improved performance for indexing and retrieval of biomedical images. We exploit the current popular and multi-layered deep neural networks, namely, stacked denoising autoencoders (SDAE) and convolutional neural networks (CNN) to represent the discriminative features of biomedical images by transferring the feature representations and parameters of pre-trained deep neural networks from another domain. Moreover, in order to index all the images for finding the similarly referenced images, we also introduce preference learning technology to train and learn a kind of a preference model for the query image, which can output the similarity ranking list of images from a biomedical image database. To the best of our knowledge, this paper introduces preference learning technology for the first time into biomedical image retrieval. We evaluate the performance of two powerful algorithms based on our proposed system and compare them with those of popular biomedical image indexing approaches and existing regular image retrieval methods with detailed experiments over several well-known public biomedical image databases. Based on different criteria for the evaluation of retrieval performance, experimental results demonstrate that our proposed algorithms outperform the state

  4. Annotating image ROIs with text descriptions for multimodal biomedical document retrieval

    Science.gov (United States)

    You, Daekeun; Simpson, Matthew; Antani, Sameer; Demner-Fushman, Dina; Thoma, George R.

    2013-01-01

    Regions of interest (ROIs) that are pointed to by overlaid markers (arrows, asterisks, etc.) in biomedical images are expected to contain more important and relevant information than other regions for biomedical article indexing and retrieval. We have developed several algorithms that localize and extract the ROIs by recognizing markers on images. Cropped ROIs then need to be annotated with contents describing them best. In most cases accurate textual descriptions of the ROIs can be found from figure captions, and these need to be combined with image ROIs for annotation. The annotated ROIs can then be used to, for example, train classifiers that separate ROIs into known categories (medical concepts), or to build visual ontologies, for indexing and retrieval of biomedical articles. We propose an algorithm that pairs visual and textual ROIs that are extracted from images and figure captions, respectively. This algorithm based on dynamic time warping (DTW) clusters recognized pointers into groups, each of which contains pointers with identical visual properties (shape, size, color, etc.). Then a rule-based matching algorithm finds the best matching group for each textual ROI mention. Our method yields a precision and recall of 96% and 79%, respectively, when ground truth textual ROI data is used.

  5. Biomedical image representation approach using visualness and spatial information in a concept feature space for interactive region-of-interest-based retrieval.

    Science.gov (United States)

    Rahman, Md Mahmudur; Antani, Sameer K; Demner-Fushman, Dina; Thoma, George R

    2015-10-01

    This article presents an approach to biomedical image retrieval by mapping image regions to local concepts where images are represented in a weighted entropy-based concept feature space. The term "concept" refers to perceptually distinguishable visual patches that are identified locally in image regions and can be mapped to a glossary of imaging terms. Further, the visual significance (e.g., visualness) of concepts is measured as the Shannon entropy of pixel values in image patches and is used to refine the feature vector. Moreover, the system can assist the user in interactively selecting a region-of-interest (ROI) and searching for similar image ROIs. Further, a spatial verification step is used as a postprocessing step to improve retrieval results based on location information. The hypothesis that such approaches would improve biomedical image retrieval is validated through experiments on two different data sets, which are collected from open access biomedical literature.

  6. A novel method for efficient archiving and retrieval of biomedical images using MPEG-7

    Science.gov (United States)

    Meyer, Joerg; Pahwa, Ash

    2004-10-01

    Digital archiving and efficient retrieval of radiological scans have become critical steps in contemporary medical diagnostics. Since more and more images and image sequences (single scans or video) from various modalities (CT/MRI/PET/digital X-ray) are now available in digital formats (e.g., DICOM-3), hospitals and radiology clinics need to implement efficient protocols capable of managing the enormous amounts of data generated daily in a typical clinical routine. We present a method that appears to be a viable way to eliminate the tedious step of manually annotating image and video material for database indexing. MPEG-7 is a new framework that standardizes the way images are characterized in terms of color, shape, and other abstract, content-related criteria. A set of standardized descriptors that are automatically generated from an image is used to compare an image to other images in a database, and to compute the distance between two images for a given application domain. Text-based database queries can be replaced with image-based queries using MPEG-7. Consequently, image queries can be conducted without any prior knowledge of the keys that were used as indices in the database. Since the decoding and matching steps are not part of the MPEG-7 standard, this method also enables searches that were not planned by the time the keys were generated.

  7. Biomedical information retrieval across languages.

    Science.gov (United States)

    Daumke, Philipp; Markü, Kornél; Poprat, Michael; Schulz, Stefan; Klar, Rüdiger

    2007-06-01

    This work presents a new dictionary-based approach to biomedical cross-language information retrieval (CLIR) that addresses many of the general and domain-specific challenges in current CLIR research. Our method is based on a multilingual lexicon that was generated partly manually and partly automatically, and currently covers six European languages. It contains morphologically meaningful word fragments, termed subwords. Using subwords instead of entire words significantly reduces the number of lexical entries necessary to sufficiently cover a specific language and domain. Mediation between queries and documents is based on these subwords as well as on lists of word-n-grams that are generated from large monolingual corpora and constitute possible translation units. The translations are then sent to a standard Internet search engine. This process makes our approach an effective tool for searching the biomedical content of the World Wide Web in different languages. We evaluate this approach using the OHSUMED corpus, a large medical document collection, within a cross-language retrieval setting.

  8. Image retrieval

    DEFF Research Database (Denmark)

    Ørnager, Susanne

    1997-01-01

    The paper touches upon indexing and retrieval for effective searches of digitized images. Different conceptions of what subject indexing means are described as a basis for defining an operational subject indexing strategy for images. The methodology is based on the art historian Erwin Panofsky......), special knowledge about image codes, and special knowledge about history of ideas. The semiologist Roland Barthes has established a semiology for pictorial expressions based on advertising photos. Barthes uses the concepts denotation/connotation where denotations can be explained as the sober expression...

  9. Information Retrieval in Biomedical Research: From Articles to Datasets

    Science.gov (United States)

    Wei, Wei

    2017-01-01

    Information retrieval techniques have been applied to biomedical research for a variety of purposes, such as textual document retrieval and molecular data retrieval. As biomedical research evolves over time, information retrieval is also constantly facing new challenges, including the growing number of available data, the emerging new data types,…

  10. Biomedical Image Registration

    DEFF Research Database (Denmark)

    This book constitutes the refereed proceedings of the 8th International Workshop on Biomedical Image Registration, WBIR 2018, held in Leiden, The Netherlands, in June 2018. The 11 full and poster papers included in this volume were carefully reviewed and selected from 17 submitted papers. The pap...

  11. Proof of concept: concept-based biomedical information retrieval

    NARCIS (Netherlands)

    Trieschnigg, Rudolf Berend

    2010-01-01

    In this thesis we investigate the possibility to integrate domain-specific knowledge into biomedical information retrieval (IR). Recent decades have shown a fast growing interest in biomedical research, reflected by an exponential growth in scientific literature. An important problem for biomedical

  12. Three-dimensional biomedical imaging

    International Nuclear Information System (INIS)

    Robb, R.A.

    1985-01-01

    Scientists in biomedical imaging provide researchers, physicians, and academicians with an understanding of the fundamental theories and practical applications of three-dimensional biomedical imaging methodologies. Succinct descriptions of each imaging modality are supported by numerous diagrams and illustrations which clarify important concepts and demonstrate system performance in a variety of applications. Comparison of the different functional attributes, relative advantages and limitations, complementary capabilities, and future directions of three-dimensional biomedical imaging modalities are given. Volume 1: Introductions to Three-Dimensional Biomedical Imaging Photoelectronic-Digital Imaging for Diagnostic Radiology. X-Ray Computed Tomography - Basic Principles. X-Ray Computed Tomography - Implementation and Applications. X-Ray Computed Tomography: Advanced Systems and Applications in Biomedical Research and Diagnosis. Volume II: Single Photon Emission Computed Tomography. Position Emission Tomography (PET). Computerized Ultrasound Tomography. Fundamentals of NMR Imaging. Display of Multi-Dimensional Biomedical Image Information. Summary and Prognostications

  13. Biomedical signals, imaging, and informatics

    CERN Document Server

    Bronzino, Joseph D

    2014-01-01

    Known as the bible of biomedical engineering, The Biomedical Engineering Handbook, Fourth Edition, sets the standard against which all other references of this nature are measured. As such, it has served as a major resource for both skilled professionals and novices to biomedical engineering.Biomedical Signals, Imaging, and Informatics, the third volume of the handbook, presents material from respected scientists with diverse backgrounds in biosignal processing, medical imaging, infrared imaging, and medical informatics.More than three dozen specific topics are examined, including biomedical s

  14. Retrieve An Image

    Indian Academy of Sciences (India)

    First page Back Continue Last page Overview Graphics. Retrieve An Image. “A building”. “Box-shaped”. “Brown Color”. “Foreshortened view”. OR. Why not specify a similar looking picture? -- Main Motivation!

  15. Molecular Biomedical Imaging Laboratory (MBIL)

    Data.gov (United States)

    Federal Laboratory Consortium — The Molecular Biomedical Imaging Laboratory (MBIL) is adjacent-a nd has access-to the Department of Radiology and Imaging Sciences clinical imaging facilities. MBIL...

  16. Computational intelligence in biomedical imaging

    CERN Document Server

    2014-01-01

    This book provides a comprehensive overview of the state-of-the-art computational intelligence research and technologies in biomedical images with emphasis on biomedical decision making. Biomedical imaging offers useful information on patients’ medical conditions and clues to causes of their symptoms and diseases. Biomedical images, however, provide a large number of images which physicians must interpret. Therefore, computer aids are demanded and become indispensable in physicians’ decision making. This book discusses major technical advancements and research findings in the field of computational intelligence in biomedical imaging, for example, computational intelligence in computer-aided diagnosis for breast cancer, prostate cancer, and brain disease, in lung function analysis, and in radiation therapy. The book examines technologies and studies that have reached the practical level, and those technologies that are becoming available in clinical practices in hospitals rapidly such as computational inte...

  17. Improve Biomedical Information Retrieval using Modified Learning to Rank Methods.

    Science.gov (United States)

    Xu, Bo; Lin, Hongfei; Lin, Yuan; Ma, Yunlong; Yang, Liang; Wang, Jian; Yang, Zhihao

    2016-06-14

    In these years, the number of biomedical articles has increased exponentially, which becomes a problem for biologists to capture all the needed information manually. Information retrieval technologies, as the core of search engines, can deal with the problem automatically, providing users with the needed information. However, it is a great challenge to apply these technologies directly for biomedical retrieval, because of the abundance of domain specific terminologies. To enhance biomedical retrieval, we propose a novel framework based on learning to rank. Learning to rank is a series of state-of-the-art information retrieval techniques, and has been proved effective in many information retrieval tasks. In the proposed framework, we attempt to tackle the problem of the abundance of terminologies by constructing ranking models, which focus on not only retrieving the most relevant documents, but also diversifying the searching results to increase the completeness of the resulting list for a given query. In the model training, we propose two novel document labeling strategies, and combine several traditional retrieval models as learning features. Besides, we also investigate the usefulness of different learning to rank approaches in our framework. Experimental results on TREC Genomics datasets demonstrate the effectiveness of our framework for biomedical information retrieval.

  18. Mobile medical image retrieval

    Science.gov (United States)

    Duc, Samuel; Depeursinge, Adrien; Eggel, Ivan; Müller, Henning

    2011-03-01

    Images are an integral part of medical practice for diagnosis, treatment planning and teaching. Image retrieval has gained in importance mainly as a research domain over the past 20 years. Both textual and visual retrieval of images are essential. In the process of mobile devices becoming reliable and having a functionality equaling that of formerly desktop clients, mobile computing has gained ground and many applications have been explored. This creates a new field of mobile information search & access and in this context images can play an important role as they often allow understanding complex scenarios much quicker and easier than free text. Mobile information retrieval in general has skyrocketed over the past year with many new applications and tools being developed and all sorts of interfaces being adapted to mobile clients. This article describes constraints of an information retrieval system including visual and textual information retrieval from the medical literature of BioMedCentral and of the RSNA journals Radiology and Radiographics. Solutions for mobile data access with an example on an iPhone in a web-based environment are presented as iPhones are frequently used and the operating system is bound to become the most frequent smartphone operating system in 2011. A web-based scenario was chosen to allow for a use by other smart phone platforms such as Android as well. Constraints of small screens and navigation with touch screens are taken into account in the development of the application. A hybrid choice had to be taken to allow for taking pictures with the cell phone camera and upload them for visual similarity search as most producers of smart phones block this functionality to web applications. Mobile information access and in particular access to images can be surprisingly efficient and effective on smaller screens. Images can be read on screen much faster and relevance of documents can be identified quickly through the use of images contained in

  19. The Wikipedia Image Retrieval Task

    NARCIS (Netherlands)

    T. Tsikrika (Theodora); J. Kludas

    2010-01-01

    htmlabstractThe wikipedia image retrieval task at ImageCLEF provides a testbed for the system-oriented evaluation of visual information retrieval from a collection of Wikipedia images. The aim is to investigate the effectiveness of retrieval approaches that exploit textual and visual evidence in the

  20. Biomedical Imaging Principles and Applications

    CERN Document Server

    Salzer, Reiner

    2012-01-01

    This book presents and describes imaging technologies that can be used to study chemical processes and structural interactions in dynamic systems, principally in biomedical systems. The imaging technologies, largely biomedical imaging technologies such as MRT, Fluorescence mapping, raman mapping, nanoESCA, and CARS microscopy, have been selected according to their application range and to the chemical information content of their data. These technologies allow for the analysis and evaluation of delicate biological samples, which must not be disturbed during the profess. Ultimately, this may me

  1. IMAGE DESCRIPTIONS FOR SKETCH BASED IMAGE RETRIEVAL

    OpenAIRE

    SAAVEDRA RONDO, JOSE MANUEL; SAAVEDRA RONDO, JOSE MANUEL

    2008-01-01

    Due to the massive use of Internet together with the proliferation of media devices, content based image retrieval has become an active discipline in computer science. A common content based image retrieval approach requires that the user gives a regular image (e.g, a photo) as a query. However, having a regular image as query may be a serious problem. Indeed, people commonly use an image retrieval system because they do not count on the desired image. An easy alternative way t...

  2. Biomedical Image Processing

    CERN Document Server

    Deserno, Thomas Martin

    2011-01-01

    In modern medicine, imaging is the most effective tool for diagnostics, treatment planning and therapy. Almost all modalities have went to directly digital acquisition techniques and processing of this image data have become an important option for health care in future. This book is written by a team of internationally recognized experts from all over the world. It provides a brief but complete overview on medical image processing and analysis highlighting recent advances that have been made in academics. Color figures are used extensively to illustrate the methods and help the reader to understand the complex topics.

  3. Probabilistic and machine learning-based retrieval approaches for biomedical dataset retrieval

    Science.gov (United States)

    Karisani, Payam; Qin, Zhaohui S; Agichtein, Eugene

    2018-01-01

    Abstract The bioCADDIE dataset retrieval challenge brought together different approaches to retrieval of biomedical datasets relevant to a user’s query, expressed as a text description of a needed dataset. We describe experiments in applying a data-driven, machine learning-based approach to biomedical dataset retrieval as part of this challenge. We report on a series of experiments carried out to evaluate the performance of both probabilistic and machine learning-driven techniques from information retrieval, as applied to this challenge. Our experiments with probabilistic information retrieval methods, such as query term weight optimization, automatic query expansion and simulated user relevance feedback, demonstrate that automatically boosting the weights of important keywords in a verbose query is more effective than other methods. We also show that although there is a rich space of potential representations and features available in this domain, machine learning-based re-ranking models are not able to improve on probabilistic information retrieval techniques with the currently available training data. The models and algorithms presented in this paper can serve as a viable implementation of a search engine to provide access to biomedical datasets. The retrieval performance is expected to be further improved by using additional training data that is created by expert annotation, or gathered through usage logs, clicks and other processes during natural operation of the system. Database URL: https://github.com/emory-irlab/biocaddie

  4. Biomedical signal and image processing

    CERN Document Server

    Najarian, Kayvan

    2012-01-01

    INTRODUCTION TO DIGITAL SIGNAL AND IMAGE PROCESSINGSignals and Biomedical Signal ProcessingIntroduction and OverviewWhat is a ""Signal""?Analog, Discrete, and Digital SignalsProcessing and Transformation of SignalsSignal Processing for Feature ExtractionSome Characteristics of Digital ImagesSummaryProblemsFourier TransformIntroduction and OverviewOne-Dimensional Continuous Fourier TransformSampling and NYQUIST RateOne-Dimensional Discrete Fourier TransformTwo-Dimensional Discrete Fourier TransformFilter DesignSummaryProblemsImage Filtering, Enhancement, and RestorationIntroduction and Overview

  5. Interactive Exploration for Image Retrieval

    Directory of Open Access Journals (Sweden)

    Jérôme Fournier

    2005-08-01

    Full Text Available We present a new version of our content-based image retrieval system RETIN. It is based on adaptive quantization of the color space, together with new features aiming at representing the spatial relationship between colors. Color analysis is also extended to texture. Using these powerful indexes, an original interactive retrieval strategy is introduced. The process is based on two steps for handling the retrieval of very large image categories. First, a controlled exploration method of the database is presented. Second, a relevance feedback method based on statistical learning is proposed. All the steps are evaluated by experiments on a generalist database.

  6. Biomedical signal and image processing.

    Science.gov (United States)

    Cerutti, Sergio; Baselli, Giuseppe; Bianchi, Anna; Caiani, Enrico; Contini, Davide; Cubeddu, Rinaldo; Dercole, Fabio; Rienzo, Luca; Liberati, Diego; Mainardi, Luca; Ravazzani, Paolo; Rinaldi, Sergio; Signorini, Maria; Torricelli, Alessandro

    2011-01-01

    Generally, physiological modeling and biomedical signal processing constitute two important paradigms of biomedical engineering (BME): their fundamental concepts are taught starting from undergraduate studies and are more completely dealt with in the last years of graduate curricula, as well as in Ph.D. courses. Traditionally, these two cultural aspects were separated, with the first one more oriented to physiological issues and how to model them and the second one more dedicated to the development of processing tools or algorithms to enhance useful information from clinical data. A practical consequence was that those who did models did not do signal processing and vice versa. However, in recent years,the need for closer integration between signal processing and modeling of the relevant biological systems emerged very clearly [1], [2]. This is not only true for training purposes(i.e., to properly prepare the new professional members of BME) but also for the development of newly conceived research projects in which the integration between biomedical signal and image processing (BSIP) and modeling plays a crucial role. Just to give simple examples, topics such as brain–computer machine or interfaces,neuroengineering, nonlinear dynamical analysis of the cardiovascular (CV) system,integration of sensory-motor characteristics aimed at the building of advanced prostheses and rehabilitation tools, and wearable devices for vital sign monitoring and others do require an intelligent fusion of modeling and signal processing competences that are certainly peculiar of our discipline of BME.

  7. Biomedical Optical Imaging Technologies Design and Applications

    CERN Document Server

    2013-01-01

    This book provides an introduction to design of biomedical optical imaging technologies and their applications. The main topics include: fluorescence imaging, confocal imaging, micro-endoscope, polarization imaging, hyperspectral imaging, OCT imaging, multimodal imaging and spectroscopic systems. Each chapter is written by the world leaders of the respective fields, and will cover: principles and limitations of optical imaging technology, system design and practical implementation for one or two specific applications, including design guidelines, system configuration, optical design, component requirements and selection, system optimization and design examples, recent advances and applications in biomedical researches and clinical imaging. This book serves as a reference for students and researchers in optics and biomedical engineering.

  8. Review of Biomedical Image Processing

    Directory of Open Access Journals (Sweden)

    Ciaccio Edward J

    2011-11-01

    Full Text Available Abstract This article is a review of the book: 'Biomedical Image Processing', by Thomas M. Deserno, which is published by Springer-Verlag. Salient information that will be useful to decide whether the book is relevant to topics of interest to the reader, and whether it might be suitable as a course textbook, are presented in the review. This includes information about the book details, a summary, the suitability of the text in course and research work, the framework of the book, its specific content, and conclusions.

  9. Mathematics and physics of emerging biomedical imaging

    National Research Council Canada - National Science Library

    Committee on the Mathematics and Physics of Emerging Dynamic Biomedical Imaging, National Research Council

    .... Incorporating input from dozens of biomedical researchers who described what they perceived as key open problems of imaging that are amenable to attack by mathematical scientists and physicists...

  10. Development of an information retrieval tool for biomedical patents.

    Science.gov (United States)

    Alves, Tiago; Rodrigues, Rúben; Costa, Hugo; Rocha, Miguel

    2018-06-01

    The volume of biomedical literature has been increasing in the last years. Patent documents have also followed this trend, being important sources of biomedical knowledge, technical details and curated data, which are put together along the granting process. The field of Biomedical text mining (BioTM) has been creating solutions for the problems posed by the unstructured nature of natural language, which makes the search of information a challenging task. Several BioTM techniques can be applied to patents. From those, Information Retrieval (IR) includes processes where relevant data are obtained from collections of documents. In this work, the main goal was to build a patent pipeline addressing IR tasks over patent repositories to make these documents amenable to BioTM tasks. The pipeline was developed within @Note2, an open-source computational framework for BioTM, adding a number of modules to the core libraries, including patent metadata and full text retrieval, PDF to text conversion and optical character recognition. Also, user interfaces were developed for the main operations materialized in a new @Note2 plug-in. The integration of these tools in @Note2 opens opportunities to run BioTM tools over patent texts, including tasks from Information Extraction, such as Named Entity Recognition or Relation Extraction. We demonstrated the pipeline's main functions with a case study, using an available benchmark dataset from BioCreative challenges. Also, we show the use of the plug-in with a user query related to the production of vanillin. This work makes available all the relevant content from patents to the scientific community, decreasing drastically the time required for this task, and provides graphical interfaces to ease the use of these tools. Copyright © 2018 Elsevier B.V. All rights reserved.

  11. A passage retrieval method based on probabilistic information retrieval model and UMLS concepts in biomedical question answering.

    Science.gov (United States)

    Sarrouti, Mourad; Ouatik El Alaoui, Said

    2017-04-01

    Passage retrieval, the identification of top-ranked passages that may contain the answer for a given biomedical question, is a crucial component for any biomedical question answering (QA) system. Passage retrieval in open-domain QA is a longstanding challenge widely studied over the last decades. However, it still requires further efforts in biomedical QA. In this paper, we present a new biomedical passage retrieval method based on Stanford CoreNLP sentence/passage length, probabilistic information retrieval (IR) model and UMLS concepts. In the proposed method, we first use our document retrieval system based on PubMed search engine and UMLS similarity to retrieve relevant documents to a given biomedical question. We then take the abstracts from the retrieved documents and use Stanford CoreNLP for sentence splitter to make a set of sentences, i.e., candidate passages. Using stemmed words and UMLS concepts as features for the BM25 model, we finally compute the similarity scores between the biomedical question and each of the candidate passages and keep the N top-ranked ones. Experimental evaluations performed on large standard datasets, provided by the BioASQ challenge, show that the proposed method achieves good performances compared with the current state-of-the-art methods. The proposed method significantly outperforms the current state-of-the-art methods by an average of 6.84% in terms of mean average precision (MAP). We have proposed an efficient passage retrieval method which can be used to retrieve relevant passages in biomedical QA systems with high mean average precision. Copyright © 2017 Elsevier Inc. All rights reserved.

  12. Double-compression method for biomedical images

    Science.gov (United States)

    Antonenko, Yevhenii A.; Mustetsov, Timofey N.; Hamdi, Rami R.; Małecka-Massalska, Teresa; Orshubekov, Nurbek; DzierŻak, RóŻa; Uvaysova, Svetlana

    2017-08-01

    This paper describes a double compression method (DCM) of biomedical images. A comparison of image compression factors in size JPEG, PNG and developed DCM was carried out. The main purpose of the DCM - compression of medical images while maintaining the key points that carry diagnostic information. To estimate the minimum compression factor an analysis of the coding of random noise image is presented.

  13. Computer vision for biomedical image applications. Proceedings

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Yanxi [Carnegie Mellon Univ., Pittsburgh, PA (United States). School of Computer Science, The Robotics Institute; Jiang, Tianzi [Chinese Academy of Sciences, Beijing (China). National Lab. of Pattern Recognition, Inst. of Automation; Zhang, Changshui (eds.) [Tsinghua Univ., Beijing, BJ (China). Dept. of Automation

    2005-07-01

    This book constitutes the refereed proceedings of the First International Workshop on Computer Vision for Biomedical Image Applications: Current Techniques and Future Trends, CVBIA 2005, held in Beijing, China, in October 2005 within the scope of ICCV 20. (orig.)

  14. Document image retrieval through word shape coding.

    Science.gov (United States)

    Lu, Shijian; Li, Linlin; Tan, Chew Lim

    2008-11-01

    This paper presents a document retrieval technique that is capable of searching document images without OCR (optical character recognition). The proposed technique retrieves document images by a new word shape coding scheme, which captures the document content through annotating each word image by a word shape code. In particular, we annotate word images by using a set of topological shape features including character ascenders/descenders, character holes, and character water reservoirs. With the annotated word shape codes, document images can be retrieved by either query keywords or a query document image. Experimental results show that the proposed document image retrieval technique is fast, efficient, and tolerant to various types of document degradation.

  15. Image BOSS: a biomedical object storage system

    Science.gov (United States)

    Stacy, Mahlon C.; Augustine, Kurt E.; Robb, Richard A.

    1997-05-01

    Researchers using biomedical images have data management needs which are oriented perpendicular to clinical PACS. The image BOSS system is designed to permit researchers to organize and select images based on research topic, image metadata, and a thumbnail of the image. Image information is captured from existing images in a Unix based filesystem, stored in an object oriented database, and presented to the user in a familiar laboratory notebook metaphor. In addition, the ImageBOSS is designed to provide an extensible infrastructure for future content-based queries directly on the images.

  16. Multiplicative calculus in biomedical image analysis

    NARCIS (Netherlands)

    Florack, L.M.J.; Assen, van H.C.

    2011-01-01

    We advocate the use of an alternative calculus in biomedical image analysis, known as multiplicative (a.k.a. non-Newtonian) calculus. It provides a natural framework in problems in which positive images or positive definite matrix fields and positivity preserving operators are of interest. Indeed,

  17. University of Vermont Center for Biomedical Imaging

    Energy Technology Data Exchange (ETDEWEB)

    Bernstein, Dr. Ira [University of Vermont and State Agricultural College

    2013-08-02

    This grant was awarded in support of Phase 2 of the University of Vermont Center for Biomedical Imaging. Phase 2 outlined several specific aims including: The development of expertise in MRI and fMRI imaging and their applications The acquisition of peer reviewed extramural funding in support of the Center The development of a Core Imaging Advisory Board, fee structure and protocol review and approval process.

  18. IEEE International Symposium on Biomedical Imaging.

    Science.gov (United States)

    2017-01-01

    The IEEE International Symposium on Biomedical Imaging (ISBI) is a scientific conference dedicated to mathematical, algorithmic, and computational aspects of biological and biomedical imaging, across all scales of observation. It fosters knowledge transfer among different imaging communities and contributes to an integrative approach to biomedical imaging. ISBI is a joint initiative from the IEEE Signal Processing Society (SPS) and the IEEE Engineering in Medicine and Biology Society (EMBS). The 2018 meeting will include tutorials, and a scientific program composed of plenary talks, invited special sessions, challenges, as well as oral and poster presentations of peer-reviewed papers. High-quality papers are requested containing original contributions to the topics of interest including image formation and reconstruction, computational and statistical image processing and analysis, dynamic imaging, visualization, image quality assessment, and physical, biological, and statistical modeling. Accepted 4-page regular papers will be published in the symposium proceedings published by IEEE and included in IEEE Xplore. To encourage attendance by a broader audience of imaging scientists and offer additional presentation opportunities, ISBI 2018 will continue to have a second track featuring posters selected from 1-page abstract submissions without subsequent archival publication.

  19. Compound image segmentation of published biomedical figures.

    Science.gov (United States)

    Li, Pengyuan; Jiang, Xiangying; Kambhamettu, Chandra; Shatkay, Hagit

    2018-04-01

    Images convey essential information in biomedical publications. As such, there is a growing interest within the bio-curation and the bio-databases communities, to store images within publications as evidence for biomedical processes and for experimental results. However, many of the images in biomedical publications are compound images consisting of multiple panels, where each individual panel potentially conveys a different type of information. Segmenting such images into constituent panels is an essential first step toward utilizing images. In this article, we develop a new compound image segmentation system, FigSplit, which is based on Connected Component Analysis. To overcome shortcomings typically manifested by existing methods, we develop a quality assessment step for evaluating and modifying segmentations. Two methods are proposed to re-segment the images if the initial segmentation is inaccurate. Experimental results show the effectiveness of our method compared with other methods. The system is publicly available for use at: https://www.eecis.udel.edu/~compbio/FigSplit. The code is available upon request. shatkay@udel.edu. Supplementary data are available online at Bioinformatics.

  20. Transformation invariant image indexing and retrieval for image databases

    NARCIS (Netherlands)

    Gevers, Th.; Smeulders, A.W.M.

    1994-01-01

    This paper presents a novel design of an image database system which supports storage, indexing and retrieval of images by content. The image retrieval methodology is based on the observation that images can be discriminated by the presence of image objects and their spatial relations. Images in the

  1. Mathematics and physics of emerging biomedical imaging

    International Nuclear Information System (INIS)

    1996-01-01

    Although the mathematical sciences were used in a general way for image processing, they were of little importance in biomedical work until the development in the 1970s of computed tomography (CT) for the imaging of x-rays and isotope emission tomography. In the 1980s, MRI eclipsed the other modalities in many ways as the most informative medical imaging methodology. Besides these well-established techniques, computer-based mathematical methods are being explored in applications to other well-known methods, such as ultrasound and electroencephalography, as well as new techniques of optical imaging, impedance tomography, and magnetic source imaging. It is worth pointing out that, while the final images of many of these techniques bear many similarities to each other, the technologies involved in each are completely different and the parameters represented in the images are very different in character as well as in medical usefulness. In each case, rather different mathematical or statistical models are used, with different equations. One common thread is the paradigm of reconstruction from indirect measurements--this is the unifying theme of this report. The imaging methods used in biomedical applications that this report discusses include: (1) x-ray projection imaging; (2) x-ray computed tomography (CT); (3) magnetic resonance imaging (MRI) and magnetic resonance spectroscopy; (4) single photon emission computed tomography (SPECT); (5) positron emission tomography (PET); (6) ultrasonics; (7) electrical source imaging (ESI); (8) electrical impedance tomography (EIT); (9) magnetic source imaging (MSI); and (10) medical optical imaging

  2. Rotation Covariant Image Processing for Biomedical Applications

    Directory of Open Access Journals (Sweden)

    Henrik Skibbe

    2013-01-01

    Full Text Available With the advent of novel biomedical 3D image acquisition techniques, the efficient and reliable analysis of volumetric images has become more and more important. The amount of data is enormous and demands an automated processing. The applications are manifold, ranging from image enhancement, image reconstruction, and image description to object/feature detection and high-level contextual feature extraction. In most scenarios, it is expected that geometric transformations alter the output in a mathematically well-defined manner. In this paper we emphasis on 3D translations and rotations. Many algorithms rely on intensity or low-order tensorial-like descriptions to fulfill this demand. This paper proposes a general mathematical framework based on mathematical concepts and theories transferred from mathematical physics and harmonic analysis into the domain of image analysis and pattern recognition. Based on two basic operations, spherical tensor differentiation and spherical tensor multiplication, we show how to design a variety of 3D image processing methods in an efficient way. The framework has already been applied to several biomedical applications ranging from feature and object detection tasks to image enhancement and image restoration techniques. In this paper, the proposed methods are applied on a variety of different 3D data modalities stemming from medical and biological sciences.

  3. Molecular imaging in biomedical research

    International Nuclear Information System (INIS)

    Jagannathan, N.R.

    2007-01-01

    Molecular imaging (MI) is a diverse technology that revolutionized preclinical, clinical and drug-discovery research. It integrates biology and medicine, and the technique presents a unique opportunity to examine living systems in vivo as a dynamic biological system. It is a hybrid technology that combines PET, SPECT, ultrasound, optical imaging and MR. Several MI methodologies are developed to examine the integrative functions of molecules, cells, organ systems and whole organisms. MI is superior to conventional diagnostic techniques in allowing better staging as well as to monitor the response of cancer/tumour to treatment. In addition, it helps visualization of specific molecular targets or pathways and cells in living systems and ultimately in the clinic. (author)

  4. BIG: a Grid Portal for Biomedical Data and Images

    Directory of Open Access Journals (Sweden)

    Giovanni Aloisio

    2004-06-01

    Full Text Available Modern management of biomedical systems involves the use of many distributed resources, such as high performance computational resources to analyze biomedical data, mass storage systems to store them, medical instruments (microscopes, tomographs, etc., advanced visualization and rendering tools. Grids offer the computational power, security and availability needed by such novel applications. This paper presents BIG (Biomedical Imaging Grid, a Web-based Grid portal for management of biomedical information (data and images in a distributed environment. BIG is an interactive environment that deals with complex user's requests, regarding the acquisition of biomedical data, the "processing" and "delivering" of biomedical images, using the power and security of Computational Grids.

  5. Feature hashing for fast image retrieval

    Science.gov (United States)

    Yan, Lingyu; Fu, Jiarun; Zhang, Hongxin; Yuan, Lu; Xu, Hui

    2018-03-01

    Currently, researches on content based image retrieval mainly focus on robust feature extraction. However, due to the exponential growth of online images, it is necessary to consider searching among large scale images, which is very timeconsuming and unscalable. Hence, we need to pay much attention to the efficiency of image retrieval. In this paper, we propose a feature hashing method for image retrieval which not only generates compact fingerprint for image representation, but also prevents huge semantic loss during the process of hashing. To generate the fingerprint, an objective function of semantic loss is constructed and minimized, which combine the influence of both the neighborhood structure of feature data and mapping error. Since the machine learning based hashing effectively preserves neighborhood structure of data, it yields visual words with strong discriminability. Furthermore, the generated binary codes leads image representation building to be of low-complexity, making it efficient and scalable to large scale databases. Experimental results show good performance of our approach.

  6. Dialog-based Interactive Image Retrieval

    OpenAIRE

    Guo, Xiaoxiao; Wu, Hui; Cheng, Yu; Rennie, Steven; Feris, Rogerio Schmidt

    2018-01-01

    Existing methods for interactive image retrieval have demonstrated the merit of integrating user feedback, improving retrieval results. However, most current systems rely on restricted forms of user feedback, such as binary relevance responses, or feedback based on a fixed set of relative attributes, which limits their impact. In this paper, we introduce a new approach to interactive image search that enables users to provide feedback via natural language, allowing for more natural and effect...

  7. A Semantics-Based Approach to Retrieving Biomedical Information

    DEFF Research Database (Denmark)

    Andreasen, Troels; Bulskov, Henrik; Zambach, Sine

    2011-01-01

    This paper describes an approach to representing, organising, and accessing conceptual content of biomedical texts using a formal ontology. The ontology is based on UMLS resources supplemented with domain ontologies developed in the project. The approach introduces the notion of ‘generative ontol...... of data mining of texts identifying paraphrases and concept relations and measuring distances between key concepts in texts. Thus, the project is distinct in its attempt to provide a formal underpinning of conceptual similarity or relatedness of meaning.......This paper describes an approach to representing, organising, and accessing conceptual content of biomedical texts using a formal ontology. The ontology is based on UMLS resources supplemented with domain ontologies developed in the project. The approach introduces the notion of ‘generative...... ontologies’, i.e., ontologies providing increasingly specialised concepts reflecting the phrase structure of natural language. Furthermore, we propose a novel so called ontological semantics which maps noun phrases from texts and queries into nodes in the generative ontology. This enables an advanced form...

  8. Toward privacy-preserving JPEG image retrieval

    Science.gov (United States)

    Cheng, Hang; Wang, Jingyue; Wang, Meiqing; Zhong, Shangping

    2017-07-01

    This paper proposes a privacy-preserving retrieval scheme for JPEG images based on local variance. Three parties are involved in the scheme: the content owner, the server, and the authorized user. The content owner encrypts JPEG images for privacy protection by jointly using permutation cipher and stream cipher, and then, the encrypted versions are uploaded to the server. With an encrypted query image provided by an authorized user, the server may extract blockwise local variances in different directions without knowing the plaintext content. After that, it can calculate the similarity between the encrypted query image and each encrypted database image by a local variance-based feature comparison mechanism. The authorized user with the encryption key can decrypt the returned encrypted images with plaintext content similar to the query image. The experimental results show that the proposed scheme not only provides effective privacy-preserving retrieval service but also ensures both format compliance and file size preservation for encrypted JPEG images.

  9. Hybrid Histogram Descriptor: A Fusion Feature Representation for Image Retrieval.

    Science.gov (United States)

    Feng, Qinghe; Hao, Qiaohong; Chen, Yuqi; Yi, Yugen; Wei, Ying; Dai, Jiangyan

    2018-06-15

    Currently, visual sensors are becoming increasingly affordable and fashionable, acceleratingly the increasing number of image data. Image retrieval has attracted increasing interest due to space exploration, industrial, and biomedical applications. Nevertheless, designing effective feature representation is acknowledged as a hard yet fundamental issue. This paper presents a fusion feature representation called a hybrid histogram descriptor (HHD) for image retrieval. The proposed descriptor comprises two histograms jointly: a perceptually uniform histogram which is extracted by exploiting the color and edge orientation information in perceptually uniform regions; and a motif co-occurrence histogram which is acquired by calculating the probability of a pair of motif patterns. To evaluate the performance, we benchmarked the proposed descriptor on RSSCN7, AID, Outex-00013, Outex-00014 and ETHZ-53 datasets. Experimental results suggest that the proposed descriptor is more effective and robust than ten recent fusion-based descriptors under the content-based image retrieval framework. The computational complexity was also analyzed to give an in-depth evaluation. Furthermore, compared with the state-of-the-art convolutional neural network (CNN)-based descriptors, the proposed descriptor also achieves comparable performance, but does not require any training process.

  10. Generic information can retrieve known biological associations: implications for biomedical knowledge discovery.

    Directory of Open Access Journals (Sweden)

    Herman H H B M van Haagen

    Full Text Available MOTIVATION: Weighted semantic networks built from text-mined literature can be used to retrieve known protein-protein or gene-disease associations, and have been shown to anticipate associations years before they are explicitly stated in the literature. Our text-mining system recognizes over 640,000 biomedical concepts: some are specific (i.e., names of genes or proteins others generic (e.g., 'Homo sapiens'. Generic concepts may play important roles in automated information retrieval, extraction, and inference but may also result in concept overload and confound retrieval and reasoning with low-relevance or even spurious links. Here, we attempted to optimize the retrieval performance for protein-protein interactions (PPI by filtering generic concepts (node filtering or links to generic concepts (edge filtering from a weighted semantic network. First, we defined metrics based on network properties that quantify the specificity of concepts. Then using these metrics, we systematically filtered generic information from the network while monitoring retrieval performance of known protein-protein interactions. We also systematically filtered specific information from the network (inverse filtering, and assessed the retrieval performance of networks composed of generic information alone. RESULTS: Filtering generic or specific information induced a two-phase response in retrieval performance: initially the effects of filtering were minimal but beyond a critical threshold network performance suddenly drops. Contrary to expectations, networks composed exclusively of generic information demonstrated retrieval performance comparable to unfiltered networks that also contain specific concepts. Furthermore, an analysis using individual generic concepts demonstrated that they can effectively support the retrieval of known protein-protein interactions. For instance the concept "binding" is indicative for PPI retrieval and the concept "mutation abnormality" is

  11. VICAR - VIDEO IMAGE COMMUNICATION AND RETRIEVAL

    Science.gov (United States)

    Wall, R. J.

    1994-01-01

    VICAR (Video Image Communication and Retrieval) is a general purpose image processing software system that has been under continuous development since the late 1960's. Originally intended for data from the NASA Jet Propulsion Laboratory's unmanned planetary spacecraft, VICAR is now used for a variety of other applications including biomedical image processing, cartography, earth resources, and geological exploration. The development of this newest version of VICAR emphasized a standardized, easily-understood user interface, a shield between the user and the host operating system, and a comprehensive array of image processing capabilities. Structurally, VICAR can be divided into roughly two parts; a suite of applications programs and an executive which serves as the interfaces between the applications, the operating system, and the user. There are several hundred applications programs ranging in function from interactive image editing, data compression/decompression, and map projection, to blemish, noise, and artifact removal, mosaic generation, and pattern recognition and location. An information management system designed specifically for handling image related data can merge image data with other types of data files. The user accesses these programs through the VICAR executive, which consists of a supervisor and a run-time library. From the viewpoint of the user and the applications programs, the executive is an environment that is independent of the operating system. VICAR does not replace the host computer's operating system; instead, it overlays the host resources. The core of the executive is the VICAR Supervisor, which is based on NASA Goddard Space Flight Center's Transportable Applications Executive (TAE). Various modifications and extensions have been made to optimize TAE for image processing applications, resulting in a user friendly environment. The rest of the executive consists of the VICAR Run-Time Library, which provides a set of subroutines (image

  12. Secure image retrieval with multiple keys

    Science.gov (United States)

    Liang, Haihua; Zhang, Xinpeng; Wei, Qiuhan; Cheng, Hang

    2018-03-01

    This article proposes a secure image retrieval scheme under a multiuser scenario. In this scheme, the owner first encrypts and uploads images and their corresponding features to the cloud; then, the user submits the encrypted feature of the query image to the cloud; next, the cloud compares the encrypted features and returns encrypted images with similar content to the user. To find the nearest neighbor in the encrypted features, an encryption with multiple keys is proposed, in which the query feature of each user is encrypted by his/her own key. To improve the key security and space utilization, global optimization and Gaussian distribution are, respectively, employed to generate multiple keys. The experiments show that the proposed encryption can provide effective and secure image retrieval for each user and ensure confidentiality of the query feature of each user.

  13. Image Information Retrieval: An Overview of Current Research

    OpenAIRE

    Abby A. Goodrum

    2000-01-01

    This paper provides an overview of current research in image information retrieval and provides an outline of areas for future research. The approach is broad and interdisciplinary and focuses on three aspects of image research (IR): text-based retrieval, content-based retrieval, and user interactions with image information retrieval systems. The review concludes with a call for image retrieval evaluation studies similar to TREC.

  14. Intelligent image retrieval based on radiology reports

    Energy Technology Data Exchange (ETDEWEB)

    Gerstmair, Axel; Langer, Mathias; Kotter, Elmar [University Medical Center Freiburg, Department of Diagnostic Radiology, Freiburg (Germany); Daumke, Philipp; Simon, Kai [Averbis GmbH, Freiburg (Germany)

    2012-12-15

    To create an advanced image retrieval and data-mining system based on in-house radiology reports. Radiology reports are semantically analysed using natural language processing (NLP) techniques and stored in a state-of-the-art search engine. Images referenced by sequence and image number in the reports are retrieved from the picture archiving and communication system (PACS) and stored for later viewing. A web-based front end is used as an interface to query for images and show the results with the retrieved images and report text. Using a comprehensive radiological lexicon for the underlying terminology, the search algorithm also finds results for synonyms, abbreviations and related topics. The test set was 108 manually annotated reports analysed by different system configurations. Best results were achieved using full syntactic and semantic analysis with a precision of 0.929 and recall of 0.952. Operating successfully since October 2010, 258,824 reports have been indexed and a total of 405,146 preview images are stored in the database. Data-mining and NLP techniques provide quick access to a vast repository of images and radiology reports with both high precision and recall values. Consequently, the system has become a valuable tool in daily clinical routine, education and research. (orig.)

  15. Intelligent image retrieval based on radiology reports

    International Nuclear Information System (INIS)

    Gerstmair, Axel; Langer, Mathias; Kotter, Elmar; Daumke, Philipp; Simon, Kai

    2012-01-01

    To create an advanced image retrieval and data-mining system based on in-house radiology reports. Radiology reports are semantically analysed using natural language processing (NLP) techniques and stored in a state-of-the-art search engine. Images referenced by sequence and image number in the reports are retrieved from the picture archiving and communication system (PACS) and stored for later viewing. A web-based front end is used as an interface to query for images and show the results with the retrieved images and report text. Using a comprehensive radiological lexicon for the underlying terminology, the search algorithm also finds results for synonyms, abbreviations and related topics. The test set was 108 manually annotated reports analysed by different system configurations. Best results were achieved using full syntactic and semantic analysis with a precision of 0.929 and recall of 0.952. Operating successfully since October 2010, 258,824 reports have been indexed and a total of 405,146 preview images are stored in the database. Data-mining and NLP techniques provide quick access to a vast repository of images and radiology reports with both high precision and recall values. Consequently, the system has become a valuable tool in daily clinical routine, education and research. (orig.)

  16. Modeling and mining term association for improving biomedical information retrieval performance.

    Science.gov (United States)

    Hu, Qinmin; Huang, Jimmy Xiangji; Hu, Xiaohua

    2012-06-11

    The growth of the biomedical information requires most information retrieval systems to provide short and specific answers in response to complex user queries. Semantic information in the form of free text that is structured in a way makes it straightforward for humans to read but more difficult for computers to interpret automatically and search efficiently. One of the reasons is that most traditional information retrieval models assume terms are conditionally independent given a document/passage. Therefore, we are motivated to consider term associations within different contexts to help the models understand semantic information and use it for improving biomedical information retrieval performance. We propose a term association approach to discover term associations among the keywords from a query. The experiments are conducted on the TREC 2004-2007 Genomics data sets and the TREC 2004 HARD data set. The proposed approach is promising and achieves superiority over the baselines and the GSP results. The parameter settings and different indices are investigated that the sentence-based index produces the best results in terms of the document-level, the word-based index for the best results in terms of the passage-level and the paragraph-based index for the best results in terms of the passage2-level. Furthermore, the best term association results always come from the best baseline. The tuning number k in the proposed recursive re-ranking algorithm is discussed and locally optimized to be 10. First, modelling term association for improving biomedical information retrieval using factor analysis, is one of the major contributions in our work. Second, the experiments confirm that term association considering co-occurrence and dependency among the keywords can produce better results than the baselines treating the keywords independently. Third, the baselines are re-ranked according to the importance and reliance of latent factors behind term associations. These latent

  17. Robust histogram-based image retrieval

    Czech Academy of Sciences Publication Activity Database

    Höschl, Cyril; Flusser, Jan

    2016-01-01

    Roč. 69, č. 1 (2016), s. 72-81 ISSN 0167-8655 R&D Projects: GA ČR GA15-16928S Institutional support: RVO:67985556 Keywords : Image retrieval * Noisy image * Histogram * Convolution * Moments * Invariants Subject RIV: JD - Computer Applications, Robotics Impact factor: 1.995, year: 2016 http://library.utia.cas.cz/separaty/2015/ZOI/hoschl-0452147.pdf

  18. Contextual Distance Refining for Image Retrieval

    KAUST Repository

    Islam, Almasri

    2014-01-01

    Recently, a number of methods have been proposed to improve image retrieval accuracy by capturing context information. These methods try to compensate for the fact that a visually less similar image might be more relevant because it depicts the same object. We propose a new quick method for refining any pairwise distance metric, it works by iteratively discovering the object in the image from the most similar images, and then refine the distance metric accordingly. Test show that our technique improves over the state of art in terms of accuracy over the MPEG7 dataset.

  19. Contextual Distance Refining for Image Retrieval

    KAUST Repository

    Islam, Almasri

    2014-09-16

    Recently, a number of methods have been proposed to improve image retrieval accuracy by capturing context information. These methods try to compensate for the fact that a visually less similar image might be more relevant because it depicts the same object. We propose a new quick method for refining any pairwise distance metric, it works by iteratively discovering the object in the image from the most similar images, and then refine the distance metric accordingly. Test show that our technique improves over the state of art in terms of accuracy over the MPEG7 dataset.

  20. Improving biomedical information retrieval by linear combinations of different query expansion techniques.

    Science.gov (United States)

    Abdulla, Ahmed AbdoAziz Ahmed; Lin, Hongfei; Xu, Bo; Banbhrani, Santosh Kumar

    2016-07-25

    Biomedical literature retrieval is becoming increasingly complex, and there is a fundamental need for advanced information retrieval systems. Information Retrieval (IR) programs scour unstructured materials such as text documents in large reserves of data that are usually stored on computers. IR is related to the representation, storage, and organization of information items, as well as to access. In IR one of the main problems is to determine which documents are relevant and which are not to the user's needs. Under the current regime, users cannot precisely construct queries in an accurate way to retrieve particular pieces of data from large reserves of data. Basic information retrieval systems are producing low-quality search results. In our proposed system for this paper we present a new technique to refine Information Retrieval searches to better represent the user's information need in order to enhance the performance of information retrieval by using different query expansion techniques and apply a linear combinations between them, where the combinations was linearly between two expansion results at one time. Query expansions expand the search query, for example, by finding synonyms and reweighting original terms. They provide significantly more focused, particularized search results than do basic search queries. The retrieval performance is measured by some variants of MAP (Mean Average Precision) and according to our experimental results, the combination of best results of query expansion is enhanced the retrieved documents and outperforms our baseline by 21.06 %, even it outperforms a previous study by 7.12 %. We propose several query expansion techniques and their combinations (linearly) to make user queries more cognizable to search engines and to produce higher-quality search results.

  1. Active learning methods for interactive image retrieval.

    Science.gov (United States)

    Gosselin, Philippe Henri; Cord, Matthieu

    2008-07-01

    Active learning methods have been considered with increased interest in the statistical learning community. Initially developed within a classification framework, a lot of extensions are now being proposed to handle multimedia applications. This paper provides algorithms within a statistical framework to extend active learning for online content-based image retrieval (CBIR). The classification framework is presented with experiments to compare several powerful classification techniques in this information retrieval context. Focusing on interactive methods, active learning strategy is then described. The limitations of this approach for CBIR are emphasized before presenting our new active selection process RETIN. First, as any active method is sensitive to the boundary estimation between classes, the RETIN strategy carries out a boundary correction to make the retrieval process more robust. Second, the criterion of generalization error to optimize the active learning selection is modified to better represent the CBIR objective of database ranking. Third, a batch processing of images is proposed. Our strategy leads to a fast and efficient active learning scheme to retrieve sets of online images (query concept). Experiments on large databases show that the RETIN method performs well in comparison to several other active strategies.

  2. Proceedings of the international society for optical engineering biomedical image processing 2

    International Nuclear Information System (INIS)

    Bovik, A.G.; Howard, V.

    1991-01-01

    This book contains the proceedings of biomedical image processing. Topics covered include: Filtering and reconstruction of biomedical images; analysis, classification and recognition of biomedical images; and 3-D microscopy

  3. Terahertz Imaging for Biomedical Applications Pattern Recognition and Tomographic Reconstruction

    CERN Document Server

    Yin, Xiaoxia; Abbott, Derek

    2012-01-01

    Terahertz Imaging for Biomedical Applications: Pattern Recognition and Tomographic Reconstruction presents the necessary algorithms needed to assist screening, diagnosis, and treatment, and these algorithms will play a critical role in the accurate detection of abnormalities present in biomedical imaging. Terahertz biomedical imaging has become an area of interest due to its ability to simultaneously acquire both image and spectral information. Terahertz imaging systems are being commercialized with an increasing number of trials performed in a biomedical setting. Terahertz tomographic imaging and detection technology contributes to the ability to identify opaque objects with clear boundaries,and would be useful to both in vivo and ex vivo environments. This book also: Introduces terahertz radiation techniques and provides a number of topical examples of signal and image processing, as well as machine learning Presents the most recent developments in an emerging field, terahertz radiation Utilizes new methods...

  4. An unsupervised strategy for biomedical image segmentation

    Directory of Open Access Journals (Sweden)

    Roberto Rodríguez

    2010-09-01

    Full Text Available Roberto Rodríguez1, Rubén Hernández21Digital Signal Processing Group, Institute of Cybernetics, Mathematics, and Physics, Havana, Cuba; 2Interdisciplinary Professional Unit of Engineering and Advanced Technology, IPN, MexicoAbstract: Many segmentation techniques have been published, and some of them have been widely used in different application problems. Most of these segmentation techniques have been motivated by specific application purposes. Unsupervised methods, which do not assume any prior scene knowledge can be learned to help the segmentation process, and are obviously more challenging than the supervised ones. In this paper, we present an unsupervised strategy for biomedical image segmentation using an algorithm based on recursively applying mean shift filtering, where entropy is used as a stopping criterion. This strategy is proven with many real images, and a comparison is carried out with manual segmentation. With the proposed strategy, errors less than 20% for false positives and 0% for false negatives are obtained.Keywords: segmentation, mean shift, unsupervised segmentation, entropy

  5. CDAPubMed: a browser extension to retrieve EHR-based biomedical literature

    Directory of Open Access Journals (Sweden)

    Perez-Rey David

    2012-04-01

    Full Text Available Abstract Background Over the last few decades, the ever-increasing output of scientific publications has led to new challenges to keep up to date with the literature. In the biomedical area, this growth has introduced new requirements for professionals, e.g., physicians, who have to locate the exact papers that they need for their clinical and research work amongst a huge number of publications. Against this backdrop, novel information retrieval methods are even more necessary. While web search engines are widespread in many areas, facilitating access to all kinds of information, additional tools are required to automatically link information retrieved from these engines to specific biomedical applications. In the case of clinical environments, this also means considering aspects such as patient data security and confidentiality or structured contents, e.g., electronic health records (EHRs. In this scenario, we have developed a new tool to facilitate query building to retrieve scientific literature related to EHRs. Results We have developed CDAPubMed, an open-source web browser extension to integrate EHR features in biomedical literature retrieval approaches. Clinical users can use CDAPubMed to: (i load patient clinical documents, i.e., EHRs based on the Health Level 7-Clinical Document Architecture Standard (HL7-CDA, (ii identify relevant terms for scientific literature search in these documents, i.e., Medical Subject Headings (MeSH, automatically driven by the CDAPubMed configuration, which advanced users can optimize to adapt to each specific situation, and (iii generate and launch literature search queries to a major search engine, i.e., PubMed, to retrieve citations related to the EHR under examination. Conclusions CDAPubMed is a platform-independent tool designed to facilitate literature searching using keywords contained in specific EHRs. CDAPubMed is visually integrated, as an extension of a widespread web browser, within the standard

  6. Retrieval and classification of food images.

    Science.gov (United States)

    Farinella, Giovanni Maria; Allegra, Dario; Moltisanti, Marco; Stanco, Filippo; Battiato, Sebastiano

    2016-10-01

    Automatic food understanding from images is an interesting challenge with applications in different domains. In particular, food intake monitoring is becoming more and more important because of the key role that it plays in health and market economies. In this paper, we address the study of food image processing from the perspective of Computer Vision. As first contribution we present a survey of the studies in the context of food image processing from the early attempts to the current state-of-the-art methods. Since retrieval and classification engines able to work on food images are required to build automatic systems for diet monitoring (e.g., to be embedded in wearable cameras), we focus our attention on the aspect of the representation of the food images because it plays a fundamental role in the understanding engines. The food retrieval and classification is a challenging task since the food presents high variableness and an intrinsic deformability. To properly study the peculiarities of different image representations we propose the UNICT-FD1200 dataset. It was composed of 4754 food images of 1200 distinct dishes acquired during real meals. Each food plate is acquired multiple times and the overall dataset presents both geometric and photometric variabilities. The images of the dataset have been manually labeled considering 8 categories: Appetizer, Main Course, Second Course, Single Course, Side Dish, Dessert, Breakfast, Fruit. We have performed tests employing different representations of the state-of-the-art to assess the related performances on the UNICT-FD1200 dataset. Finally, we propose a new representation based on the perceptual concept of Anti-Textons which is able to encode spatial information between Textons outperforming other representations in the context of food retrieval and Classification. Copyright © 2016 Elsevier Ltd. All rights reserved.

  7. Biomedical imaging graduate curricula and courses: report from the 2005 Whitaker Biomedical Engineering Educational Summit.

    Science.gov (United States)

    Louie, Angelique; Izatt, Joseph; Ferrara, Katherine

    2006-02-01

    We present an overview of graduate programs in biomedical imaging that are currently available in the US. Special attention is given to the emerging technologies of molecular imaging and biophotonics. Discussions from the workshop on Graduate Imaging at the 2005 Whitaker Educational Summit meeting are summarized.

  8. Semantics-driven modelling of user preferences for information retrieval in the biomedical domain.

    Science.gov (United States)

    Gladun, Anatoly; Rogushina, Julia; Valencia-García, Rafael; Béjar, Rodrigo Martínez

    2013-03-01

    A large amount of biomedical and genomic data are currently available on the Internet. However, data are distributed into heterogeneous biological information sources, with little or even no organization. Semantic technologies provide a consistent and reliable basis with which to confront the challenges involved in the organization, manipulation and visualization of data and knowledge. One of the knowledge representation techniques used in semantic processing is the ontology, which is commonly defined as a formal and explicit specification of a shared conceptualization of a domain of interest. The work presented here introduces a set of interoperable algorithms that can use domain and ontological information to improve information-retrieval processes. This work presents an ontology-based information-retrieval system for the biomedical domain. This system, with which some experiments have been carried out that are described in this paper, is based on the use of domain ontologies for the creation and normalization of lightweight ontologies that represent user preferences in a determined domain in order to improve information-retrieval processes.

  9. Storage and retrieval of large digital images

    Science.gov (United States)

    Bradley, J.N.

    1998-01-20

    Image compression and viewing are implemented with (1) a method for performing DWT-based compression on a large digital image with a computer system possessing a two-level system of memory and (2) a method for selectively viewing areas of the image from its compressed representation at multiple resolutions and, if desired, in a client-server environment. The compression of a large digital image I(x,y) is accomplished by first defining a plurality of discrete tile image data subsets T{sub ij}(x,y) that, upon superposition, form the complete set of image data I(x,y). A seamless wavelet-based compression process is effected on I(x,y) that is comprised of successively inputting the tiles T{sub ij}(x,y) in a selected sequence to a DWT routine, and storing the resulting DWT coefficients in a first primary memory. These coefficients are periodically compressed and transferred to a secondary memory to maintain sufficient memory in the primary memory for data processing. The sequence of DWT operations on the tiles T{sub ij}(x,y) effectively calculates a seamless DWT of I(x,y). Data retrieval consists of specifying a resolution and a region of I(x,y) for display. The subset of stored DWT coefficients corresponding to each requested scene is determined and then decompressed for input to an inverse DWT, the output of which forms the image display. The repeated process whereby image views are specified may take the form an interaction with a computer pointing device on an image display from a previous retrieval. 6 figs.

  10. Advances in biomedical signal and image processing – A systematic review

    Directory of Open Access Journals (Sweden)

    J. Rajeswari

    Full Text Available Biomedical signal and image processing establish a dynamic area of specialization in both academic as well as research aspects of biomedical engineering. The concepts of signal and image processing have been widely used for extracting the physiological information in implementing many clinical procedures for sophisticated medical practices and applications. In this paper, the relationship between electrophysiological signals, i.e., electrocardiogram (ECG, electromyogram (EMG, electroencephalogram (EEG and functional image processing and their derived interactions have been discussed. Examples have been investigated in various case studies such as neurosciences, functional imaging, and cardiovascular system, by using different algorithms and methods. The interaction between the extracted information obtained from multiple signals and modalities seems to be very promising. The advanced algorithms and methods in the area of information retrieval based on time-frequency representation have been investigated. Finally, some examples of algorithms have been discussed in which the electrophysiological signals and functional images have been properly extracted and have a significant impact on various biomedical applications. Keywords: Biomedical signals and images, Processing, Analysis

  11. An optimal big data workflow for biomedical image analysis

    Directory of Open Access Journals (Sweden)

    Aurelle Tchagna Kouanou

    Full Text Available Background and objective: In the medical field, data volume is increasingly growing, and traditional methods cannot manage it efficiently. In biomedical computation, the continuous challenges are: management, analysis, and storage of the biomedical data. Nowadays, big data technology plays a significant role in the management, organization, and analysis of data, using machine learning and artificial intelligence techniques. It also allows a quick access to data using the NoSQL database. Thus, big data technologies include new frameworks to process medical data in a manner similar to biomedical images. It becomes very important to develop methods and/or architectures based on big data technologies, for a complete processing of biomedical image data. Method: This paper describes big data analytics for biomedical images, shows examples reported in the literature, briefly discusses new methods used in processing, and offers conclusions. We argue for adapting and extending related work methods in the field of big data software, using Hadoop and Spark frameworks. These provide an optimal and efficient architecture for biomedical image analysis. This paper thus gives a broad overview of big data analytics to automate biomedical image diagnosis. A workflow with optimal methods and algorithm for each step is proposed. Results: Two architectures for image classification are suggested. We use the Hadoop framework to design the first, and the Spark framework for the second. The proposed Spark architecture allows us to develop appropriate and efficient methods to leverage a large number of images for classification, which can be customized with respect to each other. Conclusions: The proposed architectures are more complete, easier, and are adaptable in all of the steps from conception. The obtained Spark architecture is the most complete, because it facilitates the implementation of algorithms with its embedded libraries. Keywords: Biomedical images, Big

  12. An enhanced approach for biomedical image restoration using image fusion techniques

    Science.gov (United States)

    Karam, Ghada Sabah; Abbas, Fatma Ismail; Abood, Ziad M.; Kadhim, Kadhim K.; Karam, Nada S.

    2018-05-01

    Biomedical image is generally noisy and little blur due to the physical mechanisms of the acquisition process, so one of the common degradations in biomedical image is their noise and poor contrast. The idea of biomedical image enhancement is to improve the quality of the image for early diagnosis. In this paper we are using Wavelet Transformation to remove the Gaussian noise from biomedical images: Positron Emission Tomography (PET) image and Radiography (Radio) image, in different color spaces (RGB, HSV, YCbCr), and we perform the fusion of the denoised images resulting from the above denoising techniques using add image method. Then some quantive performance metrics such as signal -to -noise ratio (SNR), peak signal-to-noise ratio (PSNR), and Mean Square Error (MSE), etc. are computed. Since this statistical measurement helps in the assessment of fidelity and image quality. The results showed that our approach can be applied of Image types of color spaces for biomedical images.

  13. Image Retrieval Berdasarkan Fitur Warna, Bentuk, dan Tekstur

    Directory of Open Access Journals (Sweden)

    Rita Layona

    2014-12-01

    Full Text Available Along with the times, information retrieval is no longer just on textual data, but also the visual data. The technique was originally used is Text-Based Image Retrieval (TBIR, but the technique still has some shortcomings such as the relevance of the picture successfully retrieved, and the specific space required to store meta-data in the image. Seeing the shortage of Text-Based Image Retrieval techniques, then other techniques were developed, namely Image Retrieval based on content or commonly called Content Based Image Retrieval (CBIR. In this research, CBIR will be discussed based on color, shape and texture using a color histogram, Gabor and SIFT. This study aimed to compare the results of image retrieval with some of these techniques. The results obtained are by combining color, shape and texture features, the performance of the system can be improved.

  14. Enhancing Image Retrieval System Using Content Based Search ...

    African Journals Online (AJOL)

    The output shows more efficiency in retrieval because instead of performing the search on the entire image database, the image category option directs the retrieval engine to the specified category. Also, there is provision to update or modify the different image categories in the image database as need arise. Keywords: ...

  15. G-Bean: an ontology-graph based web tool for biomedical literature retrieval.

    Science.gov (United States)

    Wang, James Z; Zhang, Yuanyuan; Dong, Liang; Li, Lin; Srimani, Pradip K; Yu, Philip S

    2014-01-01

    Currently, most people use NCBI's PubMed to search the MEDLINE database, an important bibliographical information source for life science and biomedical information. However, PubMed has some drawbacks that make it difficult to find relevant publications pertaining to users' individual intentions, especially for non-expert users. To ameliorate the disadvantages of PubMed, we developed G-Bean, a graph based biomedical search engine, to search biomedical articles in MEDLINE database more efficiently. G-Bean addresses PubMed's limitations with three innovations: (1) Parallel document index creation: a multithreaded index creation strategy is employed to generate the document index for G-Bean in parallel; (2) Ontology-graph based query expansion: an ontology graph is constructed by merging four major UMLS (Version 2013AA) vocabularies, MeSH, SNOMEDCT, CSP and AOD, to cover all concepts in National Library of Medicine (NLM) database; a Personalized PageRank algorithm is used to compute concept relevance in this ontology graph and the Term Frequency - Inverse Document Frequency (TF-IDF) weighting scheme is used to re-rank the concepts. The top 500 ranked concepts are selected for expanding the initial query to retrieve more accurate and relevant information; (3) Retrieval and re-ranking of documents based on user's search intention: after the user selects any article from the existing search results, G-Bean analyzes user's selections to determine his/her true search intention and then uses more relevant and more specific terms to retrieve additional related articles. The new articles are presented to the user in the order of their relevance to the already selected articles. Performance evaluation with 106 OHSUMED benchmark queries shows that G-Bean returns more relevant results than PubMed does when using these queries to search the MEDLINE database. PubMed could not even return any search result for some OHSUMED queries because it failed to form the appropriate Boolean

  16. A Part-Of-Speech term weighting scheme for biomedical information retrieval.

    Science.gov (United States)

    Wang, Yanshan; Wu, Stephen; Li, Dingcheng; Mehrabi, Saeed; Liu, Hongfang

    2016-10-01

    In the era of digitalization, information retrieval (IR), which retrieves and ranks documents from large collections according to users' search queries, has been popularly applied in the biomedical domain. Building patient cohorts using electronic health records (EHRs) and searching literature for topics of interest are some IR use cases. Meanwhile, natural language processing (NLP), such as tokenization or Part-Of-Speech (POS) tagging, has been developed for processing clinical documents or biomedical literature. We hypothesize that NLP can be incorporated into IR to strengthen the conventional IR models. In this study, we propose two NLP-empowered IR models, POS-BoW and POS-MRF, which incorporate automatic POS-based term weighting schemes into bag-of-word (BoW) and Markov Random Field (MRF) IR models, respectively. In the proposed models, the POS-based term weights are iteratively calculated by utilizing a cyclic coordinate method where golden section line search algorithm is applied along each coordinate to optimize the objective function defined by mean average precision (MAP). In the empirical experiments, we used the data sets from the Medical Records track in Text REtrieval Conference (TREC) 2011 and 2012 and the Genomics track in TREC 2004. The evaluation on TREC 2011 and 2012 Medical Records tracks shows that, for the POS-BoW models, the mean improvement rates for IR evaluation metrics, MAP, bpref, and P@10, are 10.88%, 4.54%, and 3.82%, compared to the BoW models; and for the POS-MRF models, these rates are 13.59%, 8.20%, and 8.78%, compared to the MRF models. Additionally, we experimentally verify that the proposed weighting approach is superior to the simple heuristic and frequency based weighting approaches, and validate our POS category selection. Using the optimal weights calculated in this experiment, we tested the proposed models on the TREC 2004 Genomics track and obtained average of 8.63% and 10.04% improvement rates for POS-BoW and POS

  17. Ontology of gaps in content-based image retrieval.

    Science.gov (United States)

    Deserno, Thomas M; Antani, Sameer; Long, Rodney

    2009-04-01

    Content-based image retrieval (CBIR) is a promising technology to enrich the core functionality of picture archiving and communication systems (PACS). CBIR has a potential for making a strong impact in diagnostics, research, and education. Research as reported in the scientific literature, however, has not made significant inroads as medical CBIR applications incorporated into routine clinical medicine or medical research. The cause is often attributed (without supporting analysis) to the inability of these applications in overcoming the "semantic gap." The semantic gap divides the high-level scene understanding and interpretation available with human cognitive capabilities from the low-level pixel analysis of computers, based on mathematical processing and artificial intelligence methods. In this paper, we suggest a more systematic and comprehensive view of the concept of "gaps" in medical CBIR research. In particular, we define an ontology of 14 gaps that addresses the image content and features, as well as system performance and usability. In addition to these gaps, we identify seven system characteristics that impact CBIR applicability and performance. The framework we have created can be used a posteriori to compare medical CBIR systems and approaches for specific biomedical image domains and goals and a priori during the design phase of a medical CBIR application, as the systematic analysis of gaps provides detailed insight in system comparison and helps to direct future research.

  18. Design and implementation of a biomedical image database (BDIM).

    Science.gov (United States)

    Aubry, F; Badaoui, S; Kaplan, H; Di Paola, R

    1988-01-01

    We developed a biomedical image database (BDIM) which proposes a standardized representation of value arrays such as images and curves, and of their associated parameters, independently of their acquisition mode to make their transmission and processing easier. It includes three kinds of interactions, oriented to the users. The network concept was kept as a constraint to incorporate the BDIM in a distributed structure and we maintained compatibility with the ACR/NEMA communication protocol. The management of arrays and their associated parameters includes two distinct bases of objects, linked together via a gateway. The first one manages arrays according to their storage mode: long term storage on optionally on-line mass storage devices, and, for consultations, partial copies of long term stored arrays on hard disk. The second one manages the associated parameters and the gateway by means of the relational DBMS ORACLE. Parameters are grouped into relations. Some of them are in agreement with groups defined by the ACR/NEMA. The other relations describe objects resulting from processed initial objects. These new objects are not described by the ACR/NEMA but they can be inserted as shadow groups of ACR/NEMA description. The relations describing the storage and their pathname constitute the gateway. ORACLE distributed tools and the two-level storage technique will allow the integration of the BDIM into a distributed structure, Queries and array (alone or in sequences) retrieval module has access to the relations via a level in which a dictionary managed by ORACLE is included. This dictionary translates ACR/NEMA objects into objects that can be handled by the DBMS.(ABSTRACT TRUNCATED AT 250 WORDS)

  19. Modelling of chromatic contrast for retrieval of wallpaper images

    OpenAIRE

    Gao, Xiaohong W.; Wang, Yuanlei; Qian, Yu; Gao, Alice

    2015-01-01

    Colour remains one of the key factors in presenting an object and consequently has been widely applied in retrieval of images based on their visual contents. However, a colour appearance changes with the change of viewing surroundings, the phenomenon that has not been paid attention yet while performing colour-based image retrieval. To comprehend this effect, in this paper, a chromatic contrast model, CAMcc, is developed for the application of retrieval of colour intensive images, cementing t...

  20. A Statistical Approach to Retrieving Historical Manuscript Images without Recognition

    National Research Council Canada - National Science Library

    Rath, Toni M; Lavrenko, Victor; Manmatha, R

    2003-01-01

    ...), and word spotting -- an image matching approach (computationally expensive). In this work, the authors present a novel retrieval approach for historical document collections that does not require recognition...

  1. The Use of QBIC Content-Based Image Retrieval System

    Directory of Open Access Journals (Sweden)

    Ching-Yi Wu

    2004-03-01

    Full Text Available The fast increase in digital images has caught increasing attention on the development of image retrieval technologies. Content-based image retrieval (CBIR has become an important approach in retrieving image data from a large collection. This article reports our results on the use and users study of a CBIR system. Thirty-eight students majored in art and design were invited to use the IBM’s OBIC (Query by Image Content system through the Internet. Data from their information needs, behaviors, and retrieval strategies were collected through an in-depth interview, observation, and self-described think-aloud process. Important conclusions are:(1)There are four types of information needs for image data: implicit, inspirational, ever-changing, and purposive. The types of needs may change during the retrieval process. (2)CBIR is suitable for the example-type query, text retrieval is suitable for the scenario-type query, and image browsing is suitable for the symbolic query. (3)Different from text retrieval, detailed description of the query condition may lead to retrieval failure more easily. (4)CBIR is suitable for the domain-specific image collection, not for the images on the Word-Wide Web.[Article content in Chinese

  2. Biomedical Imaging and Computational Modeling in Biomechanics

    CERN Document Server

    Iacoviello, Daniela

    2013-01-01

    This book collects the state-of-art and new trends in image analysis and biomechanics. It covers a wide field of scientific and cultural topics, ranging from remodeling of bone tissue under the mechanical stimulus up to optimizing the performance of sports equipment, through the patient-specific modeling in orthopedics, microtomography and its application in oral and implant research, computational modeling in the field of hip prostheses, image based model development and analysis of the human knee joint, kinematics of the hip joint, micro-scale analysis of compositional and mechanical properties of dentin, automated techniques for cervical cell image analysis, and iomedical imaging and computational modeling in cardiovascular disease.   The book will be of interest to researchers, Ph.D students, and graduate students with multidisciplinary interests related to image analysis and understanding, medical imaging, biomechanics, simulation and modeling, experimental analysis.

  3. Mobile object retrieval in server-based image databases

    Science.gov (United States)

    Manger, D.; Pagel, F.; Widak, H.

    2013-05-01

    The increasing number of mobile phones equipped with powerful cameras leads to huge collections of user-generated images. To utilize the information of the images on site, image retrieval systems are becoming more and more popular to search for similar objects in an own image database. As the computational performance and the memory capacity of mobile devices are constantly increasing, this search can often be performed on the device itself. This is feasible, for example, if the images are represented with global image features or if the search is done using EXIF or textual metadata. However, for larger image databases, if multiple users are meant to contribute to a growing image database or if powerful content-based image retrieval methods with local features are required, a server-based image retrieval backend is needed. In this work, we present a content-based image retrieval system with a client server architecture working with local features. On the server side, the scalability to large image databases is addressed with the popular bag-of-word model with state-of-the-art extensions. The client end of the system focuses on a lightweight user interface presenting the most similar images of the database highlighting the visual information which is common with the query image. Additionally, new images can be added to the database making it a powerful and interactive tool for mobile contentbased image retrieval.

  4. Ultrasmall lanthanide oxide nanoparticles for biomedical imaging and therapy

    CERN Document Server

    Lee, Gang Ho

    2014-01-01

    Most books discuss general and broad topics regarding molecular imagings. However, Ultrasmall Lanthanide Oxide Nanoparticles for Biomedical Imaging and Therapy, will mainly focus on lanthanide oxide nanoparticles for molecular imaging and therapeutics. Multi-modal imaging capabilities will discussed, along with up-converting FI by using lanthanide oxide nanoparticles. The synthesis will cover polyol synthesis of lanthanide oxide nanoparticles, Surface coatings with biocompatible and hydrophilic ligands will be discussed and TEM images and dynamic light scattering (DLS) patterns will be

  5. Strict integrity control of biomedical images

    Science.gov (United States)

    Coatrieux, Gouenou; Maitre, Henri; Sankur, Bulent

    2001-08-01

    The control of the integrity and authentication of medical images is becoming ever more important within the Medical Information Systems (MIS). The intra- and interhospital exchange of images, such as in the PACS (Picture Archiving and Communication Systems), and the ease of copying, manipulation and distribution of images have brought forth the security aspects. In this paper we focus on the role of watermarking for MIS security and address the problem of integrity control of medical images. We discuss alternative schemes to extract verification signatures and compare their tamper detection performance.

  6. PageRank without hyperlinks: Reranking with PubMed related article networks for biomedical text retrieval

    Directory of Open Access Journals (Sweden)

    Lin Jimmy

    2008-06-01

    Full Text Available Abstract Background Graph analysis algorithms such as PageRank and HITS have been successful in Web environments because they are able to extract important inter-document relationships from manually-created hyperlinks. We consider the application of these techniques to biomedical text retrieval. In the current PubMed® search interface, a MEDLINE® citation is connected to a number of related citations, which are in turn connected to other citations. Thus, a MEDLINE record represents a node in a vast content-similarity network. This article explores the hypothesis that these networks can be exploited for text retrieval, in the same manner as hyperlink graphs on the Web. Results We conducted a number of reranking experiments using the TREC 2005 genomics track test collection in which scores extracted from PageRank and HITS analysis were combined with scores returned by an off-the-shelf retrieval engine. Experiments demonstrate that incorporating PageRank scores yields significant improvements in terms of standard ranked-retrieval metrics. Conclusion The link structure of content-similarity networks can be exploited to improve the effectiveness of information retrieval systems. These results generalize the applicability of graph analysis algorithms to text retrieval in the biomedical domain.

  7. PageRank without hyperlinks: reranking with PubMed related article networks for biomedical text retrieval.

    Science.gov (United States)

    Lin, Jimmy

    2008-06-06

    Graph analysis algorithms such as PageRank and HITS have been successful in Web environments because they are able to extract important inter-document relationships from manually-created hyperlinks. We consider the application of these techniques to biomedical text retrieval. In the current PubMed(R) search interface, a MEDLINE(R) citation is connected to a number of related citations, which are in turn connected to other citations. Thus, a MEDLINE record represents a node in a vast content-similarity network. This article explores the hypothesis that these networks can be exploited for text retrieval, in the same manner as hyperlink graphs on the Web. We conducted a number of reranking experiments using the TREC 2005 genomics track test collection in which scores extracted from PageRank and HITS analysis were combined with scores returned by an off-the-shelf retrieval engine. Experiments demonstrate that incorporating PageRank scores yields significant improvements in terms of standard ranked-retrieval metrics. The link structure of content-similarity networks can be exploited to improve the effectiveness of information retrieval systems. These results generalize the applicability of graph analysis algorithms to text retrieval in the biomedical domain.

  8. Biomedical Image Analysis: Rapid prototyping with Mathematica

    NARCIS (Netherlands)

    Haar Romenij, ter B.M.; Almsick, van M.A.

    2004-01-01

    Digital acquisition techniques have caused an explosion in the production of medical images, especially with the advent of multi-slice CT and volume MRI. One third of the financial investments in a modern hospital's equipment are dedicated to imaging. Emerging screening programs add to this flood of

  9. Automatic medical image annotation and keyword-based image retrieval using relevance feedback.

    Science.gov (United States)

    Ko, Byoung Chul; Lee, JiHyeon; Nam, Jae-Yeal

    2012-08-01

    This paper presents novel multiple keywords annotation for medical images, keyword-based medical image retrieval, and relevance feedback method for image retrieval for enhancing image retrieval performance. For semantic keyword annotation, this study proposes a novel medical image classification method combining local wavelet-based center symmetric-local binary patterns with random forests. For keyword-based image retrieval, our retrieval system use the confidence score that is assigned to each annotated keyword by combining probabilities of random forests with predefined body relation graph. To overcome the limitation of keyword-based image retrieval, we combine our image retrieval system with relevance feedback mechanism based on visual feature and pattern classifier. Compared with other annotation and relevance feedback algorithms, the proposed method shows both improved annotation performance and accurate retrieval results.

  10. Content Based Retrieval System for Magnetic Resonance Images

    International Nuclear Information System (INIS)

    Trojachanets, Katarina

    2010-01-01

    The amount of medical images is continuously increasing as a consequence of the constant growth and development of techniques for digital image acquisition. Manual annotation and description of each image is impractical, expensive and time consuming approach. Moreover, it is an imprecise and insufficient way for describing all information stored in medical images. This induces the necessity for developing efficient image storage, annotation and retrieval systems. Content based image retrieval (CBIR) emerges as an efficient approach for digital image retrieval from large databases. It includes two phases. In the first phase, the visual content of the image is analyzed and the feature extraction process is performed. An appropriate descriptor, namely, feature vector is then associated with each image. These descriptors are used in the second phase, i.e. the retrieval process. With the aim to improve the efficiency and precision of the content based image retrieval systems, feature extraction and automatic image annotation techniques are subject of continuous researches and development. Including the classification techniques in the retrieval process enables automatic image annotation in an existing CBIR system. It contributes to more efficient and easier image organization in the system.Applying content based retrieval in the field of magnetic resonance is a big challenge. Magnetic resonance imaging is an image based diagnostic technique which is widely used in medical environment. According to this, the number of magnetic resonance images is enormously growing. Magnetic resonance images provide plentiful medical information, high resolution and specific nature. Thus, the capability of CBIR systems for image retrieval from large database is of great importance for efficient analysis of this kind of images. The aim of this thesis is to propose content based retrieval system architecture for magnetic resonance images. To provide the system efficiency, feature

  11. An Effective Combined Feature For Web Based Image Retrieval

    Directory of Open Access Journals (Sweden)

    H.M.R.B Herath

    2015-08-01

    Full Text Available Abstract Technology advances as well as the emergence of large scale multimedia applications and the revolution of the World Wide Web has changed the world into a digital age. Anybody can use their mobile phone to take a photo at any time anywhere and upload that image to ever growing image databases. Development of effective techniques for visual and multimedia retrieval systems is one of the most challenging and important directions of the future research. This paper proposes an effective combined feature for web based image retrieval. Frequently used colour and texture features are explored in order to develop a combined feature for this purpose. Widely used three colour features Colour moments Colour coherence vector and Colour Correlogram and three texture features Grey Level Co-occurrence matrix Tamura features and Gabor filter were analyzed for their performance. Precision and Recall were used to evaluate the performance of each of these techniques. By comparing precision and recall values the methods that performed best were taken and combined to form a hybrid feature. The developed combined feature was evaluated by developing a web based CBIR system. A web crawler was used to first crawl through Web sites and images found in those sites are downloaded and the combined feature representation technique was used to extract image features. The test results indicated that this web system can be used to index web images with the combined feature representation schema and to find similar images. Random image retrievals using the web system shows that the combined feature can be used to retrieve images belonging to the general image domain. Accuracy of the retrieval can be noted high for natural images like outdoor scenes images of flowers etc. Also images which have a similar colour and texture distribution were retrieved as similar even though the images were belonging to deferent semantic categories. This can be ideal for an artist who wants

  12. Design and implementation of Metta, a metasearch engine for biomedical literature retrieval intended for systematic reviewers.

    Science.gov (United States)

    Smalheiser, Neil R; Lin, Can; Jia, Lifeng; Jiang, Yu; Cohen, Aaron M; Yu, Clement; Davis, John M; Adams, Clive E; McDonagh, Marian S; Meng, Weiyi

    2014-01-01

    systematic reviewers in retrieving, filtering and assessing publications. As such, Metta may find wide utility for anyone who is carrying out a comprehensive search of the biomedical literature.

  13. Coherent fiber supercontinuum laser for nonlinear biomedical imaging

    DEFF Research Database (Denmark)

    Tu, Haohua; Liu, Yuan; Liu, Xiaomin

    2012-01-01

    Nonlinear biomedical imaging has not benefited from the well-known techniques of fiber supercontinuum generation for reasons such as poor coherence (or high noise), insufficient controllability, low spectral power intensity, and inadequate portability. Fortunately, a few techniques involving...... nonlinear fiber optics and femtosecond fiber laser development have emerged to overcome these critical limitations. These techniques pave the way for conducting point-of-care nonlinear biomedical imaging by a low-maintenance cost-effective coherent fiber supercontinuum laser, which covers a broad emission...... wavelength of 350-1700 nm. A prototype of this laser has been demonstrated in label-free multimodal nonlinear imaging of cell and tissue samples.© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only....

  14. Improved image retrieval based on fuzzy colour feature vector

    Science.gov (United States)

    Ben-Ahmeida, Ahlam M.; Ben Sasi, Ahmed Y.

    2013-03-01

    One of Image indexing techniques is the Content-Based Image Retrieval which is an efficient way for retrieving images from the image database automatically based on their visual contents such as colour, texture, and shape. In this paper will be discuss how using content-based image retrieval (CBIR) method by colour feature extraction and similarity checking. By dividing the query image and all images in the database into pieces and extract the features of each part separately and comparing the corresponding portions in order to increase the accuracy in the retrieval. The proposed approach is based on the use of fuzzy sets, to overcome the problem of curse of dimensionality. The contribution of colour of each pixel is associated to all the bins in the histogram using fuzzy-set membership functions. As a result, the Fuzzy Colour Histogram (FCH), outperformed the Conventional Colour Histogram (CCH) in image retrieving, due to its speedy results, where were images represented as signatures that took less size of memory, depending on the number of divisions. The results also showed that FCH is less sensitive and more robust to brightness changes than the CCH with better retrieval recall values.

  15. Computational Phase Imaging for Biomedical Applications

    Science.gov (United States)

    Nguyen, Tan Huu

    When a sample is illuminated by an imaging field, its fingerprints are left on the amplitude and the phase of the emerging wave. Capturing the information of the wavefront grants us a deeper understanding of the optical properties of the sample, and of the light-matter interaction. While the amplitude information has been intensively studied, the use of the phase information has been less common. Because all detectors are sensitive to intensity, not phase, wavefront measurements are significantly more challenging. Deploying optical interferometry to measure phase through phase-intensity conversion, quantitative phase imaging (QPI) has recently gained tremendous success in material and life sciences. The first topic of this dissertation describes our effort to develop a new QPI setup, named transmission Spatial Light Interference Microscopy (tSLIM), that uses the twisted nematic liquid-crystal (TNLC) modulators. Compared to the established SLIM technique, tSLIM is much less expensive to build than its predecessor (SLIM) while maintaining significant performance. The tSLIM system uses parallel aligned liquid-crystal (PANLC) modulators, has a slightly smaller signal-to-noise Ratio (SNR), and a more complicated model for the image formation. However, such complexity is well addressed by computing. Most importantly, tSLIM uses TNLC modulators that are popular in display LCDs. Therefore, the total cost of the system is significantly reduced. Alongside developing new imaging modalities, we also improved current QPI imaging systems. In practice, an incident field to the sample is rarely perfectly spatially coherent, i.e., plane wave. It is generally partially coherent; i.e., it comprises of many incoherent plane waves coming from multiple directions. This illumination yields artifacts in the phase measurement results, e.g., halo and phase-underestimation. One solution is using a very bright source, e.g., a laser, which can be spatially filtered very well. However, the

  16. Analyser-based x-ray imaging for biomedical research

    International Nuclear Information System (INIS)

    Suortti, Pekka; Keyriläinen, Jani; Thomlinson, William

    2013-01-01

    Analyser-based imaging (ABI) is one of the several phase-contrast x-ray imaging techniques being pursued at synchrotron radiation facilities. With advancements in compact source technology, there is a possibility that ABI will become a clinical imaging modality. This paper presents the history of ABI as it has developed from its laboratory source to synchrotron imaging. The fundamental physics of phase-contrast imaging is presented both in a general sense and specifically for ABI. The technology is dependent on the use of perfect crystal monochromator optics. The theory of the x-ray optics is developed and presented in a way that will allow optimization of the imaging for specific biomedical systems. The advancement of analytical algorithms to produce separate images of the sample absorption, refraction angle map and small-angle x-ray scattering is detailed. Several detailed applications to biomedical imaging are presented to illustrate the broad range of systems and body sites studied preclinically to date: breast, cartilage and bone, soft tissue and organs. Ultimately, the application of ABI in clinical imaging will depend partly on the availability of compact sources with sufficient x-ray intensity comparable with that of the current synchrotron environment. (paper)

  17. Pareto-depth for multiple-query image retrieval.

    Science.gov (United States)

    Hsiao, Ko-Jen; Calder, Jeff; Hero, Alfred O

    2015-02-01

    Most content-based image retrieval systems consider either one single query, or multiple queries that include the same object or represent the same semantic information. In this paper, we consider the content-based image retrieval problem for multiple query images corresponding to different image semantics. We propose a novel multiple-query information retrieval algorithm that combines the Pareto front method with efficient manifold ranking. We show that our proposed algorithm outperforms state of the art multiple-query retrieval algorithms on real-world image databases. We attribute this performance improvement to concavity properties of the Pareto fronts, and prove a theoretical result that characterizes the asymptotic concavity of the fronts.

  18. KISTI at TREC 2014 Clinical Decision Support Track: Concept-based Document Re-ranking to Biomedical Information Retrieval

    Science.gov (United States)

    2014-11-01

    sematic type. Injury or Poisoning inpo T037 Anatomical Abnormality anab T190 Given a document D, a concept vector = {1, 2, … , ...integrating biomedical terminology . Nucleic acids research 32, Database issue (2004), 267–270. 5. Chapman, W.W., Hillert, D., Velupillai, S., et...Conference (TREC), (2011). 9. Koopman, B. and Zuccon, G. Understanding negation and family history to improve clinical information retrieval. Proceedings

  19. Visualization and classification in biomedical terahertz pulsed imaging

    International Nuclear Information System (INIS)

    Loeffler, Torsten; Siebert, Karsten; Czasch, Stephanie; Bauer, Tobias; Roskos, Hartmut G

    2002-01-01

    'Visualization' in imaging is the process of extracting useful information from raw data in such a way that meaningful physical contrasts are developed. 'Classification' is the subsequent process of defining parameter ranges which allow us to identify elements of images such as different tissues or different objects. In this paper, we explore techniques for visualization and classification in terahertz pulsed imaging (TPI) for biomedical applications. For archived (formalin-fixed, alcohol-dehydrated and paraffin-mounted) test samples, we investigate both time- and frequency-domain methods based on bright- and dark-field TPI. Successful tissue classification is demonstrated

  20. Discovering biomedical semantic relations in PubMed queries for information retrieval and database curation.

    Science.gov (United States)

    Huang, Chung-Chi; Lu, Zhiyong

    2016-01-01

    Identifying relevant papers from the literature is a common task in biocuration. Most current biomedical literature search systems primarily rely on matching user keywords. Semantic search, on the other hand, seeks to improve search accuracy by understanding the entities and contextual relations in user keywords. However, past research has mostly focused on semantically identifying biological entities (e.g. chemicals, diseases and genes) with little effort on discovering semantic relations. In this work, we aim to discover biomedical semantic relations in PubMed queries in an automated and unsupervised fashion. Specifically, we focus on extracting and understanding the contextual information (or context patterns) that is used by PubMed users to represent semantic relations between entities such as 'CHEMICAL-1 compared to CHEMICAL-2' With the advances in automatic named entity recognition, we first tag entities in PubMed queries and then use tagged entities as knowledge to recognize pattern semantics. More specifically, we transform PubMed queries into context patterns involving participating entities, which are subsequently projected to latent topics via latent semantic analysis (LSA) to avoid the data sparseness and specificity issues. Finally, we mine semantically similar contextual patterns or semantic relations based on LSA topic distributions. Our two separate evaluation experiments of chemical-chemical (CC) and chemical-disease (CD) relations show that the proposed approach significantly outperforms a baseline method, which simply measures pattern semantics by similarity in participating entities. The highest performance achieved by our approach is nearly 0.9 and 0.85 respectively for the CC and CD task when compared against the ground truth in terms of normalized discounted cumulative gain (nDCG), a standard measure of ranking quality. These results suggest that our approach can effectively identify and return related semantic patterns in a ranked order

  1. Nonlinear Polarimetric Microscopy for Biomedical Imaging

    Science.gov (United States)

    Samim, Masood

    A framework for the nonlinear optical polarimetry and polarimetric microscopy is developed. Mathematical equations are derived in terms of linear and nonlinear Stokes Mueller formalism, which comprehensively characterize the polarization properties of the incoming and outgoing radiations, and provide structural information about the organization of the investigated materials. The algebraic formalism developed in this thesis simplifies many predictions for a nonlinear polarimetry study and provides an intuitive understanding of various polarization properties for radiations and the intervening medium. For polarimetric microscopy experiments, a custom fast-scanning differential polarization microscope is developed, which is also capable of real-time three-dimensional imaging. The setup is equipped with a pair of high-speed resonant and galvanometric scanning mirrors, and supplemented by advanced adaptive optics and data acquisition modules. The scanning mirrors when combined with the adaptive optics deformable mirror enable fast 3D imaging. Deformable membrane mirrors and genetic algorithm optimization routines are employed to improve the imaging conditions including correcting the optical aberrations, maximizing signal intensities, and minimizing point-spread-functions of the focal volume. A field-programmable-gate array (FPGA) chip is exploited to rapidly acquire and process the multidimensional data. Using the nonlinear optical polarimetry framework and the home-built polarization microscope, a few biologically important tissues are measured and analyzed to gain insight as to their structure and dynamics. The structure and distribution of muscle sarcomere myosins, connective tissue collagen, carbohydrate-rich starch, and fruit fly eye retinal molecules are characterized with revealing polarization studies. In each case, using the theoretical framework, polarization sensitive data are analyzed to decipher the molecular orientations and nonlinear optical

  2. Color and neighbor edge directional difference feature for image retrieval

    Institute of Scientific and Technical Information of China (English)

    Chaobing Huang; Shengsheng Yu; Jingli Zhou; Hongwei Lu

    2005-01-01

    @@ A novel image feature termed neighbor edge directional difference unit histogram is proposed, in which the neighbor edge directional difference unit is defined and computed for every pixel in the image, and is used to generate the neighbor edge directional difference unit histogram. This histogram and color histogram are used as feature indexes to retrieve color image. The feature is invariant to image scaling and translation and has more powerful descriptive for the natural color images. Experimental results show that the feature can achieve better retrieval performance than other color-spatial features.

  3. Novel plasmonic polarimeter for biomedical imaging applications

    Science.gov (United States)

    Cheney, Alec; Chen, Borui; Cartwright, Alexander; Thomay, Tim

    2018-02-01

    Using polarized light in medical imaging is a valuable tool for diagnostic purposes since light traveling through scattering tissues such as skin, blood, or cartilage may be subject to changes in polarization. We present a new detection scheme and sensor that allows for directly measuring the polarization of light electronically using a plasmonic sensor. The sensor we fabricated consists of a plasmonic nano-grating that is embedded in a Wheatstone circuit. Using resistive losses induced by optically excited plasmons has shown promise as a CMOScompatible plasmonic light detector. Since the plasmonic response is sensitive to polarization with respect to the grating orientation, measuring the resistance change under incident light supplies a direct electronic measure of the polarization of light without polarization optics. Increased electron scattering introduced by plasmons in an applied current results in a measurable decrease in electrical conductance of a grating, allowing a purely electronic readout of a plasmonic excitation. Accordingly, because of its plasmonic nature, such a detector is dependent on both the wavelength and polarization of incident light with a response time limited by the surface plasmon lifetime.

  4. Biochemical imaging of tissues by SIMS for biomedical applications

    International Nuclear Information System (INIS)

    Lee, Tae Geol; Park, Ji-Won; Shon, Hyun Kyong; Moon, Dae Won; Choi, Won Woo; Li, Kapsok; Chung, Jin Ho

    2008-01-01

    With the development of optimal surface cleaning techniques by cluster ion beam sputtering, certain applications of SIMS for analyzing cells and tissues have been actively investigated. For this report, we collaborated with bio-medical scientists to study bio-SIMS analyses of skin and cancer tissues for biomedical diagnostics. We pay close attention to the setting up of a routine procedure for preparing tissue specimens and treating the surface before obtaining the bio-SIMS data. Bio-SIMS was used to study two biosystems, skin tissues for understanding the effects of photoaging and colon cancer tissues for insight into the development of new cancer diagnostics for cancer. Time-of-flight SIMS imaging measurements were taken after surface cleaning with cluster ion bombardment by Bi n or C 60 under varying conditions. The imaging capability of bio-SIMS with a spatial resolution of a few microns combined with principal component analysis reveal biologically meaningful information, but the lack of high molecular weight peaks even with cluster ion bombardment was a problem. This, among other problems, shows that discourse with biologists and medical doctors are critical to glean any meaningful information from SIMS mass spectrometric and imaging data. For SIMS to be accepted as a routine, daily analysis tool in biomedical laboratories, various practical sample handling methodology such as surface matrix treatment, including nano-metal particles and metal coating, in addition to cluster sputtering, should be studied

  5. Generating region proposals for histopathological whole slide image retrieval.

    Science.gov (United States)

    Ma, Yibing; Jiang, Zhiguo; Zhang, Haopeng; Xie, Fengying; Zheng, Yushan; Shi, Huaqiang; Zhao, Yu; Shi, Jun

    2018-06-01

    Content-based image retrieval is an effective method for histopathological image analysis. However, given a database of huge whole slide images (WSIs), acquiring appropriate region-of-interests (ROIs) for training is significant and difficult. Moreover, histopathological images can only be annotated by pathologists, resulting in the lack of labeling information. Therefore, it is an important and challenging task to generate ROIs from WSI and retrieve image with few labels. This paper presents a novel unsupervised region proposing method for histopathological WSI based on Selective Search. Specifically, the WSI is over-segmented into regions which are hierarchically merged until the WSI becomes a single region. Nucleus-oriented similarity measures for region mergence and Nucleus-Cytoplasm color space for histopathological image are specially defined to generate accurate region proposals. Additionally, we propose a new semi-supervised hashing method for image retrieval. The semantic features of images are extracted with Latent Dirichlet Allocation and transformed into binary hashing codes with Supervised Hashing. The methods are tested on a large-scale multi-class database of breast histopathological WSIs. The results demonstrate that for one WSI, our region proposing method can generate 7.3 thousand contoured regions which fit well with 95.8% of the ROIs annotated by pathologists. The proposed hashing method can retrieve a query image among 136 thousand images in 0.29 s and reach precision of 91% with only 10% of images labeled. The unsupervised region proposing method can generate regions as predictions of lesions in histopathological WSI. The region proposals can also serve as the training samples to train machine-learning models for image retrieval. The proposed hashing method can achieve fast and precise image retrieval with small amount of labels. Furthermore, the proposed methods can be potentially applied in online computer-aided-diagnosis systems. Copyright

  6. Density-based retrieval from high-similarity image databases

    DEFF Research Database (Denmark)

    Hansen, Michael Edberg; Carstensen, Jens Michael

    2004-01-01

    Many image classification problems can fruitfully be thought of as image retrieval in a "high similarity image database" (HSID) characterized by being tuned towards a specific application and having a high degree of visual similarity between entries that should be distinguished. We introduce a me...

  7. A Learning State-Space Model for Image Retrieval

    Directory of Open Access Journals (Sweden)

    Lee Greg C

    2007-01-01

    Full Text Available This paper proposes an approach based on a state-space model for learning the user concepts in image retrieval. We first design a scheme of region-based image representation based on concept units, which are integrated with different types of feature spaces and with different region scales of image segmentation. The design of the concept units aims at describing similar characteristics at a certain perspective among relevant images. We present the details of our proposed approach based on a state-space model for interactive image retrieval, including likelihood and transition models, and we also describe some experiments that show the efficacy of our proposed model. This work demonstrates the feasibility of using a state-space model to estimate the user intuition in image retrieval.

  8. Review of spectral imaging technology in biomedical engineering: achievements and challenges.

    Science.gov (United States)

    Li, Qingli; He, Xiaofu; Wang, Yiting; Liu, Hongying; Xu, Dongrong; Guo, Fangmin

    2013-10-01

    Spectral imaging is a technology that integrates conventional imaging and spectroscopy to get both spatial and spectral information from an object. Although this technology was originally developed for remote sensing, it has been extended to the biomedical engineering field as a powerful analytical tool for biological and biomedical research. This review introduces the basics of spectral imaging, imaging methods, current equipment, and recent advances in biomedical applications. The performance and analytical capabilities of spectral imaging systems for biological and biomedical imaging are discussed. In particular, the current achievements and limitations of this technology in biomedical engineering are presented. The benefits and development trends of biomedical spectral imaging are highlighted to provide the reader with an insight into the current technological advances and its potential for biomedical research.

  9. All-optoelectronic continuous wave THz imaging for biomedical applications

    International Nuclear Information System (INIS)

    Siebert, Karsten J; Loeffler, Torsten; Quast, Holger; Thomson, Mark; Bauer, Tobias; Leonhardt, Rainer; Czasch, Stephanie; Roskos, Hartmut G

    2002-01-01

    We present an all-optoelectronic THz imaging system for ex vivo biomedical applications based on photomixing of two continuous-wave laser beams using photoconductive antennas. The application of hyperboloidal lenses is discussed. They allow for f-numbers less than 1/2 permitting better focusing and higher spatial resolution compared to off-axis paraboloidal mirrors whose f-numbers for practical reasons must be larger than 1/2. For a specific histological sample, an analysis of image noise is discussed

  10. Figure mining for biomedical research.

    Science.gov (United States)

    Rodriguez-Esteban, Raul; Iossifov, Ivan

    2009-08-15

    Figures from biomedical articles contain valuable information difficult to reach without specialized tools. Currently, there is no search engine that can retrieve specific figure types. This study describes a retrieval method that takes advantage of principles in image understanding, text mining and optical character recognition (OCR) to retrieve figure types defined conceptually. A search engine was developed to retrieve tables and figure types to aid computational and experimental research. http://iossifovlab.cshl.edu/figurome/.

  11. Multi region based image retrieval system

    Indian Academy of Sciences (India)

    data mining, information theory, statistics and psychology. ∗ .... ground complication and independent of image size and orientation (Zhang 2007). ..... Figure 2. Significant regions: (a) the input image, (b) the primary significant region, (c) the ...

  12. Learning tag relevance by neighbor voting for social image retrieval

    NARCIS (Netherlands)

    Li, X.; Snoek, C.G.M.; Worring, M.

    2008-01-01

    Social image retrieval is important for exploiting the increasing amounts of amateur-tagged multimedia such as Flickr images. Since amateur tagging is known to be uncontrolled, ambiguous, and personalized, a fundamental problem is how to reliably interpret the relevance of a tag with respect to the

  13. TRADEMARK IMAGE RETRIEVAL USING LOW LEVEL FEATURE EXTRACTION IN CBIR

    OpenAIRE

    Latika Pinjarkar*, Manisha Sharma, Smita Selot

    2016-01-01

    Trademarks work as significant responsibility in industry and commerce. Trademarks are important component of its industrial property, and violation can have severe penalty. Therefore designing an efficient trademark retrieval system and its assessment for uniqueness is thus becoming very important task now a days. Trademark image retrieval system where a new candidate trademark is compared with already registered trademarks to check that there is no possibility of resembl...

  14. Measuring and Predicting Tag Importance for Image Retrieval.

    Science.gov (United States)

    Li, Shangwen; Purushotham, Sanjay; Chen, Chen; Ren, Yuzhuo; Kuo, C-C Jay

    2017-12-01

    Textual data such as tags, sentence descriptions are combined with visual cues to reduce the semantic gap for image retrieval applications in today's Multimodal Image Retrieval (MIR) systems. However, all tags are treated as equally important in these systems, which may result in misalignment between visual and textual modalities during MIR training. This will further lead to degenerated retrieval performance at query time. To address this issue, we investigate the problem of tag importance prediction, where the goal is to automatically predict the tag importance and use it in image retrieval. To achieve this, we first propose a method to measure the relative importance of object and scene tags from image sentence descriptions. Using this as the ground truth, we present a tag importance prediction model to jointly exploit visual, semantic and context cues. The Structural Support Vector Machine (SSVM) formulation is adopted to ensure efficient training of the prediction model. Then, the Canonical Correlation Analysis (CCA) is employed to learn the relation between the image visual feature and tag importance to obtain robust retrieval performance. Experimental results on three real-world datasets show a significant performance improvement of the proposed MIR with Tag Importance Prediction (MIR/TIP) system over other MIR systems.

  15. Online Hashing for Scalable Remote Sensing Image Retrieval

    Directory of Open Access Journals (Sweden)

    Peng Li

    2018-05-01

    Full Text Available Recently, hashing-based large-scale remote sensing (RS image retrieval has attracted much attention. Many new hashing algorithms have been developed and successfully applied to fast RS image retrieval tasks. However, there exists an important problem rarely addressed in the research literature of RS image hashing. The RS images are practically produced in a streaming manner in many real-world applications, which means the data distribution keeps changing over time. Most existing RS image hashing methods are batch-based models whose hash functions are learned once for all and kept fixed all the time. Therefore, the pre-trained hash functions might not fit the ever-growing new RS images. Moreover, the batch-based models have to load all the training images into memory for model learning, which consumes many computing and memory resources. To address the above deficiencies, we propose a new online hashing method, which learns and adapts its hashing functions with respect to the newly incoming RS images in terms of a novel online partial random learning scheme. Our hash model is updated in a sequential mode such that the representative power of the learned binary codes for RS images are improved accordingly. Moreover, benefiting from the online learning strategy, our proposed hashing approach is quite suitable for scalable real-world remote sensing image retrieval. Extensive experiments on two large-scale RS image databases under online setting demonstrated the efficacy and effectiveness of the proposed method.

  16. Simultenious binary hash and features learning for image retrieval

    Science.gov (United States)

    Frantc, V. A.; Makov, S. V.; Voronin, V. V.; Marchuk, V. I.; Semenishchev, E. A.; Egiazarian, K. O.; Agaian, S.

    2016-05-01

    Content-based image retrieval systems have plenty of applications in modern world. The most important one is the image search by query image or by semantic description. Approaches to this problem are employed in personal photo-collection management systems, web-scale image search engines, medical systems, etc. Automatic analysis of large unlabeled image datasets is virtually impossible without satisfactory image-retrieval technique. It's the main reason why this kind of automatic image processing has attracted so much attention during recent years. Despite rather huge progress in the field, semantically meaningful image retrieval still remains a challenging task. The main issue here is the demand to provide reliable results in short amount of time. This paper addresses the problem by novel technique for simultaneous learning of global image features and binary hash codes. Our approach provide mapping of pixel-based image representation to hash-value space simultaneously trying to save as much of semantic image content as possible. We use deep learning methodology to generate image description with properties of similarity preservation and statistical independence. The main advantage of our approach in contrast to existing is ability to fine-tune retrieval procedure for very specific application which allow us to provide better results in comparison to general techniques. Presented in the paper framework for data- dependent image hashing is based on use two different kinds of neural networks: convolutional neural networks for image description and autoencoder for feature to hash space mapping. Experimental results confirmed that our approach has shown promising results in compare to other state-of-the-art methods.

  17. A UNIX-based prototype biomedical virtual image processor

    International Nuclear Information System (INIS)

    Fahy, J.B.; Kim, Y.

    1987-01-01

    The authors have developed a multiprocess virtual image processor for the IBM PC/AT, in order to maximize image processing software portability for biomedical applications. An interprocess communication scheme, based on two-way metacode exchange, has been developed and verified for this purpose. Application programs call a device-independent image processing library, which transfers commands over a shared data bridge to one or more Autonomous Virtual Image Processors (AVIP). Each AVIP runs as a separate process in the UNIX operating system, and implements the device-independent functions on the image processor to which it corresponds. Application programs can control multiple image processors at a time, change the image processor configuration used at any time, and are completely portable among image processors for which an AVIP has been implemented. Run-time speeds have been found to be acceptable for higher level functions, although rather slow for lower level functions, owing to the overhead associated with sending commands and data over the shared data bridge

  18. Selection of Quantum Dot Wavelengths for Biomedical Assays and Imaging

    Directory of Open Access Journals (Sweden)

    Yong Taik Lim

    2003-01-01

    Full Text Available Fluorescent semiconductor nanocrystals (quantum dots [QDs] are hypothesized to be excellent contrast agents for biomedical assays and imaging. A unique property of QDs is that their absorbance increases with increasing separation between excitation and emission wavelengths. Much of the enthusiasm for using QDs in vivo stems from this property, since photon yield should be proportional to the integral of the broadband absorption. In this study, we demonstrate that tissue scatter and absorbance can sometimes offset increasing QD absorption at bluer wavelengths, and counteract this potential advantage. By using a previously validated mathematical model, we explored the effects of tissue absorbance, tissue scatter, wavelength dependence of the scatter, water-to- hemoglobin ratio, and tissue thickness on QD performance. We conclude that when embedded in biological fluids and tissues, QD excitation wavelengths will often be quite constrained, and that excitation and emission wavelengths should be selected carefully based on the particular application. Based on our results, we produced near-infrared QDs optimized for imaging surface vasculature with white light excitation and a silicon CCD camera, and used them to image the coronary vasculature in vivo. Taken together, our data should prove useful in designing fluorescent QD contrast agents optimized for specific biomedical applications.

  19. Radioanalytical and imaging techniques. Challenges and opportunities in biomedical applications

    International Nuclear Information System (INIS)

    Spyrou, N.M.

    2008-01-01

    Where human health worldwide is under threat, radioanalytical and imaging scientists are expected to make significant difference and contribution. Diabetes, malnutrition, Alzheimer's and cardiovascular diseases can be better understood by probing elemental distributions to nano-scales and quantifying elemental compositions to ultratrace levels. As we aim towards personalized medicine, cancer management awaits new diagnostic and therapy methods which account, for example, for tissue oxygenation. In the context of such biomedical issues, recent trends and future developments are presented taking into consideration the availability of research reactors and ion beam facilities, as well as alternative and emerging techniques such as PIXE tomography (PIXE-T) and two- and three-gamma PET. (author)

  20. Development of biosensor based on imaging ellipsometry and biomedical applications

    Energy Technology Data Exchange (ETDEWEB)

    Jin, G., E-mail: gajin@imech.ac.c [NML, Institute of Mechanics, Chinese Academy of Sciences, 15 Bei-si-huan west Rd., Beijing 100190 (China); Meng, Y.H.; Liu, L.; Niu, Y.; Chen, S. [NML, Institute of Mechanics, Chinese Academy of Sciences, 15 Bei-si-huan west Rd., Beijing 100190 (China); Cai, Q.; Jiang, T.J. [Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101 (China)

    2011-02-28

    So far, combined with a microfluidic reactor array system, an engineering system of biosensor based on imaging ellipsometry is installed for biomedical applications, such as antibody screen, hepatitis B markers detection, cancer markers spectrum and virus recognition, etc. Furthermore, the biosensor in total internal reflection (TIR) mode has be improved by a spectroscopic light, optimization settings of polarization and low noise CCD which brings an obvious improvement of 10 time increase in the sensitivity and SNR, and 50 times lower concentration in the detection limit with a throughput of 48 independent channels and the time resolution of 0.04 S.

  1. Contributions on biomedical imaging, with a side-look at molecular imaging

    International Nuclear Information System (INIS)

    Winkler, G.

    2004-05-01

    This report is intended as a brief introduction to the emerging scientific field of biomedical imaging. The breadth of the subject is shown and future fields of research are indicated, which hopefully will serve as a guide to the identification of starting points for the research in 'Biomedical and/or Molecular Imaging' at the GSF-National Research Center for Environment and Health. The report starts with a brief sketch of the history. Then a - necessarily incomplete - list of research topics is presented. It is organized in two parts: the first one addresses medical imaging, and the second one is concerned with biological point aspects of the matter. (orig.) [de

  2. Dictionary Pruning with Visual Word Significance for Medical Image Retrieval.

    Science.gov (United States)

    Zhang, Fan; Song, Yang; Cai, Weidong; Hauptmann, Alexander G; Liu, Sidong; Pujol, Sonia; Kikinis, Ron; Fulham, Michael J; Feng, David Dagan; Chen, Mei

    2016-02-12

    Content-based medical image retrieval (CBMIR) is an active research area for disease diagnosis and treatment but it can be problematic given the small visual variations between anatomical structures. We propose a retrieval method based on a bag-of-visual-words (BoVW) to identify discriminative characteristics between different medical images with Pruned Dictionary based on Latent Semantic Topic description. We refer to this as the PD-LST retrieval. Our method has two main components. First, we calculate a topic-word significance value for each visual word given a certain latent topic to evaluate how the word is connected to this latent topic. The latent topics are learnt, based on the relationship between the images and words, and are employed to bridge the gap between low-level visual features and high-level semantics. These latent topics describe the images and words semantically and can thus facilitate more meaningful comparisons between the words. Second, we compute an overall-word significance value to evaluate the significance of a visual word within the entire dictionary. We designed an iterative ranking method to measure overall-word significance by considering the relationship between all latent topics and words. The words with higher values are considered meaningful with more significant discriminative power in differentiating medical images. We evaluated our method on two public medical imaging datasets and it showed improved retrieval accuracy and efficiency.

  3. Content Based Medical Image Retrieval for Histopathological, CT and MRI Images

    Directory of Open Access Journals (Sweden)

    Swarnambiga AYYACHAMY

    2013-09-01

    Full Text Available A content based approach is followed for medical images. The purpose of this study is to access the stability of these methods for medical image retrieval. The methods used in color based retrieval for histopathological images are color co-occurrence matrix (CCM and histogram with meta features. For texture based retrieval GLCM (gray level co-occurrence matrix and local binary pattern (LBP were used. For shape based retrieval canny edge detection and otsu‘s method with multivariable threshold were used. Texture and shape based retrieval were implemented using MRI (magnetic resonance images. The most remarkable characteristics of the article are its content based approach for each medical imaging modality. Our efforts were focused on the initial visual search. From our experiment, histogram with meta features in color based retrieval for histopathological images shows a precision of 60 % and recall of 30 %. Whereas GLCM in texture based retrieval for MRI images shows a precision of 70 % and recall of 20 %. Shape based retrieval for MRI images shows a precision of 50% and recall of 25 %. The retrieval results shows that this simple approach is successful.

  4. Acquisition and manipulation of computed tomography images of the maxillofacial region for biomedical prototyping

    International Nuclear Information System (INIS)

    Meurer, Maria Ines; Silva, Jorge Vicente Lopes da; Santa Barbara, Ailton; Nobre, Luiz Felipe; Oliveira, Marilia Gerhardt de; Silva, Daniela Nascimento

    2008-01-01

    Biomedical prototyping has resulted from a merger of rapid prototyping and imaging diagnosis technologies. However, this process is complex, considering the necessity of interaction between biomedical sciences and engineering. Good results are highly dependent on the acquisition of computed tomography images and their subsequent manipulation by means of specific software. The present study describes the experience of a multidisciplinary group of researchers in the acquisition and manipulation of computed tomography images of the maxillofacial region aiming at biomedical prototyping for surgical purposes. (author)

  5. Pattern recognition and expert image analysis systems in biomedical image processing (Invited Paper)

    Science.gov (United States)

    Oosterlinck, A.; Suetens, P.; Wu, Q.; Baird, M.; F. M., C.

    1987-09-01

    This paper gives an overview of pattern recoanition techniques (P.R.) used in biomedical image processing and problems related to the different P.R. solutions. Also the use of knowledge based systems to overcome P.R. difficulties, is described. This is illustrated by a common example ofabiomedical image processing application.

  6. Multi-clues image retrieval based on improved color invariants

    Science.gov (United States)

    Liu, Liu; Li, Jian-Xun

    2012-05-01

    At present, image retrieval has a great progress in indexing efficiency and memory usage, which mainly benefits from the utilization of the text retrieval technology, such as the bag-of-features (BOF) model and the inverted-file structure. Meanwhile, because the robust local feature invariants are selected to establish BOF, the retrieval precision of BOF is enhanced, especially when it is applied to a large-scale database. However, these local feature invariants mainly consider the geometric variance of the objects in the images, and thus the color information of the objects fails to be made use of. Because of the development of the information technology and Internet, the majority of our retrieval objects is color images. Therefore, retrieval performance can be further improved through proper utilization of the color information. We propose an improved method through analyzing the flaw of shadow-shading quasi-invariant. The response and performance of shadow-shading quasi-invariant for the object edge with the variance of lighting are enhanced. The color descriptors of the invariant regions are extracted and integrated into BOF based on the local feature. The robustness of the algorithm and the improvement of the performance are verified in the final experiments.

  7. Recent advances in intelligent image search and video retrieval

    CERN Document Server

    2017-01-01

    This book initially reviews the major feature representation and extraction methods and effective learning and recognition approaches, which have broad applications in the context of intelligent image search and video retrieval. It subsequently presents novel methods, such as improved soft assignment coding, Inheritable Color Space (InCS) and the Generalized InCS framework, the sparse kernel manifold learner method, the efficient Support Vector Machine (eSVM), and the Scale-Invariant Feature Transform (SIFT) features in multiple color spaces. Lastly, the book presents clothing analysis for subject identification and retrieval, and performance evaluation methods of video analytics for traffic monitoring. Digital images and videos are proliferating at an amazing speed in the fields of science, engineering and technology, media and entertainment. With the huge accumulation of such data, keyword searches and manual annotation schemes may no longer be able to meet the practical demand for retrieving relevant conte...

  8. Using the weighted keyword model to improve information retrieval for answering biomedical questions.

    Science.gov (United States)

    Yu, Hong; Cao, Yong-Gang

    2009-03-01

    Physicians ask many complex questions during the patient encounter. Information retrieval systems that can provide immediate and relevant answers to these questions can be invaluable aids to the practice of evidence-based medicine. In this study, we first automatically identify topic keywords from ad hoc clinical questions with a Condition Random Field model that is trained over thousands of manually annotated clinical questions. We then report on a linear model that assigns query weights based on their automatically identified semantic roles: topic keywords, domain specific terms, and their synonyms. Our evaluation shows that this weighted keyword model improves information retrieval from the Text Retrieval Conference Genomics track data.

  9. Molecular image in biomedical research. Molecular imaging unit of the National Cancer Research Center

    International Nuclear Information System (INIS)

    Perez Bruzon, J.; Mulero Anhiorte, F.

    2010-01-01

    This article has two basic objectives. firstly, it will review briefly the most important imaging techniques used in biomedical research indicting the most significant aspects related to their application in the preclinical stage. Secondly, it will present a practical application of these techniques in a pure biomedical research centre (not associated to a clinical facility). Practical aspects such as organisation, equipment, work norms, shielding of the Spanish National Cancer Research Centre (CNIO) Imaging Unit will be shown. This is a pioneering facility in the application of these techniques in research centres without any dependence or any direct relationship with other hospital Nuclear Medicine services. (Author) 7 refs.

  10. AMARSI: Aerosol modeling and retrieval from multi-spectral imagers

    NARCIS (Netherlands)

    Leeuw, G. de; Curier, R.L.; Staroverova, A.; Kokhanovsky, A.; Hoyningen-Huene, W. van; Rozanov, V.V.; Burrows, J.P.; Hesselmans, G.; Gale, L.; Bouvet, M.

    2008-01-01

    The AMARSI project aims at the development and validation of aerosol retrieval algorithms over ocean. One algorithm will be developed for application with data from the Multi Spectral Imager (MSI) on EarthCARE. A second algorithm will be developed using the combined information from AATSR and MERIS,

  11. Content-based image retrieval: Color-selection exploited

    NARCIS (Netherlands)

    Broek, E.L. van den; Vuurpijl, L.G.; Kisters, P. M. F.; Schmid, J.C.M. von; Moens, M.F.; Busser, R. de; Hiemstra, D.; Kraaij, W.

    2002-01-01

    This research presents a new color selection interface that facilitates query-by-color in Content-Based Image Retrieval (CBIR). Existing CBIR color selection interfaces, are being judged as non-intuitive and difficult to use. Our interface copes with these problems of usability. It is based on 11

  12. Content-Based Image Retrieval: Color-selection exploited

    NARCIS (Netherlands)

    Moens, Marie-Francine; van den Broek, Egon; Vuurpijl, L.G.; de Brusser, Rik; Kisters, P.M.F.; Hiemstra, Djoerd; Kraaij, Wessel; von Schmid, J.C.M.

    2002-01-01

    This research presents a new color selection interface that facilitates query-by-color in Content-Based Image Retrieval (CBIR). Existing CBIR color selection interfaces, are being judged as non-intuitive and difficult to use. Our interface copes with these problems of usability. It is based on 11

  13. Grid-Independent Compressive Imaging and Fourier Phase Retrieval

    Science.gov (United States)

    Liao, Wenjing

    2013-01-01

    This dissertation is composed of two parts. In the first part techniques of band exclusion(BE) and local optimization(LO) are proposed to solve linear continuum inverse problems independently of the grid spacing. The second part is devoted to the Fourier phase retrieval problem. Many situations in optics, medical imaging and signal processing call…

  14. Signature detection and matching for document image retrieval.

    Science.gov (United States)

    Zhu, Guangyu; Zheng, Yefeng; Doermann, David; Jaeger, Stefan

    2009-11-01

    As one of the most pervasive methods of individual identification and document authentication, signatures present convincing evidence and provide an important form of indexing for effective document image processing and retrieval in a broad range of applications. However, detection and segmentation of free-form objects such as signatures from clustered background is currently an open document analysis problem. In this paper, we focus on two fundamental problems in signature-based document image retrieval. First, we propose a novel multiscale approach to jointly detecting and segmenting signatures from document images. Rather than focusing on local features that typically have large variations, our approach captures the structural saliency using a signature production model and computes the dynamic curvature of 2D contour fragments over multiple scales. This detection framework is general and computationally tractable. Second, we treat the problem of signature retrieval in the unconstrained setting of translation, scale, and rotation invariant nonrigid shape matching. We propose two novel measures of shape dissimilarity based on anisotropic scaling and registration residual error and present a supervised learning framework for combining complementary shape information from different dissimilarity metrics using LDA. We quantitatively study state-of-the-art shape representations, shape matching algorithms, measures of dissimilarity, and the use of multiple instances as query in document image retrieval. We further demonstrate our matching techniques in offline signature verification. Extensive experiments using large real-world collections of English and Arabic machine-printed and handwritten documents demonstrate the excellent performance of our approaches.

  15. Image Retrieval Algorithm Based on Discrete Fractional Transforms

    Science.gov (United States)

    Jindal, Neeru; Singh, Kulbir

    2013-06-01

    The discrete fractional transforms is a signal processing tool which suggests computational algorithms and solutions to various sophisticated applications. In this paper, a new technique to retrieve the encrypted and scrambled image based on discrete fractional transforms has been proposed. Two-dimensional image was encrypted using discrete fractional transforms with three fractional orders and two random phase masks placed in the two intermediate planes. The significant feature of discrete fractional transforms benefits from its extra degree of freedom that is provided by its fractional orders. Security strength was enhanced (1024!)4 times by scrambling the encrypted image. In decryption process, image retrieval is sensitive for both correct fractional order keys and scrambling algorithm. The proposed approach make the brute force attack infeasible. Mean square error and relative error are the recital parameters to verify validity of proposed method.

  16. Applying GA for Optimizing the User Query in Image and Video Retrieval

    OpenAIRE

    Ehsan Lotfi

    2014-01-01

    In an information retrieval system, the query can be made by user sketch. The new method presented here, optimizes the user sketch and applies the optimized query to retrieval the information. This optimization may be used in Content-Based Image Retrieval (CBIR) and Content-Based Video Retrieval (CBVR) which is based on trajectory extraction. To optimize the retrieval process, one stage of retrieval is performed by the user sketch. The retrieval criterion is based on the proposed distance met...

  17. Image based book cover recognition and retrieval

    Science.gov (United States)

    Sukhadan, Kalyani; Vijayarajan, V.; Krishnamoorthi, A.; Bessie Amali, D. Geraldine

    2017-11-01

    In this we are developing a graphical user interface using MATLAB for the users to check the information related to books in real time. We are taking the photos of the book cover using GUI, then by using MSER algorithm it will automatically detect all the features from the input image, after this it will filter bifurcate non-text features which will be based on morphological difference between text and non-text regions. We implemented a text character alignment algorithm which will improve the accuracy of the original text detection. We will also have a look upon the built in MATLAB OCR recognition algorithm and an open source OCR which is commonly used to perform better detection results, post detection algorithm is implemented and natural language processing to perform word correction and false detection inhibition. Finally, the detection result will be linked to internet to perform online matching. More than 86% accuracy can be obtained by this algorithm.

  18. Mutual information based feature selection for medical image retrieval

    Science.gov (United States)

    Zhi, Lijia; Zhang, Shaomin; Li, Yan

    2018-04-01

    In this paper, authors propose a mutual information based method for lung CT image retrieval. This method is designed to adapt to different datasets and different retrieval task. For practical applying consideration, this method avoids using a large amount of training data. Instead, with a well-designed training process and robust fundamental features and measurements, the method in this paper can get promising performance and maintain economic training computation. Experimental results show that the method has potential practical values for clinical routine application.

  19. Biomedical nanotechnology for molecular imaging, diagnostics, and targeted therapy.

    Science.gov (United States)

    Nie, Shuming

    2009-01-01

    Biomedical nanotechnology is a cross-disciplinary area of research in science, engineering and medicine with broad applications for molecular imaging, molecular diagnosis, and targeted therapy. The basic rationale is that nanometer-sized particles such as semiconductor quantum dots and iron oxide nanocrystals have optical, magnetic or structural properties that are not available from either molecules or bulk solids. When linked with biotargeting ligands such as monoclonal antibodies, peptides or small molecules, these nanoparticles can be used to target diseased cells and organs (such as malignant tumors and cardiovascular plaques) with high affinity and specificity. In the "mesoscopic" size range of 5-100 nm diameter, nanoparticles also have large surface areas and functional groups for conjugating to multiple diagnostic (e.g., optical, radioisotopic, or magnetic) and therapeutic (e.g., anticancer) agents.

  20. Optimizing Ti:Sapphire laser for quantitative biomedical imaging

    Science.gov (United States)

    James, Jeemol; Thomsen, Hanna; Hanstorp, Dag; Alemán Hérnandez, Felipe Ademir; Rothe, Sebastian; Enger, Jonas; Ericson, Marica B.

    2018-02-01

    Ti:Sapphire lasers are powerful tools in the field of scientific research and industry for a wide range of applications such as spectroscopic studies and microscopic imaging where tunable near-infrared light is required. To push the limits of the applicability of Ti:Sapphire lasers, fundamental understanding of the construction and operation is required. This paper presents two projects, (i) dealing with the building and characterization of custom built tunable narrow linewidth Ti:Sapphire laser for fundamental spectroscopy studies; and the second project (ii) the implementation of a fs-pulsed commercial Ti:Sapphire laser in an experimental multiphoton microscopy platform. For the narrow linewidth laser, a gold-plated diffraction grating with a Littrow geometry was implemented for highresolution wavelength selection. We demonstrate that the laser is tunable between 700 to 950 nm, operating in a pulsed mode with a repetition rate of 1 kHz and maximum average output power around 350 mW. The output linewidth was reduced from 6 GHz to 1.5 GHz by inserting an additional 6 mm thick etalon. The bandwidth was measured by means of a scanning Fabry Perot interferometer. Future work will focus on using a fs-pulsed commercial Ti:Sapphire laser (Tsunami, Spectra physics), operating at 80 MHz and maximum average output power around 1 W, for implementation in an experimental multiphoton microscopy set up dedicated for biomedical applications. Special focus will be on controlling pulse duration and dispersion in the optical components and biological tissue using pulse compression. Furthermore, time correlated analysis of the biological samples will be performed with the help of time correlated single photon counting module (SPCM, Becker&Hickl) which will give a novel dimension in quantitative biomedical imaging.

  1. Retrieval Architecture with Classified Query for Content Based Image Recognition

    Directory of Open Access Journals (Sweden)

    Rik Das

    2016-01-01

    Full Text Available The consumer behavior has been observed to be largely influenced by image data with increasing familiarity of smart phones and World Wide Web. Traditional technique of browsing through product varieties in the Internet with text keywords has been gradually replaced by the easy accessible image data. The importance of image data has portrayed a steady growth in application orientation for business domain with the advent of different image capturing devices and social media. The paper has described a methodology of feature extraction by image binarization technique for enhancing identification and retrieval of information using content based image recognition. The proposed algorithm was tested on two public datasets, namely, Wang dataset and Oliva and Torralba (OT-Scene dataset with 3688 images on the whole. It has outclassed the state-of-the-art techniques in performance measure and has shown statistical significance.

  2. Study of Query Expansion Techniques and Their Application in the Biomedical Information Retrieval

    Directory of Open Access Journals (Sweden)

    A. R. Rivas

    2014-01-01

    retrieval systems. These techniques help to overcome vocabulary mismatch issues by expanding the original query with additional relevant terms and reweighting the terms in the expanded query. In this paper, different text preprocessing and query expansion approaches are combined to improve the documents initially retrieved by a query in a scientific documental database. A corpus belonging to MEDLINE, called Cystic Fibrosis, is used as a knowledge source. Experimental results show that the proposed combinations of techniques greatly enhance the efficiency obtained by traditional queries.

  3. Modality prediction of biomedical literature images using multimodal feature representation

    Directory of Open Access Journals (Sweden)

    Pelka, Obioma

    2016-08-01

    Full Text Available This paper presents the modelling approaches performed to automatically predict the modality of images found in biomedical literature. Various state-of-the-art visual features such as Bag-of-Keypoints computed with dense SIFT descriptors, texture features and Joint Composite Descriptors were used for visual image representation. Text representation was obtained by vector quantisation on a Bag-of-Words dictionary generated using attribute importance derived from a χ-test. Computing the principal components separately on each feature, dimension reduction as well as computational load reduction was achieved. Various multiple feature fusions were adopted to supplement visual image information with corresponding text information. The improvement obtained when using multimodal features vs. visual or text features was detected, analysed and evaluated. Random Forest models with 100 to 500 deep trees grown by resampling, a multi class linear kernel SVM with C=0.05 and a late fusion of the two classifiers were used for modality prediction. A Random Forest classifier achieved a higher accuracy and computed Bag-of-Keypoints with dense SIFT descriptors proved to be a better approach than with Lowe SIFT.

  4. Research of image retrieval technology based on color feature

    Science.gov (United States)

    Fu, Yanjun; Jiang, Guangyu; Chen, Fengying

    2009-10-01

    Recently, with the development of the communication and the computer technology and the improvement of the storage technology and the capability of the digital image equipment, more and more image resources are given to us than ever. And thus the solution of how to locate the proper image quickly and accurately is wanted.The early method is to set up a key word for searching in the database, but now the method has become very difficult when we search much more picture that we need. In order to overcome the limitation of the traditional searching method, content based image retrieval technology was aroused. Now, it is a hot research subject.Color image retrieval is the important part of it. Color is the most important feature for color image retrieval. Three key questions on how to make use of the color characteristic are discussed in the paper: the expression of color, the abstraction of color characteristic and the measurement of likeness based on color. On the basis, the extraction technology of the color histogram characteristic is especially discussed. Considering the advantages and disadvantages of the overall histogram and the partition histogram, a new method based the partition-overall histogram is proposed. The basic thought of it is to divide the image space according to a certain strategy, and then calculate color histogram of each block as the color feature of this block. Users choose the blocks that contain important space information, confirming the right value. The system calculates the distance between the corresponding blocks that users choosed. Other blocks merge into part overall histograms again, and the distance should be calculated. Then accumulate all the distance as the real distance between two pictures. The partition-overall histogram comprehensive utilizes advantages of two methods above, by choosing blocks makes the feature contain more spatial information which can improve performance; the distances between partition-overall histogram

  5. Color-Based Image Retrieval from High-Similarity Image Databases

    DEFF Research Database (Denmark)

    Hansen, Michael Adsetts Edberg; Carstensen, Jens Michael

    2003-01-01

    Many image classification problems can fruitfully be thought of as image retrieval in a "high similarity image database" (HSID) characterized by being tuned towards a specific application and having a high degree of visual similarity between entries that should be distinguished. We introduce...... a method for HSID retrieval using a similarity measure based on a linear combination of Jeffreys-Matusita (JM) distances between distributions of color (and color derivatives) estimated from a set of automatically extracted image regions. The weight coefficients are estimated based on optimal retrieval...... performance. Experimental results on the difficult task of visually identifying clones of fungal colonies grown in a petri dish and categorization of pelts show a high retrieval accuracy of the method when combined with standardized sample preparation and image acquisition....

  6. Ontology of Gaps in Content-Based Image Retrieval

    OpenAIRE

    Deserno, Thomas M.; Antani, Sameer; Long, Rodney

    2008-01-01

    Content-based image retrieval (CBIR) is a promising technology to enrich the core functionality of picture archiving and communication systems (PACS). CBIR has a potential for making a strong impact in diagnostics, research, and education. Research as reported in the scientific literature, however, has not made significant inroads as medical CBIR applications incorporated into routine clinical medicine or medical research. The cause is often attributed (without supporting analysis) to the ina...

  7. A visual perceptual descriptor with depth feature for image retrieval

    Science.gov (United States)

    Wang, Tianyang; Qin, Zhengrui

    2017-07-01

    This paper proposes a visual perceptual descriptor (VPD) and a new approach to extract perceptual depth feature for 2D image retrieval. VPD mimics human visual system, which can easily distinguish regions that have different textures, whereas for regions which have similar textures, color features are needed for further differentiation. We apply VPD on the gradient direction map of an image, capture texture-similar regions to generate a VPD map. We then impose the VPD map on a quantized color map and extract color features only from the overlapped regions. To reflect the nature of perceptual distance in single 2D image, we propose and extract the perceptual depth feature by computing the nuclear norm of the sparse depth map of an image. Extracted color features and the perceptual depth feature are both incorporated to a feature vector, we utilize this vector to represent an image and measure similarity. We observe that the proposed VPD + depth method achieves a promising result, and extensive experiments prove that it outperforms other typical methods on 2D image retrieval.

  8. Signal and image analysis for biomedical and life sciences

    CERN Document Server

    Sun, Changming; Pham, Tuan D; Vallotton, Pascal; Wang, Dadong

    2014-01-01

    With an emphasis on applications of computational models for solving modern challenging problems in biomedical and life sciences, this book aims to bring collections of articles from biologists, medical/biomedical and health science researchers together with computational scientists to focus on problems at the frontier of biomedical and life sciences. The goals of this book are to build interactions of scientists across several disciplines and to help industrial users apply advanced computational techniques for solving practical biomedical and life science problems. This book is for users in t

  9. Region-Based Color Image Indexing and Retrieval

    DEFF Research Database (Denmark)

    Kompatsiaris, Ioannis; Triantafyllou, Evangelia; Strintzis, Michael G.

    2001-01-01

    In this paper a region-based color image indexing and retrieval algorithm is presented. As a basis for the indexing, a novel K-Means segmentation algorithm is used, modified so as to take into account the coherence of the regions. A new color distance is also defined for this algorithm. Based on ....... Experimental results demonstrate the performance of the algorithm. The development of an intelligent image content-based search engine for the World Wide Web is also presented, as a direct application of the presented algorithm....

  10. Interactive classification and content-based retrieval of tissue images

    Science.gov (United States)

    Aksoy, Selim; Marchisio, Giovanni B.; Tusk, Carsten; Koperski, Krzysztof

    2002-11-01

    We describe a system for interactive classification and retrieval of microscopic tissue images. Our system models tissues in pixel, region and image levels. Pixel level features are generated using unsupervised clustering of color and texture values. Region level features include shape information and statistics of pixel level feature values. Image level features include statistics and spatial relationships of regions. To reduce the gap between low-level features and high-level expert knowledge, we define the concept of prototype regions. The system learns the prototype regions in an image collection using model-based clustering and density estimation. Different tissue types are modeled using spatial relationships of these regions. Spatial relationships are represented by fuzzy membership functions. The system automatically selects significant relationships from training data and builds models which can also be updated using user relevance feedback. A Bayesian framework is used to classify tissues based on these models. Preliminary experiments show that the spatial relationship models we developed provide a flexible and powerful framework for classification and retrieval of tissue images.

  11. The application of similar image retrieval in electronic commerce.

    Science.gov (United States)

    Hu, YuPing; Yin, Hua; Han, Dezhi; Yu, Fei

    2014-01-01

    Traditional online shopping platform (OSP), which searches product information by keywords, faces three problems: indirect search mode, large search space, and inaccuracy in search results. For solving these problems, we discuss and research the application of similar image retrieval in electronic commerce. Aiming at improving the network customers' experience and providing merchants with the accuracy of advertising, we design a reasonable and extensive electronic commerce application system, which includes three subsystems: image search display subsystem, image search subsystem, and product information collecting subsystem. This system can provide seamless connection between information platform and OSP, on which consumers can automatically and directly search similar images according to the pictures from information platform. At the same time, it can be used to provide accuracy of internet marketing for enterprises. The experiment shows the efficiency of constructing the system.

  12. The Application of Similar Image Retrieval in Electronic Commerce

    Directory of Open Access Journals (Sweden)

    YuPing Hu

    2014-01-01

    Full Text Available Traditional online shopping platform (OSP, which searches product information by keywords, faces three problems: indirect search mode, large search space, and inaccuracy in search results. For solving these problems, we discuss and research the application of similar image retrieval in electronic commerce. Aiming at improving the network customers’ experience and providing merchants with the accuracy of advertising, we design a reasonable and extensive electronic commerce application system, which includes three subsystems: image search display subsystem, image search subsystem, and product information collecting subsystem. This system can provide seamless connection between information platform and OSP, on which consumers can automatically and directly search similar images according to the pictures from information platform. At the same time, it can be used to provide accuracy of internet marketing for enterprises. The experiment shows the efficiency of constructing the system.

  13. The Application of Similar Image Retrieval in Electronic Commerce

    Science.gov (United States)

    Hu, YuPing; Yin, Hua; Han, Dezhi; Yu, Fei

    2014-01-01

    Traditional online shopping platform (OSP), which searches product information by keywords, faces three problems: indirect search mode, large search space, and inaccuracy in search results. For solving these problems, we discuss and research the application of similar image retrieval in electronic commerce. Aiming at improving the network customers' experience and providing merchants with the accuracy of advertising, we design a reasonable and extensive electronic commerce application system, which includes three subsystems: image search display subsystem, image search subsystem, and product information collecting subsystem. This system can provide seamless connection between information platform and OSP, on which consumers can automatically and directly search similar images according to the pictures from information platform. At the same time, it can be used to provide accuracy of internet marketing for enterprises. The experiment shows the efficiency of constructing the system. PMID:24883411

  14. WFIRST: Retrieval Studies of Directly Imaged Extrasolar Giant Planets

    Science.gov (United States)

    Marley, Mark; Lupu, Roxana; Lewis, Nikole K.; WFIRST Coronagraph SITs

    2018-01-01

    The typical direct imaging and spectroscopy target for the WFIRST Coronagraph will be a mature Jupiter-mass giant planet at a few AU from an FGK star. The spectra of such planets is expected to be shaped primarily by scattering from H2O clouds and absorption by gaseous NH3 and CH4. We have computed forward model spectra of such typical planets and applied noise models to understand the quality of photometry and spectra we can expect. Using such simulated datasets we have conducted Markov Chain Monte Carlo and MultiNest retrievals to derive atmospheric abundance of CH4, cloud scattering properties, gravity, and other parameters for various planets and observing modes. Our focus has primarily been to understand which combinations of photometry and spectroscopy at what SNR allow retrievals of atmospheric methane mixing ratios to within a factor of ten of the true value. This is a challenging task for directly imaged planets as the planet mass and radius--and thus surface gravity--are not as well constrained as in the case of transiting planets. We find that for plausible planets and datasets of the quality expected to be obtained by WFIRST it should be possible to place such constraints, at least for some planets. We present some examples of our retrieval results and explain how they have been utilized to help set design requirements on the coronagraph camera and integrated field spectrometer.

  15. Content-based histopathology image retrieval using CometCloud.

    Science.gov (United States)

    Qi, Xin; Wang, Daihou; Rodero, Ivan; Diaz-Montes, Javier; Gensure, Rebekah H; Xing, Fuyong; Zhong, Hua; Goodell, Lauri; Parashar, Manish; Foran, David J; Yang, Lin

    2014-08-26

    The development of digital imaging technology is creating extraordinary levels of accuracy that provide support for improved reliability in different aspects of the image analysis, such as content-based image retrieval, image segmentation, and classification. This has dramatically increased the volume and rate at which data are generated. Together these facts make querying and sharing non-trivial and render centralized solutions unfeasible. Moreover, in many cases this data is often distributed and must be shared across multiple institutions requiring decentralized solutions. In this context, a new generation of data/information driven applications must be developed to take advantage of the national advanced cyber-infrastructure (ACI) which enable investigators to seamlessly and securely interact with information/data which is distributed across geographically disparate resources. This paper presents the development and evaluation of a novel content-based image retrieval (CBIR) framework. The methods were tested extensively using both peripheral blood smears and renal glomeruli specimens. The datasets and performance were evaluated by two pathologists to determine the concordance. The CBIR algorithms that were developed can reliably retrieve the candidate image patches exhibiting intensity and morphological characteristics that are most similar to a given query image. The methods described in this paper are able to reliably discriminate among subtle staining differences and spatial pattern distributions. By integrating a newly developed dual-similarity relevance feedback module into the CBIR framework, the CBIR results were improved substantially. By aggregating the computational power of high performance computing (HPC) and cloud resources, we demonstrated that the method can be successfully executed in minutes on the Cloud compared to weeks using standard computers. In this paper, we present a set of newly developed CBIR algorithms and validate them using two

  16. Video retrieval by still-image analysis with ImageMiner

    Science.gov (United States)

    Kreyss, Jutta; Roeper, M.; Alshuth, Peter; Hermes, Thorsten; Herzog, Otthein

    1997-01-01

    The large amount of available multimedia information (e.g. videos, audio, images) requires efficient and effective annotation and retrieval methods. As videos start playing a more important role in the frame of multimedia, we want to make these available for content-based retrieval. The ImageMiner-System, which was developed at the University of Bremen in the AI group, is designed for content-based retrieval of single images by a new combination of techniques and methods from computer vision and artificial intelligence. In our approach to make videos available for retrieval in a large database of videos and images there are two necessary steps: First, the detection and extraction of shots from a video, which is done by a histogram based method and second, the construction of the separate frames in a shot to one still single images. This is performed by a mosaicing-technique. The resulting mosaiced image gives a one image visualization of the shot and can be analyzed by the ImageMiner-System. ImageMiner has been tested on several domains, (e.g. landscape images, technical drawings), which cover a wide range of applications.

  17. Rotation invariant deep binary hashing for fast image retrieval

    Science.gov (United States)

    Dai, Lai; Liu, Jianming; Jiang, Aiwen

    2017-07-01

    In this paper, we study how to compactly represent image's characteristics for fast image retrieval. We propose supervised rotation invariant compact discriminative binary descriptors through combining convolutional neural network with hashing. In the proposed network, binary codes are learned by employing a hidden layer for representing latent concepts that dominate on class labels. A loss function is proposed to minimize the difference between binary descriptors that describe reference image and the rotated one. Compared with some other supervised methods, the proposed network doesn't have to require pair-wised inputs for binary code learning. Experimental results show that our method is effective and achieves state-of-the-art results on the CIFAR-10 and MNIST datasets.

  18. e-Science platform for translational biomedical imaging research: running, statistics, and analysis

    Science.gov (United States)

    Wang, Tusheng; Yang, Yuanyuan; Zhang, Kai; Wang, Mingqing; Zhao, Jun; Xu, Lisa; Zhang, Jianguo

    2015-03-01

    In order to enable multiple disciplines of medical researchers, clinical physicians and biomedical engineers working together in a secured, efficient, and transparent cooperative environment, we had designed an e-Science platform for biomedical imaging research and application cross multiple academic institutions and hospitals in Shanghai and presented this work in SPIE Medical Imaging conference held in San Diego in 2012. In past the two-years, we implemented a biomedical image chain including communication, storage, cooperation and computing based on this e-Science platform. In this presentation, we presented the operating status of this system in supporting biomedical imaging research, analyzed and discussed results of this system in supporting multi-disciplines collaboration cross-multiple institutions.

  19. Modern technologies for retinal scanning and imaging: an introduction for the biomedical engineer

    Science.gov (United States)

    2014-01-01

    This review article is meant to help biomedical engineers and nonphysical scientists better understand the principles of, and the main trends in modern scanning and imaging modalities used in ophthalmology. It is intended to ease the communication between physicists, medical doctors and engineers, and hopefully encourage “classical” biomedical engineers to generate new ideas and to initiate projects in an area which has traditionally been dominated by optical physics. Most of the methods involved are applicable to other areas of biomedical optics and optoelectronics, such as microscopic imaging, spectroscopy, spectral imaging, opto-acoustic tomography, fluorescence imaging etc., all of which are with potential biomedical application. Although all described methods are novel and important, the emphasis of this review has been placed on three technologies introduced in the 1990’s and still undergoing vigorous development: Confocal Scanning Laser Ophthalmoscopy, Optical Coherence Tomography, and polarization-sensitive retinal scanning. PMID:24779618

  20. Intelligent retrieval of chest X-ray image database using sketches

    International Nuclear Information System (INIS)

    Hasegawa, Jun-ichi; Okada, Noritake; Toriwaki, Jun-ichiro

    1988-01-01

    This paper presents further experiments on intelligent retrieval in our chest X-ray image database system using 'sketches'. First, in the previous sketch extraction procedure, vertical-location-invariant thresholding and shape-oriented smoothing are newly developed to improve the precision of lung borders and rib images in each sketch, respectively. Then, two new ways for image retrieval using sketches; (1) image-description retrieval and (2) pattern-matching retrieval, are proposed. In each retrieval way, a procedure for understanding picture queries input through a sketch is described in detail. (author)

  1. Relevance Feedback in Content Based Image Retrieval: A Review

    Directory of Open Access Journals (Sweden)

    Manesh B. Kokare

    2011-01-01

    Full Text Available This paper provides an overview of the technical achievements in the research area of relevance feedback (RF in content-based image retrieval (CBIR. Relevance feedback is a powerful technique in CBIR systems, in order to improve the performance of CBIR effectively. It is an open research area to the researcher to reduce the semantic gap between low-level features and high level concepts. The paper covers the current state of art of the research in relevance feedback in CBIR, various relevance feedback techniques and issues in relevance feedback are discussed in detail.

  2. Application of object modeling technique to medical image retrieval system

    International Nuclear Information System (INIS)

    Teshima, Fumiaki; Abe, Takeshi

    1993-01-01

    This report describes the results of discussions on the object-oriented analysis methodology, which is one of the object-oriented paradigms. In particular, we considered application of the object modeling technique (OMT) to the analysis of a medical image retrieval system. The object-oriented methodology places emphasis on the construction of an abstract model from real-world entities. The effectiveness of and future improvements to OMT are discussed from the standpoint of the system's expandability. These discussions have elucidated that the methodology is sufficiently well-organized and practical to be applied to commercial products, provided that it is applied to the appropriate problem domain. (author)

  3. Content-based image retrieval with ontological ranking

    Science.gov (United States)

    Tsai, Shen-Fu; Tsai, Min-Hsuan; Huang, Thomas S.

    2010-02-01

    Images are a much more powerful medium of expression than text, as the adage says: "One picture is worth a thousand words." It is because compared with text consisting of an array of words, an image has more degrees of freedom and therefore a more complicated structure. However, the less limited structure of images presents researchers in the computer vision community a tough task of teaching machines to understand and organize images, especially when a limit number of learning examples and background knowledge are given. The advance of internet and web technology in the past decade has changed the way human gain knowledge. People, hence, can exchange knowledge with others by discussing and contributing information on the web. As a result, the web pages in the internet have become a living and growing source of information. One is therefore tempted to wonder whether machines can learn from the web knowledge base as well. Indeed, it is possible to make computer learn from the internet and provide human with more meaningful knowledge. In this work, we explore this novel possibility on image understanding applied to semantic image search. We exploit web resources to obtain links from images to keywords and a semantic ontology constituting human's general knowledge. The former maps visual content to related text in contrast to the traditional way of associating images with surrounding text; the latter provides relations between concepts for machines to understand to what extent and in what sense an image is close to the image search query. With the aid of these two tools, the resulting image search system is thus content-based and moreover, organized. The returned images are ranked and organized such that semantically similar images are grouped together and given a rank based on the semantic closeness to the input query. The novelty of the system is twofold: first, images are retrieved not only based on text cues but their actual contents as well; second, the grouping

  4. A single-image method of aberration retrieval for imaging systems under partially coherent illumination

    International Nuclear Information System (INIS)

    Xu, Shuang; Liu, Shiyuan; Zhang, Chuanwei; Wei, Haiqing

    2014-01-01

    We propose a method for retrieving small lens aberrations in optical imaging systems under partially coherent illumination, which only requires to measure one single defocused image of intensity. By deriving a linear theory of imaging systems, we obtain a generalized formulation of aberration sensitivity in a matrix form, which provides a set of analytic kernels that relate the measured intensity distribution directly to the unknown Zernike coefficients. Sensitivity analysis is performed and test patterns are optimized to ensure well-posedness of the inverse problem. Optical lithography simulations have validated the theoretical derivation and confirmed its simplicity and superior performance in retrieving small lens aberrations. (fast track communication)

  5. Model-based magnetization retrieval from holographic phase images

    Energy Technology Data Exchange (ETDEWEB)

    Röder, Falk, E-mail: f.roeder@hzdr.de [Helmholtz-Zentrum Dresden-Rossendorf, Institut für Ionenstrahlphysik und Materialforschung, Bautzner Landstr. 400, D-01328 Dresden (Germany); Triebenberg Labor, Institut für Strukturphysik, Technische Universität Dresden, D-01062 Dresden (Germany); Vogel, Karin [Triebenberg Labor, Institut für Strukturphysik, Technische Universität Dresden, D-01062 Dresden (Germany); Wolf, Daniel [Helmholtz-Zentrum Dresden-Rossendorf, Institut für Ionenstrahlphysik und Materialforschung, Bautzner Landstr. 400, D-01328 Dresden (Germany); Triebenberg Labor, Institut für Strukturphysik, Technische Universität Dresden, D-01062 Dresden (Germany); Hellwig, Olav [Helmholtz-Zentrum Dresden-Rossendorf, Institut für Ionenstrahlphysik und Materialforschung, Bautzner Landstr. 400, D-01328 Dresden (Germany); AG Magnetische Funktionsmaterialien, Institut für Physik, Technische Universität Chemnitz, D-09126 Chemnitz (Germany); HGST, A Western Digital Company, 3403 Yerba Buena Rd., San Jose, CA 95135 (United States); Wee, Sung Hun [HGST, A Western Digital Company, 3403 Yerba Buena Rd., San Jose, CA 95135 (United States); Wicht, Sebastian; Rellinghaus, Bernd [IFW Dresden, Institute for Metallic Materials, P.O. Box 270116, D-01171 Dresden (Germany)

    2017-05-15

    The phase shift of the electron wave is a useful measure for the projected magnetic flux density of magnetic objects at the nanometer scale. More important for materials science, however, is the knowledge about the magnetization in a magnetic nano-structure. As demonstrated here, a dominating presence of stray fields prohibits a direct interpretation of the phase in terms of magnetization modulus and direction. We therefore present a model-based approach for retrieving the magnetization by considering the projected shape of the nano-structure and assuming a homogeneous magnetization therein. We apply this method to FePt nano-islands epitaxially grown on a SrTiO{sub 3} substrate, which indicates an inclination of their magnetization direction relative to the structural easy magnetic [001] axis. By means of this real-world example, we discuss prospects and limits of this approach. - Highlights: • Retrieval of the magnetization from holographic phase images. • Magnetostatic model constructed for a magnetic nano-structure. • Decomposition into homogeneously magnetized components. • Discretization of a each component by elementary cuboids. • Analytic solution for the phase of a magnetized cuboid considered. • Fitting a set of magnetization vectors to experimental phase images.

  6. ImageGrouper: a group-oriented user interface for content-based image retrieval and digital image arrangement

    NARCIS (Netherlands)

    Nakazato, Munehiro; Manola, L.; Huang, Thomas S.

    In content-based image retrieval (CBIR), experimental (trial-and-error) query with relevance feedback is essential for successful retrieval. Unfortunately, the traditional user interfaces are not suitable for trying different combinations of query examples. This is because first, these systems

  7. Biased discriminant euclidean embedding for content-based image retrieval.

    Science.gov (United States)

    Bian, Wei; Tao, Dacheng

    2010-02-01

    With many potential multimedia applications, content-based image retrieval (CBIR) has recently gained more attention for image management and web search. A wide variety of relevance feedback (RF) algorithms have been developed in recent years to improve the performance of CBIR systems. These RF algorithms capture user's preferences and bridge the semantic gap. However, there is still a big room to further the RF performance, because the popular RF algorithms ignore the manifold structure of image low-level visual features. In this paper, we propose the biased discriminative Euclidean embedding (BDEE) which parameterises samples in the original high-dimensional ambient space to discover the intrinsic coordinate of image low-level visual features. BDEE precisely models both the intraclass geometry and interclass discrimination and never meets the undersampled problem. To consider unlabelled samples, a manifold regularization-based item is introduced and combined with BDEE to form the semi-supervised BDEE, or semi-BDEE for short. To justify the effectiveness of the proposed BDEE and semi-BDEE, we compare them against the conventional RF algorithms and show a significant improvement in terms of accuracy and stability based on a subset of the Corel image gallery.

  8. Retrieving high-resolution images over the Internet from an anatomical image database

    Science.gov (United States)

    Strupp-Adams, Annette; Henderson, Earl

    1999-12-01

    The Visible Human Data set is an important contribution to the national collection of anatomical images. To enhance the availability of these images, the National Library of Medicine has supported the design and development of a prototype object-oriented image database which imports, stores, and distributes high resolution anatomical images in both pixel and voxel formats. One of the key database modules is its client-server Internet interface. This Web interface provides a query engine with retrieval access to high-resolution anatomical images that range in size from 100KB for browser viewable rendered images, to 1GB for anatomical structures in voxel file formats. The Web query and retrieval client-server system is composed of applet GUIs, servlets, and RMI application modules which communicate with each other to allow users to query for specific anatomical structures, and retrieve image data as well as associated anatomical images from the database. Selected images can be downloaded individually as single files via HTTP or downloaded in batch-mode over the Internet to the user's machine through an applet that uses Netscape's Object Signing mechanism. The image database uses ObjectDesign's object-oriented DBMS, ObjectStore that has a Java interface. The query and retrieval systems has been tested with a Java-CDE window system, and on the x86 architecture using Windows NT 4.0. This paper describes the Java applet client search engine that queries the database; the Java client module that enables users to view anatomical images online; the Java application server interface to the database which organizes data returned to the user, and its distribution engine that allow users to download image files individually and/or in batch-mode.

  9. Coupled binary embedding for large-scale image retrieval.

    Science.gov (United States)

    Zheng, Liang; Wang, Shengjin; Tian, Qi

    2014-08-01

    Visual matching is a crucial step in image retrieval based on the bag-of-words (BoW) model. In the baseline method, two keypoints are considered as a matching pair if their SIFT descriptors are quantized to the same visual word. However, the SIFT visual word has two limitations. First, it loses most of its discriminative power during quantization. Second, SIFT only describes the local texture feature. Both drawbacks impair the discriminative power of the BoW model and lead to false positive matches. To tackle this problem, this paper proposes to embed multiple binary features at indexing level. To model correlation between features, a multi-IDF scheme is introduced, through which different binary features are coupled into the inverted file. We show that matching verification methods based on binary features, such as Hamming embedding, can be effectively incorporated in our framework. As an extension, we explore the fusion of binary color feature into image retrieval. The joint integration of the SIFT visual word and binary features greatly enhances the precision of visual matching, reducing the impact of false positive matches. Our method is evaluated through extensive experiments on four benchmark datasets (Ukbench, Holidays, DupImage, and MIR Flickr 1M). We show that our method significantly improves the baseline approach. In addition, large-scale experiments indicate that the proposed method requires acceptable memory usage and query time compared with other approaches. Further, when global color feature is integrated, our method yields competitive performance with the state-of-the-arts.

  10. Large-Scale Partial-Duplicate Image Retrieval and Its Applications

    Science.gov (United States)

    2016-04-23

    tree based image retrieval , a semantic-aware co-indexing algorithm is proposed to jointly embed two strong cues into the inverted indexes: 1) local...based image retrieval , a semantic-aware co-indexing algorithm is proposed to jointly embed two strong cues into the inverted indexes: 1) local...Distribution Unlimited UU UU UU UU 23-04-2016 23-Jan-2012 22-Jan-2016 Final Report: Large-Scale Partial-Duplicate Image Retrieval and Its Applications

  11. Design Guidelines for a Content-Based Image Retrieval Color-Selection Interface

    NARCIS (Netherlands)

    Eggen, Berry; van den Broek, Egon; van der Veer, Gerrit C.; Kisters, Peter M.F.; Willems, Rob; Vuurpijl, Louis G.

    2004-01-01

    In Content-Based Image Retrieval (CBIR) two query-methods exist: query-by-example and query-by-memory. The user either selects an example image or selects image features retrieved from memory (such as color, texture, spatial attributes, and shape) to define his query. Hitherto, research on CBIR

  12. Interactive Processing and Visualization of Image Data forBiomedical and Life Science Applications

    Energy Technology Data Exchange (ETDEWEB)

    Staadt, Oliver G.; Natarjan, Vijay; Weber, Gunther H.; Wiley,David F.; Hamann, Bernd

    2007-02-01

    Background: Applications in biomedical science and life science produce large data sets using increasingly powerful imaging devices and computer simulations. It is becoming increasingly difficult for scientists to explore and analyze these data using traditional tools. Interactive data processing and visualization tools can support scientists to overcome these limitations. Results: We show that new data processing tools and visualization systems can be used successfully in biomedical and life science applications. We present an adaptive high-resolution display system suitable for biomedical image data, algorithms for analyzing and visualization protein surfaces and retinal optical coherence tomography data, and visualization tools for 3D gene expression data. Conclusion: We demonstrated that interactive processing and visualization methods and systems can support scientists in a variety of biomedical and life science application areas concerned with massive data analysis.

  13. Collaborative Initiative in Biomedical Imaging to Study Complex Diseases

    Energy Technology Data Exchange (ETDEWEB)

    Lin, Weili [The University of North Carolina at Chapel Hill; Fiddy, Michael A. [The University of North Carolina at Charlotte

    2012-03-31

    The work reported addressed these topics: Fluorescence imaging; Optical coherence tomography; X-ray interferometer/phase imaging system; Quantitative imaging from scattered fields, Terahertz imaging and spectroscopy; and Multiphoton and Raman microscopy.

  14. The ImageJ ecosystem: An open platform for biomedical image analysis.

    Science.gov (United States)

    Schindelin, Johannes; Rueden, Curtis T; Hiner, Mark C; Eliceiri, Kevin W

    2015-01-01

    Technology in microscopy advances rapidly, enabling increasingly affordable, faster, and more precise quantitative biomedical imaging, which necessitates correspondingly more-advanced image processing and analysis techniques. A wide range of software is available-from commercial to academic, special-purpose to Swiss army knife, small to large-but a key characteristic of software that is suitable for scientific inquiry is its accessibility. Open-source software is ideal for scientific endeavors because it can be freely inspected, modified, and redistributed; in particular, the open-software platform ImageJ has had a huge impact on the life sciences, and continues to do so. From its inception, ImageJ has grown significantly due largely to being freely available and its vibrant and helpful user community. Scientists as diverse as interested hobbyists, technical assistants, students, scientific staff, and advanced biology researchers use ImageJ on a daily basis, and exchange knowledge via its dedicated mailing list. Uses of ImageJ range from data visualization and teaching to advanced image processing and statistical analysis. The software's extensibility continues to attract biologists at all career stages as well as computer scientists who wish to effectively implement specific image-processing algorithms. In this review, we use the ImageJ project as a case study of how open-source software fosters its suites of software tools, making multitudes of image-analysis technology easily accessible to the scientific community. We specifically explore what makes ImageJ so popular, how it impacts the life sciences, how it inspires other projects, and how it is self-influenced by coevolving projects within the ImageJ ecosystem. © 2015 Wiley Periodicals, Inc.

  15. Design of e-Science platform for biomedical imaging research cross multiple academic institutions and hospitals

    Science.gov (United States)

    Zhang, Jianguo; Zhang, Kai; Yang, Yuanyuan; Ling, Tonghui; Wang, Tusheng; Wang, Mingqing; Hu, Haibo; Xu, Xuemin

    2012-02-01

    More and more image informatics researchers and engineers are considering to re-construct imaging and informatics infrastructure or to build new framework to enable multiple disciplines of medical researchers, clinical physicians and biomedical engineers working together in a secured, efficient, and transparent cooperative environment. In this presentation, we show an outline and our preliminary design work of building an e-Science platform for biomedical imaging and informatics research and application in Shanghai. We will present our consideration and strategy on designing this platform, and preliminary results. We also will discuss some challenges and solutions in building this platform.

  16. Content-based image retrieval applied to bone age assessment

    Science.gov (United States)

    Fischer, Benedikt; Brosig, André; Welter, Petra; Grouls, Christoph; Günther, Rolf W.; Deserno, Thomas M.

    2010-03-01

    Radiological bone age assessment is based on local image regions of interest (ROI), such as the epiphysis or the area of carpal bones. These are compared to a standardized reference and scores determining the skeletal maturity are calculated. For computer-aided diagnosis, automatic ROI extraction and analysis is done so far mainly by heuristic approaches. Due to high variations in the imaged biological material and differences in age, gender and ethnic origin, automatic analysis is difficult and frequently requires manual interactions. On the contrary, epiphyseal regions (eROIs) can be compared to previous cases with known age by content-based image retrieval (CBIR). This requires a sufficient number of cases with reliable positioning of the eROI centers. In this first approach to bone age assessment by CBIR, we conduct leaving-oneout experiments on 1,102 left hand radiographs and 15,428 metacarpal and phalangeal eROIs from the USC hand atlas. The similarity of the eROIs is assessed by cross-correlation of 16x16 scaled eROIs. The effects of the number of eROIs, two age computation methods as well as the number of considered CBIR references are analyzed. The best results yield an error rate of 1.16 years and a standard deviation of 0.85 years. As the appearance of the hand varies naturally by up to two years, these results clearly demonstrate the applicability of the CBIR approach for bone age estimation.

  17. INTEGRATION OF SPATIAL INFORMATION WITH COLOR FOR CONTENT RETRIEVAL OF REMOTE SENSING IMAGES

    Directory of Open Access Journals (Sweden)

    Bikesh Kumar Singh

    2010-08-01

    Full Text Available There is rapid increase in image databases of remote sensing images due to image satellites with high resolution, commercial applications of remote sensing & high available bandwidth in last few years. The problem of content-based image retrieval (CBIR of remotely sensed images presents a major challenge not only because of the surprisingly increasing volume of images acquired from a wide range of sensors but also because of the complexity of images themselves. In this paper, a software system for content-based retrieval of remote sensing images using RGB and HSV color spaces is presented. Further, we also compare our results with spatiogram based content retrieval which integrates spatial information along with color histogram. Experimental results show that the integration of spatial information in color improves the image analysis of remote sensing data. In general, retrievals in HSV color space showed better performance than in RGB color space.

  18. Biomedical informatics and translational medicine

    Directory of Open Access Journals (Sweden)

    Sarkar Indra

    2010-02-01

    Full Text Available Abstract Biomedical informatics involves a core set of methodologies that can provide a foundation for crossing the "translational barriers" associated with translational medicine. To this end, the fundamental aspects of biomedical informatics (e.g., bioinformatics, imaging informatics, clinical informatics, and public health informatics may be essential in helping improve the ability to bring basic research findings to the bedside, evaluate the efficacy of interventions across communities, and enable the assessment of the eventual impact of translational medicine innovations on health policies. Here, a brief description is provided for a selection of key biomedical informatics topics (Decision Support, Natural Language Processing, Standards, Information Retrieval, and Electronic Health Records and their relevance to translational medicine. Based on contributions and advancements in each of these topic areas, the article proposes that biomedical informatics practitioners ("biomedical informaticians" can be essential members of translational medicine teams.

  19. Combining textual and visual information for image retrieval in the medical domain.

    Science.gov (United States)

    Gkoufas, Yiannis; Morou, Anna; Kalamboukis, Theodore

    2011-01-01

    In this article we have assembled the experience obtained from our participation in the imageCLEF evaluation task over the past two years. Exploitation on the use of linear combinations for image retrieval has been attempted by combining visual and textual sources of images. From our experiments we conclude that a mixed retrieval technique that applies both textual and visual retrieval in an interchangeably repeated manner improves the performance while overcoming the scalability limitations of visual retrieval. In particular, the mean average precision (MAP) has increased from 0.01 to 0.15 and 0.087 for 2009 and 2010 data, respectively, when content-based image retrieval (CBIR) is performed on the top 1000 results from textual retrieval based on natural language processing (NLP).

  20. Scientific Programs and Funding Opportunities at the National Institute of Biomedical Imaging and Bioengineering

    Science.gov (United States)

    Baird, Richard

    2006-03-01

    The mission of the National Institute of Biomedical Imaging and Bioengineering (NIBIB) is to improve human health by promoting the development and translation of emerging technologies in biomedical imaging and bioengineering. To this end, NIBIB supports a coordinated agenda of research programs in advanced imaging technologies and engineering methods that enable fundamental biomedical discoveries across a broad spectrum of biological processes, disorders, and diseases and have significant potential for direct medical application. These research programs dramatically advance the Nation's healthcare by improving the detection, management and, ultimately, the prevention of disease. The research promoted and supported by NIBIB also is strongly synergistic with other NIH Institutes and Centers as well as across government agencies. This presentation will provide an overview of the scientific programs and funding opportunities supported by NIBIB, highlighting those that are of particular important to the field of medical physics.

  1. Multiscale integration of -omic, imaging, and clinical data in biomedical informatics.

    Science.gov (United States)

    Phan, John H; Quo, Chang F; Cheng, Chihwen; Wang, May Dongmei

    2012-01-01

    This paper reviews challenges and opportunities in multiscale data integration for biomedical informatics. Biomedical data can come from different biological origins, data acquisition technologies, and clinical applications. Integrating such data across multiple scales (e.g., molecular, cellular/tissue, and patient) can lead to more informed decisions for personalized, predictive, and preventive medicine. However, data heterogeneity, community standards in data acquisition, and computational complexity are big challenges for such decision making. This review describes genomic and proteomic (i.e., molecular), histopathological imaging (i.e., cellular/tissue), and clinical (i.e., patient) data; it includes case studies for single-scale (e.g., combining genomic or histopathological image data), multiscale (e.g., combining histopathological image and clinical data), and multiscale and multiplatform (e.g., the Human Protein Atlas and The Cancer Genome Atlas) data integration. Numerous opportunities exist in biomedical informatics research focusing on integration of multiscale and multiplatform data.

  2. New software developments for quality mesh generation and optimization from biomedical imaging data.

    Science.gov (United States)

    Yu, Zeyun; Wang, Jun; Gao, Zhanheng; Xu, Ming; Hoshijima, Masahiko

    2014-01-01

    In this paper we present a new software toolkit for generating and optimizing surface and volumetric meshes from three-dimensional (3D) biomedical imaging data, targeted at image-based finite element analysis of some biomedical activities in a single material domain. Our toolkit includes a series of geometric processing algorithms including surface re-meshing and quality-guaranteed tetrahedral mesh generation and optimization. All methods described have been encapsulated into a user-friendly graphical interface for easy manipulation and informative visualization of biomedical images and mesh models. Numerous examples are presented to demonstrate the effectiveness and efficiency of the described methods and toolkit. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  3. Blind phase retrieval for aberrated linear shift-invariant imaging systems

    International Nuclear Information System (INIS)

    Yu, Rotha P; Paganin, David M

    2010-01-01

    We develop a means to reconstruct an input complex coherent scalar wavefield, given a through focal series (TFS) of three intensity images output from a two-dimensional (2D) linear shift-invariant optical imaging system with unknown aberrations. This blind phase retrieval technique unites two methods, namely (i) TFS phase retrieval and (ii) iterative blind deconvolution. The efficacy of our blind phase retrieval procedure has been demonstrated using simulated data, for a variety of Poisson noise levels.

  4. Scalable Integrated Region-Based Image Retrieval Using IRM and Statistical Clustering.

    Science.gov (United States)

    Wang, James Z.; Du, Yanping

    Statistical clustering is critical in designing scalable image retrieval systems. This paper presents a scalable algorithm for indexing and retrieving images based on region segmentation. The method uses statistical clustering on region features and IRM (Integrated Region Matching), a measure developed to evaluate overall similarity between images…

  5. Learning effective color features for content based image retrieval in dermatology

    NARCIS (Netherlands)

    Bunte, Kerstin; Biehl, Michael; Jonkman, Marcel F.; Petkov, Nicolai

    We investigate the extraction of effective color features for a content-based image retrieval (CBIR) application in dermatology. Effectiveness is measured by the rate of correct retrieval of images from four color classes of skin lesions. We employ and compare two different methods to learn

  6. A Fast, Background-Independent Retrieval Strategy for Color Image Databases

    National Research Council Canada - National Science Library

    Das, M; Draper, B. A; Lim, W. J; Manmatha, R; Riseman, E. M

    1996-01-01

    We describe an interactive, multi-phase color-based image retrieval system which is capable of identifying query objects specified by the user in an image in the presence of significant, interfering backgrounds...

  7. Bio-medical X-ray imaging with spectroscopic pixel detectors

    CERN Document Server

    Butler, A P H; Tipples, R; Cook, N; Watts, R; Meyer, J; Bell, A J; Melzer, T R; Butler, P H

    2008-01-01

    The aim of this study is to review the clinical potential of spectroscopic X-ray detectors and to undertake a feasibility study using a novel detector in a clinical hospital setting. Detectors currently in development, such as Medipix-3, will have multiple energy thresholds allowing for routine use of spectroscopic bio-medical imaging. We have coined the term MARS (Medipix All Resolution System) for bio-medical images that provide spatial, temporal, and energy information. The full clinical significance of spectroscopic X-ray imaging is difficult to predict but insights can be gained by examining both image reconstruction artifacts and the current uses of dual-energy techniques. This paper reviews the known uses of energy information in vascular imaging and mammography, clinically important fields. It then presents initial results from using Medipix-2, to image human tissues within a clinical radiology department. Detectors currently in development, such as Medipix-3, will have multiple energy thresholds allo...

  8. Biomedical image analysis recipes in Matlab for life scientists and engineers

    CERN Document Server

    Reyes-Aldasoro, Constantino Carlos

    2015-01-01

    As its title suggests, this innovative book has been written for life scientists needing to analyse their data sets, and programmers, wanting a better understanding of the types of experimental images life scientists investigate on a regular basis. Each chapter presents one self-contained biomedical experiment to be analysed. Part I of the book presents its two basic ingredients: essential concepts of image analysis and Matlab. In Part II, algorithms and techniques are shown as series of 'recipes' or solved examples that show how specific techniques are applied to a biomedical experiments like

  9. Face Image Retrieval of Efficient Sparse Code words and Multiple Attribute in Binning Image

    Directory of Open Access Journals (Sweden)

    Suchitra S

    2017-08-01

    Full Text Available ABSTRACT In photography, face recognition and face retrieval play an important role in many applications such as security, criminology and image forensics. Advancements in face recognition make easier for identity matching of an individual with attributes. Latest development in computer vision technologies enables us to extract facial attributes from the input image and provide similar image results. In this paper, we propose a novel LOP and sparse codewords method to provide similar matching results with respect to input query image. To improve accuracy in image results with input image and dynamic facial attributes, Local octal pattern algorithm [LOP] and Sparse codeword applied in offline and online. The offline and online procedures in face image binning techniques apply with sparse code. Experimental results with Pubfig dataset shows that the proposed LOP along with sparse codewords able to provide matching results with increased accuracy of 90%.

  10. An intelligent framework for medical image retrieval using MDCT and multi SVM.

    Science.gov (United States)

    Balan, J A Alex Rajju; Rajan, S Edward

    2014-01-01

    Volumes of medical images are rapidly generated in medical field and to manage them effectively has become a great challenge. This paper studies the development of innovative medical image retrieval based on texture features and accuracy. The objective of the paper is to analyze the image retrieval based on diagnosis of healthcare management systems. This paper traces the development of innovative medical image retrieval to estimate both the image texture features and accuracy. The texture features of medical images are extracted using MDCT and multi SVM. Both the theoretical approach and the simulation results revealed interesting observations and they were corroborated using MDCT coefficients and SVM methodology. All attempts to extract the data about the image in response to the query has been computed successfully and perfect image retrieval performance has been obtained. Experimental results on a database of 100 trademark medical images show that an integrated texture feature representation results in 98% of the images being retrieved using MDCT and multi SVM. Thus we have studied a multiclassification technique based on SVM which is prior suitable for medical images. The results show the retrieval accuracy of 98%, 99% for different sets of medical images with respect to the class of image.

  11. Filled carbon nanotubes in biomedical imaging and drug delivery.

    Science.gov (United States)

    Martincic, Markus; Tobias, Gerard

    2015-04-01

    Carbon nanotubes have been advocated as promising candidates in the biomedical field in the areas of diagnosis and therapy. In terms of drug delivery, the use of carbon nanotubes can overcome some limitations of 'free' drugs by improving the formulation of poorly water-soluble drugs, allowing targeted delivery and even enabling the co-delivery of two or more drugs for combination therapy. Two different approaches are currently being explored for the delivery of diagnostic and therapeutic agents by carbon nanotubes, namely attachment of the payload to the external sidewalls or encapsulation into the inner cavities. Although less explored, the latter confers additional stability to the chosen diagnostic or therapeutic agents, and leaves the backbone structure of the nanotubes available for its functionalization with dispersing and targeting moieties. Several drug delivery systems and diagnostic agents have been developed in the last years employing the inner tubular cavities of carbon nanotubes. The research discussed in this review focuses on the use of carbon nanotubes that contain in their interior drug molecules and diagnosis-related compounds. The approaches employed for the development of such nanoscale vehicles along with targeting and releasing strategies are discussed. The encapsulation of both biomedical contrast agents and drugs inside carbon nanotubes is further expanding the possibilities to allow an early diagnosis and treatment of diseases.

  12. An image fiber based fluorescent probe with associated signal processing scheme for biomedical diagnostics

    International Nuclear Information System (INIS)

    Vaishakh, M; Murukeshan, V M; Seah, L K

    2008-01-01

    A dual-modality image fiber based fluorescent probe that can be used for depth sensitive imaging and suppression of fluorescent emissions with nanosecond lifetime difference is proposed and illustrated in this paper. The system can give high optical sectioning and employs an algorithm for obtaining phase sensitive images. The system can find main application in in vivo biomedical diagnostics for detecting biochemical changes for distinguishing malignant tissue from healthy tissue

  13. Socializing the Semantic Gap: A Comparative Survey on Image Tag Assignment, Refinement and Retrieval

    NARCIS (Netherlands)

    Li, X.; Uricchio, T.; Ballan, L.; Bertini, M.; Snoek, C.G.M.; Del Bimbo, A.

    2016-01-01

    Where previous reviews on content-based image retrieval emphasize what can be seen in an image to bridge the semantic gap, this survey considers what people tag about an image. A comprehensive treatise of three closely linked problems (i.e., image tag assignment, refinement, and tag-based image

  14. Image retrieval by information fusion based on scalable vocabulary tree and robust Hausdorff distance

    Science.gov (United States)

    Che, Chang; Yu, Xiaoyang; Sun, Xiaoming; Yu, Boyang

    2017-12-01

    In recent years, Scalable Vocabulary Tree (SVT) has been shown to be effective in image retrieval. However, for general images where the foreground is the object to be recognized while the background is cluttered, the performance of the current SVT framework is restricted. In this paper, a new image retrieval framework that incorporates a robust distance metric and information fusion is proposed, which improves the retrieval performance relative to the baseline SVT approach. First, the visual words that represent the background are diminished by using a robust Hausdorff distance between different images. Second, image matching results based on three image signature representations are fused, which enhances the retrieval precision. We conducted intensive experiments on small-scale to large-scale image datasets: Corel-9, Corel-48, and PKU-198, where the proposed Hausdorff metric and information fusion outperforms the state-of-the-art methods by about 13, 15, and 15%, respectively.

  15. Content-Based Image Retrieval Based on Electromagnetism-Like Mechanism

    Directory of Open Access Journals (Sweden)

    Hamid A. Jalab

    2013-01-01

    Full Text Available Recently, many researchers in the field of automatic content-based image retrieval have devoted a remarkable amount of research looking for methods to retrieve the best relevant images to the query image. This paper presents a novel algorithm for increasing the precision in content-based image retrieval based on electromagnetism optimization technique. The electromagnetism optimization is a nature-inspired technique that follows the collective attraction-repulsion mechanism by considering each image as an electrical charge. The algorithm is composed of two phases: fitness function measurement and electromagnetism optimization technique. It is implemented on a database with 8,000 images spread across 80 classes with 100 images in each class. Eight thousand queries are fired on the database, and the overall average precision is computed. Experimental results of the proposed approach have shown significant improvement in the retrieval performance in regard to precision.

  16. Biomedical applications of nanodiamonds in imaging and therapy.

    Science.gov (United States)

    Perevedentseva, Elena; Lin, Yu-Chung; Jani, Mona; Cheng, Chia-Liang

    2013-12-01

    Nanodiamonds have attracted remarkable scientific attention for bioimaging and therapeutic applications owing to their low toxicity with many cell lines, convenient surface properties and stable fluorescence without photobleaching. Newer techniques are being applied to enhance fluorescence. Interest is also growing in exploring the possibilities for modifying the nanodiamond surface and functionalities by attaching various biomolecules of interest for interaction with the targets. The potential of Raman spectroscopy and fluorescence properties of nanodiamonds has been explored for bioimaging and drug delivery tracing. The interest in nanodiamonds' biological/medical application appears to be continuing with enhanced focus. In this review an attempt is made to capture the scope, spirit and recent developments in the field of nanodiamonds for biomedical applications.

  17. A Novel Technique for Shape Feature Extraction Using Content Based Image Retrieval

    Directory of Open Access Journals (Sweden)

    Dhanoa Jaspreet Singh

    2016-01-01

    Full Text Available With the advent of technology and multimedia information, digital images are increasing very quickly. Various techniques are being developed to retrieve/search digital information or data contained in the image. Traditional Text Based Image Retrieval System is not plentiful. Since it is time consuming as it require manual image annotation. Also, the image annotation differs with different peoples. An alternate to this is Content Based Image Retrieval (CBIR system. It retrieves/search for image using its contents rather the text, keywords etc. A lot of exploration has been compassed in the range of Content Based Image Retrieval (CBIR with various feature extraction techniques. Shape is a significant image feature as it reflects the human perception. Moreover, Shape is quite simple to use by the user to define object in an image as compared to other features such as Color, texture etc. Over and above, if applied alone, no descriptor will give fruitful results. Further, by combining it with an improved classifier, one can use the positive features of both the descriptor and classifier. So, a tryout will be made to establish an algorithm for accurate feature (Shape extraction in Content Based Image Retrieval (CBIR. The main objectives of this project are: (a To propose an algorithm for shape feature extraction using CBIR, (b To evaluate the performance of proposed algorithm and (c To compare the proposed algorithm with state of art techniques.

  18. Random laser illumination: an ideal source for biomedical polarization imaging?

    Science.gov (United States)

    Carvalho, Mariana T.; Lotay, Amrit S.; Kenny, Fiona M.; Girkin, John M.; Gomes, Anderson S. L.

    2016-03-01

    Imaging applications increasingly require light sources with high spectral density (power over spectral bandwidth. This has led in many cases to the replacement of conventional thermal light sources with bright light-emitting diodes (LEDs), lasers and superluminescent diodes. Although lasers and superluminescent diodes appear to be ideal light sources due to their narrow bandwidth and power, however, in the case of full-field imaging, their spatial coherence leads to coherent artefacts, such as speckle, that corrupt the image. LEDs, in contrast, have lower spatial coherence and thus seem the natural choice, but they have low spectral density. Random Lasers are an unconventional type of laser that can be engineered to provide low spatial coherence with high spectral density. These characteristics makes them potential sources for biological imaging applications where specific absorption and reflection are the characteristics required for state of the art imaging. In this work, a Random Laser (RL) is used to demonstrate speckle-free full-field imaging for polarization-dependent imaging in an epi-illumination configuration. We compare LED and RL illumination analysing the resulting images demonstrating that the RL illumination produces an imaging system with higher performance (image quality and spectral density) than that provided by LEDs.

  19. Biomedical imaging modality classification using combined visual features and textual terms.

    Science.gov (United States)

    Han, Xian-Hua; Chen, Yen-Wei

    2011-01-01

    We describe an approach for the automatic modality classification in medical image retrieval task of the 2010 CLEF cross-language image retrieval campaign (ImageCLEF). This paper is focused on the process of feature extraction from medical images and fuses the different extracted visual features and textual feature for modality classification. To extract visual features from the images, we used histogram descriptor of edge, gray, or color intensity and block-based variation as global features and SIFT histogram as local feature. For textual feature of image representation, the binary histogram of some predefined vocabulary words from image captions is used. Then, we combine the different features using normalized kernel functions for SVM classification. Furthermore, for some easy misclassified modality pairs such as CT and MR or PET and NM modalities, a local classifier is used for distinguishing samples in the pair modality to improve performance. The proposed strategy is evaluated with the provided modality dataset by ImageCLEF 2010.

  20. Robustness of phase retrieval methods in x-ray phase contrast imaging: A comparison

    International Nuclear Information System (INIS)

    Yan, Aimin; Wu, Xizeng; Liu, Hong

    2011-01-01

    Purpose: The robustness of the phase retrieval methods is of critical importance for limiting and reducing radiation doses involved in x-ray phase contrast imaging. This work is to compare the robustness of two phase retrieval methods by analyzing the phase maps retrieved from the experimental images of a phantom. Methods: Two phase retrieval methods were compared. One method is based on the transport of intensity equation (TIE) for phase contrast projections, and the TIE-based method is the most commonly used method for phase retrieval in the literature. The other is the recently developed attenuation-partition based (AP-based) phase retrieval method. The authors applied these two methods to experimental projection images of an air-bubble wrap phantom for retrieving the phase map of the bubble wrap. The retrieved phase maps obtained by using the two methods are compared. Results: In the wrap's phase map retrieved by using the TIE-based method, no bubble is recognizable, hence, this method failed completely for phase retrieval from these bubble wrap images. Even with the help of the Tikhonov regularization, the bubbles are still hardly visible and buried in the cluttered background in the retrieved phase map. The retrieved phase values with this method are grossly erroneous. In contrast, in the wrap's phase map retrieved by using the AP-based method, the bubbles are clearly recovered. The retrieved phase values with the AP-based method are reasonably close to the estimate based on the thickness-based measurement. The authors traced these stark performance differences of the two methods to their different techniques employed to deal with the singularity problem involved in the phase retrievals. Conclusions: This comparison shows that the conventional TIE-based phase retrieval method, regardless if Tikhonov regularization is used or not, is unstable against the noise in the wrap's projection images, while the AP-based phase retrieval method is shown in these

  1. W-transform method for feature-oriented multiresolution image retrieval

    Energy Technology Data Exchange (ETDEWEB)

    Kwong, M.K.; Lin, B. [Argonne National Lab., IL (United States). Mathematics and Computer Science Div.

    1995-07-01

    Image database management is important in the development of multimedia technology. Since an enormous amount of digital images is likely to be generated within the next few decades in order to integrate computers, television, VCR, cables, telephone and various imaging devices. Effective image indexing and retrieval systems are urgently needed so that images can be easily organized, searched, transmitted, and presented. Here, the authors present a local-feature-oriented image indexing and retrieval method based on Kwong, and Tang`s W-transform. Multiresolution histogram comparison is an effective method for content-based image indexing and retrieval. However, most recent approaches perform multiresolution analysis for whole images but do not exploit the local features present in the images. Since W-transform is featured by its ability to handle images of arbitrary size, with no periodicity assumptions, it provides a natural tool for analyzing local image features and building indexing systems based on such features. In this approach, the histograms of the local features of images are used in the indexing, system. The system not only can retrieve images that are similar or identical to the query images but also can retrieve images that contain features specified in the query images, even if the retrieved images as a whole might be very different from the query images. The local-feature-oriented method also provides a speed advantage over the global multiresolution histogram comparison method. The feature-oriented approach is expected to be applicable in managing large-scale image systems such as video databases and medical image databases.

  2. Optical image transformation and encryption by phase-retrieval-based double random-phase encoding and compressive ghost imaging

    Science.gov (United States)

    Yuan, Sheng; Yang, Yangrui; Liu, Xuemei; Zhou, Xin; Wei, Zhenzhuo

    2018-01-01

    An optical image transformation and encryption scheme is proposed based on double random-phase encoding (DRPE) and compressive ghost imaging (CGI) techniques. In this scheme, a secret image is first transformed into a binary image with the phase-retrieval-based DRPE technique, and then encoded by a series of random amplitude patterns according to the ghost imaging (GI) principle. Compressive sensing, corrosion and expansion operations are implemented to retrieve the secret image in the decryption process. This encryption scheme takes the advantage of complementary capabilities offered by the phase-retrieval-based DRPE and GI-based encryption techniques. That is the phase-retrieval-based DRPE is used to overcome the blurring defect of the decrypted image in the GI-based encryption, and the CGI not only reduces the data amount of the ciphertext, but also enhances the security of DRPE. Computer simulation results are presented to verify the performance of the proposed encryption scheme.

  3. Endovascular Device Testing with Particle Image Velocimetry Enhances Undergraduate Biomedical Engineering Education

    Science.gov (United States)

    Nair, Priya; Ankeny, Casey J.; Ryan, Justin; Okcay, Murat; Frakes, David H.

    2016-01-01

    We investigated the use of a new system, HemoFlow™, which utilizes state of the art technologies such as particle image velocimetry to test endovascular devices as part of an undergraduate biomedical engineering curriculum. Students deployed an endovascular stent into an anatomical model of a cerebral aneurysm and measured intra-aneurysmal flow…

  4. Retrieving clinically relevant diabetic retinopathy images using a multi-class multiple-instance framework

    Science.gov (United States)

    Chandakkar, Parag S.; Venkatesan, Ragav; Li, Baoxin

    2013-02-01

    Diabetic retinopathy (DR) is a vision-threatening complication from diabetes mellitus, a medical condition that is rising globally. Unfortunately, many patients are unaware of this complication because of absence of symptoms. Regular screening of DR is necessary to detect the condition for timely treatment. Content-based image retrieval, using archived and diagnosed fundus (retinal) camera DR images can improve screening efficiency of DR. This content-based image retrieval study focuses on two DR clinical findings, microaneurysm and neovascularization, which are clinical signs of non-proliferative and proliferative diabetic retinopathy. The authors propose a multi-class multiple-instance image retrieval framework which deploys a modified color correlogram and statistics of steerable Gaussian Filter responses, for retrieving clinically relevant images from a database of DR fundus image database.

  5. Implementation and evaluation of a medical image management system with content-based retrieval support

    International Nuclear Information System (INIS)

    Carita, Edilson Carlos; Seraphim, Enzo; Honda, Marcelo Ossamu; Azevedo-Marques, Paulo Mazzoncini de

    2008-01-01

    Objective: the present paper describes the implementation and evaluation of a medical images management system with content-based retrieval support (PACS-CBIR) integrating modules focused on images acquisition, storage and distribution, and text retrieval by keyword and images retrieval by similarity. Materials and methods: internet-compatible technologies were utilized for the system implementation with free ware, and C ++ , PHP and Java languages on a Linux platform. There is a DICOM-compatible image management module and two query modules, one of them based on text and the other on similarity of image texture attributes. Results: results demonstrate an appropriate images management and storage, and that the images retrieval time, always < 15 sec, was found to be good by users. The evaluation of retrieval by similarity has demonstrated that the selected images extractor allowed the sorting of images according to anatomical areas. Conclusion: based on these results, one can conclude that the PACS-CBIR implementation is feasible. The system has demonstrated to be DICOM-compatible, and that it can be integrated with the local information system. The similar images retrieval functionality can be enhanced by the introduction of further descriptors. (author)

  6. Molecular mass spectrometry imaging in biomedical and life science research

    Czech Academy of Sciences Publication Activity Database

    Pól, Jaroslav; Strohalm, Martin; Havlíček, Vladimír; Volný, Michael

    2010-01-01

    Roč. 134, č. 5 (2010), s. 423-443 ISSN 0948-6143 R&D Projects: GA MŠk LC545; GA ČR GPP206/10/P018 Institutional research plan: CEZ:AV0Z50200510 Keywords : Mass spectrometry * Chemical imaging * Molecular imaging Subject RIV: EE - Microbiology, Virology Impact factor: 4.727, year: 2010

  7. Advanced Contrast Agents for Multimodal Biomedical Imaging Based on Nanotechnology.

    Science.gov (United States)

    Calle, Daniel; Ballesteros, Paloma; Cerdán, Sebastián

    2018-01-01

    Clinical imaging modalities have reached a prominent role in medical diagnosis and patient management in the last decades. Different image methodologies as Positron Emission Tomography, Single Photon Emission Tomography, X-Rays, or Magnetic Resonance Imaging are in continuous evolution to satisfy the increasing demands of current medical diagnosis. Progress in these methodologies has been favored by the parallel development of increasingly more powerful contrast agents. These are molecules that enhance the intrinsic contrast of the images in the tissues where they accumulate, revealing noninvasively the presence of characteristic molecular targets or differential physiopathological microenvironments. The contrast agent field is currently moving to improve the performance of these molecules by incorporating the advantages that modern nanotechnology offers. These include, mainly, the possibilities to combine imaging and therapeutic capabilities over the same theranostic platform or improve the targeting efficiency in vivo by molecular engineering of the nanostructures. In this review, we provide an introduction to multimodal imaging methods in biomedicine, the sub-nanometric imaging agents previously used and the development of advanced multimodal and theranostic imaging agents based in nanotechnology. We conclude providing some illustrative examples from our own laboratories, including recent progress in theranostic formulations of magnetoliposomes containing ω-3 poly-unsaturated fatty acids to treat inflammatory diseases, or the use of stealth liposomes engineered with a pH-sensitive nanovalve to release their cargo specifically in the acidic extracellular pH microenvironment of tumors.

  8. The Prevalence of Inappropriate Image Duplication in Biomedical Research Publications

    Science.gov (United States)

    Casadevall, Arturo; Fang, Ferric C.

    2016-01-01

    ABSTRACT Inaccurate data in scientific papers can result from honest error or intentional falsification. This study attempted to determine the percentage of published papers that contain inappropriate image duplication, a specific type of inaccurate data. The images from a total of 20,621 papers published in 40 scientific journals from 1995 to 2014 were visually screened. Overall, 3.8% of published papers contained problematic figures, with at least half exhibiting features suggestive of deliberate manipulation. The prevalence of papers with problematic images has risen markedly during the past decade. Additional papers written by authors of papers with problematic images had an increased likelihood of containing problematic images as well. As this analysis focused only on one type of data, it is likely that the actual prevalence of inaccurate data in the published literature is higher. The marked variation in the frequency of problematic images among journals suggests that journal practices, such as prepublication image screening, influence the quality of the scientific literature. PMID:27273827

  9. Indexing, learning and content-based retrieval for special purpose image databases

    NARCIS (Netherlands)

    M.J. Huiskes (Mark); E.J. Pauwels (Eric)

    2005-01-01

    textabstractThis chapter deals with content-based image retrieval in special purpose image databases. As image data is amassed ever more effortlessly, building efficient systems for searching and browsing of image databases becomes increasingly urgent. We provide an overview of the current

  10. A software package for biomedical image processing and analysis

    International Nuclear Information System (INIS)

    Goncalves, J.G.M.; Mealha, O.

    1988-01-01

    The decreasing cost of computing power and the introduction of low cost imaging boards justifies the increasing number of applications of digital image processing techniques in the area of biomedicine. There is however a large software gap to be fulfilled, between the application and the equipment. The requirements to bridge this gap are twofold: good knowledge of the hardware provided and its interface to the host computer, and expertise in digital image processing and analysis techniques. A software package incorporating these two requirements was developed using the C programming language, in order to create a user friendly image processing programming environment. The software package can be considered in two different ways: as a data structure adapted to image processing and analysis, which acts as the backbone and the standard of communication for all the software; and as a set of routines implementing the basic algorithms used in image processing and analysis. Hardware dependency is restricted to a single module upon which all hardware calls are based. The data structure that was built has four main features: hierchical, open, object oriented, and object dependent dimensions. Considering the vast amount of memory needed by imaging applications and the memory available in small imaging systems, an effective image memory management scheme was implemented. This software package is being used for more than one and a half years by users with different applications. It proved to be an excellent tool for helping people to get adapted into the system, and for standardizing and exchanging software, yet preserving flexibility allowing for users' specific implementations. The philosophy of the software package is discussed and the data structure that was built is described in detail

  11. Image Retrieval based on Integration between Color and Geometric Moment Features

    International Nuclear Information System (INIS)

    Saad, M.H.; Saleh, H.I.; Konbor, H.; Ashour, M.

    2012-01-01

    Content based image retrieval is the retrieval of images based on visual features such as colour, texture and shape. .the Current approaches to CBIR differ in terms of which image features are extracted; recent work deals with combination of distances or scores from different and usually independent representations in an attempt to induce high level semantics from the low level descriptors of the images. content-based image retrieval has many application areas such as, education, commerce, military, searching, commerce, and biomedicine and Web image classification. This paper proposes a new image retrieval system, which uses color and geometric moment feature to form the feature vectors. Bhattacharyya distance and histogram intersection are used to perform feature matching. This framework integrates the color histogram which represents the global feature and geometric moment as local descriptor to enhance the retrieval results. The proposed technique is proper for precisely retrieving images even in deformation cases such as geometric deformations and noise. It is tested on a standard the results shows that a combination of our approach as a local image descriptor with other global descriptors outperforms other approaches.

  12. Non-Contact Optical Ultrasound Concept for Biomedical Imaging

    Science.gov (United States)

    2016-11-03

    reflection images of a phantom limb that contains muscle and bone surrogate materials and use the data for inversion of the Young’s modulus...CT are the dominant modalities used for many medical imaging applications including head injury, cancer, fractures and musculoskeletal disease. MRI...original higher frequency signal, but is oscillating at a lower more easily processed carrier frequency. Electrical field oscillations in the optical

  13. Performance analysis of algorithms for retrieval of magnetic resonance images for interactive teleradiology

    Science.gov (United States)

    Atkins, M. Stella; Hwang, Robert; Tang, Simon

    2001-05-01

    We have implemented a prototype system consisting of a Java- based image viewer and a web server extension component for transmitting Magnetic Resonance Images (MRI) to an image viewer, to test the performance of different image retrieval techniques. We used full-resolution images, and images compressed/decompressed using the Set Partitioning in Hierarchical Trees (SPIHT) image compression algorithm. We examined the SPIHT decompression algorithm using both non- progressive and progressive transmission, focusing on the running times of the algorithm, client memory usage and garbage collection. We also compared the Java implementation with a native C++ implementation of the non- progressive SPIHT decompression variant. Our performance measurements showed that for uncompressed image retrieval using a 10Mbps Ethernet, a film of 16 MR images can be retrieved and displayed almost within interactive times. The native C++ code implementation of the client-side decoder is twice as fast as the Java decoder. If the network bandwidth is low, the high communication time for retrieving uncompressed images may be reduced by use of SPIHT-compressed images, although the image quality is then degraded. To provide diagnostic quality images, we also investigated the retrieval of up to 3 images on a MR film at full-resolution, using progressive SPIHT decompression. The Java-based implementation of progressive decompression performed badly, mainly due to the memory requirements for maintaining the image states, and the high cost of execution of the Java garbage collector. Hence, in systems where the bandwidth is high, such as found in a hospital intranet, SPIHT image compression does not provide advantages for image retrieval performance.

  14. Implementation of Texture Based Image Retrieval Using M-band Wavelet Transform

    Institute of Scientific and Technical Information of China (English)

    LiaoYa-li; Yangyan; CaoYang

    2003-01-01

    Wavelet transform has attracted attention because it is a very useful tool for signal analyzing. As a fundamental characteristic of an image, texture traits play an important role in the human vision system for recognition and interpretation of images. The paper presents an approach to implement texture-based image retrieval using M-band wavelet transform. Firstly the traditional 2-band wavelet is extended to M-band wavelet transform. Then the wavelet moments are computed by M-band wavelet coefficients in the wavelet domain. The set of wavelet moments forms the feature vector related to the texture distribution of each wavelet images. The distances between the feature vectors describe the similarities of different images. The experimental result shows that the M-band wavelet moment features of the images are effective for image indexing.The retrieval method has lower computational complexity, yet it is capable of giving better retrieval performance for a given medical image database.

  15. Low-dose multiple-information retrieval algorithm for X-ray grating-based imaging

    International Nuclear Information System (INIS)

    Wang Zhentian; Huang Zhifeng; Chen Zhiqiang; Zhang Li; Jiang Xiaolei; Kang Kejun; Yin Hongxia; Wang Zhenchang; Stampanoni, Marco

    2011-01-01

    The present work proposes a low dose information retrieval algorithm for X-ray grating-based multiple-information imaging (GB-MII) method, which can retrieve the attenuation, refraction and scattering information of samples by only three images. This algorithm aims at reducing the exposure time and the doses delivered to the sample. The multiple-information retrieval problem in GB-MII is solved by transforming a nonlinear equations set to a linear equations and adopting the nature of the trigonometric functions. The proposed algorithm is validated by experiments both on conventional X-ray source and synchrotron X-ray source, and compared with the traditional multiple-image-based retrieval algorithm. The experimental results show that our algorithm is comparable with the traditional retrieval algorithm and especially suitable for high Signal-to-Noise system.

  16. Fundus Image Features Extraction for Exudate Mining in Coordination with Content Based Image Retrieval: A Study

    Science.gov (United States)

    Gururaj, C.; Jayadevappa, D.; Tunga, Satish

    2018-06-01

    Medical field has seen a phenomenal improvement over the previous years. The invention of computers with appropriate increase in the processing and internet speed has changed the face of the medical technology. However there is still scope for improvement of the technologies in use today. One of the many such technologies of medical aid is the detection of afflictions of the eye. Although a repertoire of research has been accomplished in this field, most of them fail to address how to take the detection forward to a stage where it will be beneficial to the society at large. An automated system that can predict the current medical condition of a patient after taking the fundus image of his eye is yet to see the light of the day. Such a system is explored in this paper by summarizing a number of techniques for fundus image features extraction, predominantly hard exudate mining, coupled with Content Based Image Retrieval to develop an automation tool. The knowledge of the same would bring about worthy changes in the domain of exudates extraction of the eye. This is essential in cases where the patients may not have access to the best of technologies. This paper attempts at a comprehensive summary of the techniques for Content Based Image Retrieval (CBIR) or fundus features image extraction, and few choice methods of both, and an exploration which aims to find ways to combine these two attractive features, and combine them so that it is beneficial to all.

  17. Fundus Image Features Extraction for Exudate Mining in Coordination with Content Based Image Retrieval: A Study

    Science.gov (United States)

    Gururaj, C.; Jayadevappa, D.; Tunga, Satish

    2018-02-01

    Medical field has seen a phenomenal improvement over the previous years. The invention of computers with appropriate increase in the processing and internet speed has changed the face of the medical technology. However there is still scope for improvement of the technologies in use today. One of the many such technologies of medical aid is the detection of afflictions of the eye. Although a repertoire of research has been accomplished in this field, most of them fail to address how to take the detection forward to a stage where it will be beneficial to the society at large. An automated system that can predict the current medical condition of a patient after taking the fundus image of his eye is yet to see the light of the day. Such a system is explored in this paper by summarizing a number of techniques for fundus image features extraction, predominantly hard exudate mining, coupled with Content Based Image Retrieval to develop an automation tool. The knowledge of the same would bring about worthy changes in the domain of exudates extraction of the eye. This is essential in cases where the patients may not have access to the best of technologies. This paper attempts at a comprehensive summary of the techniques for Content Based Image Retrieval (CBIR) or fundus features image extraction, and few choice methods of both, and an exploration which aims to find ways to combine these two attractive features, and combine them so that it is beneficial to all.

  18. A Novel Optimization-Based Approach for Content-Based Image Retrieval

    Directory of Open Access Journals (Sweden)

    Manyu Xiao

    2013-01-01

    Full Text Available Content-based image retrieval is nowadays one of the possible and promising solutions to manage image databases effectively. However, with the large number of images, there still exists a great discrepancy between the users’ expectations (accuracy and efficiency and the real performance in image retrieval. In this work, new optimization strategies are proposed on vocabulary tree building, retrieval, and matching methods. More precisely, a new clustering strategy combining classification and conventional K-Means method is firstly redefined. Then a new matching technique is built to eliminate the error caused by large-scaled scale-invariant feature transform (SIFT. Additionally, a new unit mechanism is proposed to reduce the cost of indexing time. Finally, the numerical results show that excellent performances are obtained in both accuracy and efficiency based on the proposed improvements for image retrieval.

  19. The Potential of User Feedback Through the Iterative Refining of Queries in an Image Retrieval System

    NARCIS (Netherlands)

    Ben Moussa, Maher; Pasch, Marco; Hiemstra, Djoerd; van der Vet, P.E.; Huibers, Theo W.C.; Marchand-Maillet, Stephane; Bruno, Eric; Nürnberger, Andreas; Detyniecki, Marcin

    2007-01-01

    Inaccurate or ambiguous expressions in queries lead to poor results in information retrieval. We assume that iterative user feedback can improve the quality of queries. To this end we developed a system for image retrieval that utilizes user feedback to refine the user’s search query. This is done

  20. Joint Textual And Visual Cues For Retrieving Images Using Latent Semantic Indexing

    OpenAIRE

    Pecenovic, Zoran; Ayer, Serge; Vetterli, Martin

    2001-01-01

    In this article we present a novel approach of integrating textual and visual descriptors of images in a unified retrieval structure. The methodology, inspired from text retrieval and information filtering is based on Latent Semantic Indexing (LS1).

  1. Using Fuzzy SOM Strategy for Satellite Image Retrieval and Information Mining

    Directory of Open Access Journals (Sweden)

    Yo-Ping Huang

    2008-02-01

    Full Text Available This paper proposes an efficient satellite image retrieval and knowledge discovery model. The strategy comprises two major parts. First, a computational algorithm is used for off-line satellite image feature extraction, image data representation and image retrieval. Low level features are automatically extracted from the segmented regions of satellite images. A self-organization feature map is used to construct a two-layer satellite image concept hierarchy. The events are stored in one layer and the corresponding feature vectors are categorized in the other layer. Second, a user friendly interface is provided that retrieves images of interest and mines useful information based on the events in the concept hierarchy. The proposed system is evaluated with prominent features such as typhoons or high-pressure masses.

  2. Retrieval of bilingual autobiographical memories: effects of cue language and cue imageability.

    Science.gov (United States)

    Mortensen, Linda; Berntsen, Dorthe; Bohn, Ocke-Schwen

    2015-01-01

    An important issue in theories of bilingual autobiographical memory is whether linguistically encoded memories are represented in language-specific stores or in a common language-independent store. Previous research has found that autobiographical memory retrieval is facilitated when the language of the cue is the same as the language of encoding, consistent with language-specific memory stores. The present study examined whether this language congruency effect is influenced by cue imageability. Danish-English bilinguals retrieved autobiographical memories in response to Danish and English high- or low-imageability cues. Retrieval latencies were shorter to Danish than English cues and shorter to high- than low-imageability cues. Importantly, the cue language effect was stronger for low-than high-imageability cues. To examine the relationship between cue language and the language of internal retrieval, participants identified the language in which the memories were internally retrieved. More memories were retrieved when the cue language was the same as the internal language than when the cue was in the other language, and more memories were identified as being internally retrieved in Danish than English, regardless of the cue language. These results provide further evidence for language congruency effects in bilingual memory and suggest that this effect is influenced by cue imageability.

  3. A Fast, Background-Independent Retrieval Strategy for Color Image Databases

    National Research Council Canada - National Science Library

    Das, M; Draper, B. A; Lim, W. J; Manmatha, R; Riseman, E. M

    1996-01-01

    .... The method is fast and has low storage overhead. Good retrieval results are obtained with multi-colored query objects even when they occur in arbitrary sizes, rotations and locations in the database images...

  4. Medical Image Retrieval Based On the Parallelization of the Cluster Sampling Algorithm

    OpenAIRE

    Ali, Hesham Arafat; Attiya, Salah; El-henawy, Ibrahim

    2017-01-01

    In this paper we develop parallel cluster sampling algorithms and show that a multi-chain version is embarrassingly parallel and can be used efficiently for medical image retrieval among other applications.

  5. High resolution satellite image indexing and retrieval using SURF features and bag of visual words

    Science.gov (United States)

    Bouteldja, Samia; Kourgli, Assia

    2017-03-01

    In this paper, we evaluate the performance of SURF descriptor for high resolution satellite imagery (HRSI) retrieval through a BoVW model on a land-use/land-cover (LULC) dataset. Local feature approaches such as SIFT and SURF descriptors can deal with a large variation of scale, rotation and illumination of the images, providing, therefore, a better discriminative power and retrieval efficiency than global features, especially for HRSI which contain a great range of objects and spatial patterns. Moreover, we combine SURF and color features to improve the retrieval accuracy, and we propose to learn a category-specific dictionary for each image category which results in a more discriminative image representation and boosts the image retrieval performance.

  6. Biomedical image acquisition system using a gamma camera

    International Nuclear Information System (INIS)

    Jara B, A.T.; Sevillano, J.; Del Carpio S, J.A.

    2003-01-01

    A gamma camera images PC acquisition board has been developed. The digital system has been described using VHDL and has been synthesized and implemented in a Altera Max7128S CPLD and two PALs 16L8. The use of programmable-logic technologies has afforded a higher scale integration and a reduction of the digital delays and also has allowed us to modify and bring up to date the entire digital design easily. (orig.)

  7. Large-Scale Query-by-Image Video Retrieval Using Bloom Filters

    OpenAIRE

    Araujo, Andre; Chaves, Jason; Lakshman, Haricharan; Angst, Roland; Girod, Bernd

    2016-01-01

    We consider the problem of using image queries to retrieve videos from a database. Our focus is on large-scale applications, where it is infeasible to index each database video frame independently. Our main contribution is a framework based on Bloom filters, which can be used to index long video segments, enabling efficient image-to-video comparisons. Using this framework, we investigate several retrieval architectures, by considering different types of aggregation and different functions to ...

  8. An improved ptychographical phase retrieval algorithm for diffractive imaging

    International Nuclear Information System (INIS)

    Maiden, Andrew M.; Rodenburg, John M.

    2009-01-01

    The ptychographical iterative engine (or PIE) is a recently developed phase retrieval algorithm that employs a series of diffraction patterns recorded as a known illumination function is translated to a set of overlapping positions relative to a target sample. The technique has been demonstrated successfully at optical and X-ray wavelengths and has been shown to be robust to detector noise and to converge considerably faster than support-based phase retrieval methods. In this paper, the PIE is extended so that the requirement for an accurate model of the illumination function is removed.

  9. A novel end-to-end classifier using domain transferred deep convolutional neural networks for biomedical images.

    Science.gov (United States)

    Pang, Shuchao; Yu, Zhezhou; Orgun, Mehmet A

    2017-03-01

    Highly accurate classification of biomedical images is an essential task in the clinical diagnosis of numerous medical diseases identified from those images. Traditional image classification methods combined with hand-crafted image feature descriptors and various classifiers are not able to effectively improve the accuracy rate and meet the high requirements of classification of biomedical images. The same also holds true for artificial neural network models directly trained with limited biomedical images used as training data or directly used as a black box to extract the deep features based on another distant dataset. In this study, we propose a highly reliable and accurate end-to-end classifier for all kinds of biomedical images via deep learning and transfer learning. We first apply domain transferred deep convolutional neural network for building a deep model; and then develop an overall deep learning architecture based on the raw pixels of original biomedical images using supervised training. In our model, we do not need the manual design of the feature space, seek an effective feature vector classifier or segment specific detection object and image patches, which are the main technological difficulties in the adoption of traditional image classification methods. Moreover, we do not need to be concerned with whether there are large training sets of annotated biomedical images, affordable parallel computing resources featuring GPUs or long times to wait for training a perfect deep model, which are the main problems to train deep neural networks for biomedical image classification as observed in recent works. With the utilization of a simple data augmentation method and fast convergence speed, our algorithm can achieve the best accuracy rate and outstanding classification ability for biomedical images. We have evaluated our classifier on several well-known public biomedical datasets and compared it with several state-of-the-art approaches. We propose a robust

  10. Microfabricated optically pumped magnetometer arrays for biomedical imaging

    Science.gov (United States)

    Perry, A. R.; Sheng, D.; Krzyzewski, S. P.; Geller, S.; Knappe, S.

    2017-02-01

    Optically-pumped magnetometers have demonstrated magnetic field measurements as precise as the best superconducting quantum interference device magnetometers. Our group develops miniature alkali atom-based magnetic sensors using microfabrication technology. Our sensors do not require cryogenic cooling, and can be positioned very close to the sample, making these sensors an attractive option for development in the medical community. We will present our latest chip-scale optically-pumped gradiometer developed for array applications to image magnetic fields from the brain noninvasively. These developments should lead to improved spatial resolution, and potentially sensitive measurements in unshielded environments.

  11. A Novel Image Retrieval Based on Visual Words Integration of SIFT and SURF.

    Directory of Open Access Journals (Sweden)

    Nouman Ali

    Full Text Available With the recent evolution of technology, the number of image archives has increased exponentially. In Content-Based Image Retrieval (CBIR, high-level visual information is represented in the form of low-level features. The semantic gap between the low-level features and the high-level image concepts is an open research problem. In this paper, we present a novel visual words integration of Scale Invariant Feature Transform (SIFT and Speeded-Up Robust Features (SURF. The two local features representations are selected for image retrieval because SIFT is more robust to the change in scale and rotation, while SURF is robust to changes in illumination. The visual words integration of SIFT and SURF adds the robustness of both features to image retrieval. The qualitative and quantitative comparisons conducted on Corel-1000, Corel-1500, Corel-2000, Oliva and Torralba and Ground Truth image benchmarks demonstrate the effectiveness of the proposed visual words integration.

  12. Diversification in an image retrieval system based on text and image processing

    Directory of Open Access Journals (Sweden)

    Adrian Iftene

    2014-11-01

    Full Text Available In this paper we present an image retrieval system created within the research project MUCKE (Multimedia and User Credibility Knowledge Extraction, a CHIST-ERA research project where UAIC{\\footnote{"Alexandru Ioan Cuza" University of Iasi}} is one of the partners{\\footnote{Together with Technical University from Wienna, Austria, CEA-LIST Institute from Paris, France and BILKENT University from Ankara, Turkey}}. Our discussion in this work will focus mainly on components that are part of our image retrieval system proposed in MUCKE, and we present the work done by the UAIC group. MUCKE incorporates modules for processing multimedia content in different modes and languages (like English, French, German and Romanian and UAIC is responsible with text processing tasks (for Romanian and English. One of the problems addressed by our work is related to search results diversification. In order to solve this problem, we first process the user queries in both languages and secondly, we create clusters of similar images.

  13. Design and development of a content-based medical image retrieval system for spine vertebrae irregularity.

    Science.gov (United States)

    Mustapha, Aouache; Hussain, Aini; Samad, Salina Abdul; Zulkifley, Mohd Asyraf; Diyana Wan Zaki, Wan Mimi; Hamid, Hamzaini Abdul

    2015-01-16

    Content-based medical image retrieval (CBMIR) system enables medical practitioners to perform fast diagnosis through quantitative assessment of the visual information of various modalities. In this paper, a more robust CBMIR system that deals with both cervical and lumbar vertebrae irregularity is afforded. It comprises three main phases, namely modelling, indexing and retrieval of the vertebrae image. The main tasks in the modelling phase are to improve and enhance the visibility of the x-ray image for better segmentation results using active shape model (ASM). The segmented vertebral fractures are then characterized in the indexing phase using region-based fracture characterization (RB-FC) and contour-based fracture characterization (CB-FC). Upon a query, the characterized features are compared to the query image. Effectiveness of the retrieval phase is determined by its retrieval, thus, we propose an integration of the predictor model based cross validation neural network (PMCVNN) and similarity matching (SM) in this stage. The PMCVNN task is to identify the correct vertebral irregularity class through classification allowing the SM process to be more efficient. Retrieval performance between the proposed and the standard retrieval architectures are then compared using retrieval precision (Pr@M) and average group score (AGS) measures. Experimental results show that the new integrated retrieval architecture performs better than those of the standard CBMIR architecture with retrieval results of cervical (AGS > 87%) and lumbar (AGS > 82%) datasets. The proposed CBMIR architecture shows encouraging results with high Pr@M accuracy. As a result, images from the same visualization class are returned for further used by the medical personnel.

  14. Quantifying the margin sharpness of lesions on radiological images for content-based image retrieval

    International Nuclear Information System (INIS)

    Xu Jiajing; Napel, Sandy; Greenspan, Hayit; Beaulieu, Christopher F.; Agrawal, Neeraj; Rubin, Daniel

    2012-01-01

    . Equivalence across deformations was assessed using Schuirmann's paired two one-sided tests. Results: In simulated images, the concordance correlation between measured gradient and actual gradient was 0.994. The mean (s.d.) and standard deviation NDCG score for the retrieval of K images, K = 5, 10, and 15, were 84% (8%), 85% (7%), and 85% (7%) for CT images containing liver lesions, and 82% (7%), 84% (6%), and 85% (4%) for CT images containing lung nodules, respectively. The authors’ proposed method outperformed the two existing margin characterization methods in average NDCG scores over all K, by 1.5% and 3% in datasets containing liver lesion, and 4.5% and 5% in datasets containing lung nodules. Equivalence testing showed that the authors’ feature is more robust across all margin deformations (p < 0.05) than the two existing methods for margin sharpness characterization in both simulated and clinical datasets. Conclusions: The authors have described a new image feature to quantify the margin sharpness of lesions. It has strong correlation with known margin sharpness in simulated images and in clinical CT images containing liver lesions and lung nodules. This image feature has excellent performance for retrieving images with similar margin characteristics, suggesting potential utility, in conjunction with other lesion features, for content-based image retrieval applications.

  15. Pleasant/Unpleasant Filtering for Affective Image Retrieval Based on Cross-Correlation of EEG Features

    Directory of Open Access Journals (Sweden)

    Keranmu Xielifuguli

    2014-01-01

    Full Text Available People often make decisions based on sensitivity rather than rationality. In the field of biological information processing, methods are available for analyzing biological information directly based on electroencephalogram: EEG to determine the pleasant/unpleasant reactions of users. In this study, we propose a sensitivity filtering technique for discriminating preferences (pleasant/unpleasant for images using a sensitivity image filtering system based on EEG. Using a set of images retrieved by similarity retrieval, we perform the sensitivity-based pleasant/unpleasant classification of images based on the affective features extracted from images with the maximum entropy method: MEM. In the present study, the affective features comprised cross-correlation features obtained from EEGs produced when an individual observed an image. However, it is difficult to measure the EEG when a subject visualizes an unknown image. Thus, we propose a solution where a linear regression method based on canonical correlation is used to estimate the cross-correlation features from image features. Experiments were conducted to evaluate the validity of sensitivity filtering compared with image similarity retrieval methods based on image features. We found that sensitivity filtering using color correlograms was suitable for the classification of preferred images, while sensitivity filtering using local binary patterns was suitable for the classification of unpleasant images. Moreover, sensitivity filtering using local binary patterns for unpleasant images had a 90% success rate. Thus, we conclude that the proposed method is efficient for filtering unpleasant images.

  16. Morphological image processing for quantitative shape analysis of biomedical structures: effective contrast enhancement

    International Nuclear Information System (INIS)

    Kimori, Yoshitaka

    2013-01-01

    A contrast enhancement approach utilizing a new type of mathematical morphology called rotational morphological processing is introduced. The method is quantitatively evaluated and then applied to some medical images. Image processing methods significantly contribute to visualization of images captured by biomedical modalities (such as mammography, X-ray computed tomography, magnetic resonance imaging, and light and electron microscopy). Quantitative interpretation of the deluge of complicated biomedical images, however, poses many research challenges, one of which is to enhance structural features that are scarcely perceptible to the human eye. This study introduces a contrast enhancement approach based on a new type of mathematical morphology called rotational morphological processing. The proposed method is applied to medical images for the enhancement of structural features. The effectiveness of the method is evaluated quantitatively by the contrast improvement ratio (CIR). The CIR of the proposed method is 12.1, versus 4.7 and 0.1 for two conventional contrast enhancement methods, clearly indicating the high contrasting capability of the method

  17. Content-based image retrieval using a signature graph and a self-organizing map

    Directory of Open Access Journals (Sweden)

    Van Thanh The

    2016-06-01

    Full Text Available In order to effectively retrieve a large database of images, a method of creating an image retrieval system CBIR (contentbased image retrieval is applied based on a binary index which aims to describe features of an image object of interest. This index is called the binary signature and builds input data for the problem of matching similar images. To extract the object of interest, we propose an image segmentation method on the basis of low-level visual features including the color and texture of the image. These features are extracted at each block of the image by the discrete wavelet frame transform and the appropriate color space. On the basis of a segmented image, we create a binary signature to describe the location, color and shape of the objects of interest. In order to match similar images, we provide a similarity measure between the images based on binary signatures. Then, we present a CBIR model which combines a signature graph and a self-organizing map to cluster and store similar images. To illustrate the proposed method, experiments on image databases are reported, including COREL,Wang and MSRDI.

  18. Large-scale retrieval for medical image analytics: A comprehensive review.

    Science.gov (United States)

    Li, Zhongyu; Zhang, Xiaofan; Müller, Henning; Zhang, Shaoting

    2018-01-01

    Over the past decades, medical image analytics was greatly facilitated by the explosion of digital imaging techniques, where huge amounts of medical images were produced with ever-increasing quality and diversity. However, conventional methods for analyzing medical images have achieved limited success, as they are not capable to tackle the huge amount of image data. In this paper, we review state-of-the-art approaches for large-scale medical image analysis, which are mainly based on recent advances in computer vision, machine learning and information retrieval. Specifically, we first present the general pipeline of large-scale retrieval, summarize the challenges/opportunities of medical image analytics on a large-scale. Then, we provide a comprehensive review of algorithms and techniques relevant to major processes in the pipeline, including feature representation, feature indexing, searching, etc. On the basis of existing work, we introduce the evaluation protocols and multiple applications of large-scale medical image retrieval, with a variety of exploratory and diagnostic scenarios. Finally, we discuss future directions of large-scale retrieval, which can further improve the performance of medical image analysis. Copyright © 2017 Elsevier B.V. All rights reserved.

  19. Medical imaging education in biomedical engineering curriculum: courseware development and application through a hybrid teaching model.

    Science.gov (United States)

    Zhao, Weizhao; Li, Xiping; Chen, Hairong; Manns, Fabrice

    2012-01-01

    Medical Imaging is a key training component in Biomedical Engineering programs. Medical imaging education is interdisciplinary training, involving physics, mathematics, chemistry, electrical engineering, computer engineering, and applications in biology and medicine. Seeking an efficient teaching method for instructors and an effective learning environment for students has long been a goal for medical imaging education. By the support of NSF grants, we developed the medical imaging teaching software (MITS) and associated dynamic assessment tracking system (DATS). The MITS/DATS system has been applied to junior and senior medical imaging classes through a hybrid teaching model. The results show that student's learning gain improved, particularly in concept understanding and simulation project completion. The results also indicate disparities in subjective perception between junior and senior classes. Three institutions are collaborating to expand the courseware system and plan to apply it to different class settings.

  20. Fabrication of a small animal restraint for synchrotron biomedical imaging using a rapid prototyper

    International Nuclear Information System (INIS)

    Zhu Ying; Zhang Honglin; McCrea, Richard; Bewer, Brian; Wiebe, Sheldon; Nichol, Helen; Ryan, Christopher; Wysokinski, Tomasz; Chapman, Dean

    2007-01-01

    Biomedical research at synchrotron facilities may involve imaging live animals that must remain motionless for extended periods of time to obtain quality images. Even breathing movements reduce image quality but on the other hand excessive restraint of animals increases morbidity and mortality. We describe a humane animal restraint designed to eliminate head movements while promoting animal survival. This paper describes how an animal restraint that conforms to the shape of an animal's head was fabricated by a 3D prototyper. The method used to translate medical computed tomography (CT) data to a 3D stereolithography format is described and images of its use at the Canadian Light Source (CLS) are shown. This type of restraint holds great promise in improving image quality and repeatability while reducing stress on experimental animals

  1. Retrieve polarization aberration from image degradation: a new measurement method in DUV lithography

    Science.gov (United States)

    Xiang, Zhongbo; Li, Yanqiu

    2017-10-01

    Detailed knowledge of polarization aberration (PA) of projection lens in higher-NA DUV lithographic imaging is necessary due to its impact to imaging degradations, and precise measurement of PA is conductive to computational lithography techniques such as RET and OPC. Current in situ measurement method of PA thorough the detection of degradations of aerial images need to do linear approximation and apply the assumption of 3-beam/2-beam interference condition. The former approximation neglects the coupling effect of the PA coefficients, which would significantly influence the accuracy of PA retrieving. The latter assumption restricts the feasible pitch of test masks in higher-NA system, conflicts with the Kirhhoff diffraction model of test mask used in retrieving model, and introduces 3D mask effect as a source of retrieving error. In this paper, a new in situ measurement method of PA is proposed. It establishes the analytical quadratic relation between the PA coefficients and the degradations of aerial images of one-dimensional dense lines in coherent illumination through vector aerial imaging, which does not rely on the assumption of 3-beam/2- beam interference and linear approximation. In this case, the retrieval of PA from image degradation can be convert from the nonlinear system of m-quadratic equations to a multi-objective quadratic optimization problem, and finally be solved by nonlinear least square method. Some preliminary simulation results are given to demonstrate the correctness and accuracy of the new PA retrieving model.

  2. A novel 3D shape descriptor for automatic retrieval of anatomical structures from medical images

    Science.gov (United States)

    Nunes, Fátima L. S.; Bergamasco, Leila C. C.; Delmondes, Pedro H.; Valverde, Miguel A. G.; Jackowski, Marcel P.

    2017-03-01

    Content-based image retrieval (CBIR) aims at retrieving from a database objects that are similar to an object provided by a query, by taking into consideration a set of extracted features. While CBIR has been widely applied in the two-dimensional image domain, the retrieval of3D objects from medical image datasets using CBIR remains to be explored. In this context, the development of descriptors that can capture information specific to organs or structures is desirable. In this work, we focus on the retrieval of two anatomical structures commonly imaged by Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) techniques, the left ventricle of the heart and blood vessels. Towards this aim, we developed the Area-Distance Local Descriptor (ADLD), a novel 3D local shape descriptor that employs mesh geometry information, namely facet area and distance from centroid to surface, to identify shape changes. Because ADLD only considers surface meshes extracted from volumetric medical images, it substantially diminishes the amount of data to be analyzed. A 90% precision rate was obtained when retrieving both convex (left ventricle) and non-convex structures (blood vessels), allowing for detection of abnormalities associated with changes in shape. Thus, ADLD has the potential to aid in the diagnosis of a wide range of vascular and cardiac diseases.

  3. Grating-based X-ray phase contrast for biomedical imaging applications

    International Nuclear Information System (INIS)

    Pfeiffer, Franz; Willner, Marian; Chabior, Michael; Herzen, Julia; Helmholtz-Zentrum Geesthacht, Geesthacht; Auweter, Sigrid; Reiser, Maximilian; Bamberg, Fabian

    2013-01-01

    In this review article we describe the development of grating-based X-ray phase-contrast imaging, with particular emphasis on potential biomedical applications of the technology. We review the basics of image formation in grating-based phase-contrast and dark-field radiography and present some exemplary multimodal radiography results obtained with laboratory X-ray sources. Furthermore, we discuss the theoretical concepts to extend grating-based multimodal radiography to quantitative transmission, phase-contrast, and dark-field scattering computed tomography. (orig.)

  4. The Multiscale Bowler-Hat Transform for Vessel Enhancement in 3D Biomedical Images

    OpenAIRE

    Sazak, Cigdem; Nelson, Carl J.; Obara, Boguslaw

    2018-01-01

    Enhancement and detection of 3D vessel-like structures has long been an open problem as most existing image processing methods fail in many aspects, including a lack of uniform enhancement between vessels of different radii and a lack of enhancement at the junctions. Here, we propose a method based on mathematical morphology to enhance 3D vessel-like structures in biomedical images. The proposed method, 3D bowler-hat transform, combines sphere and line structuring elements to enhance vessel-l...

  5. Chinese Herbal Medicine Image Recognition and Retrieval by Convolutional Neural Network.

    Science.gov (United States)

    Sun, Xin; Qian, Huinan

    2016-01-01

    Chinese herbal medicine image recognition and retrieval have great potential of practical applications. Several previous studies have focused on the recognition with hand-crafted image features, but there are two limitations in them. Firstly, most of these hand-crafted features are low-level image representation, which is easily affected by noise and background. Secondly, the medicine images are very clean without any backgrounds, which makes it difficult to use in practical applications. Therefore, designing high-level image representation for recognition and retrieval in real world medicine images is facing a great challenge. Inspired by the recent progress of deep learning in computer vision, we realize that deep learning methods may provide robust medicine image representation. In this paper, we propose to use the Convolutional Neural Network (CNN) for Chinese herbal medicine image recognition and retrieval. For the recognition problem, we use the softmax loss to optimize the recognition network; then for the retrieval problem, we fine-tune the recognition network by adding a triplet loss to search for the most similar medicine images. To evaluate our method, we construct a public database of herbal medicine images with cluttered backgrounds, which has in total 5523 images with 95 popular Chinese medicine categories. Experimental results show that our method can achieve the average recognition precision of 71% and the average retrieval precision of 53% over all the 95 medicine categories, which are quite promising given the fact that the real world images have multiple pieces of occluded herbal and cluttered backgrounds. Besides, our proposed method achieves the state-of-the-art performance by improving previous studies with a large margin.

  6. Dual-force ISOMAP: a new relevance feedback method for medical image retrieval.

    Science.gov (United States)

    Shen, Hualei; Tao, Dacheng; Ma, Dianfu

    2013-01-01

    With great potential for assisting radiological image interpretation and decision making, content-based image retrieval in the medical domain has become a hot topic in recent years. Many methods to enhance the performance of content-based medical image retrieval have been proposed, among which the relevance feedback (RF) scheme is one of the most promising. Given user feedback information, RF algorithms interactively learn a user's preferences to bridge the "semantic gap" between low-level computerized visual features and high-level human semantic perception and thus improve retrieval performance. However, most existing RF algorithms perform in the original high-dimensional feature space and ignore the manifold structure of the low-level visual features of images. In this paper, we propose a new method, termed dual-force ISOMAP (DFISOMAP), for content-based medical image retrieval. Under the assumption that medical images lie on a low-dimensional manifold embedded in a high-dimensional ambient space, DFISOMAP operates in the following three stages. First, the geometric structure of positive examples in the learned low-dimensional embedding is preserved according to the isometric feature mapping (ISOMAP) criterion. To precisely model the geometric structure, a reconstruction error constraint is also added. Second, the average distance between positive and negative examples is maximized to separate them; this margin maximization acts as a force that pushes negative examples far away from positive examples. Finally, the similarity propagation technique is utilized to provide negative examples with another force that will pull them back into the negative sample set. We evaluate the proposed method on a subset of the IRMA medical image dataset with a RF-based medical image retrieval framework. Experimental results show that DFISOMAP outperforms popular approaches for content-based medical image retrieval in terms of accuracy and stability.

  7. Phase-preserving beam expander for biomedical X-ray imaging

    International Nuclear Information System (INIS)

    Martinson, Mercedes; Samadi, Nazanin; Bassey, Bassey; Gomez, Ariel; Chapman, Dean

    2015-01-01

    Building on previous work, a phase-preserving bent Laue beam-expanding monochromator was developed with the capability of performing live animal phase contrast dynamic imaging at the Biomedical Imaging and Therapy beamline at the Canadian Light Source. The BioMedical Imaging and Therapy beamlines at the Canadian Light Source are used by many researchers to capture phase-based imaging data. These experiments have so far been limited by the small vertical beam size, requiring vertical scanning of biological samples in order to image their full vertical extent. Previous work has been carried out to develop a bent Laue beam-expanding monochromator for use at these beamlines. However, the first attempts exhibited significant distortion in the diffraction plane, increasing the beam divergence and eliminating the usefulness of the monochromator for phase-related imaging techniques. Recent work has been carried out to more carefully match the polychromatic and geometric focal lengths in a so-called ‘magic condition’ that preserves the divergence of the beam and enables full-field phase-based imaging techniques. The new experimental parameters, namely asymmetry and Bragg angles, were evaluated by analysing knife-edge and in-line phase images to determine the effect on beam divergence in both vertical and horizontal directions, using the flat Bragg double-crystal monochromator at the beamline as a baseline. The results show that by using the magic condition, the difference between the two monochromator types is less than 10% in the diffraction plane. Phase fringes visible in test images of a biological sample demonstrate that this difference is small enough to enable in-line phase imaging, despite operating at a sub-optimal energy for the wafer and asymmetry angle that was used

  8. A theoretical-experimental methodology for assessing the sensitivity of biomedical spectral imaging platforms, assays, and analysis methods.

    Science.gov (United States)

    Leavesley, Silas J; Sweat, Brenner; Abbott, Caitlyn; Favreau, Peter; Rich, Thomas C

    2018-01-01

    Spectral imaging technologies have been used for many years by the remote sensing community. More recently, these approaches have been applied to biomedical problems, where they have shown great promise. However, biomedical spectral imaging has been complicated by the high variance of biological data and the reduced ability to construct test scenarios with fixed ground truths. Hence, it has been difficult to objectively assess and compare biomedical spectral imaging assays and technologies. Here, we present a standardized methodology that allows assessment of the performance of biomedical spectral imaging equipment, assays, and analysis algorithms. This methodology incorporates real experimental data and a theoretical sensitivity analysis, preserving the variability present in biomedical image data. We demonstrate that this approach can be applied in several ways: to compare the effectiveness of spectral analysis algorithms, to compare the response of different imaging platforms, and to assess the level of target signature required to achieve a desired performance. Results indicate that it is possible to compare even very different hardware platforms using this methodology. Future applications could include a range of optimization tasks, such as maximizing detection sensitivity or acquisition speed, providing high utility for investigators ranging from design engineers to biomedical scientists. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  9. Context-based adaptive filtering of interest points in image retrieval

    DEFF Research Database (Denmark)

    Nguyen, Phuong Giang; Andersen, Hans Jørgen

    2009-01-01

    Interest points have been used as local features with success in many computer vision applications such as image/video retrieval and object recognition. However, a major issue when using this approach is a large number of interest points detected from each image and created a dense feature space...... a subset of features. Our approach differs from others in a fact that selected feature is based on the context of the given image. Our experimental results show a significant reduction rate of features while preserving the retrieval performance....

  10. Optical multiple-image encryption based on multiplane phase retrieval and interference

    International Nuclear Information System (INIS)

    Chen, Wen; Chen, Xudong

    2011-01-01

    In this paper, we propose a new method for optical multiple-image encryption based on multiplane phase retrieval and interference. An optical encoding system is developed in the Fresnel domain. A phase-only map is iteratively extracted based on a multiplane phase retrieval algorithm, and multiple plaintexts are simultaneously encrypted. Subsequently, the extracted phase-only map is further encrypted into two phase-only masks based on a non-iterative interference algorithm. During image decryption, the advantages and security of the proposed optical cryptosystem are analyzed. Numerical results are presented to demonstrate the validity of the proposed optical multiple-image encryption method

  11. Curvature histogram features for retrieval of images of smooth 3D objects

    International Nuclear Information System (INIS)

    Zhdanov, I; Scherbakov, O; Potapov, A; Peterson, M

    2014-01-01

    We consider image features on the base of histograms of oriented gradients (HOG) with addition of contour curvature histogram (HOG-CH), and also compare it with results of known scale-invariant feature transform (SIFT) approach in application to retrieval of images of smooth 3D objects.

  12. Comparison of the effectiveness of alternative feature sets in shape retrieval of multicomponent images

    Science.gov (United States)

    Eakins, John P.; Edwards, Jonathan D.; Riley, K. Jonathan; Rosin, Paul L.

    2001-01-01

    Many different kinds of features have been used as the basis for shape retrieval from image databases. This paper investigates the relative effectiveness of several types of global shape feature, both singly and in combination. The features compared include well-established descriptors such as Fourier coefficients and moment invariants, as well as recently-proposed measures of triangularity and ellipticity. Experiments were conducted within the framework of the ARTISAN shape retrieval system, and retrieval effectiveness assessed on a database of over 10,000 images, using 24 queries and associated ground truth supplied by the UK Patent Office . Our experiments revealed only minor differences in retrieval effectiveness between different measures, suggesting that a wide variety of shape feature combinations can provide adequate discriminating power for effective shape retrieval in multi-component image collections such as trademark registries. Marked differences between measures were observed for some individual queries, suggesting that there could be considerable scope for improving retrieval effectiveness by providing users with an improved framework for searching multi-dimensional feature space.

  13. Similarity estimation for reference image retrieval in mammograms using convolutional neural network

    Science.gov (United States)

    Muramatsu, Chisako; Higuchi, Shunichi; Morita, Takako; Oiwa, Mikinao; Fujita, Hiroshi

    2018-02-01

    Periodic breast cancer screening with mammography is considered effective in decreasing breast cancer mortality. For screening programs to be successful, an intelligent image analytic system may support radiologists' efficient image interpretation. In our previous studies, we have investigated image retrieval schemes for diagnostic references of breast lesions on mammograms and ultrasound images. Using a machine learning method, reliable similarity measures that agree with radiologists' similarity were determined and relevant images could be retrieved. However, our previous method includes a feature extraction step, in which hand crafted features were determined based on manual outlines of the masses. Obtaining the manual outlines of masses is not practical in clinical practice and such data would be operator-dependent. In this study, we investigated a similarity estimation scheme using a convolutional neural network (CNN) to skip such procedure and to determine data-driven similarity scores. By using CNN as feature extractor, in which extracted features were employed in determination of similarity measures with a conventional 3-layered neural network, the determined similarity measures were correlated well with the subjective ratings and the precision of retrieving diagnostically relevant images was comparable with that of the conventional method using handcrafted features. By using CNN for determination of similarity measure directly, the result was also comparable. By optimizing the network parameters, results may be further improved. The proposed method has a potential usefulness in determination of similarity measure without precise lesion outlines for retrieval of similar mass images on mammograms.

  14. Conformal image-guided microbeam radiation therapy at the ESRF biomedical beamline ID17

    International Nuclear Information System (INIS)

    Donzelli, Mattia; Bräuer-Krisch, Elke; Nemoz, Christian; Brochard, Thierry; Oelfke, Uwe

    2016-01-01

    Purpose: Upcoming veterinary trials in microbeam radiation therapy (MRT) demand for more advanced irradiation techniques than in preclinical research with small animals. The treatment of deep-seated tumors in cats and dogs with MRT requires sophisticated irradiation geometries from multiple ports, which impose further efforts to spare the normal tissue surrounding the target. Methods: This work presents the development and benchmarking of a precise patient alignment protocol for MRT at the biomedical beamline ID17 of the European Synchrotron Radiation Facility (ESRF). The positioning of the patient prior to irradiation is verified by taking x-ray projection images from different angles. Results: Using four external fiducial markers of 1.7  mm diameter and computed tomography-based treatment planning, a target alignment error of less than 2  mm can be achieved with an angular deviation of less than 2 ∘ . Minor improvements on the protocol and the use of smaller markers indicate that even a precision better than 1  mm is technically feasible. Detailed investigations concerning the imaging dose lead to the conclusion that doses for skull radiographs lie in the same range as dose reference levels for human head radiographs. A currently used online dose monitor for MRT has been proven to give reliable results for the imaging beam. Conclusions: The ESRF biomedical beamline ID17 is technically ready to apply conformal image-guided MRT from multiple ports to large animals during future veterinary trials.

  15. Conformal image-guided microbeam radiation therapy at the ESRF biomedical beamline ID17

    Energy Technology Data Exchange (ETDEWEB)

    Donzelli, Mattia, E-mail: donzelli@esrf.fr [European Synchrotron Radiation Facility, 71, Avenue des Martyrs, Grenoble 38000, France and The Institute of Cancer Research, 15 Cotswold Road, Sutton SM2 5NG (United Kingdom); Bräuer-Krisch, Elke; Nemoz, Christian; Brochard, Thierry [European Synchrotron Radiation Facility, 71, Avenue des Martyrs, Grenoble 38000 (France); Oelfke, Uwe [The Institute of Cancer Research, 15 Cotswold Road, Sutton SM2 5NG (United Kingdom)

    2016-06-15

    Purpose: Upcoming veterinary trials in microbeam radiation therapy (MRT) demand for more advanced irradiation techniques than in preclinical research with small animals. The treatment of deep-seated tumors in cats and dogs with MRT requires sophisticated irradiation geometries from multiple ports, which impose further efforts to spare the normal tissue surrounding the target. Methods: This work presents the development and benchmarking of a precise patient alignment protocol for MRT at the biomedical beamline ID17 of the European Synchrotron Radiation Facility (ESRF). The positioning of the patient prior to irradiation is verified by taking x-ray projection images from different angles. Results: Using four external fiducial markers of 1.7  mm diameter and computed tomography-based treatment planning, a target alignment error of less than 2  mm can be achieved with an angular deviation of less than 2{sup ∘}. Minor improvements on the protocol and the use of smaller markers indicate that even a precision better than 1  mm is technically feasible. Detailed investigations concerning the imaging dose lead to the conclusion that doses for skull radiographs lie in the same range as dose reference levels for human head radiographs. A currently used online dose monitor for MRT has been proven to give reliable results for the imaging beam. Conclusions: The ESRF biomedical beamline ID17 is technically ready to apply conformal image-guided MRT from multiple ports to large animals during future veterinary trials.

  16. Significant wave height retrieval from synthetic radar images

    NARCIS (Netherlands)

    Wijaya, Andreas Parama; van Groesen, Embrecht W.C.

    2014-01-01

    In many offshore activities radar imagery is used to observe and predict ocean waves. An important issue in analyzing the radar images is to resolve the significant wave height. Different from 3DFFT methods that use an estimate related to the square root of the signal-to-noise ratio of radar images,

  17. Multiscale Distance Coherence Vector Algorithm for Content-Based Image Retrieval

    Science.gov (United States)

    Jiexian, Zeng; Xiupeng, Liu

    2014-01-01

    Multiscale distance coherence vector algorithm for content-based image retrieval (CBIR) is proposed due to the same descriptor with different shapes and the shortcomings of antinoise performance of the distance coherence vector algorithm. By this algorithm, the image contour curve is evolved by Gaussian function first, and then the distance coherence vector is, respectively, extracted from the contour of the original image and evolved images. Multiscale distance coherence vector was obtained by reasonable weight distribution of the distance coherence vectors of evolved images contour. This algorithm not only is invariable to translation, rotation, and scaling transformation but also has good performance of antinoise. The experiment results show us that the algorithm has a higher recall rate and precision rate for the retrieval of images polluted by noise. PMID:24883416

  18. Three-dimensional imaging using phase retrieval with two focus planes

    Science.gov (United States)

    Ilovitsh, Tali; Ilovitsh, Asaf; Weiss, Aryeh; Meir, Rinat; Zalevsky, Zeev

    2016-03-01

    This work presents a technique for a full 3D imaging of biological samples tagged with gold-nanoparticles (GNPs) using only two images, rather than many images per volume as is currently needed for 3D optical sectioning microscopy. The proposed approach is based on the Gerchberg-Saxton (GS) phase retrieval algorithm. The reconstructed field is free space propagated to all other focus planes using post processing, and the 2D z-stack is merged to create a 3D image of the sample with high fidelity. Because we propose to apply the phase retrieving on nano particles, the regular ambiguities typical to the Gerchberg-Saxton algorithm, are eliminated. In addition, since the method requires the capturing of two images only, it can be suitable for 3D live cell imaging. The proposed concept is presented and validated both on simulated data as well as experimentally.

  19. Content Based Radiographic Images Indexing and Retrieval Using Pattern Orientation Histogram

    Directory of Open Access Journals (Sweden)

    Abolfazl Lakdashti

    2008-06-01

    Full Text Available Introduction: Content Based Image Retrieval (CBIR is a method of image searching and retrieval in a  database. In medical applications, CBIR is a tool used by physicians to compare the previous and current  medical images associated with patients pathological conditions. As the volume of pictorial information  stored in medical image databases is in progress, efficient image indexing and retrieval is increasingly  becoming a necessity.  Materials and Methods: This paper presents a new content based radiographic image retrieval approach  based on histogram of pattern orientations, namely pattern orientation histogram (POH. POH represents  the  spatial  distribution  of  five  different  pattern  orientations:  vertical,  horizontal,  diagonal  down/left,  diagonal down/right and non-orientation. In this method, a given image is first divided into image-blocks  and  the  frequency  of  each  type  of  pattern  is  determined  in  each  image-block.  Then,  local  pattern  histograms for each of these image-blocks are computed.   Results: The method was compared to two well known texture-based image retrieval methods: Tamura  and  Edge  Histogram  Descriptors  (EHD  in  MPEG-7  standard.  Experimental  results  based  on  10000  IRMA  radiography  image  dataset,  demonstrate  that  POH  provides  better  precision  and  recall  rates  compared to Tamura and EHD. For some images, the recall and precision rates obtained by POH are,  respectively, 48% and 18% better than the best of the two above mentioned methods.    Discussion and Conclusion: Since we exploit the absolute location of the pattern in the image as well as  its global composition, the proposed matching method can retrieve semantically similar medical images.

  20. Algorithm for image retrieval based on edge gradient orientation statistical code.

    Science.gov (United States)

    Zeng, Jiexian; Zhao, Yonggang; Li, Weiye; Fu, Xiang

    2014-01-01

    Image edge gradient direction not only contains important information of the shape, but also has a simple, lower complexity characteristic. Considering that the edge gradient direction histograms and edge direction autocorrelogram do not have the rotation invariance, we put forward the image retrieval algorithm which is based on edge gradient orientation statistical code (hereinafter referred to as EGOSC) by sharing the application of the statistics method in the edge direction of the chain code in eight neighborhoods to the statistics of the edge gradient direction. Firstly, we construct the n-direction vector and make maximal summation restriction on EGOSC to make sure this algorithm is invariable for rotation effectively. Then, we use Euclidean distance of edge gradient direction entropy to measure shape similarity, so that this method is not sensitive to scaling, color, and illumination change. The experimental results and the algorithm analysis demonstrate that the algorithm can be used for content-based image retrieval and has good retrieval results.

  1. Multi-instance learning based on instance consistency for image retrieval

    Science.gov (United States)

    Zhang, Miao; Wu, Zhize; Wan, Shouhong; Yue, Lihua; Yin, Bangjie

    2017-07-01

    Multiple-instance learning (MIL) has been successfully utilized in image retrieval. Existing approaches cannot select positive instances correctly from positive bags which may result in a low accuracy. In this paper, we propose a new image retrieval approach called multiple instance learning based on instance-consistency (MILIC) to mitigate such issue. First, we select potential positive instances effectively in each positive bag by ranking instance-consistency (IC) values of instances. Then, we design a feature representation scheme, which can represent the relationship among bags and instances, based on potential positive instances to convert a bag into a single instance. Finally, we can use a standard single-instance learning strategy, such as the support vector machine, for performing object-based image retrieval. Experimental results on two challenging data sets show the effectiveness of our proposal in terms of accuracy and run time.

  2. Large Scale Hierarchical K-Means Based Image Retrieval With MapReduce

    Science.gov (United States)

    2014-03-27

    flat vocabulary on MapReduce. In 2013, Moise and Shestakov [32, 40], have been researching large scale indexing and search with MapReduce. They...time will be greatly reduced, however image retrieval performance will almost certainly suffer. Moise and Shestakov ran tests with 100M images on 108...43–72, 2005. [32] Diana Moise , Denis Shestakov, Gylfi Gudmundsson, and Laurent Amsaleg. Indexing and searching 100m images with map-reduce. In

  3. Uncertainties in cloud phase and optical thickness retrievals from the Earth Polychromatic Imaging Camera (EPIC)

    Science.gov (United States)

    Meyer, Kerry; Yang, Yuekui; Platnick, Steven

    2018-01-01

    This paper presents an investigation of the expected uncertainties of a single channel cloud optical thickness (COT) retrieval technique, as well as a simple cloud temperature threshold based thermodynamic phase approach, in support of the Deep Space Climate Observatory (DSCOVR) mission. DSCOVR cloud products will be derived from Earth Polychromatic Imaging Camera (EPIC) observations in the ultraviolet and visible spectra. Since EPIC is not equipped with a spectral channel in the shortwave or mid-wave infrared that is sensitive to cloud effective radius (CER), COT will be inferred from a single visible channel with the assumption of appropriate CER values for liquid and ice phase clouds. One month of Aqua MODIS daytime granules from April 2005 is selected for investigating cloud phase sensitivity, and a subset of these granules that has similar EPIC sun-view geometry is selected for investigating COT uncertainties. EPIC COT retrievals are simulated with the same algorithm as the operational MODIS cloud products (MOD06), except using fixed phase-dependent CER values. Uncertainty estimates are derived by comparing the single channel COT retrievals with the baseline bi-spectral MODIS retrievals. Results show that a single channel COT retrieval is feasible for EPIC. For ice clouds, single channel retrieval errors are minimal (clouds the error is mostly limited to within 10%, although for thin clouds (COT cloud masking and cloud temperature retrievals are not considered in this study. PMID:29619116

  4. An inventory of biomedical imaging physics elements-of-competence for diagnostic radiography education in Europe

    International Nuclear Information System (INIS)

    Caruana, Carmel J.; Plasek, Jaromir

    2006-01-01

    Purpose: To develop an inventory of biomedical physics elements-of-competence for diagnostic radiography education in Europe. Method: Research articles in the English literature and UK documentation pertinent to radiography education, competences and role development were subjected to a rigorous analysis of content from a functional and competence analysis perspective. Translations of radiography curricula from across Europe and relevant EU legislation were likewise analysed to ensure a pan-European perspective. Broad Subject Specific Competences for diagnostic radiography that included major biomedical physics components were singled out. These competences were in turn carefully deconstructed into specific elements-of-competence and those elements falling within the biomedical physics learning domain inventorised. A pilot version of the inventory was evaluated by participants during a meeting of the Higher Education Network for Radiography in Europe (HENRE), held in Marsascala, Malta, in November 2004. The inventory was further refined taking into consideration suggestions by HENRE members and scientific, professional and educational developments. Findings: The evaluation of the pilot inventory was very positive and indicated that the overall structure of the inventory was sensible, easily understood and acceptable - hence a good foundation for further development. Conclusions: Use of the inventory by radiography programme leaders and biomedical physics educators would guarantee that all necessary physics elements-of-competence underpinning the safe, effective and economical use of imaging devices are included within radiography curricula. It will also ensure the relevancy of physics content within radiography education. The inventory is designed to be a pragmatic tool for curriculum development across the entire range of radiography education up to doctorate level and irrespective of whether curriculum delivery is discipline-based or integrated, presentation

  5. An inventory of biomedical imaging physics elements-of-competence for diagnostic radiography education in Europe

    Energy Technology Data Exchange (ETDEWEB)

    Caruana, Carmel J. [University of Malta, Institute of Health Care, St Lukes Hospital, Gwardamangia (Malta)]. E-mail: carmel.j.caruana@um.edu.mt; Plasek, Jaromir [Charles University, Faculty of Mathematics and Physics, Institute of Physics, Division of Biophysics, Prague (Czech Republic)

    2006-08-15

    Purpose: To develop an inventory of biomedical physics elements-of-competence for diagnostic radiography education in Europe. Method: Research articles in the English literature and UK documentation pertinent to radiography education, competences and role development were subjected to a rigorous analysis of content from a functional and competence analysis perspective. Translations of radiography curricula from across Europe and relevant EU legislation were likewise analysed to ensure a pan-European perspective. Broad Subject Specific Competences for diagnostic radiography that included major biomedical physics components were singled out. These competences were in turn carefully deconstructed into specific elements-of-competence and those elements falling within the biomedical physics learning domain inventorised. A pilot version of the inventory was evaluated by participants during a meeting of the Higher Education Network for Radiography in Europe (HENRE), held in Marsascala, Malta, in November 2004. The inventory was further refined taking into consideration suggestions by HENRE members and scientific, professional and educational developments. Findings: The evaluation of the pilot inventory was very positive and indicated that the overall structure of the inventory was sensible, easily understood and acceptable - hence a good foundation for further development. Conclusions: Use of the inventory by radiography programme leaders and biomedical physics educators would guarantee that all necessary physics elements-of-competence underpinning the safe, effective and economical use of imaging devices are included within radiography curricula. It will also ensure the relevancy of physics content within radiography education. The inventory is designed to be a pragmatic tool for curriculum development across the entire range of radiography education up to doctorate level and irrespective of whether curriculum delivery is discipline-based or integrated, presentation

  6. Investigation of biomedical inner microstructures with hard X-ray phase-contrast imaging

    Energy Technology Data Exchange (ETDEWEB)

    Shu Hang [Beijing Synchrotron Radiation Facility, Institute of High Energy Physics, CAS, 100049 Beijing (China); Graduate University of the Chinese Academy of Sciences, 100864 Beijing (China); Zhu Peiping [Beijing Synchrotron Radiation Facility, Institute of High Energy Physics, CAS, 100049 Beijing (China); Chen Bo [Department of Physics, University of Science and Technology of China, Hefei 230026 (China); Liu Bo; Yin Hongxia [Capital University of Medical Sciences, 100054 Beijing (China); Li Enrong [Beijing Synchrotron Radiation Facility, Institute of High Energy Physics, CAS, 100049 Beijing (China); Graduate University of the Chinese Academy of Sciences, 100864 Beijing (China); Liu Yijin [Department of Physics, University of Science and Technology of China, Hefei 230026 (China); Wang Junyue [Beijing Synchrotron Radiation Facility, Institute of High Energy Physics, CAS, 100049 Beijing (China); Graduate University of the Chinese Academy of Sciences, 100864 Beijing (China); Yuan Qingxi; Huang Wanxia; Fang Shouxian [Beijing Synchrotron Radiation Facility, Institute of High Energy Physics, CAS, 100049 Beijing (China); Wu Ziyu [Beijing Synchrotron Radiation Facility, Institute of High Energy Physics, CAS, 100049 Beijing (China); National Center for NanoScience and Technology, 100080 Beijing (China)], E-mail: wuzy@ihep.ac.cn

    2007-09-21

    Hard X-ray Phase-Contrast Imaging (HX-PCI) is a new and valuable method that may provide information of the inner parts of an opaque object. Previous reports demonstrated its applicability in soft and hard tissue imaging. Here we provide further evidence for improved image quality and the effective capability to distinguish inner microstructures in real biomedical systems such as cochlea. Experiments performed both at the 4W1A beamline of the Beijing Synchrotron Radiation Facility (BSRF) and at the Taiwan National Synchrotron Radiation Research Center (NSRRC) clearly show details of samples' inner microstructure with a resolution of a few microns. The improved spatial resolution is a relevant achievement for future improved understanding and clinical trials.

  7. Visualization of biomedical image data and irradiation planning using a parallel computing system

    International Nuclear Information System (INIS)

    Lehrig, R.

    1991-01-01

    The contribution explains the development of a novel, low-cost workstation for the processing of biomedical tomographic data sequences. The workstation was to allow both graphical display of the data and implementation of modelling software for irradiation planning, especially for calculation of dose distributions on the basis of the measured tomogram data. The system developed according to these criteria is a parallel computing system which performs secondary, two-dimensional image reconstructions irrespective of the imaging direction of the original tomographic scans. Three-dimensional image reconstructions can be generated from any direction of view, with random selection of sections of the scanned object. (orig./MM) With 69 figs., 2 tabs [de

  8. Modeling multiple visual words assignment for bag-of-features based medical image retrieval

    KAUST Repository

    Wang, Jim Jing-Yan

    2012-01-01

    In this paper, we investigate the bag-of-features based medical image retrieval methods, which represent an image as a collection of local features, such as image patch and key points with SIFT descriptor. To improve the bag-of-features method, we first model the assignment of local descriptor as contribution functions, and then propose a new multiple assignment strategy. By assuming the local feature can be reconstructed by its neighboring visual words in vocabulary, we solve the reconstruction weights as a QP problem and then use the solved weights as contribution functions, which results in a new assignment method called the QP assignment. We carry our experiments on ImageCLEFmed datasets. Experiments\\' results show that our proposed method exceeds the performances of traditional solutions and works well for the bag-of-features based medical image retrieval tasks.

  9. Automated Region of Interest Retrieval of Metallographic Images for Quality Classification in Industry

    Directory of Open Access Journals (Sweden)

    Petr Kotas

    2012-01-01

    Full Text Available The aim of the research is development and testing of new methods to classify the quality of metallographic samples of steels with high added value (for example grades X70 according API. In this paper, we address the development of methods to classify the quality of slab samples images with the main emphasis on the quality of the image center called as segregation area. For this reason, we introduce an alternative method for automated retrieval of region of interest. In the first step, the metallographic image is segmented using both spectral method and thresholding. Then, the extracted macrostructure of the metallographic image is automatically analyzed by statistical methods. Finally, automatically extracted region of interests are compared with results of human experts.  Practical experience with retrieval of non-homogeneous noised digital images in industrial environment is discussed as well.

  10. Modeling multiple visual words assignment for bag-of-features based medical image retrieval

    KAUST Repository

    Wang, Jim Jing-Yan; Almasri, Islam

    2012-01-01

    In this paper, we investigate the bag-of-features based medical image retrieval methods, which represent an image as a collection of local features, such as image patch and key points with SIFT descriptor. To improve the bag-of-features method, we first model the assignment of local descriptor as contribution functions, and then propose a new multiple assignment strategy. By assuming the local feature can be reconstructed by its neighboring visual words in vocabulary, we solve the reconstruction weights as a QP problem and then use the solved weights as contribution functions, which results in a new assignment method called the QP assignment. We carry our experiments on ImageCLEFmed datasets. Experiments' results show that our proposed method exceeds the performances of traditional solutions and works well for the bag-of-features based medical image retrieval tasks.

  11. Quantifying Vegetation Biophysical Variables from Imaging Spectroscopy Data: A Review on Retrieval Methods

    Science.gov (United States)

    Verrelst, Jochem; Malenovský, Zbyněk; Van der Tol, Christiaan; Camps-Valls, Gustau; Gastellu-Etchegorry, Jean-Philippe; Lewis, Philip; North, Peter; Moreno, Jose

    2018-06-01

    An unprecedented spectroscopic data stream will soon become available with forthcoming Earth-observing satellite missions equipped with imaging spectroradiometers. This data stream will open up a vast array of opportunities to quantify a diversity of biochemical and structural vegetation properties. The processing requirements for such large data streams require reliable retrieval techniques enabling the spatiotemporally explicit quantification of biophysical variables. With the aim of preparing for this new era of Earth observation, this review summarizes the state-of-the-art retrieval methods that have been applied in experimental imaging spectroscopy studies inferring all kinds of vegetation biophysical variables. Identified retrieval methods are categorized into: (1) parametric regression, including vegetation indices, shape indices and spectral transformations; (2) nonparametric regression, including linear and nonlinear machine learning regression algorithms; (3) physically based, including inversion of radiative transfer models (RTMs) using numerical optimization and look-up table approaches; and (4) hybrid regression methods, which combine RTM simulations with machine learning regression methods. For each of these categories, an overview of widely applied methods with application to mapping vegetation properties is given. In view of processing imaging spectroscopy data, a critical aspect involves the challenge of dealing with spectral multicollinearity. The ability to provide robust estimates, retrieval uncertainties and acceptable retrieval processing speed are other important aspects in view of operational processing. Recommendations towards new-generation spectroscopy-based processing chains for operational production of biophysical variables are given.

  12. Multi-Spectral Cloud Retrievals from Moderate Image Spectrometer (MODIS)

    Science.gov (United States)

    Platnick, Steven

    2004-01-01

    MODIS observations from the NASA EOS Terra spacecraft (1030 local time equatorial sun-synchronous crossing) launched in December 1999 have provided a unique set of Earth observation data. With the launch of the NASA EOS Aqua spacecraft (1330 local time crossing! in May 2002: two MODIS daytime (sunlit) and nighttime observations are now available in a 24-hour period allowing some measure of diurnal variability. A comprehensive set of remote sensing algorithms for cloud masking and the retrieval of cloud physical and optical properties has been developed by members of the MODIS atmosphere science team. The archived products from these algorithms have applications in climate modeling, climate change studies, numerical weather prediction, as well as fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. An overview of the instrument and cloud algorithms will be presented along with various examples, including an initial analysis of several operational global gridded (Level-3) cloud products from the two platforms. Statistics of cloud optical and microphysical properties as a function of latitude for land and Ocean regions will be shown. Current algorithm research efforts will also be discussed.

  13. K-edge subtraction synchrotron X-ray imaging in bio-medical research.

    Science.gov (United States)

    Thomlinson, W; Elleaume, H; Porra, L; Suortti, P

    2018-05-01

    High contrast in X-ray medical imaging, while maintaining acceptable radiation dose levels to the patient, has long been a goal. One of the most promising methods is that of K-edge subtraction imaging. This technique, first advanced as long ago as 1953 by B. Jacobson, uses the large difference in the absorption coefficient of elements at energies above and below the K-edge. Two images, one taken above the edge and one below the edge, are subtracted leaving, ideally, only the image of the distribution of the target element. This paper reviews the development of the KES techniques and technology as applied to bio-medical imaging from the early low-power tube sources of X-rays to the latest high-power synchrotron sources. Applications to coronary angiography, functional lung imaging and bone growth are highlighted. A vision of possible imaging with new compact sources is presented. Copyright © 2018 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

  14. Words Matter: Scene Text for Image Classification and Retrieval

    NARCIS (Netherlands)

    Karaoglu, S.; Tao, R.; Gevers, T.; Smeulders, A.W.M.

    Text in natural images typically adds meaning to an object or scene. In particular, text specifies which business places serve drinks (e.g., cafe, teahouse) or food (e.g., restaurant, pizzeria), and what kind of service is provided (e.g., massage, repair). The mere presence of text, its words, and

  15. Aspect-based Relevance Learning for Image Retrieval

    NARCIS (Netherlands)

    M.J. Huiskes (Mark)

    2005-01-01

    htmlabstractWe analyze the special structure of the relevance feedback learning problem, focusing particularly on the effects of image selection by partial relevance on the clustering behavior of feedback examples. We propose a scheme, aspect-based relevance learning, which guarantees that feedback

  16. Genetic Algorithm Phase Retrieval for the Systematic Image-Based Optical Alignment Testbed

    Science.gov (United States)

    Taylor, Jaime; Rakoczy, John; Steincamp, James

    2003-01-01

    Phase retrieval requires calculation of the real-valued phase of the pupil fimction from the image intensity distribution and characteristics of an optical system. Genetic 'algorithms were used to solve two one-dimensional phase retrieval problem. A GA successfully estimated the coefficients of a polynomial expansion of the phase when the number of coefficients was correctly specified. A GA also successfully estimated the multiple p h e s of a segmented optical system analogous to the seven-mirror Systematic Image-Based Optical Alignment (SIBOA) testbed located at NASA s Marshall Space Flight Center. The SIBOA testbed was developed to investigate phase retrieval techniques. Tiphilt and piston motions of the mirrors accomplish phase corrections. A constant phase over each mirror can be achieved by an independent tip/tilt correction: the phase Conection term can then be factored out of the Discrete Fourier Tranform (DFT), greatly reducing computations.

  17. Neural mechanism of lmplicit and explicit memory retrieval: functional MR imaging

    International Nuclear Information System (INIS)

    Kang, Heoung Keun; Jeong, Gwang Woo; Park, Tae Jin; Seo, Jeong Jin; Kim, Hyung Joong; Eun, Sung Jong; Chung, Tae Woong

    2003-01-01

    To identify, using functional MR imaging, distinct cerebral centers and to evaluate the neural mechanism associated with implicit and explicit retrieval of words during conceptual processing. Seven healthy volunteers aged 21-25 (mean, 22) years underwent BOLD-based fMR imaging using a 1.5T signa horizon echospeed MR system. To activate the cerebral cortices, a series of tasks was performed as follows: the encoding of two-syllable words, and implicit and explicit retrieval of previously learned words during conceptual processing. The activation paradigm consisted of a cycle of alternating periods of 30 seconds of stimulation and 30 seconds of rest. Stimulation was accomplished by encoding eight two-syllable words and the retrieval of previously presented words, while the control condition was a white screen with a small fixed cross. During the tasks we acquired ten slices (6 mm slice thickness, 1 mm gap) parallel to the AC-PC line, and the resulting functional activation maps were reconstructed using a statistical parametric mapping program (SPM99). A comparison of activation ratios (percentages), based on the number of volunteers, showed that activation of Rhs-35, PoCiG-23 and ICiG-26·30 was associated with explicit retrieval only; other brain areas were activated during the performance of both implicit and explicit retrieval tasks. Activation ratios were higher for explicit tasks than for implicit; in the cingulate gyrus and temporal lobe they were 30% and 10% greater, respectively. During explicit retrieval, a distinct brain activation index (percentage) was seen in the temporal, parietal, and occipital lobe and cingulate gyrus, and PrCeG-4, Pr/ PoCeG-43 in the frontal lobe. During implicit retrieval, on the other hand, activity was greater in the frontal lobe, including the areas of SCA-25, SFG/MFG-10, IFG-44·45, OrbG-11·47, SFG-6·8 and MFG-9·46. Overall, activation was lateralized mainly in the left hemisphere during both implicit and explicit retrieval

  18. Neural mechanism of lmplicit and explicit memory retrieval: functional MR imaging

    Energy Technology Data Exchange (ETDEWEB)

    Kang, Heoung Keun; Jeong, Gwang Woo; Park, Tae Jin; Seo, Jeong Jin; Kim, Hyung Joong; Eun, Sung Jong; Chung, Tae Woong [Chonnam National University Medical School, Gwangju (Korea, Republic of)

    2003-03-01

    To identify, using functional MR imaging, distinct cerebral centers and to evaluate the neural mechanism associated with implicit and explicit retrieval of words during conceptual processing. Seven healthy volunteers aged 21-25 (mean, 22) years underwent BOLD-based fMR imaging using a 1.5T signa horizon echospeed MR system. To activate the cerebral cortices, a series of tasks was performed as follows: the encoding of two-syllable words, and implicit and explicit retrieval of previously learned words during conceptual processing. The activation paradigm consisted of a cycle of alternating periods of 30 seconds of stimulation and 30 seconds of rest. Stimulation was accomplished by encoding eight two-syllable words and the retrieval of previously presented words, while the control condition was a white screen with a small fixed cross. During the tasks we acquired ten slices (6 mm slice thickness, 1 mm gap) parallel to the AC-PC line, and the resulting functional activation maps were reconstructed using a statistical parametric mapping program (SPM99). A comparison of activation ratios (percentages), based on the number of volunteers, showed that activation of Rhs-35, PoCiG-23 and ICiG-26{center_dot}30 was associated with explicit retrieval only; other brain areas were activated during the performance of both implicit and explicit retrieval tasks. Activation ratios were higher for explicit tasks than for implicit; in the cingulate gyrus and temporal lobe they were 30% and 10% greater, respectively. During explicit retrieval, a distinct brain activation index (percentage) was seen in the temporal, parietal, and occipital lobe and cingulate gyrus, and PrCeG-4, Pr/ PoCeG-43 in the frontal lobe. During implicit retrieval, on the other hand, activity was greater in the frontal lobe, including the areas of SCA-25, SFG/MFG-10, IFG-44{center_dot}45, OrbG-11{center_dot}47, SFG-6{center_dot}8 and MFG-9{center_dot}46. Overall, activation was lateralized mainly in the left

  19. Wavelet optimization for content-based image retrieval in medical databases.

    Science.gov (United States)

    Quellec, G; Lamard, M; Cazuguel, G; Cochener, B; Roux, C

    2010-04-01

    We propose in this article a content-based image retrieval (CBIR) method for diagnosis aid in medical fields. In the proposed system, images are indexed in a generic fashion, without extracting domain-specific features: a signature is built for each image from its wavelet transform. These image signatures characterize the distribution of wavelet coefficients in each subband of the decomposition. A distance measure is then defined to compare two image signatures and thus retrieve the most similar images in a database when a query image is submitted by a physician. To retrieve relevant images from a medical database, the signatures and the distance measure must be related to the medical interpretation of images. As a consequence, we introduce several degrees of freedom in the system so that it can be tuned to any pathology and image modality. In particular, we propose to adapt the wavelet basis, within the lifting scheme framework, and to use a custom decomposition scheme. Weights are also introduced between subbands. All these parameters are tuned by an optimization procedure, using the medical grading of each image in the database to define a performance measure. The system is assessed on two medical image databases: one for diabetic retinopathy follow up and one for screening mammography, as well as a general purpose database. Results are promising: a mean precision of 56.50%, 70.91% and 96.10% is achieved for these three databases, when five images are returned by the system. Copyright 2009 Elsevier B.V. All rights reserved.

  20. Supporting Keyword Search for Image Retrieval with Integration of Probabilistic Annotation

    Directory of Open Access Journals (Sweden)

    Tie Hua Zhou

    2015-05-01

    Full Text Available The ever-increasing quantities of digital photo resources are annotated with enriching vocabularies to form semantic annotations. Photo-sharing social networks have boosted the need for efficient and intuitive querying to respond to user requirements in large-scale image collections. In order to help users formulate efficient and effective image retrieval, we present a novel integration of a probabilistic model based on keyword query architecture that models the probability distribution of image annotations: allowing users to obtain satisfactory results from image retrieval via the integration of multiple annotations. We focus on the annotation integration step in order to specify the meaning of each image annotation, thus leading to the most representative annotations of the intent of a keyword search. For this demonstration, we show how a probabilistic model has been integrated to semantic annotations to allow users to intuitively define explicit and precise keyword queries in order to retrieve satisfactory image results distributed in heterogeneous large data sources. Our experiments on SBU (collected by Stony Brook University database show that (i our integrated annotation contains higher quality representatives and semantic matches; and (ii the results indicating annotation integration can indeed improve image search result quality.

  1. 4D reconstruction of the past: the image retrieval and 3D model construction pipeline

    Science.gov (United States)

    Hadjiprocopis, Andreas; Ioannides, Marinos; Wenzel, Konrad; Rothermel, Mathias; Johnsons, Paul S.; Fritsch, Dieter; Doulamis, Anastasios; Protopapadakis, Eftychios; Kyriakaki, Georgia; Makantasis, Kostas; Weinlinger, Guenther; Klein, Michael; Fellner, Dieter; Stork, Andre; Santos, Pedro

    2014-08-01

    One of the main characteristics of the Internet era we are living in, is the free and online availability of a huge amount of data. This data is of varied reliability and accuracy and exists in various forms and formats. Often, it is cross-referenced and linked to other data, forming a nexus of text, images, animation and audio enabled by hypertext and, recently, by the Web3.0 standard. Our main goal is to enable historians, architects, archaeolo- gists, urban planners and affiliated professionals to reconstruct views of historical monuments from thousands of images floating around the web. This paper aims to provide an update of our progress in designing and imple- menting a pipeline for searching, filtering and retrieving photographs from Open Access Image Repositories and social media sites and using these images to build accurate 3D models of archaeological monuments as well as enriching multimedia of cultural / archaeological interest with metadata and harvesting the end products to EU- ROPEANA. We provide details of how our implemented software searches and retrieves images of archaeological sites from Flickr and Picasa repositories as well as strategies on how to filter the results, on two levels; a) based on their built-in metadata including geo-location information and b) based on image processing and clustering techniques. We also describe our implementation of a Structure from Motion pipeline designed for producing 3D models using the large collection of 2D input images (>1000) retrieved from Internet Repositories.

  2. Qualification of a Null Lens Using Image-Based Phase Retrieval

    Science.gov (United States)

    Bolcar, Matthew R.; Aronstein, David L.; Hill, Peter C.; Smith, J. Scott; Zielinski, Thomas P.

    2012-01-01

    In measuring the figure error of an aspheric optic using a null lens, the wavefront contribution from the null lens must be independently and accurately characterized in order to isolate the optical performance of the aspheric optic alone. Various techniques can be used to characterize such a null lens, including interferometry, profilometry and image-based methods. Only image-based methods, such as phase retrieval, can measure the null-lens wavefront in situ - in single-pass, and at the same conjugates and in the same alignment state in which the null lens will ultimately be used - with no additional optical components. Due to the intended purpose of a Dull lens (e.g., to null a large aspheric wavefront with a near-equal-but-opposite spherical wavefront), characterizing a null-lens wavefront presents several challenges to image-based phase retrieval: Large wavefront slopes and high-dynamic-range data decrease the capture range of phase-retrieval algorithms, increase the requirements on the fidelity of the forward model of the optical system, and make it difficult to extract diagnostic information (e.g., the system F/#) from the image data. In this paper, we present a study of these effects on phase-retrieval algorithms in the context of a null lens used in component development for the Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission. Approaches for mitigation are also discussed.

  3. Content-Based Image Retrieval Benchmarking: Utilizing color categories and color distributions

    NARCIS (Netherlands)

    van den Broek, Egon; Kisters, Peter M.F.; Vuurpijl, Louis G.

    From a human centered perspective three ingredients for Content-Based Image Retrieval (CBIR) were developed. First, with their existence confirmed by experimental data, 11 color categories were utilized for CBIR and used as input for a new color space segmentation technique. The complete HSI color

  4. The utilization of human color categorization for content-based image retrieval

    NARCIS (Netherlands)

    van den Broek, Egon; Rogowitz, Bernice E.; Kisters, Peter M.F.; Pappas, Thrasyvoulos N.; Vuurpijl, Louis G.

    2004-01-01

    We present the concept of intelligent Content-Based Image Retrieval (iCBIR), which incorporates knowledge concerning human cognition in system development. The present research focuses on the utilization of color categories (or focal colors) for CBIR purposes, in particularly considered to be useful

  5. Research on Techniques of Multifeatures Extraction for Tongue Image and Its Application in Retrieval

    Directory of Open Access Journals (Sweden)

    Liyan Chen

    2017-01-01

    Full Text Available Tongue diagnosis is one of the important methods in the Chinese traditional medicine. Doctors can judge the disease’s situation by observing patient’s tongue color and texture. This paper presents a novel approach to extract color and texture features of tongue images. First, we use improved GLA (Generalized Lloyd Algorithm to extract the main color of tongue image. Considering that the color feature cannot fully express tongue image information, the paper analyzes tongue edge’s texture features and proposes an algorithm to extract them. Then, we integrate the two features in retrieval by different weight. Experimental results show that the proposed method can improve the detection rate of lesion in tongue image relative to single feature retrieval.

  6. MARS Spectral Imaging: From High-Energy Physics to a Biomedical Business

    CERN Multimedia

    CERN. Geneva

    2017-01-01

    Abstract MARS spectral scanners provide colour X-Ray images. Current MARS pre-clinical scanners enable researchers and clinicians to measure biochemical and physiological processes in specimens, and animal models of disease. The scanners have developed from a 10 year scientific collaboration between New Zealand and CERN. In parallel a company, MARS Bioimaging Ltd, was founded to commercialise the technology by productising the scanner and selling it to biomedical users around the world. The New Zealand team is now more than 30 people including staff and students from the fields of physics, engineering, computing, maths, radiology, cardiology, biochemistry, oncology, and orthopaedics. Current work with pre-clinical scanners has concluded that the technology will be  useful in heart disease, stroke, arthritis, joint replacements, and cancer. In late 2014, the government announced funding for NZ to build a MARS scanner capable of imaging humans. Bio Professor Anthony Butler is a radiologist wit...

  7. Color image encryption using random transforms, phase retrieval, chaotic maps, and diffusion

    Science.gov (United States)

    Annaby, M. H.; Rushdi, M. A.; Nehary, E. A.

    2018-04-01

    The recent tremendous proliferation of color imaging applications has been accompanied by growing research in data encryption to secure color images against adversary attacks. While recent color image encryption techniques perform reasonably well, they still exhibit vulnerabilities and deficiencies in terms of statistical security measures due to image data redundancy and inherent weaknesses. This paper proposes two encryption algorithms that largely treat these deficiencies and boost the security strength through novel integration of the random fractional Fourier transforms, phase retrieval algorithms, as well as chaotic scrambling and diffusion. We show through detailed experiments and statistical analysis that the proposed enhancements significantly improve security measures and immunity to attacks.

  8. High sensitivity phase retrieval method in grating-based x-ray phase contrast imaging

    Energy Technology Data Exchange (ETDEWEB)

    Wu, Zhao; Gao, Kun; Chen, Jian; Wang, Dajiang; Wang, Shenghao; Chen, Heng; Bao, Yuan; Shao, Qigang; Wang, Zhili, E-mail: wangnsrl@ustc.edu.cn [National Synchrotron Radiation Laboratory, University of Science and Technology of China, Hefei 230029 (China); Zhang, Kai [Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049 (China); Zhu, Peiping; Wu, Ziyu, E-mail: wuzy@ustc.edu.cn [National Synchrotron Radiation Laboratory, University of Science and Technology of China, Hefei 230029, China and Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049 (China)

    2015-02-15

    Purpose: Grating-based x-ray phase contrast imaging is considered as one of the most promising techniques for future medical imaging. Many different methods have been developed to retrieve phase signal, among which the phase stepping (PS) method is widely used. However, further practical implementations are hindered, due to its complex scanning mode and high radiation dose. In contrast, the reverse projection (RP) method is a novel fast and low dose extraction approach. In this contribution, the authors present a quantitative analysis of the noise properties of the refraction signals retrieved by the two methods and compare their sensitivities. Methods: Using the error propagation formula, the authors analyze theoretically the signal-to-noise ratios (SNRs) of the refraction images retrieved by the two methods. Then, the sensitivities of the two extraction methods are compared under an identical exposure dose. Numerical experiments are performed to validate the theoretical results and provide some quantitative insight. Results: The SNRs of the two methods are both dependent on the system parameters, but in different ways. Comparison between their sensitivities reveals that for the refraction signal, the RP method possesses a higher sensitivity, especially in the case of high visibility and/or at the edge of the object. Conclusions: Compared with the PS method, the RP method has a superior sensitivity and provides refraction images with a higher SNR. Therefore, one can obtain highly sensitive refraction images in grating-based phase contrast imaging. This is very important for future preclinical and clinical implementations.

  9. High sensitivity phase retrieval method in grating-based x-ray phase contrast imaging

    International Nuclear Information System (INIS)

    Wu, Zhao; Gao, Kun; Chen, Jian; Wang, Dajiang; Wang, Shenghao; Chen, Heng; Bao, Yuan; Shao, Qigang; Wang, Zhili; Zhang, Kai; Zhu, Peiping; Wu, Ziyu

    2015-01-01

    Purpose: Grating-based x-ray phase contrast imaging is considered as one of the most promising techniques for future medical imaging. Many different methods have been developed to retrieve phase signal, among which the phase stepping (PS) method is widely used. However, further practical implementations are hindered, due to its complex scanning mode and high radiation dose. In contrast, the reverse projection (RP) method is a novel fast and low dose extraction approach. In this contribution, the authors present a quantitative analysis of the noise properties of the refraction signals retrieved by the two methods and compare their sensitivities. Methods: Using the error propagation formula, the authors analyze theoretically the signal-to-noise ratios (SNRs) of the refraction images retrieved by the two methods. Then, the sensitivities of the two extraction methods are compared under an identical exposure dose. Numerical experiments are performed to validate the theoretical results and provide some quantitative insight. Results: The SNRs of the two methods are both dependent on the system parameters, but in different ways. Comparison between their sensitivities reveals that for the refraction signal, the RP method possesses a higher sensitivity, especially in the case of high visibility and/or at the edge of the object. Conclusions: Compared with the PS method, the RP method has a superior sensitivity and provides refraction images with a higher SNR. Therefore, one can obtain highly sensitive refraction images in grating-based phase contrast imaging. This is very important for future preclinical and clinical implementations

  10. An efficient similarity measure for content based image retrieval using memetic algorithm

    Directory of Open Access Journals (Sweden)

    Mutasem K. Alsmadi

    2017-06-01

    Full Text Available Content based image retrieval (CBIR systems work by retrieving images which are related to the query image (QI from huge databases. The available CBIR systems extract limited feature sets which confine the retrieval efficacy. In this work, extensive robust and important features were extracted from the images database and then stored in the feature repository. This feature set is composed of color signature with the shape and color texture features. Where, features are extracted from the given QI in the similar fashion. Consequently, a novel similarity evaluation using a meta-heuristic algorithm called a memetic algorithm (genetic algorithm with great deluge is achieved between the features of the QI and the features of the database images. Our proposed CBIR system is assessed by inquiring number of images (from the test dataset and the efficiency of the system is evaluated by calculating precision-recall value for the results. The results were superior to other state-of-the-art CBIR systems in regard to precision.

  11. Biomedical engineering and nanotechnology

    International Nuclear Information System (INIS)

    Pawar, S.H.; Khyalappa, R.J.; Yakhmi, J.V.

    2009-01-01

    This book is predominantly a compilation of papers presented in the conference which is focused on the development in biomedical materials, biomedical devises and instrumentation, biomedical effects of electromagnetic radiation, electrotherapy, radiotherapy, biosensors, biotechnology, bioengineering, tissue engineering, clinical engineering and surgical planning, medical imaging, hospital system management, biomedical education, biomedical industry and society, bioinformatics, structured nanomaterial for biomedical application, nano-composites, nano-medicine, synthesis of nanomaterial, nano science and technology development. The papers presented herein contain the scientific substance to suffice the academic directivity of the researchers from the field of biomedicine, biomedical engineering, material science and nanotechnology. Papers relevant to INIS are indexed separately

  12. Benchmarking, Research, Development, and Support for ORNL Automated Image and Signature Retrieval (AIR/ASR) Technologies

    Energy Technology Data Exchange (ETDEWEB)

    Tobin, K.W.

    2004-06-01

    This report describes the results of a Cooperative Research and Development Agreement (CRADA) with Applied Materials, Inc. (AMAT) of Santa Clara, California. This project encompassed the continued development and integration of the ORNL Automated Image Retrieval (AIR) technology, and an extension of the technology denoted Automated Signature Retrieval (ASR), and other related technologies with the Defect Source Identification (DSI) software system that was under development by AMAT at the time this work was performed. In the semiconductor manufacturing environment, defect imagery is used to diagnose problems in the manufacturing line, train yield management engineers, and examine historical data for trends. Image management in semiconductor data systems is a growing cause of concern in the industry as fabricators are now collecting up to 20,000 images each week. In response to this concern, researchers at the Oak Ridge National Laboratory (ORNL) developed a semiconductor-specific content-based image retrieval method and system, also known as AIR. The system uses an image-based query-by-example method to locate and retrieve similar imagery from a database of digital imagery using visual image characteristics. The query method is based on a unique architecture that takes advantage of the statistical, morphological, and structural characteristics of image data, generated by inspection equipment in industrial applications. The system improves the manufacturing process by allowing rapid access to historical records of similar events so that errant process equipment can be isolated and corrective actions can be quickly taken to improve yield. The combined ORNL and AMAT technology is referred to hereafter as DSI-AIR and DSI-ASR.

  13. Optical image encryption based on phase retrieval combined with three-dimensional particle-like distribution

    International Nuclear Information System (INIS)

    Chen, Wen; Chen, Xudong; Sheppard, Colin J R

    2012-01-01

    We propose a new phase retrieval algorithm for optical image encryption in three-dimensional (3D) space. The two-dimensional (2D) plaintext is considered as a series of particles distributed in 3D space, and an iterative phase retrieval algorithm is developed to encrypt the series of particles into phase-only masks. The feasibility and effectiveness of the proposed method are demonstrated by a numerical experiment, and the advantages and security of the proposed optical cryptosystems are also analyzed and discussed. (paper)

  14. Beamlines of the biomedical imaging and therapy facility at the Canadian light source-Part 1

    International Nuclear Information System (INIS)

    Wysokinski, Tomasz W.; Chapman, Dean; Adams, Gregg; Renier, Michel; Suortti, Pekka; Thomlinson, William

    2007-01-01

    The BioMedical Imaging and Therapy (BMIT) Facility will provide synchrotron-specific imaging and therapy capabilities. This paper describes one of the BMIT beamlines: the bend magnet (BM) beamline 05B1-1. It plays a complementary role to the insertion device (ID) beamline 051D-2 and allows either monochromatic or filtered white beam to be used in the experimental hutch. The monochromatic spectral range will span 8-40 keV, and the beam is more than 200 mm wide in the experimental hutch for imaging studies of small and medium-size animals (up to sheep size). The experimental hutch will have a positioning system that will allow imaging (computed tomography and planar imaging) as well as radiation therapy applications with both filtered white and monochromatic X-ray beams and will handle subjects up to 120 kg. Several different focal plane detectors (cameras) will be available with resolutions ranging from 10 to 150 μm

  15. Object-Location-Aware Hashing for Multi-Label Image Retrieval via Automatic Mask Learning.

    Science.gov (United States)

    Huang, Chang-Qin; Yang, Shang-Ming; Pan, Yan; Lai, Han-Jiang

    2018-09-01

    Learning-based hashing is a leading approach of approximate nearest neighbor search for large-scale image retrieval. In this paper, we develop a deep supervised hashing method for multi-label image retrieval, in which we propose to learn a binary "mask" map that can identify the approximate locations of objects in an image, so that we use this binary "mask" map to obtain length-limited hash codes which mainly focus on an image's objects but ignore the background. The proposed deep architecture consists of four parts: 1) a convolutional sub-network to generate effective image features; 2) a binary "mask" sub-network to identify image objects' approximate locations; 3) a weighted average pooling operation based on the binary "mask" to obtain feature representations and hash codes that pay most attention to foreground objects but ignore the background; and 4) the combination of a triplet ranking loss designed to preserve relative similarities among images and a cross entropy loss defined on image labels. We conduct comprehensive evaluations on four multi-label image data sets. The results indicate that the proposed hashing method achieves superior performance gains over the state-of-the-art supervised or unsupervised hashing baselines.

  16. Combining semantic technologies with a content-based image retrieval system - Preliminary considerations

    Science.gov (United States)

    Chmiel, P.; Ganzha, M.; Jaworska, T.; Paprzycki, M.

    2017-10-01

    Nowadays, as a part of systematic growth of volume, and variety, of information that can be found on the Internet, we observe also dramatic increase in sizes of available image collections. There are many ways to help users browsing / selecting images of interest. One of popular approaches are Content-Based Image Retrieval (CBIR) systems, which allow users to search for images that match their interests, expressed in the form of images (query by example). However, we believe that image search and retrieval could take advantage of semantic technologies. We have decided to test this hypothesis. Specifically, on the basis of knowledge captured in the CBIR, we have developed a domain ontology of residential real estate (detached houses, in particular). This allows us to semantically represent each image (and its constitutive architectural elements) represented within the CBIR. The proposed ontology was extended to capture not only the elements resulting from image segmentation, but also "spatial relations" between them. As a result, a new approach to querying the image database (semantic querying) has materialized, thus extending capabilities of the developed system.

  17. Parallel content-based sub-image retrieval using hierarchical searching.

    Science.gov (United States)

    Yang, Lin; Qi, Xin; Xing, Fuyong; Kurc, Tahsin; Saltz, Joel; Foran, David J

    2014-04-01

    The capacity to systematically search through large image collections and ensembles and detect regions exhibiting similar morphological characteristics is central to pathology diagnosis. Unfortunately, the primary methods used to search digitized, whole-slide histopathology specimens are slow and prone to inter- and intra-observer variability. The central objective of this research was to design, develop, and evaluate a content-based image retrieval system to assist doctors for quick and reliable content-based comparative search of similar prostate image patches. Given a representative image patch (sub-image), the algorithm will return a ranked ensemble of image patches throughout the entire whole-slide histology section which exhibits the most similar morphologic characteristics. This is accomplished by first performing hierarchical searching based on a newly developed hierarchical annular histogram (HAH). The set of candidates is then further refined in the second stage of processing by computing a color histogram from eight equally divided segments within each square annular bin defined in the original HAH. A demand-driven master-worker parallelization approach is employed to speed up the searching procedure. Using this strategy, the query patch is broadcasted to all worker processes. Each worker process is dynamically assigned an image by the master process to search for and return a ranked list of similar patches in the image. The algorithm was tested using digitized hematoxylin and eosin (H&E) stained prostate cancer specimens. We have achieved an excellent image retrieval performance. The recall rate within the first 40 rank retrieved image patches is ∼90%. Both the testing data and source code can be downloaded from http://pleiad.umdnj.edu/CBII/Bioinformatics/.

  18. Experiments with a novel content-based image retrieval software: can we eliminate classification systems in adolescent idiopathic scoliosis?

    Science.gov (United States)

    Menon, K Venugopal; Kumar, Dinesh; Thomas, Tessamma

    2014-02-01

    Study Design Preliminary evaluation of new tool. Objective To ascertain whether the newly developed content-based image retrieval (CBIR) software can be used successfully to retrieve images of similar cases of adolescent idiopathic scoliosis (AIS) from a database to help plan treatment without adhering to a classification scheme. Methods Sixty-two operated cases of AIS were entered into the newly developed CBIR database. Five new cases of different curve patterns were used as query images. The images were fed into the CBIR database that retrieved similar images from the existing cases. These were analyzed by a senior surgeon for conformity to the query image. Results Within the limits of variability set for the query system, all the resultant images conformed to the query image. One case had no similar match in the series. The other four retrieved several images that were matching with the query. No matching case was left out in the series. The postoperative images were then analyzed to check for surgical strategies. Broad guidelines for treatment could be derived from the results. More precise query settings, inclusion of bending films, and a larger database will enhance accurate retrieval and better decision making. Conclusion The CBIR system is an effective tool for accurate documentation and retrieval of scoliosis images. Broad guidelines for surgical strategies can be made from the postoperative images of the existing cases without adhering to any classification scheme.

  19. Finding and accessing diagrams in biomedical publications.

    Science.gov (United States)

    Kuhn, Tobias; Luong, ThaiBinh; Krauthammer, Michael

    2012-01-01

    Complex relationships in biomedical publications are often communicated by diagrams such as bar and line charts, which are a very effective way of summarizing and communicating multi-faceted data sets. Given the ever-increasing amount of published data, we argue that the precise retrieval of such diagrams is of great value for answering specific and otherwise hard-to-meet information needs. To this end, we demonstrate the use of advanced image processing and classification for identifying bar and line charts by the shape and relative location of the different image elements that make up the charts. With recall and precisions of close to 90% for the detection of relevant figures, we discuss the use of this technology in an existing biomedical image search engine, and outline how it enables new forms of literature queries over biomedical relationships that are represented in these charts.

  20. Content-based image retrieval using spatial layout information in brain tumor T1-weighted contrast-enhanced MR images.

    Science.gov (United States)

    Huang, Meiyan; Yang, Wei; Wu, Yao; Jiang, Jun; Gao, Yang; Chen, Yang; Feng, Qianjin; Chen, Wufan; Lu, Zhentai

    2014-01-01

    This study aims to develop content-based image retrieval (CBIR) system for the retrieval of T1-weighted contrast-enhanced MR (CE-MR) images of brain tumors. When a tumor region is fed to the CBIR system as a query, the system attempts to retrieve tumors of the same pathological category. The bag-of-visual-words (BoVW) model with partition learning is incorporated into the system to extract informative features for representing the image contents. Furthermore, a distance metric learning algorithm called the Rank Error-based Metric Learning (REML) is proposed to reduce the semantic gap between low-level visual features and high-level semantic concepts. The effectiveness of the proposed method is evaluated on a brain T1-weighted CE-MR dataset with three types of brain tumors (i.e., meningioma, glioma, and pituitary tumor). Using the BoVW model with partition learning, the mean average precision (mAP) of retrieval increases beyond 4.6% with the learned distance metrics compared with the spatial pyramid BoVW method. The distance metric learned by REML significantly outperforms three other existing distance metric learning methods in terms of mAP. The mAP of the CBIR system is as high as 91.8% using the proposed method, and the precision can reach 93.1% when the top 10 images are returned by the system. These preliminary results demonstrate that the proposed method is effective and feasible for the retrieval of brain tumors in T1-weighted CE-MR Images.

  1. Content-based image retrieval using spatial layout information in brain tumor T1-weighted contrast-enhanced MR images.

    Directory of Open Access Journals (Sweden)

    Meiyan Huang

    Full Text Available This study aims to develop content-based image retrieval (CBIR system for the retrieval of T1-weighted contrast-enhanced MR (CE-MR images of brain tumors. When a tumor region is fed to the CBIR system as a query, the system attempts to retrieve tumors of the same pathological category. The bag-of-visual-words (BoVW model with partition learning is incorporated into the system to extract informative features for representing the image contents. Furthermore, a distance metric learning algorithm called the Rank Error-based Metric Learning (REML is proposed to reduce the semantic gap between low-level visual features and high-level semantic concepts. The effectiveness of the proposed method is evaluated on a brain T1-weighted CE-MR dataset with three types of brain tumors (i.e., meningioma, glioma, and pituitary tumor. Using the BoVW model with partition learning, the mean average precision (mAP of retrieval increases beyond 4.6% with the learned distance metrics compared with the spatial pyramid BoVW method. The distance metric learned by REML significantly outperforms three other existing distance metric learning methods in terms of mAP. The mAP of the CBIR system is as high as 91.8% using the proposed method, and the precision can reach 93.1% when the top 10 images are returned by the system. These preliminary results demonstrate that the proposed method is effective and feasible for the retrieval of brain tumors in T1-weighted CE-MR Images.

  2. Towards brain-activity-controlled information retrieval: Decoding image relevance from MEG signals.

    Science.gov (United States)

    Kauppi, Jukka-Pekka; Kandemir, Melih; Saarinen, Veli-Matti; Hirvenkari, Lotta; Parkkonen, Lauri; Klami, Arto; Hari, Riitta; Kaski, Samuel

    2015-05-15

    We hypothesize that brain activity can be used to control future information retrieval systems. To this end, we conducted a feasibility study on predicting the relevance of visual objects from brain activity. We analyze both magnetoencephalographic (MEG) and gaze signals from nine subjects who were viewing image collages, a subset of which was relevant to a predetermined task. We report three findings: i) the relevance of an image a subject looks at can be decoded from MEG signals with performance significantly better than chance, ii) fusion of gaze-based and MEG-based classifiers significantly improves the prediction performance compared to using either signal alone, and iii) non-linear classification of the MEG signals using Gaussian process classifiers outperforms linear classification. These findings break new ground for building brain-activity-based interactive image retrieval systems, as well as for systems utilizing feedback both from brain activity and eye movements. Copyright © 2015 Elsevier Inc. All rights reserved.

  3. Neighborhood Discriminant Hashing for Large-Scale Image Retrieval.

    Science.gov (United States)

    Tang, Jinhui; Li, Zechao; Wang, Meng; Zhao, Ruizhen

    2015-09-01

    With the proliferation of large-scale community-contributed images, hashing-based approximate nearest neighbor search in huge databases has aroused considerable interest from the fields of computer vision and multimedia in recent years because of its computational and memory efficiency. In this paper, we propose a novel hashing method named neighborhood discriminant hashing (NDH) (for short) to implement approximate similarity search. Different from the previous work, we propose to learn a discriminant hashing function by exploiting local discriminative information, i.e., the labels of a sample can be inherited from the neighbor samples it selects. The hashing function is expected to be orthogonal to avoid redundancy in the learned hashing bits as much as possible, while an information theoretic regularization is jointly exploited using maximum entropy principle. As a consequence, the learned hashing function is compact and nonredundant among bits, while each bit is highly informative. Extensive experiments are carried out on four publicly available data sets and the comparison results demonstrate the outperforming performance of the proposed NDH method over state-of-the-art hashing techniques.

  4. TBIdoc: 3D content-based CT image retrieval system for traumatic brain injury

    Science.gov (United States)

    Li, Shimiao; Gong, Tianxia; Wang, Jie; Liu, Ruizhe; Tan, Chew Lim; Leong, Tze Yun; Pang, Boon Chuan; Lim, C. C. Tchoyoson; Lee, Cheng Kiang; Tian, Qi; Zhang, Zhuo

    2010-03-01

    Traumatic brain injury (TBI) is a major cause of death and disability. Computed Tomography (CT) scan is widely used in the diagnosis of TBI. Nowadays, large amount of TBI CT data is stacked in the hospital radiology department. Such data and the associated patient information contain valuable information for clinical diagnosis and outcome prediction. However, current hospital database system does not provide an efficient and intuitive tool for doctors to search out cases relevant to the current study case. In this paper, we present the TBIdoc system: a content-based image retrieval (CBIR) system which works on the TBI CT images. In this web-based system, user can query by uploading CT image slices from one study, retrieval result is a list of TBI cases ranked according to their 3D visual similarity to the query case. Specifically, cases of TBI CT images often present diffuse or focal lesions. In TBIdoc system, these pathological image features are represented as bin-based binary feature vectors. We use the Jaccard-Needham measure as the similarity measurement. Based on these, we propose a 3D similarity measure for computing the similarity score between two series of CT slices. nDCG is used to evaluate the system performance, which shows the system produces satisfactory retrieval results. The system is expected to improve the current hospital data management in TBI and to give better support for the clinical decision-making process. It may also contribute to the computer-aided education in TBI.

  5. Conjunctive patches subspace learning with side information for collaborative image retrieval.

    Science.gov (United States)

    Zhang, Lining; Wang, Lipo; Lin, Weisi

    2012-08-01

    Content-Based Image Retrieval (CBIR) has attracted substantial attention during the past few years for its potential practical applications to image management. A variety of Relevance Feedback (RF) schemes have been designed to bridge the semantic gap between the low-level visual features and the high-level semantic concepts for an image retrieval task. Various Collaborative Image Retrieval (CIR) schemes aim to utilize the user historical feedback log data with similar and dissimilar pairwise constraints to improve the performance of a CBIR system. However, existing subspace learning approaches with explicit label information cannot be applied for a CIR task, although the subspace learning techniques play a key role in various computer vision tasks, e.g., face recognition and image classification. In this paper, we propose a novel subspace learning framework, i.e., Conjunctive Patches Subspace Learning (CPSL) with side information, for learning an effective semantic subspace by exploiting the user historical feedback log data for a CIR task. The CPSL can effectively integrate the discriminative information of labeled log images, the geometrical information of labeled log images and the weakly similar information of unlabeled images together to learn a reliable subspace. We formally formulate this problem into a constrained optimization problem and then present a new subspace learning technique to exploit the user historical feedback log data. Extensive experiments on both synthetic data sets and a real-world image database demonstrate the effectiveness of the proposed scheme in improving the performance of a CBIR system by exploiting the user historical feedback log data.

  6. Uncertainties in cloud phase and optical thickness retrievals from the Earth Polychromatic Imaging Camera (EPIC).

    Science.gov (United States)

    Meyer, Kerry; Yang, Yuekui; Platnick, Steven

    2016-01-01

    This paper presents an investigation of the expected uncertainties of a single channel cloud optical thickness (COT) retrieval technique, as well as a simple cloud temperature threshold based thermodynamic phase approach, in support of the Deep Space Climate Observatory (DSCOVR) mission. DSCOVR cloud products will be derived from Earth Polychromatic Imaging Camera (EPIC) observations in the ultraviolet and visible spectra. Since EPIC is not equipped with a spectral channel in the shortwave or mid-wave infrared that is sensitive to cloud effective radius (CER), COT will be inferred from a single visible channel with the assumption of appropriate CER values for liquid and ice phase clouds. One month of Aqua MODIS daytime granules from April 2005 is selected for investigating cloud phase sensitivity, and a subset of these granules that has similar EPIC sun-view geometry is selected for investigating COT uncertainties. EPIC COT retrievals are simulated with the same algorithm as the operational MODIS cloud products (MOD06), except using fixed phase-dependent CER values. Uncertainty estimates are derived by comparing the single channel COT retrievals with the baseline bi-spectral MODIS retrievals. Results show that a single channel COT retrieval is feasible for EPIC. For ice clouds, single channel retrieval errors are minimal (< 2%) due to the particle size insensitivity of the assumed ice crystal (i.e., severely roughened aggregate of hexagonal columns) scattering properties at visible wavelengths, while for liquid clouds the error is mostly limited to within 10%, although for thin clouds (COT < 2) the error can be higher. Potential uncertainties in EPIC cloud masking and cloud temperature retrievals are not considered in this study.

  7. Retrieval of Sentence Sequences for an Image Stream via Coherence Recurrent Convolutional Networks.

    Science.gov (United States)

    Park, Cesc Chunseong; Kim, Youngjin; Kim, Gunhee

    2018-04-01

    We propose an approach for retrieving a sequence of natural sentences for an image stream. Since general users often take a series of pictures on their experiences, much online visual information exists in the form of image streams, for which it would better take into consideration of the whole image stream to produce natural language descriptions. While almost all previous studies have dealt with the relation between a single image and a single natural sentence, our work extends both input and output dimension to a sequence of images and a sequence of sentences. For retrieving a coherent flow of multiple sentences for a photo stream, we propose a multimodal neural architecture called coherence recurrent convolutional network (CRCN), which consists of convolutional neural networks, bidirectional long short-term memory (LSTM) networks, and an entity-based local coherence model. Our approach directly learns from vast user-generated resource of blog posts as text-image parallel training data. We collect more than 22 K unique blog posts with 170 K associated images for the travel topics of NYC, Disneyland , Australia, and Hawaii. We demonstrate that our approach outperforms other state-of-the-art image captioning methods for text sequence generation, using both quantitative measures and user studies via Amazon Mechanical Turk.

  8. Single-image phase retrieval using an edge illumination X-ray phase-contrast imaging setup

    Energy Technology Data Exchange (ETDEWEB)

    Diemoz, Paul C., E-mail: p.diemoz@ucl.ac.uk; Vittoria, Fabio A. [University College London, London WC1 E6BT (United Kingdom); Research Complex at Harwell, Oxford Harwell Campus, Didcot OX11 0FA (United Kingdom); Hagen, Charlotte K.; Endrizzi, Marco [University College London, London WC1 E6BT (United Kingdom); Coan, Paola [Ludwig-Maximilians-University, Munich 81377 (Germany); Ludwig-Maximilians-University, Garching 85748 (Germany); Brun, Emmanuel [Ludwig-Maximilians-University, Garching 85748 (Germany); European Synchrotron Radiation Facility, Grenoble 38043 (France); Wagner, Ulrich H.; Rau, Christoph [Diamond Light Source, Harwell Oxford Campus, Didcot OX11 0DE (United Kingdom); Robinson, Ian K. [Research Complex at Harwell, Oxford Harwell Campus, Didcot OX11 0FA (United Kingdom); London Centre for Nanotechnology, London WC1 H0AH (United Kingdom); Bravin, Alberto [European Synchrotron Radiation Facility, Grenoble 38043 (France); Olivo, Alessandro [University College London, London WC1 E6BT (United Kingdom); Research Complex at Harwell, Oxford Harwell Campus, Didcot OX11 0FA (United Kingdom)

    2015-06-25

    A method enabling the retrieval of thickness or projected electron density of a sample from a single input image is derived theoretically and successfully demonstrated on experimental data. A method is proposed which enables the retrieval of the thickness or of the projected electron density of a sample from a single input image acquired with an edge illumination phase-contrast imaging setup. The method assumes the case of a quasi-homogeneous sample, i.e. a sample with a constant ratio between the real and imaginary parts of its complex refractive index. Compared with current methods based on combining two edge illumination images acquired in different configurations of the setup, this new approach presents advantages in terms of simplicity of acquisition procedure and shorter data collection time, which are very important especially for applications such as computed tomography and dynamical imaging. Furthermore, the fact that phase information is directly extracted, instead of its derivative, can enable a simpler image interpretation and be beneficial for subsequent processing such as segmentation. The method is first theoretically derived and its conditions of applicability defined. Quantitative accuracy in the case of homogeneous objects as well as enhanced image quality for the imaging of complex biological samples are demonstrated through experiments at two synchrotron radiation facilities. The large range of applicability, the robustness against noise and the need for only one input image suggest a high potential for investigations in various research subjects.

  9. Bio-degradable highly fluorescent conjugated polymer nanoparticles for bio-medical imaging applications.

    Science.gov (United States)

    Repenko, Tatjana; Rix, Anne; Ludwanowski, Simon; Go, Dennis; Kiessling, Fabian; Lederle, Wiltrud; Kuehne, Alexander J C

    2017-09-07

    Conjugated polymer nanoparticles exhibit strong fluorescence and have been applied for biological fluorescence imaging in cell culture and in small animals. However, conjugated polymer particles are hydrophobic and often chemically inert materials with diameters ranging from below 50 nm to several microns. As such, conjugated polymer nanoparticles cannot be excreted through the renal system. This drawback has prevented their application for clinical bio-medical imaging. Here, we present fully conjugated polymer nanoparticles based on imidazole units. These nanoparticles can be bio-degraded by activated macrophages. Reactive oxygen species induce scission of the conjugated polymer backbone at the imidazole unit, leading to complete decomposition of the particles into soluble low molecular weight fragments. Furthermore, the nanoparticles can be surface functionalized for directed targeting. The approach opens a wide range of opportunities for conjugated polymer particles in the fields of medical imaging, drug-delivery, and theranostics.Conjugated polymer nanoparticles have been applied for biological fluorescence imaging in cell culture and in small animals, but cannot readily be excreted through the renal system. Here the authors show fully conjugated polymer nanoparticles based on imidazole units that can be bio-degraded by activated macrophages.

  10. Unsupervised symmetrical trademark image retrieval in soccer telecast using wavelet energy and quadtree decomposition

    Science.gov (United States)

    Ong, Swee Khai; Lim, Wee Keong; Soo, Wooi King

    2013-04-01

    Trademark, a distinctive symbol, is used to distinguish products or services provided by a particular person, group or organization from other similar entries. As trademark represents the reputation and credit standing of the owner, it is important to differentiate one trademark from another. Many methods have been proposed to identify, classify and retrieve trademarks. However, most methods required features database and sample sets for training prior to recognition and retrieval process. In this paper, a new feature on wavelet coefficients, the localized wavelet energy, is introduced to extract features of trademarks. With this, unsupervised content-based symmetrical trademark image retrieval is proposed without the database and prior training set. The feature analysis is done by an integration of the proposed localized wavelet energy and quadtree decomposed regional symmetrical vector. The proposed framework eradicates the dependence on query database and human participation during the retrieval process. In this paper, trademarks for soccer games sponsors are the intended trademark category. Video frames from soccer telecast are extracted and processed for this study. Reasonably good localization and retrieval results on certain categories of trademarks are achieved. A distinctive symbol is used to distinguish products or services provided by a particular person, group or organization from other similar entries.

  11. Hurricane Imaging Radiometer (HIRAD) Wind Speed Retrievals and Assessment Using Dropsondes

    Science.gov (United States)

    Cecil, Daniel J.; Biswas, Sayak K.

    2018-01-01

    The Hurricane Imaging Radiometer (HIRAD) is an experimental C-band passive microwave radiometer designed to map the horizontal structure of surface wind speed fields in hurricanes. New data processing and customized retrieval approaches were developed after the 2015 Tropical Cyclone Intensity (TCI) experiment, which featured flights over Hurricanes Patricia, Joaquin, Marty, and the remnants of Tropical Storm Erika. These new approaches produced maps of surface wind speed that looked more realistic than those from previous campaigns. Dropsondes from the High Definition Sounding System (HDSS) that was flown with HIRAD on a WB-57 high altitude aircraft in TCI were used to assess the quality of the HIRAD wind speed retrievals. The root mean square difference between HIRAD-retrieved surface wind speeds and dropsonde-estimated surface wind speeds was 6.0 meters per second. The largest differences between HIRAD and dropsonde winds were from data points where storm motion during dropsonde descent compromised the validity of the comparisons. Accounting for this and for uncertainty in the dropsonde measurements themselves, we estimate the root mean square error for the HIRAD retrievals as around 4.7 meters per second. Prior to the 2015 TCI experiment, HIRAD had previously flown on the WB-57 for missions across Hurricanes Gonzalo (2014), Earl (2010), and Karl (2010). Configuration of the instrument was not identical to the 2015 flights, but the methods devised after the 2015 flights may be applied to that previous data in an attempt to improve retrievals from those cases.

  12. Challenges and opportunities in clinical translation of biomedical optical spectroscopy and imaging

    Science.gov (United States)

    Wilson, Brian C.; Jermyn, Michael; Leblond, Frederic

    2018-03-01

    Medical devices face many hurdles before they enter routine clinical practice to address unmet clinical needs. This is also the case for biomedical optical spectroscopy and imaging systems that are used here to illustrate the opportunities and challenges involved. Following initial concept, stages in clinical translation include instrument development, preclinical testing, clinical prototyping, clinical trials, prototype-to-product conversion, regulatory approval, commercialization, and finally clinical adoption and dissemination, all in the face of potentially competing technologies. Optical technologies face additional challenges from their being extremely diverse, often targeting entirely different diseases and having orders-of-magnitude differences in resolution and tissue penetration. However, these technologies can potentially address a wide variety of unmet clinical needs since they provide rich intrinsic biochemical and structural information, have high sensitivity and specificity for disease detection and localization, and are practical, safe (minimally invasive, nonionizing), and relatively affordable.

  13. Functional imaging of the semantic system: retrieval of sensory-experienced and verbally learned knowledge.

    Science.gov (United States)

    Noppeney, Uta; Price, Cathy J

    2003-01-01

    This paper considers how functional neuro-imaging can be used to investigate the organization of the semantic system and the limitations associated with this technique. The majority of the functional imaging studies of the semantic system have looked for divisions by varying stimulus category. These studies have led to divergent results and no clear anatomical hypotheses have emerged to account for the dissociations seen in behavioral studies. Only a few functional imaging studies have used task as a variable to differentiate the neural correlates of semantic features more directly. We extend these findings by presenting a new study that contrasts tasks that differentially weight sensory (color and taste) and verbally learned (origin) semantic features. Irrespective of the type of semantic feature retrieved, a common semantic system was activated as demonstrated in many previous studies. In addition, the retrieval of verbally learned, but not sensory-experienced, features enhanced activation in medial and lateral posterior parietal areas. We attribute these "verbally learned" effects to differences in retrieval strategy and conclude that evidence for segregation of semantic features at an anatomical level remains weak. We believe that functional imaging has the potential to increase our understanding of the neuronal infrastructure that sustains semantic processing but progress may require multiple experiments until a consistent explanatory framework emerges.

  14. Hurricane Imaging Radiometer Wind Speed and Rain Rate Retrievals during the 2010 GRIP Flight Experiment

    Science.gov (United States)

    Sahawneh, Saleem; Farrar, Spencer; Johnson, James; Jones, W. Linwood; Roberts, Jason; Biswas, Sayak; Cecil, Daniel

    2014-01-01

    Microwave remote sensing observations of hurricanes, from NOAA and USAF hurricane surveillance aircraft, provide vital data for hurricane research and operations, for forecasting the intensity and track of tropical storms. The current operational standard for hurricane wind speed and rain rate measurements is the Stepped Frequency Microwave Radiometer (SFMR), which is a nadir viewing passive microwave airborne remote sensor. The Hurricane Imaging Radiometer, HIRAD, will extend the nadir viewing SFMR capability to provide wide swath images of wind speed and rain rate, while flying on a high altitude aircraft. HIRAD was first flown in the Genesis and Rapid Intensification Processes, GRIP, NASA hurricane field experiment in 2010. This paper reports on geophysical retrieval results and provides hurricane images from GRIP flights. An overview of the HIRAD instrument and the radiative transfer theory based, wind speed/rain rate retrieval algorithm is included. Results are presented for hurricane wind speed and rain rate for Earl and Karl, with comparison to collocated SFMR retrievals and WP3D Fuselage Radar images for validation purposes.

  15. Deep Hashing Based Fusing Index Method for Large-Scale Image Retrieval

    Directory of Open Access Journals (Sweden)

    Lijuan Duan

    2017-01-01

    Full Text Available Hashing has been widely deployed to perform the Approximate Nearest Neighbor (ANN search for the large-scale image retrieval to solve the problem of storage and retrieval efficiency. Recently, deep hashing methods have been proposed to perform the simultaneous feature learning and the hash code learning with deep neural networks. Even though deep hashing has shown the better performance than traditional hashing methods with handcrafted features, the learned compact hash code from one deep hashing network may not provide the full representation of an image. In this paper, we propose a novel hashing indexing method, called the Deep Hashing based Fusing Index (DHFI, to generate a more compact hash code which has stronger expression ability and distinction capability. In our method, we train two different architecture’s deep hashing subnetworks and fuse the hash codes generated by the two subnetworks together to unify images. Experiments on two real datasets show that our method can outperform state-of-the-art image retrieval applications.

  16. A boosting framework for visuality-preserving distance metric learning and its application to medical image retrieval.

    Science.gov (United States)

    Yang, Liu; Jin, Rong; Mummert, Lily; Sukthankar, Rahul; Goode, Adam; Zheng, Bin; Hoi, Steven C H; Satyanarayanan, Mahadev

    2010-01-01

    Similarity measurement is a critical component in content-based image retrieval systems, and learning a good distance metric can significantly improve retrieval performance. However, despite extensive study, there are several major shortcomings with the existing approaches for distance metric learning that can significantly affect their application to medical image retrieval. In particular, "similarity" can mean very different things in image retrieval: resemblance in visual appearance (e.g., two images that look like one another) or similarity in semantic annotation (e.g., two images of tumors that look quite different yet are both malignant). Current approaches for distance metric learning typically address only one goal without consideration of the other. This is problematic for medical image retrieval where the goal is to assist doctors in decision making. In these applications, given a query image, the goal is to retrieve similar images from a reference library whose semantic annotations could provide the medical professional with greater insight into the possible interpretations of the query image. If the system were to retrieve images that did not look like the query, then users would be less likely to trust the system; on the other hand, retrieving images that appear superficially similar to the query but are semantically unrelated is undesirable because that could lead users toward an incorrect diagnosis. Hence, learning a distance metric that preserves both visual resemblance and semantic similarity is important. We emphasize that, although our study is focused on medical image retrieval, the problem addressed in this work is critical to many image retrieval systems. We present a boosting framework for distance metric learning that aims to preserve both visual and semantic similarities. The boosting framework first learns a binary representation using side information, in the form of labeled pairs, and then computes the distance as a weighted Hamming

  17. Psychophysical studies of the performance of an image database retrieval system

    Science.gov (United States)

    Papathomas, Thomas V.; Conway, Tiffany E.; Cox, Ingemar J.; Ghosn, Joumana; Miller, Matt L.; Minka, Thomas P.; Yianilos, Peter N.

    1998-07-01

    We describe psychophysical experiments conducted to study PicHunter, a content-based image retrieval (CBIR) system. Experiment 1 studies the importance of using (a) semantic information, (2) memory of earlier input and (3) relative, rather than absolute, judgements of image similarity. The target testing paradigm is used in which a user must search for an image identical to a target. We find that the best performance comes from a version of PicHunter that uses only semantic cues, with memory and relative similarity judgements. Second best is use of both pictorial and semantic cues, with memory and relative similarity judgements. Most reports of CBIR systems provide only qualitative measures of performance based on how similar retrieved images are to a target. Experiment 2 puts PicHunter into this context with a more rigorous test. We first establish a baseline for our database by measuring the time required to find an image that is similar to a target when the images are presented in random order. Although PicHunter's performance is measurably better than this, the test is weak because even random presentation of images yields reasonably short search times. This casts doubt on the strength of results given in other reports where no baseline is established.

  18. Performance of a novel wafer scale CMOS active pixel sensor for bio-medical imaging

    International Nuclear Information System (INIS)

    Esposito, M; Evans, P M; Wells, K; Anaxagoras, T; Konstantinidis, A C; Zheng, Y; Speller, R D; Allinson, N M

    2014-01-01

    Recently CMOS active pixels sensors (APSs) have become a valuable alternative to amorphous silicon and selenium flat panel imagers (FPIs) in bio-medical imaging applications. CMOS APSs can now be scaled up to the standard 20 cm diameter wafer size by means of a reticle stitching block process. However, despite wafer scale CMOS APS being monolithic, sources of non-uniformity of response and regional variations can persist representing a significant challenge for wafer scale sensor response. Non-uniformity of stitched sensors can arise from a number of factors related to the manufacturing process, including variation of amplification, variation between readout components, wafer defects and process variations across the wafer due to manufacturing processes. This paper reports on an investigation into the spatial non-uniformity and regional variations of a wafer scale stitched CMOS APS. For the first time a per-pixel analysis of the electro-optical performance of a wafer CMOS APS is presented, to address inhomogeneity issues arising from the stitching techniques used to manufacture wafer scale sensors. A complete model of the signal generation in the pixel array has been provided and proved capable of accounting for noise and gain variations across the pixel array. This novel analysis leads to readout noise and conversion gain being evaluated at pixel level, stitching block level and in regions of interest, resulting in a coefficient of variation ⩽1.9%. The uniformity of the image quality performance has been further investigated in a typical x-ray application, i.e. mammography, showing a uniformity in terms of CNR among the highest when compared with mammography detectors commonly used in clinical practice. Finally, in order to compare the detection capability of this novel APS with the technology currently used (i.e. FPIs), theoretical evaluation of the detection quantum efficiency (DQE) at zero-frequency has been performed, resulting in a higher DQE for this

  19. PREFACE: 2nd International Conference and Young Scientist School ''Magnetic resonance imaging in biomedical research''

    Science.gov (United States)

    Naumova, A. V.; Khodanovich, M. Y.; Yarnykh, V. L.

    2016-02-01

    The Second International Conference and Young Scientist School ''Magnetic resonance imaging in biomedical research'' was held on the campus of the National Research Tomsk State University (Tomsk, Russia) on September 7-9, 2015. The conference was focused on magnetic resonance imaging (MRI) applications for biomedical research. The main goal was to bring together basic scientists, clinical researchers and developers of new MRI techniques to bridge the gap between clinical/research needs and advanced technological solutions. The conference fostered research and development in basic and clinical MR science and its application to health care. It also had an educational purpose to promote understanding of cutting-edge MR developments. The conference provided an opportunity for researchers and clinicians to present their recent theoretical developments, practical applications, and to discuss unsolved problems. The program of the conference was divided into three main topics. First day of the conference was devoted to educational lectures on the fundamentals of MRI physics and image acquisition/reconstruction techniques, including recent developments in quantitative MRI. The second day was focused on developments and applications of new contrast agents. Multinuclear and spectroscopic acquisitions as well as functional MRI were presented during the third day of the conference. We would like to highlight the main developments presented at the conference and introduce the prominent speakers. The keynote speaker of the conference Dr. Vasily Yarnykh (University of Washington, Seattle, USA) presented a recently developed MRI method, macromolecular proton fraction (MPF) mapping, as a unique tool for modifying image contrast and a unique tool for quantification of the myelin content in neural tissues. Professor Yury Pirogov (Lomonosov Moscow State University) described development of new fluorocarbon compounds and applications for biomedicine. Drs. Julia Velikina and Alexey

  20. Performance of a novel wafer scale CMOS active pixel sensor for bio-medical imaging.

    Science.gov (United States)

    Esposito, M; Anaxagoras, T; Konstantinidis, A C; Zheng, Y; Speller, R D; Evans, P M; Allinson, N M; Wells, K

    2014-07-07

    Recently CMOS active pixels sensors (APSs) have become a valuable alternative to amorphous silicon and selenium flat panel imagers (FPIs) in bio-medical imaging applications. CMOS APSs can now be scaled up to the standard 20 cm diameter wafer size by means of a reticle stitching block process. However, despite wafer scale CMOS APS being monolithic, sources of non-uniformity of response and regional variations can persist representing a significant challenge for wafer scale sensor response. Non-uniformity of stitched sensors can arise from a number of factors related to the manufacturing process, including variation of amplification, variation between readout components, wafer defects and process variations across the wafer due to manufacturing processes. This paper reports on an investigation into the spatial non-uniformity and regional variations of a wafer scale stitched CMOS APS. For the first time a per-pixel analysis of the electro-optical performance of a wafer CMOS APS is presented, to address inhomogeneity issues arising from the stitching techniques used to manufacture wafer scale sensors. A complete model of the signal generation in the pixel array has been provided and proved capable of accounting for noise and gain variations across the pixel array. This novel analysis leads to readout noise and conversion gain being evaluated at pixel level, stitching block level and in regions of interest, resulting in a coefficient of variation ⩽1.9%. The uniformity of the image quality performance has been further investigated in a typical x-ray application, i.e. mammography, showing a uniformity in terms of CNR among the highest when compared with mammography detectors commonly used in clinical practice. Finally, in order to compare the detection capability of this novel APS with the technology currently used (i.e. FPIs), theoretical evaluation of the detection quantum efficiency (DQE) at zero-frequency has been performed, resulting in a higher DQE for this

  1. Coincident Aerosol and H2O Retrievals versus HSI Imager Field Campaign ReportH2O Retrievals versus HSI Imager Field Campaign Report

    Energy Technology Data Exchange (ETDEWEB)

    Anderson, Gail P. [National Oceanic and Atmospheric Administration (NOAA), Washington, DC (United States); Cipar, John [Air Force Research Lab. (AFRL), Wright-Patterson AFB, OH (United States); Armstrong, Peter S. [Air Force Research Lab. (AFRL), Wright-Patterson AFB, OH (United States); van den Bosch, J. [Air Force Research Lab. (AFRL), Wright-Patterson AFB, OH (United States)

    2016-05-01

    Two spectrally calibrated tarpaulins (tarps) were co-located at a fixed Global Positioning System (GPS) position on the gravel antenna field at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility’s Southern Great Plains (SGP) site. Their placement was timed to coincide with the overflight of a new hyperspectral imaging satellite. The intention was to provide an analysis of the data obtained, including the measured and retrieved spectral albedos for the calibration tarps. Subsequently, a full suite of retrieved values of H2O column, and the aerosol overburden, were to be compared to those determined by alternate SGP ground truth assets. To the extent possible, the down-looking cloud images would be assessed against the all-sky images. Because cloud contamination above a certain level precludes the inversion processing of the satellite data, coupled with infrequent targeting opportunities, clear-sky conditions were imposed. The SGP site was chosen not only as a target of opportunity for satellite validation, but as perhaps the best coincident field measurement site, as established by DOE’s ARM Facility. The satellite team had every expectation of using the information obtained from the SGP to improve the inversion products for all subsequent satellite images, including the cloud and radiative models and parameterizations and, thereby, the performance assessment for subsequent and historic image collections. Coordinating with the SGP onsite team, four visits, all in 2009, to the Central Facility occurred: • June 6-8 (successful exploratory visit to plan tarp placements, etc.) • July 18-24 (canceled because of forecast for heavy clouds) • Sep 9-12 (ground tarps placed, onset of clouds) • Nov 7-9 (visit ultimately canceled because of weather predictions). As noted, in each instance, any significant overcast prediction precluded image collection from the satellite. Given the long task-scheduling procedures

  2. Optical image encryption using password key based on phase retrieval algorithm

    Science.gov (United States)

    Zhao, Tieyu; Ran, Qiwen; Yuan, Lin; Chi, Yingying; Ma, Jing

    2016-04-01

    A novel optical image encryption system is proposed using password key based on phase retrieval algorithm (PRA). In the encryption process, a shared image is taken as a symmetric key and the plaintext is encoded into the phase-only mask based on the iterative PRA. The linear relationship between the plaintext and ciphertext is broken using the password key, which can resist the known plaintext attack. The symmetric key and the retrieved phase are imported into the input plane and Fourier plane of 4f system during the decryption, respectively, so as to obtain the plaintext on the CCD. Finally, we analyse the key space of the password key, and the results show that the proposed scheme can resist a brute force attack due to the flexibility of the password key.

  3. Development of an Aerosol Opacity Retrieval Algorithm for Use with Multi-Angle Land Surface Images

    Science.gov (United States)

    Diner, D.; Paradise, S.; Martonchik, J.

    1994-01-01

    In 1998, the Multi-angle Imaging SpectroRadiometer (MISR) will fly aboard the EOS-AM1 spacecraft. MISR will enable unique methods for retrieving the properties of atmospheric aerosols, by providing global imagery of the Earth at nine viewing angles in four visible and near-IR spectral bands. As part of the MISR algorithm development, theoretical methods of analyzing multi-angle, multi-spectral data are being tested using images acquired by the airborne Advanced Solid-State Array Spectroradiometer (ASAS). In this paper we derive a method to be used over land surfaces for retrieving the change in opacity between spectral bands, which can then be used in conjunction with an aerosol model to derive a bound on absolute opacity.

  4. Synthesis and Ligand-Exchange Reactions of a Tri-Tungsten Cluster with Applications in Biomedical Imaging

    Science.gov (United States)

    Noey, Elizabeth; Curtis, Jeff C.; Tam, Sylvia; Pham, David M.; Jones, Ella F.

    2011-01-01

    In this experiment students are exposed to concepts in inorganic synthesis and various spectroscopies as applied to a tri-tungsten cluster with applications in biomedical imaging. The tungsten-acetate cluster, Na[W[superscript 3](mu-O)[subscript 2](CH[superscript 3]COO)[superscript 9

  5. Retrieval of spruce leaf chlorophyll content from airborne image data using continuum removal and radiative transfer

    Czech Academy of Sciences Publication Activity Database

    Malenovský, Z.; Homolová, L.; Zurita-Milla, R.; Lukeš, Petr; Kaplan, Věroslav; Hanuš, Jan; Gastellu-Etchegory, J.P.; Schaepman, M.E.

    2013-01-01

    Roč. 131, APR (2013), s. 85-102 ISSN 0034-4257 R&D Projects: GA MŠk(CZ) ED1.1.00/02.0073; GA MŠk(CZ) LM2010007 Institutional support: RVO:67179843 Keywords : Chlorophyll retrieval * Imaging spectroscopy * Continuum removal * Radiative transfer * PROSPECT * DART * Optical indices * Norway spruce * High spatial resolution * AISA Subject RIV: EH - Ecology, Behaviour Impact factor: 4.769, year: 2013

  6. Semantics-Based Intelligent Indexing and Retrieval of Digital Images - A Case Study

    Science.gov (United States)

    Osman, Taha; Thakker, Dhavalkumar; Schaefer, Gerald

    The proliferation of digital media has led to a huge interest in classifying and indexing media objects for generic search and usage. In particular, we are witnessing colossal growth in digital image repositories that are difficult to navigate using free-text search mechanisms, which often return inaccurate matches as they typically rely on statistical analysis of query keyword recurrence in the image annotation or surrounding text. In this chapter we present a semantically enabled image annotation and retrieval engine that is designed to satisfy the requirements of commercial image collections market in terms of both accuracy and efficiency of the retrieval process. Our search engine relies on methodically structured ontologies for image annotation, thus allowing for more intelligent reasoning about the image content and subsequently obtaining a more accurate set of results and a richer set of alternatives matchmaking the original query. We also show how our well-analysed and designed domain ontology contributes to the implicit expansion of user queries as well as presenting our initial thoughts on exploiting lexical databases for explicit semantic-based query expansion.

  7. Extraction of Lesion-Partitioned Features and Retrieval of Contrast-Enhanced Liver Images

    Directory of Open Access Journals (Sweden)

    Mei Yu

    2012-01-01

    Full Text Available The most critical step in grayscale medical image retrieval systems is feature extraction. Understanding the interrelatedness between the characteristics of lesion images and corresponding imaging features is crucial for image training, as well as for features extraction. A feature-extraction algorithm is developed based on different imaging properties of lesions and on the discrepancy in density between the lesions and their surrounding normal liver tissues in triple-phase contrast-enhanced computed tomographic (CT scans. The algorithm includes mainly two processes: (1 distance transformation, which is used to divide the lesion into distinct regions and represents the spatial structure distribution and (2 representation using bag of visual words (BoW based on regions. The evaluation of this system based on the proposed feature extraction algorithm shows excellent retrieval results for three types of liver lesions visible on triple-phase scans CT images. The results of the proposed feature extraction algorithm show that although single-phase scans achieve the average precision of 81.9%, 80.8%, and 70.2%, dual- and triple-phase scans achieve 86.3% and 88.0%.

  8. Region-Based Image Retrieval Using an Object Ontology and Relevance Feedback

    Directory of Open Access Journals (Sweden)

    Kompatsiaris Ioannis

    2004-01-01

    Full Text Available An image retrieval methodology suited for search in large collections of heterogeneous images is presented. The proposed approach employs a fully unsupervised segmentation algorithm to divide images into regions and endow the indexing and retrieval system with content-based functionalities. Low-level descriptors for the color, position, size, and shape of each region are subsequently extracted. These arithmetic descriptors are automatically associated with appropriate qualitative intermediate-level descriptors, which form a simple vocabulary termed object ontology. The object ontology is used to allow the qualitative definition of the high-level concepts the user queries for (semantic objects, each represented by a keyword and their relations in a human-centered fashion. When querying for a specific semantic object (or objects, the intermediate-level descriptor values associated with both the semantic object and all image regions in the collection are initially compared, resulting in the rejection of most image regions as irrelevant. Following that, a relevance feedback mechanism, based on support vector machines and using the low-level descriptors, is invoked to rank the remaining potentially relevant image regions and produce the final query results. Experimental results and comparisons demonstrate, in practice, the effectiveness of our approach.

  9. Hybrid phase retrieval algorithm for solving the twin image problem in in-line digital holography

    Science.gov (United States)

    Zhao, Jie; Wang, Dayong; Zhang, Fucai; Wang, Yunxin

    2010-10-01

    For the reconstruction in the in-line digital holography, there are three terms overlapping with each other on the image plane, named the zero order term, the real image and the twin image respectively. The unwanted twin image degrades the real image seriously. A hybrid phase retrieval algorithm is presented to address this problem, which combines the advantages of two popular phase retrieval algorithms. One is the improved version of the universal iterative algorithm (UIA), called the phase flipping-based UIA (PFB-UIA). The key point of this algorithm is to flip the phase of the object iteratively. It is proved that the PFB-UIA is able to find the support of the complicated object. Another one is the Fienup algorithm, which is a kind of well-developed algorithm and uses the support of the object as the constraint among the iteration procedure. Thus, by following the Fienup algorithm immediately after the PFB-UIA, it is possible to produce the amplitude and the phase distributions of the object with high fidelity. The primary simulated results showed that the proposed algorithm is powerful for solving the twin image problem in the in-line digital holography.

  10. Phase retrieval for X-ray in-line phase contrast imaging

    International Nuclear Information System (INIS)

    Scattarella, F.; Bellotti, R.; Tangaro, S.; Gargano, G.; Giannini, C.

    2011-01-01

    A review article about phase retrieval problem in X-ray phase contrast imaging is presented. A simple theoretical framework of Fresnel diffraction imaging by X-rays is introduced. A review of the most important methods for phase retrieval in free-propagation-based X-ray imaging and a new method developed by our collaboration are shown. The proposed algorithm, Combined Mixed Approach (CMA) is based on a mixed transfer function and transport of intensity approach, and it requires at most an initial approximate estimate of the average phase shift introduced by the object as prior knowledge. The accuracy with which this initial estimate is known determines the convenience speed of algorithm. The new proposed algorithm is based on the retrieval of both the object phase and its complex conjugate. The results obtained by the algorithm on simulated data have shown that the obtained reconstructed phase maps are characterized by particularly low normalized mean square errors. The algorithm was also tested on noisy experimental phase contrast data, showing a good efficiency in recovering phase information and enhancing the visibility of details inside soft tissues.

  11. SOFTWARE FOR REGIONS OF INTEREST RETRIEVAL ON MEDICAL 3D IMAGES

    Directory of Open Access Journals (Sweden)

    G. G. Stromov

    2014-01-01

    Full Text Available Background. Implementation of software for areas of interest retrieval in 3D medical images is described in this article. It has been tested against large volume of model MRIs.Material and methods. We tested software against normal and pathological (severe multiple sclerosis model MRIs from tge BrainWeb resource. Technological stack is based on open-source cross-platform solutions. We implemented storage system on Maria DB (an open-sourced fork of MySQL with P/SQL extensions. Python 2.7 scripting was used for automatization of extract-transform-load operations. The computational core is written on Java 7 with Spring framework 3. MongoDB was used as a cache in the cluster of workstations. Maven 3 was chosen as a dependency manager and build system, the project is hosted at Github.Results. As testing on SSMU's LAN has showed, software has been developed is quite efficiently retrieves ROIs are matching for the morphological substratum on pathological MRIs.Conclusion. Automation of a diagnostic process using medical imaging allows to level down the subjective component in decision making and increase the availability of hi-tech medicine. Software has shown in the article is a complex solution for ROI retrieving and segmentation process on model medical images in full-automated mode.We would like to thank Robert Vincent for great help with consulting of usage the BrainWeb resource.

  12. STUDY COMPARISON OF SVM-, K-NN- AND BACKPROPAGATION-BASED CLASSIFIER FOR IMAGE RETRIEVAL

    Directory of Open Access Journals (Sweden)

    Muhammad Athoillah

    2015-03-01

    Full Text Available Classification is a method for compiling data systematically according to the rules that have been set previously. In recent years classification method has been proven to help many people’s work, such as image classification, medical biology, traffic light, text classification etc. There are many methods to solve classification problem. This variation method makes the researchers find it difficult to determine which method is best for a problem. This framework is aimed to compare the ability of classification methods, such as Support Vector Machine (SVM, K-Nearest Neighbor (K-NN, and Backpropagation, especially in study cases of image retrieval with five category of image dataset. The result shows that K-NN has the best average result in accuracy with 82%. It is also the fastest in average computation time with 17,99 second during retrieve session for all categories class. The Backpropagation, however, is the slowest among three of them. In average it needed 883 second for training session and 41,7 second for retrieve session.

  13. Phase Retrieval Using a Genetic Algorithm on the Systematic Image-Based Optical Alignment Testbed

    Science.gov (United States)

    Taylor, Jaime R.

    2003-01-01

    NASA s Marshall Space Flight Center s Systematic Image-Based Optical Alignment (SIBOA) Testbed was developed to test phase retrieval algorithms and hardware techniques. Individuals working with the facility developed the idea of implementing phase retrieval by breaking the determination of the tip/tilt of each mirror apart from the piston motion (or translation) of each mirror. Presented in this report is an algorithm that determines the optimal phase correction associated only with the piston motion of the mirrors. A description of the Phase Retrieval problem is first presented. The Systematic Image-Based Optical Alignment (SIBOA) Testbeb is then described. A Discrete Fourier Transform (DFT) is necessary to transfer the incoming wavefront (or estimate of phase error) into the spatial frequency domain to compare it with the image. A method for reducing the DFT to seven scalar/matrix multiplications is presented. A genetic algorithm is then used to search for the phase error. The results of this new algorithm on a test problem are presented.

  14. Quantitative imaging of magnetic nanoparticles by magneto-relaxometric tomography for biomedical applications

    International Nuclear Information System (INIS)

    Liebl, Maik

    2016-01-01

    Current biomedical research focuses on the development of novel biomedical applications based on magnetic nanoparticles (MNPs), e.g. for local cancer treatment. These therapy approaches employ MNPs as remotely controlled drug carriers or local heat generators. Since location and quantity of MNPs determine drug enrichment and heat production, quantitative knowledge of the MNP distribution inside a body is essential for the development and success of these therapies. Magnetorelaxometry (MRX) is capable to provide such quantitative information based on the specific response of the MNPs after switching-off an applied magnetic field. Applying a uniform (homogeneous) magnetic field to a MNP distribution and measuring the MNP response by multiple sensors at different locations allows for spatially resolved MNP quantification. However, to reconstruct the MNP distribution from this spatially resolved MRX data, an ill posed inverse problem has to be solved. So far, the solution of this problem was stabilized incorporating a-priori knowledge in the forward model, e.g. by setting priors on the vertical position of the distribution using a 2D reconstruction grid or setting priors on the number and geometry of the MNP sources inside the body. MRX tomography represents a novel approach for quantitative 3D imaging of MNPs, where the inverse solution is stabilized by a series of MRX measurements. In MRX tomography, only parts of the MNP distribution are sequentially magnetized by the use of inhomogeneous magnetic fields. Each magnetizing is followed by detection of the response of the corresponding part of the distribution by multiple sensors. The 3D reconstruction of the MNP distribution is then accomplished by a common evaluation of the distinct MRX measurement series. In this thesis the first experimental setup for MRX tomography was developed for quantitative 3D imaging of biomedical MNP distributions. It is based on a multi-channel magnetizing unit which has been engineered to

  15. apART: system for the acquisition, processing, archiving, and retrieval of digital images in an open, distributed imaging environment

    Science.gov (United States)

    Schneider, Uwe; Strack, Ruediger

    1992-04-01

    apART reflects the structure of an open, distributed environment. According to the general trend in the area of imaging, network-capable, general purpose workstations with capabilities of open system image communication and image input are used. Several heterogeneous components like CCD cameras, slide scanners, and image archives can be accessed. The system is driven by an object-oriented user interface where devices (image sources and destinations), operators (derived from a commercial image processing library), and images (of different data types) are managed and presented uniformly to the user. Browsing mechanisms are used to traverse devices, operators, and images. An audit trail mechanism is offered to record interactive operations on low-resolution image derivatives. These operations are processed off-line on the original image. Thus, the processing of extremely high-resolution raster images is possible, and the performance of resolution dependent operations is enhanced significantly during interaction. An object-oriented database system (APRIL), which can be browsed, is integrated into the system. Attribute retrieval is supported by the user interface. Other essential features of the system include: implementation on top of the X Window System (X11R4) and the OSF/Motif widget set; a SUN4 general purpose workstation, inclusive ethernet, magneto optical disc, etc., as the hardware platform for the user interface; complete graphical-interactive parametrization of all operators; support of different image interchange formats (GIF, TIFF, IIF, etc.); consideration of current IPI standard activities within ISO/IEC for further refinement and extensions.

  16. Finding and Accessing Diagrams in Biomedical Publications

    OpenAIRE

    Kuhn, Tobias; Luong, ThaiBinh; Krauthammer, Michael

    2012-01-01

    Complex relationships in biomedical publications are often communicated by diagrams such as bar and line charts, which are a very effective way of summarizing and communicating multi-faceted data sets. Given the ever-increasing amount of published data, we argue that the precise retrieval of such diagrams is of great value for answering specific and otherwise hard-to-meet information needs. To this end, we demonstrate the use of advanced image processing and classification for identifying bar...

  17. Computer-aided diagnosis of mammographic masses using geometric verification-based image retrieval

    Science.gov (United States)

    Li, Qingliang; Shi, Weili; Yang, Huamin; Zhang, Huimao; Li, Guoxin; Chen, Tao; Mori, Kensaku; Jiang, Zhengang

    2017-03-01

    Computer-Aided Diagnosis of masses in mammograms is an important indicator of breast cancer. The use of retrieval systems in breast examination is increasing gradually. In this respect, the method of exploiting the vocabulary tree framework and the inverted file in the mammographic masse retrieval have been proved high accuracy and excellent scalability. However it just considered the features in each image as a visual word and had ignored the spatial configurations of features. It greatly affect the retrieval performance. To overcome this drawback, we introduce the geometric verification method to retrieval in mammographic masses. First of all, we obtain corresponding match features based on the vocabulary tree framework and the inverted file. After that, we grasps the main point of local similarity characteristic of deformations in the local regions by constructing the circle regions of corresponding pairs. Meanwhile we segment the circle to express the geometric relationship of local matches in the area and generate the spatial encoding strictly. Finally we judge whether the matched features are correct or not, based on verifying the all spatial encoding are whether satisfied the geometric consistency. Experiments show the promising results of our approach.

  18. Target-oriented retrieval of subsurface wave fields - Pushing the resolution limits in seismic imaging

    Science.gov (United States)

    Vasconcelos, Ivan; Ozmen, Neslihan; van der Neut, Joost; Cui, Tianci

    2017-04-01

    Travelling wide-bandwidth seismic waves have long been used as a primary tool in exploration seismology because they can probe the subsurface over large distances, while retaining relatively high spatial resolution. The well-known Born resolution limit often seems to be the lower bound on spatial imaging resolution in real life examples. In practice, data acquisition cost, time constraints and other factors can worsen the resolution achieved by wavefield imaging. Could we obtain images whose resolution beats the Born limits? Would it be practical to achieve it, and what are we missing today to achieve this? In this talk, we will cover aspects of linear and nonlinear seismic imaging to understand elements that play a role in obtaining "super-resolved" seismic images. New redatuming techniques, such as the Marchenko method, enable the retrieval of subsurface fields that include multiple scattering interactions, while requiring relatively little knowledge of model parameters. Together with new concepts in imaging, such as Target-Enclosing Extended Images, these new redatuming methods enable new targeted imaging frameworks. We will make a case as to why target-oriented approaches to reconstructing subsurface-domain wavefields from surface data may help in increasing the resolving power of seismic imaging, and in pushing the limits on parameter estimation. We will illustrate this using a field data example. Finally, we will draw connections between seismic and other imaging modalities, and discuss how this framework could be put to use in other applications

  19. Segmentation Technique for Image Indexing and Retrieval on Discrete Cosines Domain

    Directory of Open Access Journals (Sweden)

    Suhendro Yusuf Irianto

    2013-03-01

    Full Text Available This paper uses region growing segmentation technique to segment the Discrete Cosines (DC  image. The problem of content Based image retrieval (CBIR is the luck of accuracy in matching between image query and image in the database as it matches object and background in the same time.   This the reason previous CBIR techniques inaccurate and time consuming. The CBIR   based on the segmented region proposed in this work  separates object from background as CBIR need only match the object not the background.  By using region growing technique on DC image, it reduces the number of image       regions.    The proposed of recursive region growing is not new technique but its application on DC images to build    indexing keys is quite new and not yet presented by many     authors. The experimental results show  that the proposed methods on   segmented images present good precision which are higher than 0.60 on all classes . It can be concluded that  region growing segmented based CBIR more efficient    compare to DC images  in term of their precision 0.59 and 0.75, respectively. Moreover,  DC based CBIR  can save time and simplify algorithm compare to DCT images.

  20. Beamlines of the biomedical imaging and therapy facility at the Canadian light source - part 3

    Science.gov (United States)

    Wysokinski, Tomasz W.; Chapman, Dean; Adams, Gregg; Renier, Michel; Suortti, Pekka; Thomlinson, William

    2015-03-01

    The BioMedical Imaging and Therapy (BMIT) facility provides synchrotron-specific imaging and radiation therapy capabilities [1-4]. We describe here the Insertion Device (ID) beamline 05ID-2 with the beam terminated in the SOE-1 (Secondary Optical Enclosure) experimental hutch. This endstation is designed for imaging and therapy research primarily in animals ranging in size from mice to humans to horses, as well as tissue specimens including plants. Core research programs include human and animal reproduction, cancer imaging and therapy, spinal cord injury and repair, cardiovascular and lung imaging and disease, bone and cartilage growth and deterioration, mammography, developmental biology, gene expression research as well as the introduction of new imaging methods. The source for the ID beamline is a multi-pole superconducting 4.3 T wiggler [5]. The high field gives a critical energy over 20 keV. The high critical energy presents shielding challenges and great care must be taken to assess shielding requirements [6-9]. The optics in the POE-1 and POE-3 hutches [4,10] prepare a monochromatic beam that is 22 cm wide in the last experimental hutch SOE-1. The double crystal bent-Laue or Bragg monochromator, or the single-crystal K-edge subtraction (KES) monochromator provide an energy range appropriate for imaging studies in animals (20-100+ keV). SOE-1 (excluding the basement structure 4 m below the experimental floor) is 6 m wide, 5 m tall and 10 m long with a removable back wall to accommodate installation and removal of the Large Animal Positioning System (LAPS) capable of positioning and manipulating animals as large as a horse [11]. This end-station also includes a unique detector positioner with a vertical travel range of 4.9 m which is required for the KES imaging angle range of +12.3° to -7.3°. The detector positioner also includes moveable shielding integrated with the safety shutters. An update on the status of the other two end-stations at BMIT, described

  1. Beamlines of the biomedical imaging and therapy facility at the Canadian light source – part 3

    International Nuclear Information System (INIS)

    Wysokinski, Tomasz W.; Chapman, Dean; Adams, Gregg; Renier, Michel; Suortti, Pekka; Thomlinson, William

    2015-01-01

    The BioMedical Imaging and Therapy (BMIT) facility provides synchrotron-specific imaging and radiation therapy capabilities [1–4]. We describe here the Insertion Device (ID) beamline 05ID-2 with the beam terminated in the SOE-1 (Secondary Optical Enclosure) experimental hutch. This endstation is designed for imaging and therapy research primarily in animals ranging in size from mice to humans to horses, as well as tissue specimens including plants. Core research programs include human and animal reproduction, cancer imaging and therapy, spinal cord injury and repair, cardiovascular and lung imaging and disease, bone and cartilage growth and deterioration, mammography, developmental biology, gene expression research as well as the introduction of new imaging methods. The source for the ID beamline is a multi-pole superconducting 4.3 T wiggler [5]. The high field gives a critical energy over 20 keV. The high critical energy presents shielding challenges and great care must be taken to assess shielding requirements [6–9]. The optics in the POE-1 and POE-3 hutches [4,10] prepare a monochromatic beam that is 22 cm wide in the last experimental hutch SOE-1. The double crystal bent-Laue or Bragg monochromator, or the single-crystal K-edge subtraction (KES) monochromator provide an energy range appropriate for imaging studies in animals (20–100+ keV). SOE-1 (excluding the basement structure 4 m below the experimental floor) is 6 m wide, 5 m tall and 10 m long with a removable back wall to accommodate installation and removal of the Large Animal Positioning System (LAPS) capable of positioning and manipulating animals as large as a horse [11]. This end-station also includes a unique detector positioner with a vertical travel range of 4.9 m which is required for the KES imaging angle range of +12.3° to –7.3°. The detector positioner also includes moveable shielding integrated with the safety shutters. An update on the status of the other two end-stations at BMIT

  2. Beamlines of the biomedical imaging and therapy facility at the Canadian light source – part 3

    Energy Technology Data Exchange (ETDEWEB)

    Wysokinski, Tomasz W., E-mail: bmit@lightsource.ca [Canadian Light Source, Saskatoon, SK (Canada); Chapman, Dean [Anatomy and Cell Biology, University of Saskatchewan, Saskatoon, SK (Canada); Adams, Gregg [Western College of Veterinary Medicine, Saskatoon, SK (Canada); Renier, Michel [European Synchrotron Radiation Facility, Grenoble (France); Suortti, Pekka [Department of Physics, University of Helsinki (Finland); Thomlinson, William [Department of Physics, University of Saskatchewan, Saskatoon, SK (Canada)

    2015-03-01

    The BioMedical Imaging and Therapy (BMIT) facility provides synchrotron-specific imaging and radiation therapy capabilities [1–4]. We describe here the Insertion Device (ID) beamline 05ID-2 with the beam terminated in the SOE-1 (Secondary Optical Enclosure) experimental hutch. This endstation is designed for imaging and therapy research primarily in animals ranging in size from mice to humans to horses, as well as tissue specimens including plants. Core research programs include human and animal reproduction, cancer imaging and therapy, spinal cord injury and repair, cardiovascular and lung imaging and disease, bone and cartilage growth and deterioration, mammography, developmental biology, gene expression research as well as the introduction of new imaging methods. The source for the ID beamline is a multi-pole superconducting 4.3 T wiggler [5]. The high field gives a critical energy over 20 keV. The high critical energy presents shielding challenges and great care must be taken to assess shielding requirements [6–9]. The optics in the POE-1 and POE-3 hutches [4,10] prepare a monochromatic beam that is 22 cm wide in the last experimental hutch SOE-1. The double crystal bent-Laue or Bragg monochromator, or the single-crystal K-edge subtraction (KES) monochromator provide an energy range appropriate for imaging studies in animals (20–100+ keV). SOE-1 (excluding the basement structure 4 m below the experimental floor) is 6 m wide, 5 m tall and 10 m long with a removable back wall to accommodate installation and removal of the Large Animal Positioning System (LAPS) capable of positioning and manipulating animals as large as a horse [11]. This end-station also includes a unique detector positioner with a vertical travel range of 4.9 m which is required for the KES imaging angle range of +12.3° to –7.3°. The detector positioner also includes moveable shielding integrated with the safety shutters. An update on the status of the other two end-stations at BMIT

  3. Plant leaf chlorophyll content retrieval based on a field imaging spectroscopy system.

    Science.gov (United States)

    Liu, Bo; Yue, Yue-Min; Li, Ru; Shen, Wen-Jing; Wang, Ke-Lin

    2014-10-23

    A field imaging spectrometer system (FISS; 380-870 nm and 344 bands) was designed for agriculture applications. In this study, FISS was used to gather spectral information from soybean leaves. The chlorophyll content was retrieved using a multiple linear regression (MLR), partial least squares (PLS) regression and support vector machine (SVM) regression. Our objective was to verify the performance of FISS in a quantitative spectral analysis through the estimation of chlorophyll content and to determine a proper quantitative spectral analysis method for processing FISS data. The results revealed that the derivative reflectance was a more sensitive indicator of chlorophyll content and could extract content information more efficiently than the spectral reflectance, which is more significant for FISS data compared to ASD (analytical spectral devices) data, reducing the corresponding RMSE (root mean squared error) by 3.3%-35.6%. Compared with the spectral features, the regression methods had smaller effects on the retrieval accuracy. A multivariate linear model could be the ideal model to retrieve chlorophyll information with a small number of significant wavelengths used. The smallest RMSE of the chlorophyll content retrieved using FISS data was 0.201 mg/g, a relative reduction of more than 30% compared with the RMSE based on a non-imaging ASD spectrometer, which represents a high estimation accuracy compared with the mean chlorophyll content of the sampled leaves (4.05 mg/g). Our study indicates that FISS could obtain both spectral and spatial detailed information of high quality. Its image-spectrum-in-one merit promotes the good performance of FISS in quantitative spectral analyses, and it can potentially be widely used in the agricultural sector.

  4. Biomedical nanotechnology.

    Science.gov (United States)

    Hurst, Sarah J

    2011-01-01

    This chapter summarizes the roles of nanomaterials in biomedical applications, focusing on those highlighted in this volume. A brief history of nanoscience and technology and a general introduction to the field are presented. Then, the chemical and physical properties of nanostructures that make them ideal for use in biomedical applications are highlighted. Examples of common applications, including sensing, imaging, and therapeutics, are given. Finally, the challenges associated with translating this field from the research laboratory to the clinic setting, in terms of the larger societal implications, are discussed.

  5. Optimizing top precision performance measure of content-based image retrieval by learning similarity function

    KAUST Repository

    Liang, Ru-Ze

    2017-04-24

    In this paper we study the problem of content-based image retrieval. In this problem, the most popular performance measure is the top precision measure, and the most important component of a retrieval system is the similarity function used to compare a query image against a database image. However, up to now, there is no existing similarity learning method proposed to optimize the top precision measure. To fill this gap, in this paper, we propose a novel similarity learning method to maximize the top precision measure. We model this problem as a minimization problem with an objective function as the combination of the losses of the relevant images ranked behind the top-ranked irrelevant image, and the squared Frobenius norm of the similarity function parameter. This minimization problem is solved as a quadratic programming problem. The experiments over two benchmark data sets show the advantages of the proposed method over other similarity learning methods when the top precision is used as the performance measure.

  6. Optimizing top precision performance measure of content-based image retrieval by learning similarity function

    KAUST Repository

    Liang, Ru-Ze; Shi, Lihui; Wang, Haoxiang; Meng, Jiandong; Wang, Jim Jing-Yan; Sun, Qingquan; Gu, Yi

    2017-01-01

    In this paper we study the problem of content-based image retrieval. In this problem, the most popular performance measure is the top precision measure, and the most important component of a retrieval system is the similarity function used to compare a query image against a database image. However, up to now, there is no existing similarity learning method proposed to optimize the top precision measure. To fill this gap, in this paper, we propose a novel similarity learning method to maximize the top precision measure. We model this problem as a minimization problem with an objective function as the combination of the losses of the relevant images ranked behind the top-ranked irrelevant image, and the squared Frobenius norm of the similarity function parameter. This minimization problem is solved as a quadratic programming problem. The experiments over two benchmark data sets show the advantages of the proposed method over other similarity learning methods when the top precision is used as the performance measure.

  7. Novel Polysaccharide Based Polymers and Nanoparticles for Controlled Drug Delivery and Biomedical Imaging

    Science.gov (United States)

    Shalviri, Alireza

    controlled delivery applications of larger molecular size compounds. The starch based hydrogels, polymers and nanoparticles developed in this work have shown great potentials for controlled drug delivery and biomedical imaging applications.

  8. Unified modeling language and design of a case-based retrieval system in medical imaging.

    Science.gov (United States)

    LeBozec, C; Jaulent, M C; Zapletal, E; Degoulet, P

    1998-01-01

    One goal of artificial intelligence research into case-based reasoning (CBR) systems is to develop approaches for designing useful and practical interactive case-based environments. Explaining each step of the design of the case-base and of the retrieval process is critical for the application of case-based systems to the real world. We describe herein our approach to the design of IDEM--Images and Diagnosis from Examples in Medicine--a medical image case-based retrieval system for pathologists. Our approach is based on the expressiveness of an object-oriented modeling language standard: the Unified Modeling Language (UML). We created a set of diagrams in UML notation illustrating the steps of the CBR methodology we used. The key aspect of this approach was selecting the relevant objects of the system according to user requirements and making visualization of cases and of the components of the case retrieval process. Further evaluation of the expressiveness of the design document is required but UML seems to be a promising formalism, improving the communication between the developers and users.

  9. Image encryption using fingerprint as key based on phase retrieval algorithm and public key cryptography

    Science.gov (United States)

    Zhao, Tieyu; Ran, Qiwen; Yuan, Lin; Chi, Yingying; Ma, Jing

    2015-09-01

    In this paper, a novel image encryption system with fingerprint used as a secret key is proposed based on the phase retrieval algorithm and RSA public key algorithm. In the system, the encryption keys include the fingerprint and the public key of RSA algorithm, while the decryption keys are the fingerprint and the private key of RSA algorithm. If the users share the fingerprint, then the system will meet the basic agreement of asymmetric cryptography. The system is also applicable for the information authentication. The fingerprint as secret key is used in both the encryption and decryption processes so that the receiver can identify the authenticity of the ciphertext by using the fingerprint in decryption process. Finally, the simulation results show the validity of the encryption scheme and the high robustness against attacks based on the phase retrieval technique.

  10. Automated segmentation of synchrotron radiation micro-computed tomography biomedical images using Graph Cuts and neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Alvarenga de Moura Meneses, Anderson, E-mail: ameneses@ieee.org [Radiological Sciences Laboratory, Rio de Janeiro State University, Rua Sao Francisco Xavier 524, CEP 20550-900, RJ (Brazil); Giusti, Alessandro [IDSIA (Dalle Molle Institute for Artificial Intelligence), University of Lugano (Switzerland); Pereira de Almeida, Andre; Parreira Nogueira, Liebert; Braz, Delson [Nuclear Engineering Program, Federal University of Rio de Janeiro, RJ (Brazil); Cely Barroso, Regina [Laboratory of Applied Physics on Biomedical Sciences, Physics Department, Rio de Janeiro State University, RJ (Brazil); Almeida, Carlos Eduardo de [Radiological Sciences Laboratory, Rio de Janeiro State University, Rua Sao Francisco Xavier 524, CEP 20550-900, RJ (Brazil)

    2011-12-21

    Synchrotron Radiation (SR) X-ray micro-Computed Tomography ({mu}CT) enables magnified images to be used as a non-invasive and non-destructive technique with a high space resolution for the qualitative and quantitative analyses of biomedical samples. The research on applications of segmentation algorithms to SR-{mu}CT is an open problem, due to the interesting and well-known characteristics of SR images for visualization, such as the high resolution and the phase contrast effect. In this article, we describe and assess the application of the Energy Minimization via Graph Cuts (EMvGC) algorithm for the segmentation of SR-{mu}CT biomedical images acquired at the Synchrotron Radiation for MEdical Physics (SYRMEP) beam line at the Elettra Laboratory (Trieste, Italy). We also propose a method using EMvGC with Artificial Neural Networks (EMANNs) for correcting misclassifications due to intensity variation of phase contrast, which are important effects and sometimes indispensable in certain biomedical applications, although they impair the segmentation provided by conventional techniques. Results demonstrate considerable success in the segmentation of SR-{mu}CT biomedical images, with average Dice Similarity Coefficient 99.88% for bony tissue in Wistar Rats rib samples (EMvGC), as well as 98.95% and 98.02% for scans of Rhodnius prolixus insect samples (Chagas's disease vector) with EMANNs, in relation to manual segmentation. The techniques EMvGC and EMANNs cope with the task of performing segmentation in images with the intensity variation due to phase contrast effects, presenting a superior performance in comparison to conventional segmentation techniques based on thresholding and linear/nonlinear image filtering, which is also discussed in the present article.

  11. Automated segmentation of synchrotron radiation micro-computed tomography biomedical images using Graph Cuts and neural networks

    International Nuclear Information System (INIS)

    Alvarenga de Moura Meneses, Anderson; Giusti, Alessandro; Pereira de Almeida, André; Parreira Nogueira, Liebert; Braz, Delson; Cely Barroso, Regina; Almeida, Carlos Eduardo de

    2011-01-01

    Synchrotron Radiation (SR) X-ray micro-Computed Tomography (μCT) enables magnified images to be used as a non-invasive and non-destructive technique with a high space resolution for the qualitative and quantitative analyses of biomedical samples. The research on applications of segmentation algorithms to SR-μCT is an open problem, due to the interesting and well-known characteristics of SR images for visualization, such as the high resolution and the phase contrast effect. In this article, we describe and assess the application of the Energy Minimization via Graph Cuts (EMvGC) algorithm for the segmentation of SR-μCT biomedical images acquired at the Synchrotron Radiation for MEdical Physics (SYRMEP) beam line at the Elettra Laboratory (Trieste, Italy). We also propose a method using EMvGC with Artificial Neural Networks (EMANNs) for correcting misclassifications due to intensity variation of phase contrast, which are important effects and sometimes indispensable in certain biomedical applications, although they impair the segmentation provided by conventional techniques. Results demonstrate considerable success in the segmentation of SR-μCT biomedical images, with average Dice Similarity Coefficient 99.88% for bony tissue in Wistar Rats rib samples (EMvGC), as well as 98.95% and 98.02% for scans of Rhodnius prolixus insect samples (Chagas's disease vector) with EMANNs, in relation to manual segmentation. The techniques EMvGC and EMANNs cope with the task of performing segmentation in images with the intensity variation due to phase contrast effects, presenting a superior performance in comparison to conventional segmentation techniques based on thresholding and linear/nonlinear image filtering, which is also discussed in the present article.

  12. Learning Low Dimensional Convolutional Neural Networks for High-Resolution Remote Sensing Image Retrieval

    Directory of Open Access Journals (Sweden)

    Weixun Zhou

    2017-05-01

    Full Text Available Learning powerful feature representations for image retrieval has always been a challenging task in the field of remote sensing. Traditional methods focus on extracting low-level hand-crafted features which are not only time-consuming but also tend to achieve unsatisfactory performance due to the complexity of remote sensing images. In this paper, we investigate how to extract deep feature representations based on convolutional neural networks (CNNs for high-resolution remote sensing image retrieval (HRRSIR. To this end, several effective schemes are proposed to generate powerful feature representations for HRRSIR. In the first scheme, a CNN pre-trained on a different problem is treated as a feature extractor since there are no sufficiently-sized remote sensing datasets to train a CNN from scratch. In the second scheme, we investigate learning features that are specific to our problem by first fine-tuning the pre-trained CNN on a remote sensing dataset and then proposing a novel CNN architecture based on convolutional layers and a three-layer perceptron. The novel CNN has fewer parameters than the pre-trained and fine-tuned CNNs and can learn low dimensional features from limited labelled images. The schemes are evaluated on several challenging, publicly available datasets. The results indicate that the proposed schemes, particularly the novel CNN, achieve state-of-the-art performance.

  13. Web tools for effective retrieval, visualization, and evaluation of cardiology medical images and records

    Science.gov (United States)

    Masseroli, Marco; Pinciroli, Francesco

    2000-12-01

    To provide easy retrieval, integration and evaluation of multimodal cardiology images and data in a web browser environment, distributed application technologies and java programming were used to implement a client-server architecture based on software agents. The server side manages secure connections and queries to heterogeneous remote databases and file systems containing patient personal and clinical data. The client side is a Java applet running in a web browser and providing a friendly medical user interface to perform queries on patient and medical test dat and integrate and visualize properly the various query results. A set of tools based on Java Advanced Imaging API enables to process and analyze the retrieved cardiology images, and quantify their features in different regions of interest. The platform-independence Java technology makes the developed prototype easy to be managed in a centralized form and provided in each site where an intranet or internet connection can be located. Giving the healthcare providers effective tools for querying, visualizing and evaluating comprehensively cardiology medical images and records in all locations where they can need them- i.e. emergency, operating theaters, ward, or even outpatient clinics- the developed prototype represents an important aid in providing more efficient diagnoses and medical treatments.

  14. Introducing Anisotropic Minkowski Functionals and Quantitative Anisotropy Measures for Local Structure Analysis in Biomedical Imaging

    Science.gov (United States)

    Wismüller, Axel; De, Titas; Lochmüller, Eva; Eckstein, Felix; Nagarajan, Mahesh B.

    2017-01-01

    The ability of Minkowski Functionals to characterize local structure in different biological tissue types has been demonstrated in a variety of medical image processing tasks. We introduce anisotropic Minkowski Functionals (AMFs) as a novel variant that captures the inherent anisotropy of the underlying gray-level structures. To quantify the anisotropy characterized by our approach, we further introduce a method to compute a quantitative measure motivated by a technique utilized in MR diffusion tensor imaging, namely fractional anisotropy. We showcase the applicability of our method in the research context of characterizing the local structure properties of trabecular bone micro-architecture in the proximal femur as visualized on multi-detector CT. To this end, AMFs were computed locally for each pixel of ROIs extracted from the head, neck and trochanter regions. Fractional anisotropy was then used to quantify the local anisotropy of the trabecular structures found in these ROIs and to compare its distribution in different anatomical regions. Our results suggest a significantly greater concentration of anisotropic trabecular structures in the head and neck regions when compared to the trochanter region (p < 10−4). We also evaluated the ability of such AMFs to predict bone strength in the femoral head of proximal femur specimens obtained from 50 donors. Our results suggest that such AMFs, when used in conjunction with multi-regression models, can outperform more conventional features such as BMD in predicting failure load. We conclude that such anisotropic Minkowski Functionals can capture valuable information regarding directional attributes of local structure, which may be useful in a wide scope of biomedical imaging applications. PMID:29170580

  15. Contributions on biomedical imaging, with a side-look at molecular imaging; Beitraege zur biomedizinischen Bildgebung mit einem Seitenblick auf Molecular Imaging

    Energy Technology Data Exchange (ETDEWEB)

    Winkler, G. (ed.)

    2004-05-01

    This report is intended as a brief introduction to the emerging scientific field of biomedical imaging. The breadth of the subject is shown and future fields of research are indicated, which hopefully will serve as a guide to the identification of starting points for the research in 'Biomedical and/or Molecular Imaging' at the GSF-National Research Center for Environment and Health. The report starts with a brief sketch of the history. Then a - necessarily incomplete - list of research topics is presented. It is organized in two parts: the first one addresses medical imaging, and the second one is concerned with biological point aspects of the matter. (orig.) [German] In diesem Bericht sind einige Beitraege zum Gebiet 'Bildgebende Verfahren in Biologie und Medizin' zusammengestellt. Sie stammen saemtlich aus dem Institut fuer Biomathematik und Biometrie, IBB, am Forschungszentrum fuer Umwelt und Gesundheit, GSF, in Muenchen/Neuherberg, und seinem engeren Umfeld. Ziel war es, zu sichten, was in und um diesen Themenkreis herum an Wissen und sonstiger Kompetenz hier vorhanden ist. Einige am IBB etablierte Gebiete wie Roentgen-Mammographie oder funktionelle Magnetresonanztherapie wurden ausgeblendet. Der Grund ist die Fokussierung auf ein nicht exakt definierbares, neues Gebiet der Bildgebung, das unter dem Namen 'Molecular Imaging' kursiert und derzeit Furore macht macht. (orig.)

  16. Contributions on biomedical imaging, with a side-look at molecular imaging; Beitraege zur biomedizinischen Bildgebung mit einem Seitenblick auf Molecular Imaging

    Energy Technology Data Exchange (ETDEWEB)

    Winkler, G [ed.

    2004-05-01

    This report is intended as a brief introduction to the emerging scientific field of biomedical imaging. The breadth of the subject is shown and future fields of research are indicated, which hopefully will serve as a guide to the identification of starting points for the research in 'Biomedical and/or Molecular Imaging' at the GSF-National Research Center for Environment and Health. The report starts with a brief sketch of the history. Then a - necessarily incomplete - list of research topics is presented. It is organized in two parts: the first one addresses medical imaging, and the second one is concerned with biological point aspects of the matter. (orig.) [German] In diesem Bericht sind einige Beitraege zum Gebiet 'Bildgebende Verfahren in Biologie und Medizin' zusammengestellt. Sie stammen saemtlich aus dem Institut fuer Biomathematik und Biometrie, IBB, am Forschungszentrum fuer Umwelt und Gesundheit, GSF, in Muenchen/Neuherberg, und seinem engeren Umfeld. Ziel war es, zu sichten, was in und um diesen Themenkreis herum an Wissen und sonstiger Kompetenz hier vorhanden ist. Einige am IBB etablierte Gebiete wie Roentgen-Mammographie oder funktionelle Magnetresonanztherapie wurden ausgeblendet. Der Grund ist die Fokussierung auf ein nicht exakt definierbares, neues Gebiet der Bildgebung, das unter dem Namen 'Molecular Imaging' kursiert und derzeit Furore macht macht. (orig.)

  17. Bag-of-features based medical image retrieval via multiple assignment and visual words weighting

    KAUST Repository

    Wang, Jingyan; Li, Yongping; Zhang, Ying; Wang, Chao; Xie, Honglan; Chen, Guoling; Gao, Xin

    2011-01-01

    Bag-of-features based approaches have become prominent for image retrieval and image classification tasks in the past decade. Such methods represent an image as a collection of local features, such as image patches and key points with scale invariant feature transform (SIFT) descriptors. To improve the bag-of-features methods, we first model the assignments of local descriptors as contribution functions, and then propose a novel multiple assignment strategy. Assuming the local features can be reconstructed by their neighboring visual words in a vocabulary, reconstruction weights can be solved by quadratic programming. The weights are then used to build contribution functions, resulting in a novel assignment method, called quadratic programming (QP) assignment. We further propose a novel visual word weighting method. The discriminative power of each visual word is analyzed by the sub-similarity function in the bin that corresponds to the visual word. Each sub-similarity function is then treated as a weak classifier. A strong classifier is learned by boosting methods that combine those weak classifiers. The weighting factors of the visual words are learned accordingly. We evaluate the proposed methods on medical image retrieval tasks. The methods are tested on three well-known data sets, i.e., the ImageCLEFmed data set, the 304 CT Set, and the basal-cell carcinoma image set. Experimental results demonstrate that the proposed QP assignment outperforms the traditional nearest neighbor assignment, the multiple assignment, and the soft assignment, whereas the proposed boosting based weighting strategy outperforms the state-of-the-art weighting methods, such as the term frequency weights and the term frequency-inverse document frequency weights. © 2011 IEEE.

  18. Bag-of-features based medical image retrieval via multiple assignment and visual words weighting

    KAUST Repository

    Wang, Jingyan

    2011-11-01

    Bag-of-features based approaches have become prominent for image retrieval and image classification tasks in the past decade. Such methods represent an image as a collection of local features, such as image patches and key points with scale invariant feature transform (SIFT) descriptors. To improve the bag-of-features methods, we first model the assignments of local descriptors as contribution functions, and then propose a novel multiple assignment strategy. Assuming the local features can be reconstructed by their neighboring visual words in a vocabulary, reconstruction weights can be solved by quadratic programming. The weights are then used to build contribution functions, resulting in a novel assignment method, called quadratic programming (QP) assignment. We further propose a novel visual word weighting method. The discriminative power of each visual word is analyzed by the sub-similarity function in the bin that corresponds to the visual word. Each sub-similarity function is then treated as a weak classifier. A strong classifier is learned by boosting methods that combine those weak classifiers. The weighting factors of the visual words are learned accordingly. We evaluate the proposed methods on medical image retrieval tasks. The methods are tested on three well-known data sets, i.e., the ImageCLEFmed data set, the 304 CT Set, and the basal-cell carcinoma image set. Experimental results demonstrate that the proposed QP assignment outperforms the traditional nearest neighbor assignment, the multiple assignment, and the soft assignment, whereas the proposed boosting based weighting strategy outperforms the state-of-the-art weighting methods, such as the term frequency weights and the term frequency-inverse document frequency weights. © 2011 IEEE.

  19. Simultaneous optical image compression and encryption using error-reduction phase retrieval algorithm

    International Nuclear Information System (INIS)

    Liu, Wei; Liu, Shutian; Liu, Zhengjun

    2015-01-01

    We report a simultaneous image compression and encryption scheme based on solving a typical optical inverse problem. The secret images to be processed are multiplexed as the input intensities of a cascaded diffractive optical system. At the output plane, a compressed complex-valued data with a lot fewer measurements can be obtained by utilizing error-reduction phase retrieval algorithm. The magnitude of the output image can serve as the final ciphertext while its phase serves as the decryption key. Therefore the compression and encryption are simultaneously completed without additional encoding and filtering operations. The proposed strategy can be straightforwardly applied to the existing optical security systems that involve diffraction and interference. Numerical simulations are performed to demonstrate the validity and security of the proposal. (paper)

  20. Vertically integrated monolithic pixel sensors for charged particle tracking and biomedical imaging

    International Nuclear Information System (INIS)

    Ratti, L.; Gaioni, L.; Manghisoni, M.; Re, V.; Traversi, G.

    2011-01-01

    Three-dimensional monolithic pixel sensors have been designed following the same approach that was exploited for the development of the so-called deep N-well (DNW) MAPS in planar CMOS process. The new 3D design relies upon stacking two homogeneous layers fabricated in a 130 nm CMOS technology. One of the two tiers, which are face-to-face bonded, has to be thinned down to about 12μm to expose the through silicon vias connecting the circuits to the back-metal bond pads. As a consequence of the way the two parts of each single chip are designed and fabricated, the prototypes of the 3D monolithic detector will include both samples with a thick substrate underneath the collecting DNW electrode, suitable for charged particle tracking, and samples with a very thin (about 6μm) sensitive volume, which may be used to detect low energy particles in biomedical imaging applications. Device physics simulations have been performed to evaluate the collection properties and detection efficiency of the proposed vertically integrated structures.

  1. Vertically integrated monolithic pixel sensors for charged particle tracking and biomedical imaging

    Energy Technology Data Exchange (ETDEWEB)

    Ratti, L., E-mail: lodovico.ratti@unipv.it [Universita di Pavia, Dipartimento di Elettronica, Via Ferrata 1, I-27100 Pavia (Italy); INFN, Sezione di Pavia, Via Bassi 6, I-27100 Pavia (Italy); Gaioni, L. [INFN, Sezione di Pavia, Via Bassi 6, I-27100 Pavia (Italy); Manghisoni, M.; Re, V.; Traversi, G. [Universita di Bergamo, Dipartimento di Ingegneria Industriale, Via Marconi 5, I-24044 Dalmine (Italy); INFN, Sezione di Pavia, Via Bassi 6, I-27100 Pavia (Italy)

    2011-10-01

    Three-dimensional monolithic pixel sensors have been designed following the same approach that was exploited for the development of the so-called deep N-well (DNW) MAPS in planar CMOS process. The new 3D design relies upon stacking two homogeneous layers fabricated in a 130 nm CMOS technology. One of the two tiers, which are face-to-face bonded, has to be thinned down to about 12{mu}m to expose the through silicon vias connecting the circuits to the back-metal bond pads. As a consequence of the way the two parts of each single chip are designed and fabricated, the prototypes of the 3D monolithic detector will include both samples with a thick substrate underneath the collecting DNW electrode, suitable for charged particle tracking, and samples with a very thin (about 6{mu}m) sensitive volume, which may be used to detect low energy particles in biomedical imaging applications. Device physics simulations have been performed to evaluate the collection properties and detection efficiency of the proposed vertically integrated structures.

  2. Attention-based image similarity measure with application to content-based information retrieval

    Science.gov (United States)

    Stentiford, Fred W. M.

    2003-01-01

    Whilst storage and capture technologies are able to cope with huge numbers of images, image retrieval is in danger of rendering many repositories valueless because of the difficulty of access. This paper proposes a similarity measure that imposes only very weak assumptions on the nature of the features used in the recognition process. This approach does not make use of a pre-defined set of feature measurements which are extracted from a query image and used to match those from database images, but instead generates features on a trial and error basis during the calculation of the similarity measure. This has the significant advantage that features that determine similarity can match whatever image property is important in a particular region whether it be a shape, a texture, a colour or a combination of all three. It means that effort is expended searching for the best feature for the region rather than expecting that a fixed feature set will perform optimally over the whole area of an image and over every image in a database. The similarity measure is evaluated on a problem of distinguishing similar shapes in sets of black and white symbols.

  3. Fast DCNN based on FWT, intelligent dropout and layer skipping for image retrieval.

    Science.gov (United States)

    ElAdel, Asma; Zaied, Mourad; Amar, Chokri Ben

    2017-11-01

    Deep Convolutional Neural Network (DCNN) can be marked as a powerful tool for object and image classification and retrieval. However, the training stage of such networks is highly consuming in terms of storage space and time. Also, the optimization is still a challenging subject. In this paper, we propose a fast DCNN based on Fast Wavelet Transform (FWT), intelligent dropout and layer skipping. The proposed approach led to improve the image retrieval accuracy as well as the searching time. This was possible thanks to three key advantages: First, the rapid way to compute the features using FWT. Second, the proposed intelligent dropout method is based on whether or not a unit is efficiently and not randomly selected. Third, it is possible to classify the image using efficient units of earlier layer(s) and skipping all the subsequent hidden layers directly to the output layer. Our experiments were performed on CIFAR-10 and MNIST datasets and the obtained results are very promising. Copyright © 2017 Elsevier Ltd. All rights reserved.

  4. INFLUENCE OF THE VIEWING GEOMETRY WITHIN HYPERSPECTRAL IMAGES RETRIEVED FROM UAV SNAPSHOT CAMERAS

    Directory of Open Access Journals (Sweden)

    H. Aasen

    2016-06-01

    Full Text Available Hyperspectral data has great potential for vegetation parameter retrieval. However, due to angular effects resulting from different sun-surface-sensor geometries, objects might appear differently depending on the position of an object within the field of view of a sensor. Recently, lightweight snapshot cameras have been introduced, which capture hyperspectral information in two spatial and one spectral dimension and can be mounted on unmanned aerial vehicles. This study investigates the influence of the different viewing geometries within an image on the apparent hyperspectral reflection retrieved by these sensors. Additionally, it is evaluated how hyperspectral vegetation indices like the NDVI are effected by the angular effects within a single image and if the viewing geometry influences the apparent heterogeneity with an area of interest. The study is carried out for a barley canopy at booting stage. The results show significant influences of the position of the area of interest within the image. The red region of the spectrum is more influenced by the position than the near infrared. The ability of the NDVI to compensate these effects was limited to the capturing positions close to nadir. The apparent heterogeneity of the area of interest is the highest close to a nadir.

  5. Compact Representation of High-Dimensional Feature Vectors for Large-Scale Image Recognition and Retrieval.

    Science.gov (United States)

    Zhang, Yu; Wu, Jianxin; Cai, Jianfei

    2016-05-01

    In large-scale visual recognition and image retrieval tasks, feature vectors, such as Fisher vector (FV) or the vector of locally aggregated descriptors (VLAD), have achieved state-of-the-art results. However, the combination of the large numbers of examples and high-dimensional vectors necessitates dimensionality reduction, in order to reduce its storage and CPU costs to a reasonable range. In spite of the popularity of various feature compression methods, this paper shows that the feature (dimension) selection is a better choice for high-dimensional FV/VLAD than the feature (dimension) compression methods, e.g., product quantization. We show that strong correlation among the feature dimensions in the FV and the VLAD may not exist, which renders feature selection a natural choice. We also show that, many dimensions in FV/VLAD are noise. Throwing them away using feature selection is better than compressing them and useful dimensions altogether using feature compression methods. To choose features, we propose an efficient importance sorting algorithm considering both the supervised and unsupervised cases, for visual recognition and image retrieval, respectively. Combining with the 1-bit quantization, feature selection has achieved both higher accuracy and less computational cost than feature compression methods, such as product quantization, on the FV and the VLAD image representations.

  6. Moderate Imaging Resolution Spectroradiometer (MODIS) Aerosol Optical Depth Retrieval for Aerosol Radiative Forcing

    Science.gov (United States)

    Asmat, A.; Jalal, K. A.; Ahmad, N.

    2018-02-01

    The present study uses the Aerosol Optical Depth (AOD) retrieved from Moderate Imaging Resolution Spectroradiometer (MODIS) data for the period from January 2011 until December 2015 over an urban area in Kuching, Sarawak. The results show the minimum AOD value retrieved from MODIS is -0.06 and the maximum value is 6.0. High aerosol loading with high AOD value observed during dry seasons and low AOD monitored during wet seasons. Multi plane regression technique used to retrieve AOD from MODIS (AODMODIS) and different statistics parameter is proposed by using relative absolute error for accuracy assessment in spatial and temporal averaging approach. The AODMODIS then compared with AOD derived from Aerosol Robotic Network (AERONET) Sunphotometer (AODAERONET) and the results shows high correlation coefficient (R2) for AODMODIS and AODAERONET with 0.93. AODMODIS used as an input parameters into Santa Barbara Discrete Ordinate Radiative Transfer (SBDART) model to estimate urban radiative forcing at Kuching. The observed hourly averaged for urban radiative forcing is -0.12 Wm-2 for top of atmosphere (TOA), -2.13 Wm-2 at the surface and 2.00 Wm-2 in the atmosphere. There is a moderate relationship observed between urban radiative forcing calculated using SBDART and AERONET which are 0.75 at the surface, 0.65 at TOA and 0.56 in atmosphere. Overall, variation in AOD tends to cause large bias in the estimated urban radiative forcing.

  7. Data-driven Green's function retrieval and application to imaging with multidimensional deconvolution

    Science.gov (United States)

    Broggini, Filippo; Wapenaar, Kees; van der Neut, Joost; Snieder, Roel

    2014-01-01

    An iterative method is presented that allows one to retrieve the Green's function originating from a virtual source located inside a medium using reflection data measured only at the acquisition surface. In addition to the reflection response, an estimate of the travel times corresponding to the direct arrivals is required. However, no detailed information about the heterogeneities in the medium is needed. The iterative scheme generalizes the Marchenko equation for inverse scattering to the seismic reflection problem. To give insight in the mechanism of the iterative method, its steps for a simple layered medium are analyzed using physical arguments based on the stationary phase method. The retrieved Green's wavefield is shown to correctly contain the multiples due to the inhomogeneities present in the medium. Additionally, a variant of the iterative scheme enables decomposition of the retrieved wavefield into its downgoing and upgoing components. These wavefields then enable creation of a ghost-free image of the medium with either cross correlation or multidimensional deconvolution, presenting an advantage over standard prestack migration.

  8. Nonlinear approaches for phase retrieval in the Fresnel region for hard X-ray imaging

    International Nuclear Information System (INIS)

    Davidoiu, Valentina

    2013-01-01

    The development of highly coherent X-ray sources offers new possibilities to image biological structures at different scales exploiting the refraction of X-rays. The coherence properties of the third-generation synchrotron radiation sources enables efficient implementations of phase contrast techniques. One of the first measurements of the intensity variations due to phase contrast has been reported in 1995 at the European Synchrotron Radiation Facility (ESRF). Phase imaging coupled to tomography acquisition allows three dimensional imaging with an increased sensitivity compared to absorption CT. This technique is particularly attractive to image samples with low absorption constituents. Phase contrast has many applications, ranging from material science, paleontology, bone research to medicine and biology. Several methods to achieve X-ray phase contrast have been proposed during the last years. In propagation based phase contrast, the measurements are made at different sample-to-detector distances. While the intensity data can be acquired and recorded, the phase information of the signal has to be 'retrieved' from the modulus data only. Phase retrieval is thus an ill-posed nonlinear problem and regularization techniques including a priori knowledge are necessary to obtain stable solutions. Several phase recovery methods have been developed in recent years. These approaches generally formulate the phase retrieval problem as a linear one. Nonlinear treatments have not been much investigated. The main purpose of this work was to propose and evaluate new algorithms, in particularly taking into account the nonlinearity of the direct problem. In the first part of this work, we present a Landweber type nonlinear iterative scheme to solve the propagation based phase retrieval problem. This approach uses the analytic expression of the Frechet derivative of the phase-intensity relationship and of its adjoint, which are presented in detail. We also study the effect of

  9. Retrieval of ion distributions in RC from TWINS ENA images by CT technique

    Science.gov (United States)

    Ma, S.; Yan, W.; Xu, L.; Goldstein, J.; McComas, D. J.

    2010-12-01

    The Two Wide-angle Imaging Neutral-atom Spectrometers (TWINS) mission is the first constellation to employ imagers on two separate spacecraft to measure energetic neutral atoms (ENA) produced by charge exchange between ring current energetic ions and cold exospheric neutral atoms. By applying the 3-D volumetric pixel (voxel) computed tomography (CT) inversion method to TWINS images, parent ion populations in the ring current (RC) and auroral regions are retrieved from their ENA signals. This methodology is implemented for data obtained during the main phase of a moderate geomagnetic storm on 11 October 2008. For this storm the two TWINS satellites were located in nearly the same meridian plane at vantage points widely separated in magnetic local time, and both more than 5 RE geocentric distance from the Earth. In the retrieval process, the energetic ion fluxes to be retrieved are assumed being isotropic with respect to pitch angle. The ENA data used in this study are differential fluxes averaged over 12 sweeps (corresponding to an interval of 16 min.) at different energy levels ranging throughout the full 1--100 keV energy range of TWINS. The ENA signals have two main components: (1) a low-latitude/ high-altitude signal from trapped RC ions and (2) a low-altitude signal from precipitating ions in the auroral/subauroral ionosphere. In the retrieved ion distributions, the main part of the RC component is located around midnight toward dawn sector with L from 3 to 7 or farther, while the subauroral low-altitude component is mainly at pre-midnight. It seems that the dominant energy of the RC ions for this storm is at the lowest energy level of 1-2 keV, with another important energy band centered about 44 keV. The low-altitude component is consistent with in situ observations by DMSP/SSJ4. The result of this study demonstrates that with satellite constellations such as TWINS, using all-sky ENA imagers deployed at multiple vantage points, 3-D distribution of RC ion

  10. Synergistic Instance-Level Subspace Alignment for Fine-Grained Sketch-Based Image Retrieval.

    Science.gov (United States)

    Li, Ke; Pang, Kaiyue; Song, Yi-Zhe; Hospedales, Timothy M; Xiang, Tao; Zhang, Honggang

    2017-08-25

    We study the problem of fine-grained sketch-based image retrieval. By performing instance-level (rather than category-level) retrieval, it embodies a timely and practical application, particularly with the ubiquitous availability of touchscreens. Three factors contribute to the challenging nature of the problem: (i) free-hand sketches are inherently abstract and iconic, making visual comparisons with photos difficult, (ii) sketches and photos are in two different visual domains, i.e. black and white lines vs. color pixels, and (iii) fine-grained distinctions are especially challenging when executed across domain and abstraction-level. To address these challenges, we propose to bridge the image-sketch gap both at the high-level via parts and attributes, as well as at the low-level, via introducing a new domain alignment method. More specifically, (i) we contribute a dataset with 304 photos and 912 sketches, where each sketch and image is annotated with its semantic parts and associated part-level attributes. With the help of this dataset, we investigate (ii) how strongly-supervised deformable part-based models can be learned that subsequently enable automatic detection of part-level attributes, and provide pose-aligned sketch-image comparisons. To reduce the sketch-image gap when comparing low-level features, we also (iii) propose a novel method for instance-level domain-alignment, that exploits both subspace and instance-level cues to better align the domains. Finally (iv) these are combined in a matching framework integrating aligned low-level features, mid-level geometric structure and high-level semantic attributes. Extensive experiments conducted on our new dataset demonstrate effectiveness of the proposed method.

  11. Color Texture Image Retrieval Based on Local Extrema Features and Riemannian Distance

    Directory of Open Access Journals (Sweden)

    Minh-Tan Pham

    2017-10-01

    Full Text Available A novel efficient method for content-based image retrieval (CBIR is developed in this paper using both texture and color features. Our motivation is to represent and characterize an input image by a set of local descriptors extracted from characteristic points (i.e., keypoints within the image. Then, dissimilarity measure between images is calculated based on the geometric distance between the topological feature spaces (i.e., manifolds formed by the sets of local descriptors generated from each image of the database. In this work, we propose to extract and use the local extrema pixels as our feature points. Then, the so-called local extrema-based descriptor (LED is generated for each keypoint by integrating all color, spatial as well as gradient information captured by its nearest local extrema. Hence, each image is encoded by an LED feature point cloud and Riemannian distances between these point clouds enable us to tackle CBIR. Experiments performed on several color texture databases including Vistex, STex, color Brodazt, USPtex and Outex TC-00013 using the proposed approach provide very efficient and competitive results compared to the state-of-the-art methods.

  12. A unified framework for image retrieval using keyword and visual features.

    Science.gov (United States)

    Jing, Feng; Li, Mingling; Zhang, Hong-Jiang; Zhang, Bo

    2005-07-01

    In this paper, a unified image retrieval framework based on both keyword annotations and visual features is proposed. In this framework, a set of statistical models are built based on visual features of a small set of manually labeled images to represent semantic concepts and used to propagate keywords to other unlabeled images. These models are updated periodically when more images implicitly labeled by users become available through relevance feedback. In this sense, the keyword models serve the function of accumulation and memorization of knowledge learned from user-provided relevance feedback. Furthermore, two sets of effective and efficient similarity measures and relevance feedback schemes are proposed for query by keyword scenario and query by image example scenario, respectively. Keyword models are combined with visual features in these schemes. In particular, a new, entropy-based active learning strategy is introduced to improve the efficiency of relevance feedback for query by keyword. Furthermore, a new algorithm is proposed to estimate the keyword features of the search concept for query by image example. It is shown to be more appropriate than two existing relevance feedback algorithms. Experimental results demonstrate the effectiveness of the proposed framework.

  13. Efficient Retrieval of Massive Ocean Remote Sensing Images via a Cloud-Based Mean-Shift Algorithm.

    Science.gov (United States)

    Yang, Mengzhao; Song, Wei; Mei, Haibin

    2017-07-23

    The rapid development of remote sensing (RS) technology has resulted in the proliferation of high-resolution images. There are challenges involved in not only storing large volumes of RS images but also in rapidly retrieving the images for ocean disaster analysis such as for storm surges and typhoon warnings. In this paper, we present an efficient retrieval of massive ocean RS images via a Cloud-based mean-shift algorithm. Distributed construction method via the pyramid model is proposed based on the maximum hierarchical layer algorithm and used to realize efficient storage structure of RS images on the Cloud platform. We achieve high-performance processing of massive RS images in the Hadoop system. Based on the pyramid Hadoop distributed file system (HDFS) storage method, an improved mean-shift algorithm for RS image retrieval is presented by fusion with the canopy algorithm via Hadoop MapReduce programming. The results show that the new method can achieve better performance for data storage than HDFS alone and WebGIS-based HDFS. Speedup and scaleup are very close to linear changes with an increase of RS images, which proves that image retrieval using our method is efficient.

  14. Retrieval of long and short lists from long term memory: a functional magnetic resonance imaging study with human subjects.

    Science.gov (United States)

    Zysset, S; Müller, K; Lehmann, C; Thöne-Otto, A I; von Cramon, D Y

    2001-11-13

    Previous studies have shown that reaction time in an item-recognition task with both short and long lists is a quadratic function of list length. This suggests that either different memory retrieval processes are implied for short and long lists or an adaptive process is involved. An event-related functional magnetic resonance imaging study with nine subjects and list lengths varying between 3 and 18 words was conducted to identify the underlying neuronal structures of retrieval from long and short lists. For the retrieval and processing of word-lists a single fronto-parietal network, including premotor, left prefrontal, left precuneal and left parietal regions, was activated. With increasing list length, no additional regions became involved in retrieving information from long-term memory, suggesting that not necessarily different, but highly adaptive retrieval processes are involved.

  15. An efficient and robutst method for shape-based image retrieval

    International Nuclear Information System (INIS)

    Salih, N.D.; Besar, R.; Abas, F.S.

    2007-01-01

    Shapes can be thought as being the words oft he visual language. Shape boundaries need to be simplified and estimated in a wide variety of image analysis applications. Representation and description of Shapes is one of the major problems in content-based image retrieval (CBIR). This paper present an a novel method for shape representation and description named block-based shape representation (BSR), which is capable of extracting reliable information of the object outline in a concise manner. Our technique is translation, scale, and rotation invariant. It works well on different types of shapes and fast enough for use in real-time. This technique has been implemented and evaluated in order to analyze its accuracy and Efficiency. Based on the experimental results, we urge that the proposed BSR is a compact and reliable shape representation method. (author)

  16. Design of a web portal for interdisciplinary image retrieval from multiple online image resources.

    Science.gov (United States)

    Kammerer, F J; Frankewitsch, T; Prokosch, H-U

    2009-01-01

    Images play an important role in medicine. Finding the desired images within the multitude of online image databases is a time-consuming and frustrating process. Existing websites do not meet all the requirements for an ideal learning environment for medical students. This work intends to establish a new web portal providing a centralized access point to a selected number of online image databases. A back-end system locates images on given websites and extracts relevant metadata. The images are indexed using UMLS and the MetaMap system provided by the US National Library of Medicine. Specially developed functions allow to create individual navigation structures. The front-end system suits the specific needs of medical students. A navigation structure consisting of several medical fields, university curricula and the ICD-10 was created. The images may be accessed via the given navigation structure or using different search functions. Cross-references are provided by the semantic relations of the UMLS. Over 25,000 images were identified and indexed. A pilot evaluation among medical students showed good first results concerning the acceptance of the developed navigation structures and search features. The integration of the images from different sources into the UMLS semantic network offers a quick and an easy-to-use learning environment.

  17. Preliminary results for X-ray phase contrast micro-tomography on the biomedical imaging beamline at SSRF

    International Nuclear Information System (INIS)

    Chen Rongchang; Du Guohao; Xie Honglan; Deng Biao; Tong Yajun; Hu Wen; Xue Yanling; Chen Can; Ren Yuqi; Zhou Guangzhao; Wang Yudan; Xiao Tiqiao; Xu Hongjie; Zhu Peiping

    2009-01-01

    With X-ray phase contrast micro-tomography(CT), one is able to obtain edge-enhanced image of internal structure of the samples. This allows visualization of the fine internal features for biology tissues, which is not able to resolve by conventional absorption CT. After preliminary modulation, monochromatic X-rays (8-72.5 keV) are available for experiments on the experimental station of the biomedical imaging beamline at Shanghai Synchrotron Radiation Facility(SSRF). In this paper, we report the in line phase contrast micro-tomography(IL-XPCT) of biology sample (locust) on the beamline. The reconstruct slice images and three dimensional rendering images of the locust were obtained, with clearly visible images of locus's wing, surface texture and internal tissue distribution. (authors)

  18. Model-based VQ for image data archival, retrieval and distribution

    Science.gov (United States)

    Manohar, Mareboyana; Tilton, James C.

    1995-01-01

    An ideal image compression technique for image data archival, retrieval and distribution would be one with the asymmetrical computational requirements of Vector Quantization (VQ), but without the complications arising from VQ codebooks. Codebook generation and maintenance are stumbling blocks which have limited the use of VQ as a practical image compression algorithm. Model-based VQ (MVQ), a variant of VQ described here, has the computational properties of VQ but does not require explicit codebooks. The codebooks are internally generated using mean removed error and Human Visual System (HVS) models. The error model assumed is the Laplacian distribution with mean, lambda-computed from a sample of the input image. A Laplacian distribution with mean, lambda, is generated with uniform random number generator. These random numbers are grouped into vectors. These vectors are further conditioned to make them perceptually meaningful by filtering the DCT coefficients from each vector. The DCT coefficients are filtered by multiplying by a weight matrix that is found to be optimal for human perception. The inverse DCT is performed to produce the conditioned vectors for the codebook. The only image dependent parameter used in the generation of codebook is the mean, lambda, that is included in the coded file to repeat the codebook generation process for decoding.

  19. Linear information retrieval method in X-ray grating-based phase contrast imaging and its interchangeability with tomographic reconstruction

    Science.gov (United States)

    Wu, Z.; Gao, K.; Wang, Z. L.; Shao, Q. G.; Hu, R. F.; Wei, C. X.; Zan, G. B.; Wali, F.; Luo, R. H.; Zhu, P. P.; Tian, Y. C.

    2017-06-01

    In X-ray grating-based phase contrast imaging, information retrieval is necessary for quantitative research, especially for phase tomography. However, numerous and repetitive processes have to be performed for tomographic reconstruction. In this paper, we report a novel information retrieval method, which enables retrieving phase and absorption information by means of a linear combination of two mutually conjugate images. Thanks to the distributive law of the multiplication as well as the commutative law and associative law of the addition, the information retrieval can be performed after tomographic reconstruction, thus simplifying the information retrieval procedure dramatically. The theoretical model of this method is established in both parallel beam geometry for Talbot interferometer and fan beam geometry for Talbot-Lau interferometer. Numerical experiments are also performed to confirm the feasibility and validity of the proposed method. In addition, we discuss its possibility in cone beam geometry and its advantages compared with other methods. Moreover, this method can also be employed in other differential phase contrast imaging methods, such as diffraction enhanced imaging, non-interferometric imaging, and edge illumination.

  20. Optimization of reference library used in content-based medical image retrieval scheme

    International Nuclear Information System (INIS)

    Park, Sang Cheol; Sukthankar, Rahul; Mummert, Lily; Satyanarayanan, Mahadev; Zheng Bin

    2007-01-01

    Building an optimal image reference library is a critical step in developing the interactive computer-aided detection and diagnosis (I-CAD) systems of medical images using content-based image retrieval (CBIR) schemes. In this study, the authors conducted two experiments to investigate (1) the relationship between I-CAD performance and size of reference library and (2) a new reference selection strategy to optimize the library and improve I-CAD performance. The authors assembled a reference library that includes 3153 regions of interest (ROI) depicting either malignant masses (1592) or CAD-cued false-positive regions (1561) and an independent testing data set including 200 masses and 200 false-positive regions. A CBIR scheme using a distance-weighted K-nearest neighbor algorithm is applied to retrieve references that are considered similar to the testing sample from the library. The area under receiver operating characteristic curve (A z ) is used as an index to evaluate the I-CAD performance. In the first experiment, the authors systematically increased reference library size and tested I-CAD performance. The result indicates that scheme performance improves initially from A z =0.715 to 0.874 and then plateaus when the library size reaches approximately half of its maximum capacity. In the second experiment, based on the hypothesis that a ROI should be removed if it performs poorly compared to a group of similar ROIs in a large and diverse reference library, the authors applied a new strategy to identify 'poorly effective' references. By removing 174 identified ROIs from the reference library, I-CAD performance significantly increases to A z =0.914 (p<0.01). The study demonstrates that increasing reference library size and removing poorly effective references can significantly improve I-CAD performance

  1. Effects of Per-Pixel Variability on Uncertainties in Bathymetric Retrievals from High-Resolution Satellite Images

    Directory of Open Access Journals (Sweden)

    Elizabeth J. Botha

    2016-05-01

    Full Text Available Increased sophistication of high spatial resolution multispectral satellite sensors provides enhanced bathymetric mapping capability. However, the enhancements are counter-acted by per-pixel variability in sunglint, atmospheric path length and directional effects. This case-study highlights retrieval errors from images acquired at non-optimal geometrical combinations. The effects of variations in the environmental noise on water surface reflectance and the accuracy of environmental variable retrievals were quantified. Two WorldView-2 satellite images were acquired, within one minute of each other, with Image 1 placed in a near-optimal sun-sensor geometric configuration and Image 2 placed close to the specular point of the Bidirectional Reflectance Distribution Function (BRDF. Image 2 had higher total environmental noise due to increased surface glint and higher atmospheric path-scattering. Generally, depths were under-estimated from Image 2, compared to Image 1. A partial improvement in retrieval error after glint correction of Image 2 resulted in an increase of the maximum depth to which accurate depth estimations were returned. This case-study indicates that critical analysis of individual images, accounting for the entire sun elevation and azimuth and satellite sensor pointing and geometry as well as anticipated wave height and direction, is required to ensure an image is fit for purpose for aquatic data analysis.

  2. Overview of intelligent data retrieval methods for waveforms and images in massive fusion databases

    Energy Technology Data Exchange (ETDEWEB)

    Vega, J. [JET-EFDA, Culham Science Center, OX14 3DB Abingdon (United Kingdom); Asociacion EURATOM/CIEMAT para Fusion, Avda. Complutense 22, 28040 Madrid (Spain)], E-mail: jesus.vega@ciemat.es; Murari, A. [JET-EFDA, Culham Science Center, OX14 3DB Abingdon (United Kingdom); Consorzio RFX-Associazione EURATOM ENEA per la Fusione, I-35127 Padua (Italy); Pereira, A.; Portas, A.; Ratta, G.A.; Castro, R. [JET-EFDA, Culham Science Center, OX14 3DB Abingdon (United Kingdom); Asociacion EURATOM/CIEMAT para Fusion, Avda. Complutense 22, 28040 Madrid (Spain)

    2009-06-15

    JET database contains more than 42 Tbytes of data (waveforms and images) and it doubles its size about every 2 years. ITER database is expected to be orders of magnitude above this quantity. Therefore, data access in such huge databases can no longer be efficiently based on shot number or temporal interval. Taking into account that diagnostics generate reproducible signal patterns (structural shapes) for similar physical behaviour, high level data access systems can be developed. In these systems, the input parameter is a pattern and the outputs are the shot numbers and the temporal locations where similar patterns appear inside the database. These pattern oriented techniques can be used for first data screening of any type of morphological aspect of waveforms and images. The article shows a new technique to look for similar images in huge databases in a fast an efficient way. Also, previous techniques to search for similar waveforms and to retrieve time-series data or images containing any kind of patterns are reviewed.

  3. Introduction to biomedical engineering

    CERN Document Server

    Enderle, John D; Blanchard, Susan M

    2005-01-01

    Under the direction of John Enderle, Susan Blanchard and Joe Bronzino, leaders in the field have contributed chapters on the most relevant subjects for biomedical engineering students. These chapters coincide with courses offered in all biomedical engineering programs so that it can be used at different levels for a variety of courses of this evolving field. Introduction to Biomedical Engineering, Second Edition provides a historical perspective of the major developments in the biomedical field. Also contained within are the fundamental principles underlying biomedical engineering design, analysis, and modeling procedures. The numerous examples, drill problems and exercises are used to reinforce concepts and develop problem-solving skills making this book an invaluable tool for all biomedical students and engineers. New to this edition: Computational Biology, Medical Imaging, Genomics and Bioinformatics. * 60% update from first edition to reflect the developing field of biomedical engineering * New chapters o...

  4. Hierarchical Recurrent Neural Hashing for Image Retrieval With Hierarchical Convolutional Features.

    Science.gov (United States)

    Lu, Xiaoqiang; Chen, Yaxiong; Li, Xuelong

    Hashing has been an important and effective technology in image retrieval due to its computational efficiency and fast search speed. The traditional hashing methods usually learn hash functions to obtain binary codes by exploiting hand-crafted features, which cannot optimally represent the information of the sample. Recently, deep learning methods can achieve better performance, since deep learning architectures can learn more effective image representation features. However, these methods only use semantic features to generate hash codes by shallow projection but ignore texture details. In this paper, we proposed a novel hashing method, namely hierarchical recurrent neural hashing (HRNH), to exploit hierarchical recurrent neural network to generate effective hash codes. There are three contributions of this paper. First, a deep hashing method is proposed to extensively exploit both spatial details and semantic information, in which, we leverage hierarchical convolutional features to construct image pyramid representation. Second, our proposed deep network can exploit directly convolutional feature maps as input to preserve the spatial structure of convolutional feature maps. Finally, we propose a new loss function that considers the quantization error of binarizing the continuous embeddings into the discrete binary codes, and simultaneously maintains the semantic similarity and balanceable property of hash codes. Experimental results on four widely used data sets demonstrate that the proposed HRNH can achieve superior performance over other state-of-the-art hashing methods.Hashing has been an important and effective technology in image retrieval due to its computational efficiency and fast search speed. The traditional hashing methods usually learn hash functions to obtain binary codes by exploiting hand-crafted features, which cannot optimally represent the information of the sample. Recently, deep learning methods can achieve better performance, since deep

  5. Data Retrieval Algorithms for Validating the Optical Transient Detector and the Lightning Imaging Sensor

    Science.gov (United States)

    Koshak, W. J.; Blakeslee, R. J.; Bailey, J. C.

    2000-01-01

    A linear algebraic solution is provided for the problem of retrieving the location and time of occurrence of lightning ground strikes from an Advanced Lightning Direction Finder (ALDF) network. The ALDF network measures field strength, magnetic bearing, and arrival time of lightning radio emissions. Solutions for the plane (i.e., no earth curvature) are provided that implement all of these measurements. The accuracy of the retrieval method is tested using computer-simulated datasets, and the relative influence of bearing and arrival time data an the outcome of the final solution is formally demonstrated. The algorithm is sufficiently accurate to validate NASA:s Optical Transient Detector and Lightning Imaging Sensor. A quadratic planar solution that is useful when only three arrival time measurements are available is also introduced. The algebra of the quadratic root results are examined in detail to clarify what portions of the analysis region lead to fundamental ambiguities in sc)iirce location, Complex root results are shown to be associated with the presence of measurement errors when the lightning source lies near an outer sensor baseline of the ALDF network. For arbitrary noncollinear network geometries and in the absence of measurement errors, it is shown that the two quadratic roots are equivalent (no source location ambiguity) on the outer sensor baselines. The accuracy of the quadratic planar method is tested with computer-generated datasets, and the results are generally better than those obtained from the three-station linear planar method when bearing errors are about 2 deg.

  6. Learning binary code via PCA of angle projection for image retrieval

    Science.gov (United States)

    Yang, Fumeng; Ye, Zhiqiang; Wei, Xueqi; Wu, Congzhong

    2018-01-01

    With benefits of low storage costs and high query speeds, binary code representation methods are widely researched for efficiently retrieving large-scale data. In image hashing method, learning hashing function to embed highdimensions feature to Hamming space is a key step for accuracy retrieval. Principal component analysis (PCA) technical is widely used in compact hashing methods, and most these hashing methods adopt PCA projection functions to project the original data into several dimensions of real values, and then each of these projected dimensions is quantized into one bit by thresholding. The variances of different projected dimensions are different, and with real-valued projection produced more quantization error. To avoid the real-valued projection with large quantization error, in this paper we proposed to use Cosine similarity projection for each dimensions, the angle projection can keep the original structure and more compact with the Cosine-valued. We used our method combined the ITQ hashing algorithm, and the extensive experiments on the public CIFAR-10 and Caltech-256 datasets validate the effectiveness of the proposed method.

  7. Stochastic Optimized Relevance Feedback Particle Swarm Optimization for Content Based Image Retrieval

    Directory of Open Access Journals (Sweden)

    Muhammad Imran

    2014-01-01

    Full Text Available One of the major challenges for the CBIR is to bridge the gap between low level features and high level semantics according to the need of the user. To overcome this gap, relevance feedback (RF coupled with support vector machine (SVM has been applied successfully. However, when the feedback sample is small, the performance of the SVM based RF is often poor. To improve the performance of RF, this paper has proposed a new technique, namely, PSO-SVM-RF, which combines SVM based RF with particle swarm optimization (PSO. The aims of this proposed technique are to enhance the performance of SVM based RF and also to minimize the user interaction with the system by minimizing the RF number. The PSO-SVM-RF was tested on the coral photo gallery containing 10908 images. The results obtained from the experiments showed that the proposed PSO-SVM-RF achieved 100% accuracy in 8 feedback iterations for top 10 retrievals and 80% accuracy in 6 iterations for 100 top retrievals. This implies that with PSO-SVM-RF technique high accuracy rate is achieved at a small number of iterations.

  8. Development of a bent Laue beam-expanding double-crystal monochromator for biomedical X-ray imaging

    International Nuclear Information System (INIS)

    Martinson, Mercedes; Samadi, Nazanin; Belev, George; Bassey, Bassey; Lewis, Rob; Aulakh, Gurpreet; Chapman, Dean

    2014-01-01

    A bent Laue beam-expanding double-crystal monochromator was developed and tested at the Biomedical Imaging and Therapy beamline at the Canadian Light Source. The expander will reduce scanning time for micro-computed tomography and allow dynamic imaging that has not previously been possible at this beamline. The Biomedical Imaging and Therapy (BMIT) beamline at the Canadian Light Source has produced some excellent biological imaging data. However, the disadvantage of a small vertical beam limits its usability in some applications. Micro-computed tomography (micro-CT) imaging requires multiple scans to produce a full projection, and certain dynamic imaging experiments are not possible. A larger vertical beam is desirable. It was cost-prohibitive to build a longer beamline that would have produced a large vertical beam. Instead, it was proposed to develop a beam expander that would create a beam appearing to originate at a source much farther away. This was accomplished using a bent Laue double-crystal monochromator in a non-dispersive divergent geometry. The design and implementation of this beam expander is presented along with results from the micro-CT and dynamic imaging tests conducted with this beam. Flux (photons per unit area per unit time) has been measured and found to be comparable with the existing flat Bragg double-crystal monochromator in use at BMIT. This increase in overall photon count is due to the enhanced bandwidth of the bent Laue configuration. Whilst the expanded beam quality is suitable for dynamic imaging and micro-CT, further work is required to improve its phase and coherence properties

  9. Texture Retrieval from VHR Optical Remote Sensed Images Using the Local Extrema Descriptor with Application to Vineyard Parcel Detection

    Directory of Open Access Journals (Sweden)

    Minh-Tan Pham

    2016-04-01

    Full Text Available In this article, we develop a novel method for the detection of vineyard parcels in agricultural landscapes based on very high resolution (VHR optical remote sensing images. Our objective is to perform texture-based image retrieval and supervised classification algorithms. To do that, the local textural and structural features inside each image are taken into account to measure its similarity to other images. In fact, VHR images usually involve a variety of local textures and structures that may verify a weak stationarity hypothesis. Hence, an approach only based on characteristic points, not on all pixels of the image, is supposed to be relevant. This work proposes to construct the local extrema-based descriptor (LED by using the local maximum and local minimum pixels extracted from the image. The LED descriptor is formed based on the radiometric, geometric and gradient features from these local extrema. We first exploit the proposed LED descriptor for the retrieval task to evaluate its performance on texture discrimination. Then, it is embedded into a supervised classification framework to detect vine parcels using VHR satellite images. Experiments performed on VHR panchromatic PLEIADES image data prove the effectiveness of the proposed strategy. Compared to state-of-the-art methods, an enhancement of about 7% in retrieval rate is achieved. For the detection task, about 90% of vineyards are correctly detected.

  10. PROTOTYPE CONTENT BASED IMAGE RETRIEVAL UNTUK DETEKSI PEN YAKIT KULIT DENGAN METODE EDGE DETECTION

    Directory of Open Access Journals (Sweden)

    Erick Fernando

    2016-05-01

    Full Text Available Dokter spesialis kulit melakukan pemeriksa secara visual objek mata, capture objek dengan kamera digital dan menanyakan riwayat perjalanan penyakit pasien, tanpa melakukan perbandingan terhadap gejala dan tanda yang ada sebelummnya. Sehingga pemeriksaan dan perkiraan jenis penyakit kulit. Pengolahan data citra dalam bentuk digital khususnya citra medis sudah sangat dibutuhkan dengan pra-processing. Banyak pasien yang dilayani di rumah sakit masih menggunakan data citra analog. Data analog ini membutuhkan ruangan khusus untuk menyimpan guna menghindarkan kerusakan mekanis. Uraian mengatasi permasalahan ini, citra medis dibuat dalam bentuk digital dan disimpan dalam sistem database dan dapat melihat kesamaan citra kulit yang baru. Citra akan dapat ditampilkan dengan pra- processing dengan identifikasi kesamaan dengan Content Based Image Retrieval (CBIR bekerja dengan cara mengukur kemiripan citra query dengan semua citra yang ada dalam database sehingga query cost berbanding lurus dengan jumlah citra dalam database.

  11. Rotation-robust math symbol recognition and retrieval using outer contours and image subsampling

    Science.gov (United States)

    Zhu, Siyu; Hu, Lei; Zanibbi, Richard

    2013-01-01

    This paper presents an unified recognition and retrieval system for isolated offline printed mathematical symbols for the first time. The system is based on nearest neighbor scheme and uses modified Turning Function and Grid Features to calculate the distance between two symbols based on Sum of Squared Difference. An unwrap process and an alignment process are applied to modify Turning Function to deal with the horizontal and vertical shift caused by the changing of staring point and rotation. This modified Turning Function make our system robust against rotation of the symbol image. The system obtains top-1 recognition rate of 96.90% and 47.27% Area Under Curve (AUC) of precision/recall plot on the InftyCDB-3 dataset. Experiment result shows that the system with modified Turning Function performs significantly better than the system with original Turning Function on the rotated InftyCDB-3 dataset.

  12. An Approach for Foliar Trait Retrieval from Airborne Imaging Spectroscopy of Tropical Forests

    Directory of Open Access Journals (Sweden)

    Roberta E. Martin

    2018-01-01

    Full Text Available Spatial information on forest functional composition is needed to inform management and conservation efforts, yet this information is lacking, particularly in tropical regions. Canopy foliar traits underpin the functional biodiversity of forests, and have been shown to be remotely measurable using airborne 350–2510 nm imaging spectrometers. We used newly acquired imaging spectroscopy data constrained with concurrent light detection and ranging (LiDAR measurements from the Carnegie Airborne Observatory (CAO, and field measurements, to test the performance of the Spectranomics approach for foliar trait retrieval. The method was previously developed in Neotropical forests, and was tested here in the humid tropical forests of Malaysian Borneo. Multiple foliar chemical traits, as well as leaf mass per area (LMA, were estimated with demonstrable precision and accuracy. The results were similar to those observed for Neotropical forests, suggesting a more general use of the Spectranomics approach for mapping canopy traits in tropical forests. Future mapping studies using this approach can advance scientific investigations and applications based on imaging spectroscopy.

  13. Content-Based High-Resolution Remote Sensing Image Retrieval via Unsupervised Feature Learning and Collaborative Affinity Metric Fusion

    Directory of Open Access Journals (Sweden)

    Yansheng Li

    2016-08-01

    Full Text Available With the urgent demand for automatic management of large numbers of high-resolution remote sensing images, content-based high-resolution remote sensing image retrieval (CB-HRRS-IR has attracted much research interest. Accordingly, this paper proposes a novel high-resolution remote sensing image retrieval approach via multiple feature representation and collaborative affinity metric fusion (IRMFRCAMF. In IRMFRCAMF, we design four unsupervised convolutional neural networks with different layers to generate four types of unsupervised features from the fine level to the coarse level. In addition to these four types of unsupervised features, we also implement four traditional feature descriptors, including local binary pattern (LBP, gray level co-occurrence (GLCM, maximal response 8 (MR8, and scale-invariant feature transform (SIFT. In order to fully incorporate the complementary information among multiple features of one image and the mutual information across auxiliary images in the image dataset, this paper advocates collaborative affinity metric fusion to measure the similarity between images. The performance evaluation of high-resolution remote sensing image retrieval is implemented on two public datasets, the UC Merced (UCM dataset and the Wuhan University (WH dataset. Large numbers of experiments show that our proposed IRMFRCAMF can significantly outperform the state-of-the-art approaches.

  14. A new method for information retrieval in two-dimensional grating-based X-ray phase contrast imaging

    International Nuclear Information System (INIS)

    Wang Zhi-Li; Gao Kun; Chen Jian; Ge Xin; Tian Yang-Chao; Wu Zi-Yu; Zhu Pei-Ping

    2012-01-01

    Grating-based X-ray phase contrast imaging has been demonstrated to be an extremely powerful phase-sensitive imaging technique. By using two-dimensional (2D) gratings, the observable contrast is extended to two refraction directions. Recently, we have developed a novel reverse-projection (RP) method, which is capable of retrieving the object information efficiently with one-dimensional (1D) grating-based phase contrast imaging. In this contribution, we present its extension to the 2D grating-based X-ray phase contrast imaging, named the two-dimensional reverse-projection (2D-RP) method, for information retrieval. The method takes into account the nonlinear contributions of two refraction directions and allows the retrieval of the absorption, the horizontal and the vertical refraction images. The obtained information can be used for the reconstruction of the three-dimensional phase gradient field, and for an improved phase map retrieval and reconstruction. Numerical experiments are carried out, and the results confirm the validity of the 2D-RP method

  15. Joseph F. Keithley Award For Advances in Measurement Science Lecture: Thermophotonic and Photoacoustic Radar Imaging Methods for Biomedical and Dental Imaging

    Science.gov (United States)

    Mandelis, Andreas

    2012-02-01

    In the first part of this presentation I will introduce thermophotonic radar imaging principles and techniques using chirped or binary-phase-coded modulation, methods which can break through the maximum detection depth/depth resolution limitations of conventional photothermal waves. Using matched-filter principles, a methodology enabling parabolic diffusion-wave energy fields to exhibit energy localization akin to propagating hyperbolic wave-fields has been developed. It allows for deconvolution of individual responses of superposed axially discrete sources, opening a new field: depth-resolved thermal coherence tomography. Several examples from dental enamel caries diagnostic imaging to metal subsurface defect thermographic imaging will be discussed. The second part will introduce the field of photoacoustic radar (or sonar) biomedical imaging. I will report the development of a novel biomedical imaging system that utilizes a continuous-wave laser source with a custom intensity modulation pattern, ultrasonic phased array for signal detection and processing coupled with a beamforming algorithm for reconstruction of photoacoustic correlation images. Utilization of specific chirped modulation waveforms (``waveform engineering'') achieves dramatic signal-to-noise-ratio increase and improved axial resolution over pulsed laser photoacoustics. The talk will conclude with aspects of instrumental sensitivity of the PA Radar to optical contrast using cancerous breast tissue-mimicking phantoms, super paramagnetic iron oxide nanoparticles as contrast enhancement agents and in-vivo tissue samples.

  16. Fractional Fourier domain optical image hiding using phase retrieval algorithm based on iterative nonlinear double random phase encoding.

    Science.gov (United States)

    Wang, Xiaogang; Chen, Wen; Chen, Xudong

    2014-09-22

    We present a novel image hiding method based on phase retrieval algorithm under the framework of nonlinear double random phase encoding in fractional Fourier domain. Two phase-only masks (POMs) are efficiently determined by using the phase retrieval algorithm, in which two cascaded phase-truncated fractional Fourier transforms (FrFTs) are involved. No undesired information disclosure, post-processing of the POMs or digital inverse computation appears in our proposed method. In order to achieve the reduction in key transmission, a modified image hiding method based on the modified phase retrieval algorithm and logistic map is further proposed in this paper, in which the fractional orders and the parameters with respect to the logistic map are regarded as encryption keys. Numerical results have demonstrated the feasibility and effectiveness of the proposed algorithms.

  17. Computer-aided diagnostics of screening mammography using content-based image retrieval

    Science.gov (United States)

    Deserno, Thomas M.; Soiron, Michael; de Oliveira, Júlia E. E.; de A. Araújo, Arnaldo

    2012-03-01

    Breast cancer is one of the main causes of death among women in occidental countries. In the last years, screening mammography has been established worldwide for early detection of breast cancer, and computer-aided diagnostics (CAD) is being developed to assist physicians reading mammograms. A promising method for CAD is content-based image retrieval (CBIR). Recently, we have developed a classification scheme of suspicious tissue pattern based on the support vector machine (SVM). In this paper, we continue moving towards automatic CAD of screening mammography. The experiments are based on in total 10,509 radiographs that have been collected from different sources. From this, 3,375 images are provided with one and 430 radiographs with more than one chain code annotation of cancerous regions. In different experiments, this data is divided into 12 and 20 classes, distinguishing between four categories of tissue density, three categories of pathology and in the 20 class problem two categories of different types of lesions. Balancing the number of images in each class yields 233 and 45 images remaining in each of the 12 and 20 classes, respectively. Using a two-dimensional principal component analysis, features are extracted from small patches of 128 x 128 pixels and classified by means of a SVM. Overall, the accuracy of the raw classification was 61.6 % and 52.1 % for the 12 and the 20 class problem, respectively. The confusion matrices are assessed for detailed analysis. Furthermore, an implementation of a SVM-based CBIR system for CADx in screening mammography is presented. In conclusion, with a smarter patch extraction, the CBIR approach might reach precision rates that are helpful for the physicians. This, however, needs more comprehensive evaluation on clinical data.

  18. PCI bus content-addressable-memory (CAM) implementation on FPGA for pattern recognition/image retrieval in a distributed environment

    Science.gov (United States)

    Megherbi, Dalila B.; Yan, Yin; Tanmay, Parikh; Khoury, Jed; Woods, C. L.

    2004-11-01

    Recently surveillance and Automatic Target Recognition (ATR) applications are increasing as the cost of computing power needed to process the massive amount of information continues to fall. This computing power has been made possible partly by the latest advances in FPGAs and SOPCs. In particular, to design and implement state-of-the-Art electro-optical imaging systems to provide advanced surveillance capabilities, there is a need to integrate several technologies (e.g. telescope, precise optics, cameras, image/compute vision algorithms, which can be geographically distributed or sharing distributed resources) into a programmable system and DSP systems. Additionally, pattern recognition techniques and fast information retrieval, are often important components of intelligent systems. The aim of this work is using embedded FPGA as a fast, configurable and synthesizable search engine in fast image pattern recognition/retrieval in a distributed hardware/software co-design environment. In particular, we propose and show a low cost Content Addressable Memory (CAM)-based distributed embedded FPGA hardware architecture solution with real time recognition capabilities and computing for pattern look-up, pattern recognition, and image retrieval. We show how the distributed CAM-based architecture offers a performance advantage of an order-of-magnitude over RAM-based architecture (Random Access Memory) search for implementing high speed pattern recognition for image retrieval. The methods of designing, implementing, and analyzing the proposed CAM based embedded architecture are described here. Other SOPC solutions/design issues are covered. Finally, experimental results, hardware verification, and performance evaluations using both the Xilinx Virtex-II and the Altera Apex20k are provided to show the potential and power of the proposed method for low cost reconfigurable fast image pattern recognition/retrieval at the hardware/software co-design level.

  19. Stress distribution retrieval in granular materials: A multi-scale model and digital image correlation measurements

    Science.gov (United States)

    Bruno, Luigi; Decuzzi, Paolo; Gentile, Francesco

    2016-01-01

    The promise of nanotechnology lies in the possibility of engineering matter on the nanoscale and creating technological interfaces that, because of their small scales, may directly interact with biological objects, creating new strategies for the treatment of pathologies that are otherwise beyond the reach of conventional medicine. Nanotechnology is inherently a multiscale, multiphenomena challenge. Fundamental understanding and highly accurate predictive methods are critical to successful manufacturing of nanostructured materials, bio/mechanical devices and systems. In biomedical engineering, and in the mechanical analysis of biological tissues, classical continuum approaches are routinely utilized, even if these disregard the discrete nature of tissues, that are an interpenetrating network of a matrix (the extra cellular matrix, ECM) and a generally large but finite number of cells with a size falling in the micrometer range. Here, we introduce a nano-mechanical theory that accounts for the-non continuum nature of bio systems and other discrete systems. This discrete field theory, doublet mechanics (DM), is a technique to model the mechanical behavior of materials over multiple scales, ranging from some millimeters down to few nanometers. In the paper, we use this theory to predict the response of a granular material to an external applied load. Such a representation is extremely attractive in modeling biological tissues which may be considered as a spatial set of a large number of particulate (cells) dispersed in an extracellular matrix. Possibly more important of this, using digital image correlation (DIC) optical methods, we provide an experimental verification of the model.

  20. Encryption of QR code and grayscale image in interference-based scheme with high quality retrieval and silhouette problem removal

    Science.gov (United States)

    Qin, Yi; Wang, Hongjuan; Wang, Zhipeng; Gong, Qiong; Wang, Danchen

    2016-09-01

    In optical interference-based encryption (IBE) scheme, the currently available methods have to employ the iterative algorithms in order to encrypt two images and retrieve cross-talk free decrypted images. In this paper, we shall show that this goal can be achieved via an analytical process if one of the two images is QR code. For decryption, the QR code is decrypted in the conventional architecture and the decryption has a noisy appearance. Nevertheless, the robustness of QR code against noise enables the accurate acquisition of its content from the noisy retrieval, as a result of which the primary QR code can be exactly regenerated. Thereafter, a novel optical architecture is proposed to recover the grayscale image by aid of the QR code. In addition, the proposal has totally eliminated the silhouette problem existing in the previous IBE schemes, and its effectiveness and feasibility have been demonstrated by numerical simulations.

  1. Retrieval of suspended sediment concentrations using Landsat-8 OLI satellite images in the Orinoco River (Venezuela)

    Science.gov (United States)

    Yepez, Santiago; Laraque, Alain; Martinez, Jean-Michel; De Sa, Jose; Carrera, Juan Manuel; Castellanos, Bartolo; Gallay, Marjorie; Lopez, Jose L.

    2018-01-01

    In this study, 81 Landsat-8 scenes acquired from 2013 to 2015 were used to estimate the suspended sediment concentration (SSC) in the Orinoco River at its main hydrological station at Ciudad Bolivar, Venezuela. This gauging station monitors an upstream area corresponding to 89% of the total catchment area where the mean discharge is of 33,000 m3·s-1. SSC spatial and temporal variabilities were analyzed in relation to the hydrological cycle and to local geomorphological characteristics of the river mainstream. Three types of atmospheric correction models were evaluated to correct the Landsat-8 images: DOS, FLAASH, and L8SR. Surface reflectance was compared with monthly water sampling to calibrate a SSC retrieval model using a bootstrapping resampling. A regression model based on surface reflectance at the Near-Infrared wavelengths showed the best performance: R2 = 0.92 (N = 27) for the whole range of SSC (18 to 203 mg·l-1) measured at this station during the studied period. The method offers a simple new approach to estimate the SSC along the lower Orinoco River and demonstrates the feasibility and reliability of remote sensing images to map the spatiotemporal variability in sediment transport over large rivers.

  2. Atmospheric retrieval analysis of the directly imaged exoplanet HR 8799b

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Jae-Min [University of Zürich, Institute for Theoretical Physics, Winterthurerstrasse 190, CH-8057 Zürich (Switzerland); Heng, Kevin [University of Bern, Center for Space and Habitability, Sidlerstrasse 5, CH-3012 Bern (Switzerland); Irwin, Patrick G. J., E-mail: lee@physik.uzh.ch, E-mail: kevin.heng@csh.unibe.ch, E-mail: irwin@atm.ox.ac.uk [University of Oxford, Atmospheric, Oceanic and Planetary Physics, Clarendon Laboratory, Parks Road, Oxford OX1 3PU (United Kingdom)

    2013-12-01

    Directly imaged exoplanets are unexplored laboratories for the application of the spectral and temperature retrieval method, where the chemistry and composition of their atmospheres are inferred from inverse modeling of the available data. As a pilot study, we focus on the extrasolar gas giant HR 8799b, for which more than 50 data points are available. We upgrade our non-linear optimal estimation retrieval method to include a phenomenological model of clouds that requires the cloud optical depth and monodisperse particle size to be specified. Previous studies have focused on forward models with assumed values of the exoplanetary properties; there is no consensus on the best-fit values of the radius, mass, surface gravity, and effective temperature of HR 8799b. We show that cloud-free models produce reasonable fits to the data if the atmosphere is of super-solar metallicity and non-solar elemental abundances. Intermediate cloudy models with moderate values of the cloud optical depth and micron-sized particles provide an equally reasonable fit to the data and require a lower mean molecular weight. We report our best-fit values for the radius, mass, surface gravity, and effective temperature of HR 8799b. The mean molecular weight is about 3.8, while the carbon-to-oxygen ratio is about unity due to the prevalence of carbon monoxide. Our study emphasizes the need for robust claims about the nature of an exoplanetary atmosphere to be based on analyses involving both photometry and spectroscopy and inferred from beyond a few photometric data points, such as are typically reported for hot Jupiters.

  3. Facilitating medical information search using Google Glass connected to a content-based medical image retrieval system.

    Science.gov (United States)

    Widmer, Antoine; Schaer, Roger; Markonis, Dimitrios; Muller, Henning

    2014-01-01

    Wearable computing devices are starting to change the way users interact with computers and the Internet. Among them, Google Glass includes a small screen located in front of the right eye, a camera filming in front of the user and a small computing unit. Google Glass has the advantage to provide online services while allowing the user to perform tasks with his/her hands. These augmented glasses uncover many useful applications, also in the medical domain. For example, Google Glass can easily provide video conference between medical doctors to discuss a live case. Using these glasses can also facilitate medical information search by allowing the access of a large amount of annotated medical cases during a consultation in a non-disruptive fashion for medical staff. In this paper, we developed a Google Glass application able to take a photo and send it to a medical image retrieval system along with keywords in order to retrieve similar cases. As a preliminary assessment of the usability of the application, we tested the application under three conditions (images of the skin; printed CT scans and MRI images; and CT and MRI images acquired directly from an LCD screen) to explore whether using Google Glass affects the accuracy of the results returned by the medical image retrieval system. The preliminary results show that despite minor problems due to the relative stability of the Google Glass, images can be sent to and processed by the medical image retrieval system and similar images are returned to the user, potentially helping in the decision making process.

  4. High-resolution fluorescence imaging for red and far-red SIF retrieval at leaf and canopy scales

    Science.gov (United States)

    Albert, L.; Alonso, L.; Cushman, K.; Kellner, J. R.

    2017-12-01

    New commercial-off-the-shelf imaging spectrometers promise the combination of high spatial and spectral resolution needed to retrieve solar induced fluorescence (SIF) at multiple wavelengths for individual plants and even individual leaves from low-altitude airborne or ground-based platforms. Data from these instruments could provide insight into the status of the photosynthetic apparatus at scales of space and time not observable from high-altitude and space-based platforms, and could support calibration and validation activities of current and forthcoming space missions to quantify SIF (OCO-2, OCO-3, FLEX, and GEOCARB). High-spectral resolution enables SIF retrieval from regions of strong telluric absorption by molecular oxygen, and also within numerous solar Fraunhofer lines in atmospheric windows not obscured by oxygen or water absorptions. Here we evaluate algorithms for SIF retrieval using a commercial-off-the-shelf diffraction-grating imaging spectrometer with a spectral sampling interval of 0.05 nm and a FWHM 650 or 700 nm. These filters enable a direct measurement of SIF emission > 650 or 700 nm that serves as a benchmark against which retrievals from reflectance spectra can be evaluated. We repeated this comparison between leaf-level SIF emission spectra and retrieved SIF emission spectra for leaves treated with drought stress and an herbicide (DCMU) that inhibits electron transfer from QA to QB of PSII.

  5. Nanodiamond-Based Composite Structures for Biomedical Imaging and Drug Delivery.

    Science.gov (United States)

    Rosenholm, Jessica M; Vlasov, Igor I; Burikov, Sergey A; Dolenko, Tatiana A; Shenderova, Olga A

    2015-02-01

    Nanodiamond particles are widely recognized candidates for biomedical applications due to their excellent biocompatibility, bright photoluminescence based on color centers and outstanding photostability. Recently, more complex architectures with a nanodiamond core and an external shell or nanostructure which provides synergistic benefits have been developed, and their feasibility for biomedical applications has been demonstrated. This review is aimed at summarizing recent achievements in the fabrication and functional demonstrations of nanodiamond-based composite structures, along with critical considerations that should be taken into account in the design of such structures from a biomedical point of view. A particular focus of the review is core/shell structures of nanodiamond surrounded by porous silica shells, which demonstrate a remarkable increase in drug loading efficiency; as well as nanodiamonds decorated with carbon dots, which have excellent potential as bioimaging probes. Other combinations are also considered, relying on the discussed inherent properties of the inorganic materials being integrated in a way to advance inorganic nanomedicine in the quest for better health-related nanotechnology.

  6. Imaging the 3D structure of secondary osteons in human cortical bone using phase-retrieval tomography

    Energy Technology Data Exchange (ETDEWEB)

    Arhatari, B D; Peele, A G [Department of Physics, La Trobe University, Victoria 3086 (Australia); Cooper, D M L [Department of Anatomy and Cell Biology, University of Saskatchewan, Saskatoon (Canada); Thomas, C D L; Clement, J G [Melbourne Dental School, University of Melbourne, Victoria 3010 (Australia)

    2011-08-21

    By applying a phase-retrieval step before carrying out standard filtered back-projection reconstructions in tomographic imaging, we were able to resolve structures with small differences in density within a densely absorbing sample. This phase-retrieval tomography is particularly suited for the three-dimensional segmentation of secondary osteons (roughly cylindrical structures) which are superimposed upon an existing cortical bone structure through the process of turnover known as remodelling. The resulting images make possible the analysis of the secondary osteon structure and the relationship between an osteon and the surrounding tissue. Our observations have revealed many different and complex 3D structures of osteons that could not be studied using previous methods. This work was carried out using a laboratory-based x-ray source, which makes obtaining these sorts of images readily accessible.

  7. Modern Trends in Imaging XI: Impedance Measurements in the Biomedical Sciences

    Directory of Open Access Journals (Sweden)

    Frederick D. Coffman

    2012-01-01

    Full Text Available Biological organisms and their component organs, tissues and cells have unique electrical impedance properties. Impedance properties often change with changes in structure, composition, and metabolism, and can be indicative of the onset and progression of disease states. Over the past 100 years, instruments and analytical methods have been developed to measure the impedance properties of biological specimens and to utilize these measurements in both clinical and basic science settings. This chapter will review the applications of impedance measurements in the biomedical sciences, from whole body analysis to impedance measurements of single cells and cell monolayers, and how cellular impedance measuring instruments can now be used in high throughput screening applications.

  8. Lensless coherent imaging of proteins and supramolecular assemblies: Efficient phase retrieval by the charge flipping algorithm.

    Science.gov (United States)

    Dumas, Christian; van der Lee, Arie; Palatinus, Lukáš

    2013-05-01

    Diffractive imaging using the intense and coherent beam of X-ray free-electron lasers opens new perspectives for structural studies of single nanoparticles and biomolecules. Simulations were carried out to generate 3D oversampled diffraction patterns of non-crystalline biological samples, ranging from peptides and proteins to megadalton complex assemblies, and to recover their molecular structure from nanometer to near-atomic resolutions. Using these simulated data, we show here that iterative reconstruction methods based on standard and variant forms of the charge flipping algorithm, can efficiently solve the phase retrieval problem and extract a unique and reliable molecular structure. Contrary to the case of conventional algorithms, where the estimation and the use of a compact support is imposed, our approach does not require any prior information about the molecular assembly, and is amenable to a wide range of biological assemblies. Importantly, the robustness of this ab initio approach is illustrated by the fact that it tolerates experimental noise and incompleteness of the intensity data at the center of the speckle pattern. Copyright © 2013 Elsevier Inc. All rights reserved.

  9. CERES cloud property retrievals from imagers on TRMM, Terra, and Aqua

    Science.gov (United States)

    Minnis, Patrick; Young, David F.; Sun-Mack, Sunny; Heck, Patrick W.; Doelling, David R.; Trepte, Qing Z.

    2004-02-01

    The micro- and macrophysical properties of clouds play a crucial role in Earth"s radiation budget. The NASA Clouds and Earth"s Radiant Energy System (CERES) is providing simultaneous measurements of the radiation and cloud fields on a global basis to improve the understanding and modeling of the interaction between clouds and radiation at the top of the atmosphere, at the surface, and within the atmosphere. Cloud properties derived for CERES from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua satellites are compared to ensure consistency between the products to ensure the reliability of the retrievals from multiple platforms at different times of day. Comparisons of cloud fraction, height, optical depth, phase, effective particle size, and ice and liquid water paths from the two satellites show excellent consistency. Initial calibration comparisons are also very favorable. Differences between the Aqua and Terra results are generally due to diurnally dependent changes in the clouds. Additional algorithm refinement is needed over the polar regions for Aqua and at night over those same areas for Terra. The results should be extremely valuable for model validation and improvement and for improving our understanding of the relationship between clouds and the radiation budget.

  10. Retrieval of Garstang's emission function from all-sky camera images

    Science.gov (United States)

    Kocifaj, Miroslav; Solano Lamphar, Héctor Antonio; Kundracik, František

    2015-10-01

    The emission function from ground-based light sources predetermines the skyglow features to a large extent, while most mathematical models that are used to predict the night sky brightness require the information on this function. The radiant intensity distribution on a clear sky is experimentally determined as a function of zenith angle using the theoretical approach published only recently in MNRAS, 439, 3405-3413. We have made the experiments in two localities in Slovakia and Mexico by means of two digital single lens reflex professional cameras operating with different lenses that limit the system's field-of-view to either 180º or 167º. The purpose of using two cameras was to identify variances between two different apertures. Images are taken at different distances from an artificial light source (a city) with intention to determine the ratio of zenith radiance relative to horizontal irradiance. Subsequently, the information on the fraction of the light radiated directly into the upward hemisphere (F) is extracted. The results show that inexpensive devices can properly identify the upward emissions with adequate reliability as long as the clear sky radiance distribution is dominated by a largest ground-based light source. Highly unstable turbidity conditions can also make the parameter F difficult to find or even impossible to retrieve. The measurements at low elevation angles should be avoided due to a potentially parasitic effect of direct light emissions from luminaires surrounding the measuring site.

  11. A review of content-based image retrieval systems in medical applications-clinical benefits and future directions.

    Science.gov (United States)

    Müller, Henning; Michoux, Nicolas; Bandon, David; Geissbuhler, Antoine

    2004-02-01

    Content-based visual information retrieval (CBVIR) or content-based image retrieval (CBIR) has been one on the most vivid research areas in the field of computer vision over the last 10 years. The availability of large and steadily growing amounts of visual and multimedia data, and the development of the Internet underline the need to create thematic access methods that offer more than simple text-based queries or requests based on matching exact database fields. Many programs and tools have been developed to formulate and execute queries based on the visual or audio content and to help browsing large multimedia repositories. Still, no general breakthrough has been achieved with respect to large varied databases with documents of differing sorts and with varying characteristics. Answers to many questions with respect to speed, semantic descriptors or objective image interpretations are still unanswered. In the medical field, images, and especially digital images, are produced in ever-increasing quantities and used for diagnostics and therapy. The Radiology Department of the University Hospital of Geneva alone produced more than 12,000 images a day in 2002. The cardiology is currently the second largest producer of digital images, especially with videos of cardiac catheterization ( approximately 1800 exams per year containing almost 2000 images each). The total amount of cardiologic image data produced in the Geneva University Hospital was around 1 TB in 2002. Endoscopic videos can equally produce enormous amounts of data. With digital imaging and communications in medicine (DICOM), a standard for image communication has been set and patient information can be stored with the actual image(s), although still a few problems prevail with respect to the standardization. In several articles, content-based access to medical images for supporting clinical decision-making has been proposed that would ease the management of clinical data and scenarios for the integration of

  12. Search and retrieval of medical images for improved diagnosis of neurodegenerative diseases

    Science.gov (United States)

    Ekin, Ahmet; Jasinschi, Radu; Turan, Erman; Engbers, Rene; van der Grond, Jeroen; van Buchem, Mark A.

    2007-01-01

    In the medical world, the accuracy of diagnosis is mainly affected by either lack of sufficient understanding of some diseases or the inter-, and/or intra-observer variability of the diagnoses. The former requires understanding the progress of diseases at much earlier stages, extraction of important information from ever growing amounts of data, and finally finding correlations with certain features and complications that will illuminate the disease progression. The latter (inter-, and intra- observer variability) is caused by the differences in the experience levels of different medical experts (inter-observer variability) or by mental and physical tiredness of one expert (intra-observer variability). We believe that the use of large databases can help improve the current status of disease understanding and decision making. By comparing large number of patients, some of the otherwise hidden relations can be revealed that results in better understanding, patients with similar complications can be found, the diagnosis and treatment can be compared so that the medical expert can make a better diagnosis. To this effect, this paper introduces a search and retrieval system for brain MR databases and shows that brain iron accumulation shape provides additional information to the shape-insensitive features, such as the total brain iron load, that are commonly used in the clinics. We propose to use Kendall's correlation value to automatically compare various returns to a query. We also describe a fully automated and fast brain MR image analysis system to detect degenerative iron accumulation in brain, as it is the case in Alzheimer's and Parkinson's. The system is composed of several novel image processing algorithms and has been extensively tested in Leiden University Medical Center over so far more than 600 patients.

  13. A game-based platform for crowd-sourcing biomedical image diagnosis and standardized remote training and education of diagnosticians

    Science.gov (United States)

    Feng, Steve; Woo, Minjae; Chandramouli, Krithika; Ozcan, Aydogan

    2015-03-01

    Over the past decade, crowd-sourcing complex image analysis tasks to a human crowd has emerged as an alternative to energy-inefficient and difficult-to-implement computational approaches. Following this trend, we have developed a mathematical framework for statistically combining human crowd-sourcing of biomedical image analysis and diagnosis through games. Using a web-based smart game (BioGames), we demonstrated this platform's effectiveness for telediagnosis of malaria from microscopic images of individual red blood cells (RBCs). After public release in early 2012 (http://biogames.ee.ucla.edu), more than 3000 gamers (experts and non-experts) used this BioGames platform to diagnose over 2800 distinct RBC images, marking them as positive (infected) or negative (non-infected). Furthermore, we asked expert diagnosticians to tag the same set of cells with labels of positive, negative, or questionable (insufficient information for a reliable diagnosis) and statistically combined their decisions to generate a gold standard malaria image library. Our framework utilized minimally trained gamers' diagnoses to generate a set of statistical labels with an accuracy that is within 98% of our gold standard image library, demonstrating the "wisdom of the crowd". Using the same image library, we have recently launched a web-based malaria training and educational game allowing diagnosticians to compare their performance with their peers. After diagnosing a set of ~500 cells per game, diagnosticians can compare their quantified scores against a leaderboard and view their misdiagnosed cells. Using this platform, we aim to expand our gold standard library with new RBC images and provide a quantified digital tool for measuring and improving diagnostician training globally.

  14. Linear iterative near-field phase retrieval (LIPR) for dual-energy x-ray imaging and material discrimination.

    Science.gov (United States)

    Li, Heyang Thomas; Kingston, Andrew M; Myers, Glenn R; Beeching, Levi; Sheppard, Adrian P

    2018-01-01

    Near-field x-ray refraction (phase) contrast is unavoidable in many lab-based micro-CT imaging systems. Quantitative analysis of x-ray refraction (a.k.a. phase retrieval) is in general an under-constrained problem. Regularizing assumptions may not hold true for interesting samples; popular single-material methods are inappropriate for heterogeneous samples, leading to undesired blurring and/or over-sharpening. In this paper, we constrain and solve the phase-retrieval problem for heterogeneous objects, using the Alvarez-Macovski model for x-ray attenuation. Under this assumption we neglect Rayleigh scattering and pair production, considering only Compton scattering and the photoelectric effect. We formulate and test the resulting method to extract the material properties of density and atomic number from single-distance, dual-energy imaging of both strongly and weakly attenuating multi-material objects with polychromatic x-ray spectra. Simulation and experimental data are used to compare our proposed method with the Paganin single-material phase-retrieval algorithm, and an innovative interpretation of the data-constrained modeling phase-retrieval technique.

  15. Multidimensional Processing and Visual Rendering of Complex 3D Biomedical Images – Year 3

    Data.gov (United States)

    National Aeronautics and Space Administration — To develop and utilize advanced image analysis techniques to maximize the resolution and utility of medical imaging methods being used during spaceflight. We have...

  16. AN ENSEMBLE TEMPLATE MATCHING AND CONTENT-BASED IMAGE RETRIEVAL SCHEME TOWARDS EARLY STAGE DETECTION OF MELANOMA

    Directory of Open Access Journals (Sweden)

    Spiros Kostopoulos

    2016-12-01

    Full Text Available Malignant melanoma represents the most dangerous type of skin cancer. In this study we present an ensemble classification scheme, employing the mutual information, the cross-correlation and the clustering based on proximity of image features methods, for early stage assessment of melanomas on plain photography images. The proposed scheme performs two main operations. First, it retrieves the most similar, to the unknown case, image samples from an available image database with verified benign moles and malignant melanoma cases. Second, it provides an automated estimation regarding the nature of the unknown image sample based on the majority of the most similar images retrieved from the available database. Clinical material comprised 75 melanoma and 75 benign plain photography images collected from publicly available dermatological atlases. Results showed that the ensemble scheme outperformed all other methods tested in terms of accuracy with 94.9±1.5%, following an external cross-validation evaluation methodology. The proposed scheme may benefit patients by providing a second opinion consultation during the self-skin examination process and the physician by providing a second opinion estimation regarding the nature of suspicious moles that may assist towards decision making especially for ambiguous cases, safeguarding, in this way from potential diagnostic misinterpretations.

  17. Interferometric microstructured polymer optical fiber ultrasound sensor for optoacoustic endoscopic imaging in biomedical applications

    DEFF Research Database (Denmark)

    Gallego, Daniel; Sáez-Rodríguez, David; Webb, David

    2014-01-01

    to conventional piezoelectric transducers. These kind of sensors, made of biocompatible polymers, are good candidates for the sensing element in an optoacoustic endoscope because of its high sensitivity, its shape and its non-brittle and non-electric nature. The acoustic sensitivity of the intrinsic fiber optic......We report a characterization of the acoustic sensitivity of microstructured polymer optical fiber interferometric sensors at ultrasonic frequencies from 100kHz to 10MHz. The use of wide-band ultrasonic fiber optic sensors in biomedical ultrasonic and optoacoustic applications is an open alternative...... interferometric sensors depends strongly of the material which is composed of. In this work we compare experimentally the intrinsic ultrasonic sensitivities of a PMMA mPOF with other three optical fibers: a singlemode silica optical fiber, a single-mode polymer optical fiber and a multimode graded...

  18. Retrieval of the ocean wave spectrum in open and thin ice covered ocean waters from ERS Synthetic Aperture Radar images

    International Nuclear Information System (INIS)

    De Carolis, G.

    2001-01-01

    This paper concerns with the task of retrieving ocean wave spectra form imagery provided by space-borne SAR systems such as that on board ERS satellite. SAR imagery of surface wave fields travelling into open ocean and into thin sea ice covers composed of frazil and pancake icefields is considered. The major purpose is to gain insight on how the spectral changes can be related to sea ice properties of geophysical interest such as the thickness. Starting from SAR image cross spectra computed from Single Look Complex (SLC) SAR images, the ocean wave spectrum is retrieved using an inversion procedure based on the gradient descent algorithm. The capability of this method when applied to satellite SAR sensors is investigated. Interest in the SAR image cross spectrum exploitation is twofold: first, the directional properties of the ocean wave spectra are retained; second, external wave information needed to initialize the inversion procedure may be greatly reduced using only information included in the SAR image cross spectrum itself. The main drawback is that the wind waves spectrum could be partly lost and its spectral peak wave number underestimated. An ERS-SAR SLC image acquired on April 10, 1993 over the Greenland Sea was selected as test image. A pair of windows that include open-sea only and sea ice cover, respectively, were selected. The inversions were carried out using different guess wave spectra taken from SAR image cross spectra. Moreover, care was taken to properly handle negative values eventually occurring during the inversion runs. This results in a modification of the gradient descending the technique that is required if a non-negative solution of the wave spectrum is searched for. Results are discussed in view of the possibility of SAR data to detect ocean wave dispersion as a means for the retrieval of ice thickness

  19. Increased transverse relaxivity in ultrasmall superparamagnetic iron oxide nanoparticles used as MRI contrast agent for biomedical imaging.

    Science.gov (United States)

    Mishra, Sushanta Kumar; Kumar, B S Hemanth; Khushu, Subash; Tripathi, Rajendra P; Gangenahalli, Gurudutta

    2016-09-01

    Synthesis of a contrast agent for biomedical imaging is of great interest where magnetic nanoparticles are concerned, because of the strong influence of particle size on transverse relaxivity. In the present study, biocompatible magnetic iron oxide nanoparticles were synthesized by co-precipitation of Fe 2+ and Fe 3+ salts, followed by surface adsorption with reduced dextran. The synthesized nanoparticles were spherical in shape, and 12 ± 2 nm in size as measured using transmission electron microscopy; this was corroborated with results from X-ray diffraction and dynamic light scattering studies. The nanoparticles exhibited superparamagnetic behavior, superior T 2 relaxation rate and high relaxivities (r 1  = 18.4 ± 0.3, r 2  = 90.5 ± 0.8 s -1 mM -1 , at 7 T). MR image analysis of animals before and after magnetic nanoparticle administration revealed that the signal intensity of tumor imaging, specific organ imaging and whole body imaging can be clearly distinguished, due to the strong relaxation properties of these nanoparticles. Very low concentrations (3.0 mg Fe/kg body weight) of iron oxides are sufficient for early detection of tumors, and also have a clear distinction in pre- and post-enhancement of contrast in organs and body imaging. Many investigators have demonstrated high relaxivities of magnetic nanoparticles at superparamagnetic iron oxide level above 50 nm, but this investigation presents a satisfactory, ultrasmall, superparamagnetic and high transverse relaxivity negative contrast agent for diagnosis in pre-clinical studies. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  20. COMPRESSING BIOMEDICAL IMAGE BY USING INTEGER WAVELET TRANSFORM AND PREDICTIVE ENCODER

    OpenAIRE

    Anushree Srivastava*, Narendra Kumar Chaurasia

    2016-01-01

    Image compression has become an important process in today’s world of information exchange. It helps in effective utilization of high speed network resources. Medical image compression has an important role in medical field because they are used for future reference of patients. Medical data is compressed in such a way so that the diagnostics capabilities are not compromised or no medical information is lost. Medical imaging poses the great challenge of having compression algorithms that redu...

  1. A Versatile High Speed 250 MHz Pulse Imager for Biomedical Applications

    Science.gov (United States)

    Epel, Boris; Sundramoorthy, Subramanian V.; Mailer, Colin; Halpern, Howard J.

    2009-01-01

    A versatile 250 MHz pulse electron paramagnetic resonance (EPR) instrument for imaging of small animals is presented. Flexible design of the imager hardware and software makes it possible to use virtually any pulse EPR imaging modality. A fast pulse generation and data acquisition system based on general purpose PCI boards performs measurements with minimal additional delays. Careful design of receiver protection circuitry allowed us to achieve very high sensitivity of the instrument. In this article we demonstrate the ability of the instrument to obtain three dimensional images using the electron spin echo (ESE) and single point imaging (SPI) methods. In a phantom that contains a 1 mM solution of narrow line (16 μT, peak-to-peak) paramagnetic spin probe we achieved an acquisition time of 32 seconds per image with a fast 3D ESE imaging protocol. Using an 18 minute 3D phase relaxation (T2e) ESE imaging protocol in a homogeneous sample a spatial resolution of 1.4 mm and a standard deviation of T2e of 8.5% were achieved. When applied to in vivo imaging this precision of T2e determination would be equivalent to 2 torr resolution of oxygen partial pressure in animal tissues. PMID:19924261

  2. Quantification of signal detection performance degradation induced by phase-retrieval in propagation-based x-ray phase-contrast imaging

    Science.gov (United States)

    Chou, Cheng-Ying; Anastasio, Mark A.

    2016-04-01

    In propagation-based X-ray phase-contrast (PB XPC) imaging, the measured image contains a mixture of absorption- and phase-contrast. To obtain separate images of the projected absorption and phase (i.e., refractive) properties of a sample, phase retrieval methods can be employed. It has been suggested that phase-retrieval can always improve image quality in PB XPC imaging. However, when objective (task-based) measures of image quality are employed, this is not necessarily true and phase retrieval can be detrimental. In this work, signal detection theory is utilized to quantify the performance of a Hotelling observer (HO) for detecting a known signal in a known background. Two cases are considered. In the first case, the HO acts directly on the measured intensity data. In the second case, the HO acts on either the retrieved phase or absorption image. We demonstrate that the performance of the HO is superior when acting on the measured intensity data. The loss of task-specific information induced by phase-retrieval is quantified by computing the efficiency of the HO as the ratio of the test statistic signal-to-noise ratio (SNR) for the two cases. The effect of the system geometry on this efficiency is systematically investigated. Our findings confirm that phase-retrieval can impair signal detection performance in XPC imaging.

  3. Biomedical Imaging Modality Classification Using Combined Visual Features and Textual Terms

    Directory of Open Access Journals (Sweden)

    Xian-Hua Han

    2011-01-01

    extraction from medical images and fuses the different extracted visual features and textual feature for modality classification. To extract visual features from the images, we used histogram descriptor of edge, gray, or color intensity and block-based variation as global features and SIFT histogram as local feature. For textual feature of image representation, the binary histogram of some predefined vocabulary words from image captions is used. Then, we combine the different features using normalized kernel functions for SVM classification. Furthermore, for some easy misclassified modality pairs such as CT and MR or PET and NM modalities, a local classifier is used for distinguishing samples in the pair modality to improve performance. The proposed strategy is evaluated with the provided modality dataset by ImageCLEF 2010.

  4. A general system for automatic biomedical image segmentation using intensity neighborhoods.

    Science.gov (United States)

    Chen, Cheng; Ozolek, John A; Wang, Wei; Rohde, Gustavo K

    2011-01-01

    Image segmentation is important with applications to several problems in biology and medicine. While extensively researched, generally, current segmentation methods perform adequately in the applications for which they were designed, but often require extensive modifications or calibrations before being used in a different application. We describe an approach that, with few modifications, can be used in a variety of image segmentation problems. The approach is based on a supervised learning strategy that utilizes intensity neighborhoods to assign each pixel in a test image its correct class based on training data. We describe methods for modeling rotations and variations in scales as well as a subset selection for training the classifiers. We show that the performance of our approach in tissue segmentation tasks in magnetic resonance and histopathology microscopy images, as well as nuclei segmentation from fluorescence microscopy images, is similar to or better than several algorithms specifically designed for each of these applications.

  5. A General System for Automatic Biomedical Image Segmentation Using Intensity Neighborhoods

    Directory of Open Access Journals (Sweden)

    Cheng Chen

    2011-01-01

    Full Text Available Image segmentation is important with applications to several problems in biology and medicine. While extensively researched, generally, current segmentation methods perform adequately in the applications for which they were designed, but often require extensive modifications or calibrations before being used in a different application. We describe an approach that, with few modifications, can be used in a variety of image segmentation problems. The approach is based on a supervised learning strategy that utilizes intensity neighborhoods to assign each pixel in a test image its correct class based on training data. We describe methods for modeling rotations and variations in scales as well as a subset selection for training the classifiers. We show that the performance of our approach in tissue segmentation tasks in magnetic resonance and histopathology microscopy images, as well as nuclei segmentation from fluorescence microscopy images, is similar to or better than several algorithms specifically designed for each of these applications.

  6. Parallel Processing and Bio-inspired Computing for Biomedical Image Registration

    Directory of Open Access Journals (Sweden)

    Silviu Ioan Bejinariu

    2014-07-01

    Full Text Available Image Registration (IR is an optimization problem computing optimal parameters of a geometric transform used to overlay one or more source images to a given model by maximizing a similarity measure. In this paper the use of bio-inspired optimization algorithms in image registration is analyzed. Results obtained by means of three different algorithms are compared: Bacterial Foraging Optimization Algorithm (BFOA, Genetic Algorithm (GA and Clonal Selection Algorithm (CSA. Depending on the images type, the registration may be: area based, which is slow but more precise, and features based, which is faster. In this paper a feature based approach based on the Scale Invariant Feature Transform (SIFT is proposed. Finally, results obtained using sequential and parallel implementations on multi-core systems for area based and features based image registration are compared.

  7. An update on carbon nanotube-enabled X-ray sources for biomedical imaging.

    Science.gov (United States)

    Puett, Connor; Inscoe, Christina; Hartman, Allison; Calliste, Jabari; Franceschi, Dora K; Lu, Jianping; Zhou, Otto; Lee, Yueh Z

    2018-01-01

    A new imaging technology has emerged that uses carbon nanotubes (CNT) as the electron emitter (cathode) for the X-ray tube. Since the performance of the CNT cathode is controlled by simple voltage manipulation, CNT-enabled X-ray sources are ideal for the repetitive imaging steps needed to capture three-dimensional information. As such, they have allowed the development of a gated micro-computed tomography (CT) scanner for small animal research as well as stationary tomosynthesis, an experimental technology for large field-of-view human imaging. The small animal CT can acquire images at specific points in the respiratory and cardiac cycles. Longitudinal imaging therefore becomes possible and has been applied to many research questions, ranging from tumor response to the noninvasive assessment of cardiac output. Digital tomosynthesis (DT) is a low-dose and low-cost human imaging tool that captures some depth information. Known as three-dimensional mammography, DT is now used clinically for breast imaging. However, the resolution of currently-approved DT is limited by the need to swing the X-ray source through space to collect a series of projection views. An array of fixed and distributed CNT-enabled sources provides the solution and has been used to construct stationary DT devices for breast, lung, and dental imaging. To date, over 100 patients have been imaged on Institutional Review Board-approved study protocols. Early experience is promising, showing an excellent conspicuity of soft-tissue features, while also highlighting technical and post-acquisition processing limitations that are guiding continued research and development. Additionally, CNT-enabled sources are being tested in miniature X-ray tubes that are capable of generating adequate photon energies and tube currents for clinical imaging. Although there are many potential applications for these small field-of-view devices, initial experience has been with an X-ray source that can be inserted into the

  8. Asymmetric double-image encryption method by using iterative phase retrieval algorithm in fractional Fourier transform domain

    Science.gov (United States)

    Sui, Liansheng; Lu, Haiwei; Ning, Xiaojuan; Wang, Yinghui

    2014-02-01

    A double-image encryption scheme is proposed based on an asymmetric technique, in which the encryption and decryption processes are different and the encryption keys are not identical to the decryption ones. First, a phase-only function (POF) of each plain image is retrieved by using an iterative process and then encoded into an interim matrix. Two interim matrices are directly modulated into a complex image by using the convolution operation in the fractional Fourier transform (FrFT) domain. Second, the complex image is encrypted into the gray scale ciphertext with stationary white-noise distribution by using the FrFT. In the encryption process, three random phase functions are used as encryption keys to retrieve the POFs of plain images. Simultaneously, two decryption keys are generated in the encryption process, which make the optical implementation of the decryption process convenient and efficient. The proposed encryption scheme has high robustness to various attacks, such as brute-force attack, known plaintext attack, cipher-only attack, and specific attack. Numerical simulations demonstrate the validity and security of the proposed method.

  9. Combined X-ray CT and mass spectrometry for biomedical imaging applications

    Science.gov (United States)

    Schioppa, E., Jr.; Ellis, S.; Bruinen, A. L.; Visser, J.; Heeren, R. M. A.; Uher, J.; Koffeman, E.

    2014-04-01

    Imaging technologies play a key role in many branches of science, especially in biology and medicine. They provide an invaluable insight into both internal structure and processes within a broad range of samples. There are many techniques that allow one to obtain images of an object. Different techniques are based on the analysis of a particular sample property by means of a dedicated imaging system, and as such, each imaging modality provides the researcher with different information. The use of multimodal imaging (imaging with several different techniques) can provide additional and complementary information that is not possible when employing a single imaging technique alone. In this study, we present for the first time a multi-modal imaging technique where X-ray computerized tomography (CT) is combined with mass spectrometry imaging (MSI). While X-ray CT provides 3-dimensional information regarding the internal structure of the sample based on X-ray absorption coefficients, MSI of thin sections acquired from the same sample allows the spatial distribution of many elements/molecules, each distinguished by its unique mass-to-charge ratio (m/z), to be determined within a single measurement and with a spatial resolution as low as 1 μm or even less. The aim of the work is to demonstrate how molecular information from MSI can be spatially correlated with 3D structural information acquired from X-ray CT. In these experiments, frozen samples are imaged in an X-ray CT setup using Medipix based detectors equipped with a CO2 cooled sample holder. Single projections are pre-processed before tomographic reconstruction using a signal-to-thickness calibration. In the second step, the object is sliced into thin sections (circa 20 μm) that are then imaged using both matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) and secondary ion (SIMS) mass spectrometry, where the spatial distribution of specific molecules within the sample is determined. The

  10. WE-B-210-02: The Advent of Ultrafast Imaging in Biomedical Ultrasound

    International Nuclear Information System (INIS)

    Tanter, M.

    2015-01-01

    In the last fifteen years, the introduction of plane or diverging wave transmissions rather than line by line scanning focused beams has broken the conventional barriers of ultrasound imaging. By using such large field of view transmissions, the frame rate reaches the theoretical limit of physics dictated by the ultrasound speed and an ultrasonic map can be provided typically in tens of micro-seconds (several thousands of frames per second). Interestingly, this leap in frame rate is not only a technological breakthrough but it permits the advent of completely new ultrasound imaging modes, including shear wave elastography, electromechanical wave imaging, ultrafast doppler, ultrafast contrast imaging, and even functional ultrasound imaging of brain activity (fUltrasound) introducing Ultrasound as an emerging full-fledged neuroimaging modality. At ultrafast frame rates, it becomes possible to track in real time the transient vibrations – known as shear waves – propagating through organs. Such “human body seismology” provides quantitative maps of local tissue stiffness whose added value for diagnosis has been recently demonstrated in many fields of radiology (breast, prostate and liver cancer, cardiovascular imaging, …). Today, Supersonic Imagine company is commercializing the first clinical ultrafast ultrasound scanner, Aixplorer with real time Shear Wave Elastography. This is the first example of an ultrafast Ultrasound approach surpassing the research phase and now widely spread in the clinical medical ultrasound community with an installed base of more than 1000 Aixplorer systems in 54 countries worldwide. For blood flow imaging, ultrafast Doppler permits high-precision characterization of complex vascular and cardiac flows. It also gives ultrasound the ability to detect very subtle blood flow in very small vessels. In the brain, such ultrasensitive Doppler paves the way for fUltrasound (functional ultrasound imaging) of brain activity with unprecedented

  11. Probing the potential of neutron imaging for biomedical and biological applications

    International Nuclear Information System (INIS)

    Watkin, Kenneth L.; Bilheux, Hassina Z.; Ankner, John Francis

    2009-01-01

    Neutron imaging of biological specimens began soon after the discovery of the neutron by Chadwick in 1932. The first samples included tumors in tissues, internal organs in rats, and bones. These studies mainly employed thermal neutrons and were often compared with X-ray images of the same or equivalent samples. Although neutron scattering is widely used in biological studies, neutron imaging has yet to be exploited to its full capability in this area. This chapter summarizes past and current research efforts to apply neutron radiography to the study of biological specimens, in the expectation that clinical and medical research, as well as forensic science, may benefit from it.

  12. WE-B-210-02: The Advent of Ultrafast Imaging in Biomedical Ultrasound

    Energy Technology Data Exchange (ETDEWEB)

    Tanter, M. [Laboratoire Ondes et Acoustique (France)

    2015-06-15

    In the last fifteen years, the introduction of plane or diverging wave transmissions rather than line by line scanning focused beams has broken the conventional barriers of ultrasound imaging. By using such large field of view transmissions, the frame rate reaches the theoretical limit of physics dictated by the ultrasound speed and an ultrasonic map can be provided typically in tens of micro-seconds (several thousands of frames per second). Interestingly, this leap in frame rate is not only a technological breakthrough but it permits the advent of completely new ultrasound imaging modes, including shear wave elastography, electromechanical wave imaging, ultrafast doppler, ultrafast contrast imaging, and even functional ultrasound imaging of brain activity (fUltrasound) introducing Ultrasound as an emerging full-fledged neuroimaging modality. At ultrafast frame rates, it becomes possible to track in real time the transient vibrations – known as shear waves – propagating through organs. Such “human body seismology” provides quantitative maps of local tissue stiffness whose added value for diagnosis has been recently demonstrated in many fields of radiology (breast, prostate and liver cancer, cardiovascular imaging, …). Today, Supersonic Imagine company is commercializing the first clinical ultrafast ultrasound scanner, Aixplorer with real time Shear Wave Elastography. This is the first example of an ultrafast Ultrasound approach surpassing the research phase and now widely spread in the clinical medical ultrasound community with an installed base of more than 1000 Aixplorer systems in 54 countries worldwide. For blood flow imaging, ultrafast Doppler permits high-precision characterization of complex vascular and cardiac flows. It also gives ultrasound the ability to detect very subtle blood flow in very small vessels. In the brain, such ultrasensitive Doppler paves the way for fUltrasound (functional ultrasound imaging) of brain activity with unprecedented

  13. Automation of Hessian-Based Tubularity Measure Response Function in 3D Biomedical Images.

    Science.gov (United States)

    Dzyubak, Oleksandr P; Ritman, Erik L

    2011-01-01

    The blood vessels and nerve trees consist of tubular objects interconnected into a complex tree- or web-like structure that has a range of structural scale 5 μm diameter capillaries to 3 cm aorta. This large-scale range presents two major problems; one is just making the measurements, and the other is the exponential increase of component numbers with decreasing scale. With the remarkable increase in the volume imaged by, and resolution of, modern day 3D imagers, it is almost impossible to make manual tracking of the complex multiscale parameters from those large image data sets. In addition, the manual tracking is quite subjective and unreliable. We propose a solution for automation of an adaptive nonsupervised system for tracking tubular objects based on multiscale framework and use of Hessian-based object shape detector incorporating National Library of Medicine Insight Segmentation and Registration Toolkit (ITK) image processing libraries.

  14. SIproc: an open-source biomedical data processing platform for large hyperspectral images.

    Science.gov (United States)

    Berisha, Sebastian; Chang, Shengyuan; Saki, Sam; Daeinejad, Davar; He, Ziqi; Mankar, Rupali; Mayerich, David

    2017-04-10

    There has recently been significant interest within the vibrational spectroscopy community to apply quantitative spectroscopic imaging techniques to histology and clinical diagnosis. However, many of the proposed methods require collecting spectroscopic images that have a similar region size and resolution to the corresponding histological images. Since spectroscopic images contain significantly more spectral samples than traditional histology, the resulting data sets can approach hundreds of gigabytes to terabytes in size. This makes them difficult to store and process, and the tools available to researchers for handling large spectroscopic data sets are limited. Fundamental mathematical tools, such as MATLAB, Octave, and SciPy, are extremely powerful but require that the data be stored in fast memory. This memory limitation becomes impractical for even modestly sized histological images, which can be hundreds of gigabytes in size. In this paper, we propose an open-source toolkit designed to perform out-of-core processing of hyperspectral images. By taking advantage of graphical processing unit (GPU) computing combined with adaptive data streaming, our software alleviates common workstation memory limitations while achieving better performance than existing applications.

  15. Time-series MODIS image-based retrieval and distribution analysis of total suspended matter concentrations in Lake Taihu (China).

    Science.gov (United States)

    Zhang, Yuchao; Lin, Shan; Liu, Jianping; Qian, Xin; Ge, Yi

    2010-09-01

    Although there has been considerable effort to use remotely sensed images to provide synoptic maps of total suspended matter (TSM), there are limited studies on universal TSM retrieval models. In this paper, we have developed a TSM retrieval model for Lake Taihu using TSM concentrations measured in situ and a time series of quasi-synchronous MODIS 250 m images from 2005. After simple geometric and atmospheric correction, we found a significant relationship (R = 0.8736, N = 166) between in situ measured TSM concentrations and MODIS band normalization difference of band 3 and band 1. From this, we retrieved TSM concentrations in eight regions of Lake Taihu in 2007 and analyzed the characteristic distribution and variation of TSM. Synoptic maps of model-estimated TSM of 2007 showed clear geographical and seasonal variations. TSM in Central Lake and Southern Lakeshore were consistently higher than in other regions, while TSM in East Taihu was generally the lowest among the regions throughout the year. Furthermore, a wide range of TSM concentrations appeared from winter to summer. TSM in winter could be several times that in summer.

  16. A Study on Retrieval Algorithm of Black Water Aggregation in Taihu Lake Based on HJ-1 Satellite Images

    International Nuclear Information System (INIS)

    Lei, Zou; Bing, Zhang; Junsheng, Li; Qian, Shen; Fangfang, Zhang; Ganlin, Wang

    2014-01-01

    The phenomenon of black water aggregation (BWA) occurs in inland water when massive algal bodies aggregate, die, and react with the toxic sludge in certain climate conditions to deprive the water of oxygen. This process results in the deterioration of water quality and damage to the ecosystem. Because charge coupled device (CCD) camera data from the Chinese HJ environmental satellite shows high potential in monitoring BWA, we acquired four HJ-CCD images of Taihu Lake captured during 2009 to 2011 to study this phenomenon. The first study site was selected near the Shore of Taihu Lake. We pre-processed the HJ-CCD images and analyzed the digital number (DN) gray values in the research area and in typical BWA areas. The results show that the DN values of visible bands in BWA areas are obviously lower than those in the research areas. Moreover, we developed an empirical retrieving algorithm of BWA based on the DN mean values and variances of research areas. Finally, we tested the accuracy of this empirical algorithm. The retrieving accuracies were89.9%, 58.1%, 73.4%, and 85.5%, respectively, which demonstrates the efficiency of empirical algorithm in retrieving the approximate distributions of BWA

  17. Combined multi-plane phase retrieval and super-resolution optical fluctuation imaging for 4D cell microscopy

    Science.gov (United States)

    Descloux, A.; Grußmayer, K. S.; Bostan, E.; Lukes, T.; Bouwens, A.; Sharipov, A.; Geissbuehler, S.; Mahul-Mellier, A.-L.; Lashuel, H. A.; Leutenegger, M.; Lasser, T.

    2018-03-01

    Super-resolution fluorescence microscopy provides unprecedented insight into cellular and subcellular structures. However, going `beyond the diffraction barrier' comes at a price, since most far-field super-resolution imaging techniques trade temporal for spatial super-resolution. We propose the combination of a novel label-free white light quantitative phase imaging with fluorescence to provide high-speed imaging and spatial super-resolution. The non-iterative phase retrieval relies on the acquisition of single images at each z-location and thus enables straightforward 3D phase imaging using a classical microscope. We realized multi-plane imaging using a customized prism for the simultaneous acquisition of eight planes. This allowed us to not only image live cells in 3D at up to 200 Hz, but also to integrate fluorescence super-resolution optical fluctuation imaging within the same optical instrument. The 4D microscope platform unifies the sensitivity and high temporal resolution of phase imaging with the specificity and high spatial resolution of fluorescence microscopy.

  18. A game-based crowdsourcing platform for rapidly training middle and high school students to perform biomedical image analysis

    Science.gov (United States)

    Feng, Steve; Woo, Min-jae; Kim, Hannah; Kim, Eunso; Ki, Sojung; Shao, Lei; Ozcan, Aydogan

    2016-03-01

    We developed an easy-to-use and widely accessible crowd-sourcing tool for rapidly training humans to perform biomedical image diagnostic tasks and demonstrated this platform's ability on middle and high school students in South Korea to diagnose malaria infected red-blood-cells (RBCs) using Giemsa-stained thin blood smears imaged under light microscopes. We previously used the same platform (i.e., BioGames) to crowd-source diagnostics of individual RBC images, marking them as malaria positive (infected), negative (uninfected), or questionable (insufficient information for a reliable diagnosis). Using a custom-developed statistical framework, we combined the diagnoses from both expert diagnosticians and the minimally trained human crowd to generate a gold standard library of malaria-infection labels for RBCs. Using this library of labels, we developed a web-based training and educational toolset that provides a quantified score for diagnosticians/users to compare their performance against their peers and view misdiagnosed cells. We have since demonstrated the ability of this platform to quickly train humans without prior training to reach high diagnostic accuracy as compared to expert diagnosticians. Our initial trial group of 55 middle and high school students has collectively played more than 170 hours, each demonstrating significant improvements after only 3 hours of training games, with diagnostic scores that match expert diagnosticians'. Next, through a national-scale educational outreach program in South Korea we recruited >1660 students who demonstrated a similar performance level after 5 hours of training. We plan to further demonstrate this tool's effectiveness for other diagnostic tasks involving image labeling and aim to provide an easily-accessible and quickly adaptable framework for online training of new diagnosticians.

  19. Automated hexahedral mesh generation from biomedical image data: applications in limb prosthetics.

    Science.gov (United States)

    Zachariah, S G; Sanders, J E; Turkiyyah, G M

    1996-06-01

    A general method to generate hexahedral meshes for finite element analysis of residual limbs and similar biomedical geometries is presented. The method utilizes skeleton-based subdivision of cross-sectional domains to produce simple subdomains in which structured meshes are easily generated. Application to a below-knee residual limb and external prosthetic socket is described. The residual limb was modeled as consisting of bones, soft tissue, and skin. The prosthetic socket model comprised a socket wall with an inner liner. The geometries of these structures were defined using axial cross-sectional contour data from X-ray computed tomography, optical scanning, and mechanical surface digitization. A tubular surface representation, using B-splines to define the directrix and generator, is shown to be convenient for definition of the structure geometries. Conversion of cross-sectional data to the compact tubular surface representation is direct, and the analytical representation simplifies geometric querying and numerical optimization within the mesh generation algorithms. The element meshes remain geometrically accurate since boundary nodes are constrained to lie on the tubular surfaces. Several element meshes of increasing mesh density were generated for two residual limbs and prosthetic sockets. Convergence testing demonstrated that approximately 19 elements are required along a circumference of the residual limb surface for a simple linear elastic model. A model with the fibula absent compared with the same geometry with the fibula present showed differences suggesting higher distal stresses in the absence of the fibula. Automated hexahedral mesh generation algorithms for sliced data represent an advancement in prosthetic stress analysis since they allow rapid modeling of any given residual limb and optimization of mesh parameters.

  20. Dynamic Nuclear Polarization at low temperature and high magnetic eld for biomedical applications in Magnetic Resonance Spectroscopic Imaging

    International Nuclear Information System (INIS)

    Goutailler, Florent

    2011-01-01

    The aim of this thesis work was to design, build and optimize a large volume multi-samples DNP (Dynamic Nuclear Polarization) polarizer dedicated to Magnetic Resonance Spectroscopic Imaging applications. The experimental system is made up of a high magnetic field magnet (3,35 T) in which takes place a cryogenic system with a pumped bath of liquid helium ("4He) allowing temperatures lower than 1,2 K. A set of inserts is used for the different steps of DNP: irradiation of the sample by a microwave field (f=94 GHz and P=50 mW), polarization measurement by Nuclear Magnetic Resonance... With this system, up to three samples of 1 mL volume can be polarized to a rate of few per-cents. The system has a long autonomy of four hours, so it can be used for polarizing molecules with a long time constant of polarization. Finally, the possibility to get quasi-simultaneously, after dissolution, several samples with a high rate of polarization opens the way of new applications in biomedical imaging. (author) [fr

  1. Parametric biomedical imaging - what defines the quality of quantitative radiological approaches?

    International Nuclear Information System (INIS)

    Glueer, C.C.; Barkmann, R.; Bolte, H.; Heller, M.; Hahn, H.K.; Dicken, V.; Majumdar, S.; Eckstein, F.; Nickelsen, T.N.

    2006-01-01

    Quantitative parametric imaging approaches provide new perspectives for radiological imaging. These include quantitative 2D, 3D, and 4D visualization options along with the parametric depiction of biological tissue properties and tissue function. This allows the interpretation of radiological data from a biochemical, biomechanical, or physiological perspective. Quantification permits the detection of small changes that are not yet visually apparent, thus allowing application in early disease diagnosis and monitoring therapy with enhanced sensitivity. This review outlines the potential of quantitative parametric imaging methods and demonstrates this on the basis of a few exemplary applications. One field of particular interest, the use of these methods for investigational new drug application studies, is presented. Assessment criteria for judging the quality of quantitative imaging approaches are discussed in the context of the potential and the limitations of these methods. While quantitative parametric imaging methods do not replace but rather supplement established visual interpretation methods in radiology, they do open up new perspectives for diagnosis and prognosis and in particular for monitoring disease progression and therapy. (orig.)

  2. Parallel scan hyperspectral fluorescence imaging system and biomedical application for microarrays

    International Nuclear Information System (INIS)

    Liu Zhiyi; Ma Suihua; Liu Le; Guo Jihua; He Yonghong; Ji Yanhong

    2011-01-01

    Microarray research offers great potential for analysis of gene expression profile and leads to greatly improved experimental throughput. A number of instruments have been reported for microarray detection, such as chemiluminescence, surface plasmon resonance, and fluorescence markers. Fluorescence imaging is popular for the readout of microarrays. In this paper we develop a quasi-confocal, multichannel parallel scan hyperspectral fluorescence imaging system for microarray research. Hyperspectral imaging records the entire emission spectrum for every voxel within the imaged area in contrast to recording only fluorescence intensities of filter-based scanners. Coupled with data analysis, the recorded spectral information allows for quantitative identification of the contributions of multiple, spectrally overlapping fluorescent dyes and elimination of unwanted artifacts. The mechanism of quasi-confocal imaging provides a high signal-to-noise ratio, and parallel scan makes this approach a high throughput technique for microarray analysis. This system is improved with a specifically designed spectrometer which can offer a spectral resolution of 0.2 nm, and operates with spatial resolutions ranging from 2 to 30 μm . Finally, the application of the system is demonstrated by reading out microarrays for identification of bacteria.

  3. Thermoacoustic emission induced by deeply-penetrating radiation and its application to biomedical imaging

    International Nuclear Information System (INIS)

    Liew, Soo Chin.

    1989-01-01

    Thermoacoustic emissions induced by 2450 MHz microwave pulses in water, tissue-simulating phantoms and dog kidneys have been detected. The analytic signal magnitude has been employed in generating A-mode images with excellent depth resolution. Thermoacoustic emissions have also been detected from the dose-gradient at the beam edges of a 4 MeV x-ray beam in water. These results establish the feasibility of employing thermoacoustic signals in generating diagnostic images, and in locating x-ray beam edges during radiation therapy. A theoretical model for thermoacoustic imaging using a directional transducer has been developed, which may be used in the design of future thermoacoustic imaging system, and in facilitating comparisons with other types of imaging systems. A method of characterizing biological tissues has been proposed, which relates the power spectrum of the detected thermoacoustic signals to the autocorrelation function of the thermoacoustic source distribution in the tissues. The temperature dependence of acoustic signals induced by microwave pulses in water has been investigated. A microwave-induced thermoacoustic source capable of launching large aperture, unipolar ultrasonic plane wave pulses in water has been constructed

  4. Hierarchical multiple binary image encryption based on a chaos and phase retrieval algorithm in the Fresnel domain

    International Nuclear Information System (INIS)

    Wang, Zhipeng; Hou, Chenxia; Lv, Xiaodong; Wang, Hongjuan; Gong, Qiong; Qin, Yi

    2016-01-01

    Based on the chaos and phase retrieval algorithm, a hierarchical multiple binary image encryption is proposed. In the encryption process, each plaintext is encrypted into a diffraction intensity pattern by two chaos-generated random phase masks (RPMs). Thereafter, the captured diffraction intensity patterns are partially selected by different binary masks and then combined together to form a single intensity pattern. The combined intensity pattern is saved as ciphertext. For decryption, an iterative phase retrieval algorithm is performed, in which a support constraint in the output plane and a median filtering operation are utilized to achieve a rapid convergence rate without a stagnation problem. The proposed scheme has a simple optical setup and large encryption capacity. In particular, it is well suited for constructing a hierarchical security system. The security and robustness of the proposal are also investigated. (letter)

  5. Robust information encryption diffractive-imaging-based scheme with special phase retrieval algorithm for a customized data container

    Science.gov (United States)

    Qin, Yi; Wang, Zhipeng; Wang, Hongjuan; Gong, Qiong; Zhou, Nanrun

    2018-06-01

    The diffractive-imaging-based encryption (DIBE) scheme has aroused wide interesting due to its compact architecture and low requirement of conditions. Nevertheless, the primary information can hardly be recovered exactly in the real applications when considering the speckle noise and potential occlusion imposed on the ciphertext. To deal with this issue, the customized data container (CDC) into DIBE is introduced and a new phase retrieval algorithm (PRA) for plaintext retrieval is proposed. The PRA, designed according to the peculiarity of the CDC, combines two key techniques from previous approaches, i.e., input-support-constraint and median-filtering. The proposed scheme can guarantee totally the reconstruction of the primary information despite heavy noise or occlusion and its effectiveness and feasibility have been demonstrated with simulation results.

  6. Automation of Hessian-Based Tubularity Measure Response Function in 3D Biomedical Images

    OpenAIRE

    Dzyubak, Oleksandr P.; Ritman, Erik L.

    2011-01-01

    The blood vessels and nerve trees consist of tubular objects interconnected into a complex tree- or web-like structure that has a range of structural scale 5 μm diameter capillaries to 3 cm aorta. This large-scale range presents two major problems; one is just making the measurements, and the other is the exponential increase of component numbers with decreasing scale. With the remarkable increase in the volume imaged by, and resolution of, modern day 3D imagers, it is almost impossible to ma...

  7. 77 FR 54584 - National Institute of Biomedical Imaging and Bioengineering; Notice of Closed Meeting

    Science.gov (United States)

    2012-09-05

    ... DEPARTMENT OF HEALTH AND HUMAN SERVICES National Institutes of Health National Institute of... Imaging and Bioengineering Special Emphasis Panel, ZEB1 OSR-D(J2) P Tissue Engineering Resource Center... applications. Place: Best Western Hotel III Tria, 220 Alewife Brook Parkway, Cambridge, MA 02138. Contact...

  8. Combining nanotechnology with current biomedical knowledge for the vascular imaging and treatment of atherosclerosis.

    Science.gov (United States)

    Slevin, M; Badimon, L; Grau-Olivares, M; Ramis, M; Sendra, J; Morrison, M; Krupinski, J

    2010-03-01

    Activation of vasa vasorum (the microvessels supplying the major arteries) at specific sites in the adventitia initiates their proliferation or 'angiogenesis' concomitant with development of atherosclerotic plaques. Haemorrhagic, leaky blood vessels from unstable plaques proliferate abnormally, are of relatively large calibre but are immature neovessels poorly invested with smooth muscle cells and possess structural weaknesses which may contribute to instability of the plaque by facilitation of inflammatory cell infiltration and haemorrhagic complications. Weak neovascular beds in plaque intima as well as activated adventitial blood vessels are potential targets for molecular imaging and targeted drug therapy, however, the majority of tested, currently available imaging and therapeutic agents have been unsuccessful because of their limited capacity to reach and remain stably within the target tissue or cells in vivo. Nanoparticle technology together with magnetic resonance imaging has allowed the possibility of imaging of neovessels in coronary or carotid plaques, and infusion of nanoparticle suspensions using infusion catheters or implant-based drug delivery represents a novel and potentially much more efficient option for treatment. This review will describe the importance of angiogenesis in mediation of plaque growth and development of plaque instability and go on to investigate the possibility of future design of superparamagnetic/perfluorocarbon-derived nanoparticles for imaging of the vasculature in this disease or which could be directed to the adventitial vasa vasorum or indeed intimal microvessels and which can release active payloads directed against primary key external mitogens and intracellular signalling molecules in endothelial cells responsible for their activation with a view to inhibition of angiogenesis.

  9. [Biomedical informatics].

    Science.gov (United States)

    Capurro, Daniel; Soto, Mauricio; Vivent, Macarena; Lopetegui, Marcelo; Herskovic, Jorge R

    2011-12-01

    Biomedical Informatics is a new discipline that arose from the need to incorporate information technologies to the generation, storage, distribution and analysis of information in the domain of biomedical sciences. This discipline comprises basic biomedical informatics, and public health informatics. The development of the discipline in Chile has been modest and most projects have originated from the interest of individual people or institutions, without a systematic and coordinated national development. Considering the unique features of health care system of our country, research in the area of biomedical informatics is becoming an imperative.

  10. Chiral DOTA chelators as an improved platform for biomedical imaging and therapy applications.

    Science.gov (United States)

    Dai, Lixiong; Jones, Chloe M; Chan, Wesley Ting Kwok; Pham, Tiffany A; Ling, Xiaoxi; Gale, Eric M; Rotile, Nicholas J; Tai, William Chi-Shing; Anderson, Carolyn J; Caravan, Peter; Law, Ga-Lai

    2018-02-27

    Despite established clinical utilisation, there is an increasing need for safer, more inert gadolinium-based contrast agents, and for chelators that react rapidly with radiometals. Here we report the syntheses of a series of chiral DOTA chelators and their corresponding metal complexes and reveal properties that transcend the parent DOTA compound. We incorporated symmetrical chiral substituents around the tetraaza ring, imparting enhanced rigidity to the DOTA cavity, enabling control over the range of stereoisomers of the lanthanide complexes. The Gd chiral DOTA complexes are shown to be orders of magnitude more inert to Gd release than [GdDOTA] - . These compounds also exhibit very-fast water exchange rates in an optimal range for high field imaging. Radiolabeling studies with (Cu-64/Lu-177) also demonstrate faster labelling properties. These chiral DOTA chelators are alternative general platforms for the development of stable, high relaxivity contrast agents, and for radiometal complexes used for imaging and/or therapy.

  11. An Imaging Camera for Biomedical Application Based on Compton Scattering of Gamma Rays

    OpenAIRE

    Fontana, Cristiano Lino

    2013-01-01

    In this thesis we present the R&D of a Compton Camera (CC) for small object imaging. The CC concept requires two detectors to obtain the incoming direction of the gamma ray. This approach, sometimes named ``Electronic Collimation,'' differs from the usual technique that employs collimators for physically selecting gamma-rays of a given direction. This solution offers the advantage of much greater sensitivity and hence smaller doses. We propose a novel design, which uses two simila...

  12. Thermoacoustic Emission Induced by Deeply-Penetrating Radiation and its Application to Biomedical Imaging.

    Science.gov (United States)

    Liew, Soo Chin

    Thermoacoustic emissions induced by 2450 MHz microwave pulses in water, tissue-simulating phantoms and dog kidneys have been detected. The analytic signal magnitude has been employed in generating 'A-mode' images with excellent depth resolution. Thermoacoustic emissions have also been detected from the dose-gradient at the beam edges of a 4 MeV x-ray beam in water. These results establish the feasibility of employing thermoacoustic signals in generating diagnostic images, and in locating x-ray beam edges during radiation therapy. A theoretical model for thermoacoustic imaging using a directional transducer has been developed, which may be used in the design of future thermoacoustic imaging system, and in facilitating comparisons with other types of imaging systems. A method of characterizing biological tissues has been proposed, which relates the power spectrum of the detected thermoacoustic signals to the autocorrelation function of the thermoacoustic source distribution in the tissues. The temperature dependence of acoustic signals induced by microwave pulses in water has been investigated. The signal amplitudes vary with temperature as the thermal expansion of water, except near 4^circ C. The signal waveforms show a gradual phase change as the temperature changes from below 4^ circ to above 4^circ C. This anomaly is due to the presence of a nonthermal component detected near 4^circC, whose waveform is similar to the derivative of the room temperature signal. The results are compared to a model based on a nonequilibrium relaxation mechanism proposed by Pierce and Hsieh. The relaxation time was found to be (0.20 +/- 0.02) ns and (0.13 +/- 0.02) ns for 200 ns and 400 ns microwave pulse widths, respectively. A microwave-induced thermoacoustic source capable of launching large aperture, unipolar ultrasonic plane wave pulses in water has been constructed. This source consists of a thin water layer trapped between two dielectric media. Due to the large mismatch in the

  13. A Novel Relevance Feedback Approach Based on Similarity Measure Modification in an X-Ray Image Retrieval System Based on Fuzzy Representation Using Fuzzy Attributed Relational Graph

    Directory of Open Access Journals (Sweden)

    Hossien Pourghassem

    2011-04-01

    Full Text Available Relevance feedback approaches is used to improve the performance of content-based image retrieval systems. In this paper, a novel relevance feedback approach based on similarity measure modification in an X-ray image retrieval system based on fuzzy representation using fuzzy attributed relational graph (FARG is presented. In this approach, optimum weight of each feature in feature vector is calculated using similarity rate between query image and relevant and irrelevant images in user feedback. The calculated weight is used to tune fuzzy graph matching algorithm as a modifier parameter in similarity measure. The standard deviation of the retrieved image features is applied to calculate the optimum weight. The proposed image retrieval system uses a FARG for representation of images, a fuzzy matching graph algorithm as similarity measure and a semantic classifier based on merging scheme for determination of the search space in image database. To evaluate relevance feedback approach in the proposed system, a standard X-ray image database consisting of 10000 images in 57 classes is used. The improvement of the evaluation parameters shows proficiency and efficiency of the proposed system.

  14. Biomedical imaging and therapy with physically and physiologically tailored magnetic nanoparticles

    Science.gov (United States)

    Khandhar, Amit Praful

    Magnetic particle imaging (MPI) and magnetic fluid hyperthermia (MFH) are emerging imaging and therapy approaches that have the potential to improve diagnostic safety and disease management of heart disease and cancer - the number 1 and 2 leading causes of deaths in the United States. MPI promises real-time, tomographic and quantitative imaging of superparamagnetic iron oxide nanoparticle (SPION) tracers distributed in vivo, and is targeted to offer a safer angiography alternative for its first clinical application. MFH uses ac-fields to dissipate heat from SPIONs that can be delivered locally to promote hyperthermia therapy (~42°C) in cancer cells. Both technologies use safe radiofrequency magnetic fields to exploit the fundamental magnetic relaxation properties of superparamagnetic iron oxide nanoparticles (SPIONs), which must be tailored for optimal imaging in the case of MPI, and maximum hyperthermia potency in the case of MFH. Furthermore, the magnetic core and shell of SPIONs are both central to the optimization process; the shell, in particular, bridges the translational gap between the optimized core and its safe and effective use in the physiological environment. Unfortunately, existing SPIONs that were originally designed as MRI contrast agents lack the basic physical properties that enable the clinical translation of MPI and MFH. In this work, the core and shell of monodisperse SPIONs were optimized in concert to accomplish two equally important objectives: (1) biocompatibility, and (2) MPI and MFH efficacy of SPIONs in physiological environments. Critically, it was found that the physical and physiological responses of SPIONs are coupled, and impacting one can have consequences on the other. It was shown that the poly(ethylene glycol) (PEG)-based shell when properly optimized reduced protein adsorption to SPION surface and phagocytic uptake in macrophages - both prerequisites for designing long-circulating SPIONs. In MPI, tailoring the surface coating

  15. Numerical Solution of Diffusion Models in Biomedical Imaging on Multicore Processors

    Directory of Open Access Journals (Sweden)

    Luisa D'Amore

    2011-01-01

    Full Text Available In this paper, we consider nonlinear partial differential equations (PDEs of diffusion/advection type underlying most problems in image analysis. As case study, we address the segmentation of medical structures. We perform a comparative study of numerical algorithms arising from using the semi-implicit and the fully implicit discretization schemes. Comparison criteria take into account both the accuracy and the efficiency of the algorithms. As measure of accuracy, we consider the Hausdorff distance and the residuals of numerical solvers, while as measure of efficiency we consider convergence history, execution time, speedup, and parallel efficiency. This analysis is carried out in a multicore-based parallel computing environment.

  16. Brucellar spondylitis: evaluation by NMR imaging, CT and biomedical radiography - a case report

    International Nuclear Information System (INIS)

    Campos, Juliana C. de; Marins, Jose Luiz C.; Pereira, Rubens Marcondes

    1999-01-01

    A 50-year-old white woman presented with a 4-month history of low pain with lower extremity irradiation. Image studies showed inflammatory changes of the vertebral bodies and invertebral disk at L3-L4 level. Considering she had no previous spinal surgery, negative tests for tuberculosis and a positive history of exposure to brucellosis, further studies were done, and the serologic tests were positive for brucellar antibodies. Follow-up studies within the first two months demonstrated the progressive spinal changes in brucellar spondylitis. (author)

  17. Information retrieval based on single-pixel optical imaging with quick-response code

    Science.gov (United States)

    Xiao, Yin; Chen, Wen

    2018-04-01

    Quick-response (QR) code technique is combined with ghost imaging (GI) to recover original information with high quality. An image is first transformed into a QR code. Then the QR code is treated as an input image in the input plane of a ghost imaging setup. After measurements, traditional correlation algorithm of ghost imaging is utilized to reconstruct an image (QR code form) with low quality. With this low-quality image as an initial guess, a Gerchberg-Saxton-like algorithm is used to improve its contrast, which is actually a post processing. Taking advantage of high error correction capability of QR code, original information can be recovered with high quality. Compared to the previous method, our method can obtain a high-quality image with comparatively fewer measurements, which means that the time-consuming postprocessing procedure can be avoided to some extent. In addition, for conventional ghost imaging, the larger the image size is, the more measurements are needed. However, for our method, images with different sizes can be converted into QR code with the same small size by using a QR generator. Hence, for the larger-size images, the time required to recover original information with high quality will be dramatically reduced. Our method makes it easy to recover a color image in a ghost imaging setup, because it is not necessary to divide the color image into three channels and respectively recover them.

  18. Nanodiamonds as novel nanomaterials for biomedical applications: drug delivery and imaging systems.

    Science.gov (United States)

    Kaur, Randeep; Badea, Ildiko

    2013-01-01

    Detonation nanodiamonds (NDs) are emerging as delivery vehicles for small chemical drugs and macromolecular biotechnology products due to their primary particle size of 4 to 5 nm, stable inert core, reactive surface, and ability to form hydrogels. Nanoprobe technology capitalizes on the intrinsic fluorescence, high refractive index, and unique Raman signal of the NDs, rendering them attractive for in vitro and in vivo imaging applications. This review provides a brief introduction of the various types of NDs and describes the development of procedures that have led to stable single-digit-sized ND dispersions, a crucial feature for drug delivery systems and nanoprobes. Various approaches used for functionalizing the surface of NDs are highlighted, along with a discussion of their biocompatibility status. The utilization of NDs to provide sustained release and improve the dispersion of hydrophobic molecules, of which chemotherapeutic drugs are the most investigated, is described. The prospects of improving the intracellular delivery of nucleic acids by using NDs as a platform are exemplified. The photoluminescent and optical scattering properties of NDs, together with their applications in cellular labeling, are also reviewed. Considering the progress that has been made in understanding the properties of NDs, they can be envisioned as highly efficient drug delivery and imaging biomaterials for use in animals and humans.

  19. Nanodiamonds as novel nanomaterials for biomedical applications: drug delivery and imaging systems

    Directory of Open Access Journals (Sweden)

    Kaur R

    2013-01-01

    Full Text Available Randeep Kaur, Ildiko BadeaDrug Design and Discovery Research Group, College of Pharmacy and Nutrition, University of Saskatchewan, Saskatoon, Saskatchewan, CanadaAbstract: Detonation nanodiamonds (NDs are emerging as delivery vehicles for small chemical drugs and macromolecular biotechnology products due to their primary particle size of 4 to 5 nm, stable inert core, reactive surface, and ability to form hydrogels. Nanoprobe technology capitalizes on the intrinsic fluorescence, high refractive index, and unique Raman signal of the NDs, rendering them attractive for in vitro and in vivo imaging applications. This review provides a brief introduction of the various types of NDs and describes the development of procedures that have led to stable single-digit-sized ND dispersions, a crucial feature for drug delivery systems and nanoprobes. Various approaches used for functionalizing the surface of NDs are highlighted, along with a discussion of their biocompatibility status. The utilization of NDs to provide sustained release and improve the dispersion of hydrophobic molecules, of which chemotherapeutic drugs are the most investigated, is described. The prospects of improving the intracellular delivery of nucleic acids by using NDs as a platform are exemplified. The photoluminescent and optical scattering properties of NDs, together with their applications in cellular labeling, are also reviewed. Considering the progress that has been made in understanding the properties of NDs, they can be envisioned as highly efficient drug delivery and imaging biomaterials for use in animals and humans.Keywords: dispersion, surface functionalization, toxicity, carriers, fluorescence, light scattering

  20. INFLUENCE OF THE VIEWING GEOMETRY WITHIN HYPERSPECTRAL IMAGES RETRIEVED FROM UAV SNAPSHOT CAMERAS

    OpenAIRE

    Aasen, Helge

    2016-01-01

    Hyperspectral data has great potential for vegetation parameter retrieval. However, due to angular effects resulting from different sun-surface-sensor geometries, objects might appear differently depending on the position of an object within the field of view of a sensor. Recently, lightweight snapshot cameras have been introduced, which capture hyperspectral information in two spatial and one spectral dimension and can be mounted on unmanned aerial vehicles. This study investigates th...

  1. Advances in digital SiPMs and their application in biomedical imaging

    Energy Technology Data Exchange (ETDEWEB)

    Schaart, Dennis R., E-mail: d.r.schaart@tudelft.nl [Delft University of Technology, Faculty of Applied Sciences, Radiation Science and Technology, Mekelweg 15, 2629 JB Delft (Netherlands); Charbon, Edoardo [Delft University of Technology, Faculty of Electrical Engineering, Circuits and Systems, Mekelweg 4, 2628 CD Delft (Netherlands); Frach, Thomas [Philips Digital Photon Counting, Pauwelsstraße 17, 52074 Aachen (Germany); Schulz, Volkmar [Department for Physics of Molecular Imaging Systems, Institute for Experimental Molecular Imaging, RWTH Aachen University, Germany and Philips Research Europe, Aachen (Germany)

    2016-02-11

    Similar to analog silicon photomultipliers (SiPMs), digital SiPMs (dSiPMs) essentially consist of an array of single-photon avalanche photodiodes (SPADs). Instead of a passive quench resistor, however, an active quenching circuit is locally integrated with each SPAD, making the sensor response faster and less sensitive to the gains of the individual SPADs. Moreover, additional circuits for the fully digital acquisition, processing, and readout of optical signals are integrated within the sensor. As a result, dSiPMs offer high photo-detection efficiency, high single-photon time resolution (SPTR), and high uniformity, as well as many practical advantages, such as a very compact form factor, low voltage operation, magnetic field compatibility, high stability of operation, low gain drift, and a high degree of scalability. At the same time, dSiPMs represent a new paradigm in low-level light sensing technology. That is, their fully digital operation makes them true photon counting devices, preserving at least partly the discrete spatio-temporal structure of the information embedded in the optical signal. This means that the operation of dSiPMs can be fully understood only in statistical terms, but also opens up novel possibilities for extracting information from the measured data. So far, the main driver behind the development of dSiPMs has been the detection of scintillation pulses in detectors for time-of-flight (TOF) positron emission tomography (PET). Several types of dSiPM have been developed in recent years. Moreover, first imaging devices based on dSiPMs have been realized by various groups. This review summarizes the main dSiPM concepts and technologies currently under development, provides an overview of the results obtained recently with dSiPMs-based PET and SPECT devices, and presents a critical outlook on the challenges and chances for dSiPMs in future radiomolecular imaging systems.

  2. The second-order differential phase contrast and its retrieval for imaging with x-ray Talbot interferometry

    International Nuclear Information System (INIS)

    Yang Yi; Tang Xiangyang

    2012-01-01

    Purpose: The x-ray differential phase contrast imaging implemented with the Talbot interferometry has recently been reported to be capable of providing tomographic images corresponding to attenuation-contrast, phase-contrast, and dark-field contrast, simultaneously, from a single set of projection data. The authors believe that, along with small-angle x-ray scattering, the second-order phase derivative Φ ″ s (x) plays a role in the generation of dark-field contrast. In this paper, the authors derive the analytic formulae to characterize the contribution made by the second-order phase derivative to the dark-field contrast (namely, second-order differential phase contrast) and validate them via computer simulation study. By proposing a practical retrieval method, the authors investigate the potential of second-order differential phase contrast imaging for extensive applications. Methods: The theoretical derivation starts at assuming that the refractive index decrement of an object can be decomposed into δ=δ s +δ f , where δ f corresponds to the object's fine structures and manifests itself in the dark-field contrast via small-angle scattering. Based on the paraxial Fresnel-Kirchhoff theory, the analytic formulae to characterize the contribution made by δ s , which corresponds to the object's smooth structures, to the dark-field contrast are derived. Through computer simulation with specially designed numerical phantoms, an x-ray differential phase contrast imaging system implemented with the Talbot interferometry is utilized to evaluate and validate the derived formulae. The same imaging system is also utilized to evaluate and verify the capability of the proposed method to retrieve the second-order differential phase contrast for imaging, as well as its robustness over the dimension of detector cell and the number of steps in grating shifting. Results: Both analytic formulae and computer simulations show that, in addition to small-angle scattering, the

  3. The retrieval of two-dimensional distribution of the earth's surface aerodynamic roughness using SAR image and TM thermal infrared image

    Institute of Scientific and Technical Information of China (English)

    ZHANG; Renhua; WANG; Jinfeng; ZHU; Caiying; SUN; Xiaomin

    2004-01-01

    After having analyzed the requirement on the aerodynamic earth's surface roughness in two-dimensional distribution in the research field of interaction between land surface and atmosphere, this paper presents a new way to calculate the aerodynamic roughness using the earth's surface geometric roughness retrieved from SAR (Synthetic Aperture Radar) and TM thermal infrared image data. On the one hand, the SPM (Small Perturbation Model) was used as a theoretical SAR backscattering model to describe the relationship between the SAR backscattering coefficient and the earth's surface geometric roughness and its dielectric constant retrieved from the physical model between the soil thermal inertia and the soil surface moisture with the simultaneous TM thermal infrared image data and the ground microclimate data. On the basis of the SAR image matching with the TM image, the non-volume scattering surface geometric information was obtained from the SPM model at the TM image pixel scale, and the ground pixel surface's equivalent geometric roughness-height standard RMS (Root Mean Square) was achieved from the geometric information by the transformation of the typical topographic factors. The vegetation (wheat, tree) height retrieved from spectrum model was also transferred into its equivalent geometric roughness. A completely two-dimensional distribution map of the equivalent geometric roughness over the experimental area was produced by the data mosaic technique. On the other hand, according to the atmospheric eddy currents theory, the aerodynamic surface roughness was iterated out with the atmosphere stability correction method using the wind and the temperature profiles data measured at several typical fields such as bare soil field and vegetation field. After having analyzed the effect of surface equivalent geometric roughness together with dynamic and thermodynamic factors on the aerodynamic surface roughness within the working area, this paper first establishes a scale

  4. Imaging, scattering, and spectroscopic systems for biomedical optics: Tools for bench top and clinical applications

    Science.gov (United States)

    Cottrell, William J.

    Optical advances have had a profound impact on biology and medicine. The capabilities range from sensing biological analytes to whole animal and subcellular imaging and clinical therapies. The work presented in this thesis describes three independent and multifunctional optical systems, which explore clinical therapy at the tissue level, biological structure at the cell/organelle level, and the function of underlying fundamental cellular processes. First, we present a portable clinical instrument for delivering delta-aminolevulinic acid photodynamic therapy (ALA-PDT) while performing noninvasive spectroscopic monitoring in vivo. Using an off-surface probe, the instrument delivered the treatment beam to a user-defined field on the skin and performed reflectance and fluorescence spectroscopies at two regions within this field. The instrument was used to monitor photosensitizer fluorescence photobleaching, fluorescent photoproduct kinetics, and blood oxygen saturation during a clinical ALA-PDT trial on superficial basal cell carcinoma (sBCC). Protoporphyrin IX and photoproduct fluorescence excited by the 632.8 nm PDT treatment laser was collected between 665 and 775 nm. During a series of brief treatment interruptions at programmable time points, white-light reflectance spectra between 475 and 775 nm were acquired. Fluorescence spectra were corrected for the effects of absorption and scattering, informed by the reflectance measurements, and then decomposed into known fluorophore contributions in real time using a robust singular-value decomposition fitting routine. Reflectance spectra additionally provided information on hemoglobin oxygen saturation. We next describe the incorporation of this instrument into clinical trials at Roswell Park Cancer Institute (Buffalo, NY). In this trial we examined the effects of light irradiance on photodynamic efficiency and pain. The rate of singlet-oxygen production depends on the product of irradiance and photosensitizer and oxygen

  5. Gender differences in autobiographical memory for everyday events: retrieval elicited by SenseCam images versus verbal cues.

    Science.gov (United States)

    St Jacques, Peggy L; Conway, Martin A; Cabeza, Roberto

    2011-10-01

    Gender differences are frequently observed in autobiographical memory (AM). However, few studies have investigated the neural basis of potential gender differences in AM. In the present functional MRI (fMRI) study we investigated gender differences in AMs elicited using dynamic visual images vs verbal cues. We used a novel technology called a SenseCam, a wearable device that automatically takes thousands of photographs. SenseCam differs considerably from other prospective methods of generating retrieval cues because it does not disrupt the ongoing experience. This allowed us to control for potential gender differences in emotional processing and elaborative rehearsal, while manipulating how the AMs were elicited. We predicted that males would retrieve more richly experienced AMs elicited by the SenseCam images vs the verbal cues, whereas females would show equal sensitivity to both cues. The behavioural results indicated that there were no gender differences in subjective ratings of reliving, importance, vividness, emotion, and uniqueness, suggesting that gender differences in brain activity were not due to differences in these measures of phenomenological experience. Consistent with our predictions, the fMRI results revealed that males showed a greater difference in functional activity associated with the rich experience of SenseCam vs verbal cues, than did females.

  6. Electric field tomography for contactless imaging of resistivity in biomedical applications.

    Science.gov (United States)

    Korjenevsky, A V

    2004-02-01

    The technique of contactless imaging of resistivity distribution inside conductive objects, which can be applied in medical diagnostics, has been suggested and analyzed. The method exploits the interaction of a high-frequency electric field with a conductive medium. Unlike electrical impedance tomography, no electric current is injected into the medium from outside. The interaction is accompanied with excitation of high-frequency currents and redistribution of free charges inside the medium leading to strong and irregular perturbation of the field's magnitude outside and inside the object. Along with this the considered interaction also leads to small and regular phase shifts of the field in the area surrounding the object. Measuring these phase shifts using a set of electrodes placed around the object enables us to reconstruct the internal structure of the medium. The basics of this technique, which we name electric field tomography (EFT), are described, simple analytical estimations are made and requirements for measuring equipment are formulated. The realizability of the technique is verified by numerical simulations based on the finite elements method. Results of simulation have confirmed initial estimations and show that in the case of EFT even a comparatively simple filtered backprojection algorithm can be used for reconstructing the static resistivity distribution in biological tissues.

  7. Synthesis and characterization of bioresorbable calcium phosphosilicate nanocomposite particles for fluorescence imaging and biomedical applications

    Science.gov (United States)

    Morgan, Thomas T.

    Organically doped calcium phosphosilicate nanoparticles (CPSNPs) were developed and characterized, driven by the need for non-toxic vectors for drug delivery and fluorescence biological imaging applications. In particular, advancement in drug delivery for the chemotherapeutic treatment of cancers is required to increase drug efficacy and improve patient quality of life. Additionally, brighter and more photostable fluorophores are needed to meet demands for improved sensitivity and experimental diversity, which may lead to improvements in early detection of solid tumors and advancement in understanding of biological processes. A literature survey on the state of the field for nanoparticle based biological fluorescence imaging and drug delivery is presented in Chapter 1. Chapter 2 focuses on the characterization techniques used in this work. The development and optical characterization of 20-40 nm diameter, citrate functionalized Cy3 amidite doped calcium phosphosilicate nanoparticles (Cy3 CPSNPs) for in vitro fluorescence imaging is outlined in Chapters 3 and 4, respectively. In particular, sodium citrate was used to functionalize the surface and provide electrosteric dispersion of these particles. CPSNPs stabilized with sodium citrate routinely exhibited highly negative zeta potentials greater than -25 mV in magnitude. Furthermore, the fluorescence quantum yield of the encapsulated fluorophore was improved by more than 4.5-fold when compared to the unencapsulated dye. The bioimaging and drug delivery capability of CPSNPs was explored. Cy3 CPSNPs dissolved quickly in the acidic environment experienced during endocytosis, releasing the encapsulated fluorophore. This is consistent with solution phase experiments that show the particles are dissolved at pH 5. CPSNPs loaded with fluorescein and a hydrophobic growth inhibitor, ceramide C6, proved the ability to simultaneously image and delivery of the hydrophobic drug to cells in vitro. Chapter 5 examined the colloidal

  8. Contrast agent based on nano-emulsion for targeted biomedical imaging

    International Nuclear Information System (INIS)

    Attia, Mohamed

    2016-01-01

    X-ray imaging agents are essential in combination with X-ray computed tomography to improve contrast enhancement aiming at providing complete visualization of blood vessels and giving structural and functional information on lesions allowing the detection of a tumor. As well as it is fundamental tool to discriminate between healthy cells and pathogens. We successfully limit the problems presented in commercial X-ray contrast agents like poor contrasting in Fenestra VC associated with short blood circulation time and to avoid rapid renal elimination from the body as found in Xenetix (Iobitriol). We developed nontoxic and blood pool iodine-containing nano-emulsion contrast agents serving in preclinical X-ray μ-CT imaging such as, a- Tocopherol (vitamin E), Cholecalciferol (vitamin D3), Castor oil, Capmul MCMC8 oil and oleic acid. Those formulated nano emulsions were prepared by low energy spontaneous emulsification technic with slight modification for each platform. They showed new specific features rendering them promising agents in in vivo experiments as improving the balance between the efficacy and the toxicity of targeted therapeutic interventions. We investigate the effect of size and the chemical composition of the nanoparticles on their biodistribution, pharmacokinetics and toxicity. They demonstrated that the chemical structures of the droplet's cores have significant role in targeting for example vitamin E was mainly accumulated in liver and castor oil formulation was passively accumulated in spleen explaining the proof-of-concept of EPR effect. On the other hand, two different platform sizes of Cholecalciferol molecule revealing that no real impact on the pharmacokinetics and biodistribution but presented remarkable effect on the toxicity. Of particular interest is studying the effect of the surface charge of nanoparticles on their biodistribution, this is why oleic acid nano-emulsion was selected to proceed this study by presence of amphiphilic polymer

  9. System and technique for retrieving depth information about a surface by projecting a composite image of modulated light patterns

    Science.gov (United States)

    Hassebrook, Laurence G. (Inventor); Lau, Daniel L. (Inventor); Guan, Chun (Inventor)

    2010-01-01

    A technique, associated system and program code, for retrieving depth information about at least one surface of an object, such as an anatomical feature. Core features include: projecting a composite image comprising a plurality of modulated structured light patterns, at the anatomical feature; capturing an image reflected from the surface; and recovering pattern information from the reflected image, for each of the modulated structured light patterns. Pattern information is preferably recovered for each modulated structured light pattern used to create the composite, by performing a demodulation of the reflected image. Reconstruction of the surface can be accomplished by using depth information from the recovered patterns to produce a depth map/mapping thereof. Each signal waveform used for the modulation of a respective structured light pattern, is distinct from each of the other signal waveforms used for the modulation of other structured light patterns of a composite image; these signal waveforms may be selected from suitable types in any combination of distinct signal waveforms, provided the waveforms used are uncorrelated with respect to each other. The depth map/mapping to be utilized in a host of applications, for example: displaying a 3-D view of the object; virtual reality user-interaction interface with a computerized device; face--or other animal feature or inanimate object--recognition and comparison techniques for security or identification purposes; and 3-D video teleconferencing/telecollaboration.

  10. Coupled Retrieval of Liquid Water Cloud and Above-Cloud Aerosol Properties Using the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI)

    Science.gov (United States)

    Xu, Feng; van Harten, Gerard; Diner, David J.; Davis, Anthony B.; Seidel, Felix C.; Rheingans, Brian; Tosca, Mika; Alexandrov, Mikhail D.; Cairns, Brian; Ferrare, Richard A.; Burton, Sharon P.; Fenn, Marta A.; Hostetler, Chris A.; Wood, Robert; Redemann, Jens

    2018-03-01

    An optimization algorithm is developed to retrieve liquid water cloud properties including cloud optical depth (COD), droplet size distribution and cloud top height (CTH), and above-cloud aerosol properties including aerosol optical depth (AOD), single-scattering albedo, and microphysical properties from sweep-mode observations by Jet Propulsion Laboratory's Airborne Multiangle SpectroPolarimetric Imager (AirMSPI) instrument. The retrieval is composed of three major steps: (1) initial estimate of the mean droplet size distribution across the entire image of 80-100 km along track by 10-25 km across track from polarimetric cloudbow observations, (2) coupled retrieval of image-scale cloud and above-cloud aerosol properties by fitting the polarimetric data at all observation angles, and (3) iterative retrieval of 1-D radiative transfer-based COD and droplet size distribution at pixel scale (25 m) by establishing relationships between COD and droplet size and fitting the total radiance measurements. Our retrieval is tested using 134 AirMSPI data sets acquired during the National Aeronautics and Space Administration (NASA) field campaign ObseRvations of Aerosols above CLouds and their intEractionS. The retrieved above-cloud AOD and CTH are compared to coincident HSRL-2 (HSRL-2, NASA Langley Research Center) data, and COD and droplet size distribution parameters (effective radius reff and effective variance veff) are compared to coincident Research Scanning Polarimeter (RSP) (NASA Goddard Institute for Space Studies) data. Mean absolute differences between AirMSPI and HSRL-2 retrievals of above-cloud AOD at 532 nm and CTH are 0.03 and mean absolute differences between RSP and AirMSPI retrievals of COD, reff, and veff in the cloudbow area are 2.33, 0.69 μm, and 0.020, respectively. Neglect of smoke aerosols above cloud leads to an underestimate of image-averaged COD by 15%.

  11. An Image Retrieval and Processing Expert System for the World Wide Web

    Science.gov (United States)

    Rodriguez, Ricardo; Rondon, Angelica; Bruno, Maria I.; Vasquez, Ramon

    1998-01-01

    This paper presents a system that is being developed in the Laboratory of Applied Remote Sensing and Image Processing at the University of P.R. at Mayaguez. It describes the components that constitute its architecture. The main elements are: a Data Warehouse, an Image Processing Engine, and an Expert System. Together, they provide a complete solution to researchers from different fields that make use of images in their investigations. Also, since it is available to the World Wide Web, it provides remote access and processing of images.

  12. Mining big data sets of plankton images: a zero-shot learning approach to retrieve labels without training data

    Science.gov (United States)

    Orenstein, E. C.; Morgado, P. M.; Peacock, E.; Sosik, H. M.; Jaffe, J. S.

    2016-02-01

    Technological advances in instrumentation and computing have allowed oceanographers to develop imaging systems capable of collecting extremely large data sets. With the advent of in situ plankton imaging systems, scientists must now commonly deal with "big data" sets containing tens of millions of samples spanning hundreds of classes, making manual classification untenable. Automated annotation methods are now considered to be the bottleneck between collection and interpretation. Typically, such classifiers learn to approximate a function that predicts a predefined set of classes for which a considerable amount of labeled training data is available. The requirement that the training data span all the classes of concern is problematic for plankton imaging systems since they sample such diverse, rapidly changing populations. These data sets may contain relatively rare, sparsely distributed, taxa that will not have associated training data; a classifier trained on a limited set of classes will miss these samples. The computer vision community, leveraging advances in Convolutional Neural Networks (CNNs), has recently attempted to tackle such problems using "zero-shot" object categorization methods. Under a zero-shot framework, a classifier is trained to map samples onto a set of attributes rather than a class label. These attributes can include visual and non-visual information such as what an organism is made out of, where it is distributed globally, or how it reproduces. A second stage classifier is then used to extrapolate a class. In this work, we demonstrate a zero-shot classifier, implemented with a CNN, to retrieve out-of-training-set labels from images. This method is applied to data from two continuously imaging, moored instruments: the Scripps Plankton Camera System (SPCS) and the Imaging FlowCytobot (IFCB). Results from simulated deployment scenarios indicate zero-shot classifiers could be successful at recovering samples of rare taxa in image sets. This

  13. Phase object retrieval through scattering medium

    Science.gov (United States)

    Zhao, Ming; Zhao, Meijing; Wu, Houde; Xu, Wenhai

    2018-05-01

    Optical imaging through a scattering medium has been an interesting and important research topic, especially in the field of biomedical imaging. However, it is still a challenging task due to strong scattering. This paper proposes to recover the phase object behind the scattering medium from one single-shot speckle intensity image using calibrated transmission matrices (TMs). We construct the forward model as a non-linear mapping, since the intensity image loses the phase information, and then a generalized phase retrieval algorithm is employed to recover the hidden object. Moreover, we show that a phase object can be reconstructed with a small portion of the speckle image captured by the camera. The simulation is performed to demonstrate our scheme and test its performance. Finally, a real experiment is set up, we measure the TMs from the scattering medium, and then use it to reconstruct the hidden object. We show that a phase object of size 32 × 32 is retrieved from 150 × 150 speckle grains, which is only 1/50 of the speckles area. We believe our proposed method can benefit the community of imaging through the scattering medium.

  14. Anatomy for Biomedical Engineers

    Science.gov (United States)

    Carmichael, Stephen W.; Robb, Richard A.

    2008-01-01

    There is a perceived need for anatomy instruction for graduate students enrolled in a biomedical engineering program. This appeared especially important for students interested in and using medical images. These students typically did not have a strong background in biology. The authors arranged for students to dissect regions of the body that…

  15. Image storage, cataloguing and retrieval using a personal computer database software application

    International Nuclear Information System (INIS)

    Lewis, G.; Howman-Giles, R.

    1999-01-01

    Full text: Interesting images and cases are collected and collated by most nuclear medicine practitioners throughout the world. Changing imaging technology has altered the way in which images may be presented and are reported, with less reliance on 'hard copy' for both reporting and archiving purposes. Digital image generation and storage is rapidly replacing film in both radiological and nuclear medicine practice. A personal computer database based interesting case filing system is described and demonstrated. The digital image storage format allows instant access to both case information (e.g. history and examination, scan report or teaching point) and the relevant images. The database design allows rapid selection of cases and images appropriate to a particular diagnosis, scan type, age or other search criteria. Correlative X-ray, CT, MRI and ultrasound images can also be stored and accessed. The application is in use at The New Children's Hospital as an aid to postgraduate medical education, with new cases being regularly added to the database

  16. Telemedicine optoelectronic biomedical data processing system

    Science.gov (United States)

    Prosolovska, Vita V.

    2010-08-01

    The telemedicine optoelectronic biomedical data processing system is created to share medical information for the control of health rights and timely and rapid response to crisis. The system includes the main blocks: bioprocessor, analog-digital converter biomedical images, optoelectronic module for image processing, optoelectronic module for parallel recording and storage of biomedical imaging and matrix screen display of biomedical images. Rated temporal characteristics of the blocks defined by a particular triggering optoelectronic couple in analog-digital converters and time imaging for matrix screen. The element base for hardware implementation of the developed matrix screen is integrated optoelectronic couples produced by selective epitaxy.

  17. Biomedical Applications of Mid-Infrared Spectroscopic Imaging and Multivariate Data Analysis: Contribution to the Understanding of Diabetes Pathogenesis

    Science.gov (United States)

    Aboualizadeh, Ebrahim

    Diabetic retinopathy (DR) is a microvascular complication of diabetes and a leading cause of adult vision loss. Although a great deal of progress has been made in ophthalmological examinations and clinical approaches to detect the signs of retinopathy in patients with diabetes, there still remain outstanding questions regarding the molecular and biochemical changes involved. To discover the biochemical mechanisms underlying the development and progression of changes in the retina as a result of diabetes, a more comprehensive understanding of the bio-molecular processes, in individual retinal cells subjected to hyperglycemia, is required. Animal models provide a suitable resource for temporal detection of the underlying pathophysiological and biochemical changes associated with DR, which is not fully attainable in human studies. In the present study, I aimed to determine the nature of diabetes-induced, highly localized biochemical changes in the retinal tissue from Ins2Akita/+ (Akita/+; a model of Type I diabetes) male mice with different duration of diabetes. Employing label-free, spatially resolved Fourier transform infrared (FT-IR) imaging engaged with chemometric tools enabled me to identify temporal-dependent reproducible biomarkers of the diabetic retinal tissue from mice with 6 or 12 weeks, and 6 or 10 months of diabetes. I report, for the first time, the origin of molecular changes in the biochemistry of individual retinal layers with different duration of diabetes. A robust classification between distinctive retinal layers - namely photoreceptor layer (PRL), outer plexiform layer (OPL), inner nuclear layer (INL), and inner plexiform layer (IPL) - and associated temporal-dependent spectral biomarkers, were delineated. Spatially-resolved super resolution chemical images revealed oxidative stress-induced structural and morphological alterations within the nucleus of the photoreceptors. Comparison among the PRL, OPL, INL, and IPL suggested that the

  18. Rotation Invariant Color Retrieval

    OpenAIRE

    Swapna Borde; Udhav Bhosle

    2013-01-01

    The new technique for image retrieval using the color features extracted from images based on LogHistogram is proposed. The proposed technique is compared with Global color histogram and histogram ofcorners .It has been observed that number of histogram bins used for retrieval comparison of proposedtechnique (Log Histogram)is less as compared to Global Color Histogram and Histogram of corners. Theexperimental results on a database of 792 images with 11 classes indicate that proposed method (L...

  19. Retrieving atmospheric dust opacity on Mars by imaging spectroscopy at large angles

    Science.gov (United States)

    Douté, S.; Ceamanos, X.; Appéré, T.

    2013-09-01

    We propose a new method to retrieve the optical depth of Martian aerosols (AOD) from OMEGA and CRISM hyperspectral imagery at a reference wavelength of 1 μm. Our method works even if the underlying surface is completely made of minerals, corresponding to a low contrast between surface and atmospheric dust, while being observed at a fixed geometry. Minimizing the effect of the surface reflectance properties on the AOD retrieval is the second principal asset of our method. The method is based on the parametrization of the radiative coupling between particles and gas determining, with local altimetry, acquisition geometry, and the meteorological situation, the absorption band depth of gaseous CO2. Because the last three factors can be predicted to some extent, we can define a new parameter β that expresses specifically the strength of the gas-aerosols coupling while directly depending on the AOD. Combining estimations of β and top of the atmosphere radiance values extracted from the observed spectra within the CO2 gas band at 2 μm, we evaluate the AOD and the surface reflectance by radiative transfer inversion. One should note that practically β can be estimated for a large variety of mineral or icy surfaces with the exception of CO2 ice when its 2 μm solid band is not sufficiently saturated. Validation of the proposed method shows that it is reliable if two conditions are fulfilled: (i) the observation conditions provide large incidence or/and emergence angles (ii) the aerosols are vertically well mixed in the atmosphere. Experiments conducted on OMEGA nadir looking observations as well as CRISM multi-angular acquisitions with incidence angles higher than 65° in the first case and 33° in the second case produce very satisfactory results. Finally in a companion paper the method is applied to monitoring atmospheric dust spring activity at high southern latitudes on Mars using OMEGA.

  20. ALDF Data Retrieval Algorithms for Validating the Optical Transient Detector (OTD) and the Lightning Imaging Sensor (LIS)

    Science.gov (United States)

    Koshak, W. J.; Blakeslee, R. J.; Bailey, J. C.

    1997-01-01

    A linear algebraic solution is provided for the problem of retrieving the location and time of occurrence of lightning ground strikes from in Advanced Lightning Direction Finder (ALDF) network. The ALDF network measures field strength, magnetic bearing, and arrival time of lightning radio emissions and solutions for the plane (i.e.. no Earth curvature) are provided that implement all of these measurements. The accuracy of the retrieval method is tested using computer-simulated data sets and the relative influence of bearing and arrival time data on the outcome of the final solution is formally demonstrated. The algorithm is sufficiently accurate to validate NASA's Optical Transient Detector (OTD) and Lightning Imaging System (LIS). We also introduce a quadratic planar solution that is useful when only three arrival time measurements are available. The algebra of the quadratic root results are examined in detail to clarify what portions of the analysis region lead to fundamental ambiguities in source location. Complex root results are shown to be associated with the presence of measurement errors when the lightning source lies near an outer sensor baseline of the ALDF network. For arbitrary noncollinear network geometries and in the absence of measurement errors, it is shown that the two quadratic roots are equivalent (no source location ambiguity) on the outer sensor baselines. The accuracy of the quadratic planar method is tested with computer-generated data sets and the results are generally better than those obtained from the three station linear planar method when bearing errors are about 2 degrees.

  1. Optimized and secure technique for multiplexing QR code images of single characters: application to noiseless messages retrieval

    International Nuclear Information System (INIS)

    Trejos, Sorayda; Barrera, John Fredy; Torroba, Roberto

    2015-01-01

    We present for the first time an optical encrypting–decrypting protocol for recovering messages without speckle noise. This is a digital holographic technique using a 2f scheme to process QR codes entries. In the procedure, letters used to compose eventual messages are individually converted into a QR code, and then each QR code is divided into portions. Through a holographic technique, we store each processed portion. After filtering and repositioning, we add all processed data to create a single pack, thus simplifying the handling and recovery of multiple QR code images, representing the first multiplexing procedure applied to processed QR codes. All QR codes are recovered in a single step and in the same plane, showing neither cross-talk nor noise problems as in other methods. Experiments have been conducted using an interferometric configuration and comparisons between unprocessed and recovered QR codes have been performed, showing differences between them due to the involved processing. Recovered QR codes can be successfully scanned, thanks to their noise tolerance. Finally, the appropriate sequence in the scanning of the recovered QR codes brings a noiseless retrieved message. Additionally, to procure maximum security, the multiplexed pack could be multiplied by a digital diffuser as to encrypt it. The encrypted pack is easily decoded by multiplying the multiplexing with the complex conjugate of the diffuser. As it is a digital operation, no noise is added. Therefore, this technique is threefold robust, involving multiplexing, encryption, and the need of a sequence to retrieve the outcome. (paper)

  2. Optimized and secure technique for multiplexing QR code images of single characters: application to noiseless messages retrieval

    Science.gov (United States)

    Trejos, Sorayda; Fredy Barrera, John; Torroba, Roberto

    2015-08-01

    We present for the first time an optical encrypting-decrypting protocol for recovering messages without speckle noise. This is a digital holographic technique using a 2f scheme to process QR codes entries. In the procedure, letters used to compose eventual messages are individually converted into a QR code, and then each QR code is divided into portions. Through a holographic technique, we store each processed portion. After filtering and repositioning, we add all processed data to create a single pack, thus simplifying the handling and recovery of multiple QR code images, representing the first multiplexing procedure applied to processed QR codes. All QR codes are recovered in a single step and in the same plane, showing neither cross-talk nor noise problems as in other methods. Experiments have been conducted using an interferometric configuration and comparisons between unprocessed and recovered QR codes have been performed, showing differences between them due to the involved processing. Recovered QR codes can be successfully scanned, thanks to their noise tolerance. Finally, the appropriate sequence in the scanning of the recovered QR codes brings a noiseless retrieved message. Additionally, to procure maximum security, the multiplexed pack could be multiplied by a digital diffuser as to encrypt it. The encrypted pack is easily decoded by multiplying the multiplexing with the complex conjugate of the diffuser. As it is a digital operation, no noise is added. Therefore, this technique is threefold robust, involving multiplexing, encryption, and the need of a sequence to retrieve the outcome.

  3. A fully automatic end-to-end method for content-based image retrieval of CT scans with similar liver lesion annotations.

    Science.gov (United States)

    Spanier, A B; Caplan, N; Sosna, J; Acar, B; Joskowicz, L

    2018-01-01

    The goal of medical content-based image retrieval (M-CBIR) is to assist radiologists in the decision-making process by retrieving medical cases similar to a given image. One of the key interests of radiologists is lesions and their annotations, since the patient treatment depends on the lesion diagnosis. Therefore, a key feature of M-CBIR systems is the retrieval of scans with the most similar lesion annotations. To be of value, M-CBIR systems should be fully automatic to handle large case databases. We present a fully automatic end-to-end method for the retrieval of CT scans with similar liver lesion annotations. The input is a database of abdominal CT scans labeled with liver lesions, a query CT scan, and optionally one radiologist-specified lesion annotation of interest. The output is an ordered list of the database CT scans with the most similar liver lesion annotations. The method starts by automatically segmenting the liver in the scan. It then extracts a histogram-based features vector from the segmented region, learns the features' relative importance, and ranks the database scans according to the relative importance measure. The main advantages of our method are that it fully automates the end-to-end querying process, that it uses simple and efficient techniques that are scalable to large datasets, and that it produces quality retrieval results using an unannotated CT scan. Our experimental results on 9 CT queries on a dataset of 41 volumetric CT scans from the 2014 Image CLEF Liver Annotation Task yield an average retrieval accuracy (Normalized Discounted Cumulative Gain index) of 0.77 and 0.84 without/with annotation, respectively. Fully automatic end-to-end retrieval of similar cases based on image information alone, rather that on disease diagnosis, may help radiologists to better diagnose liver lesions.

  4. Biomedical photonics handbook biomedical diagnostics

    CERN Document Server

    Vo-Dinh, Tuan

    2014-01-01

    Shaped by Quantum Theory, Technology, and the Genomics RevolutionThe integration of photonics, electronics, biomaterials, and nanotechnology holds great promise for the future of medicine. This topic has recently experienced an explosive growth due to the noninvasive or minimally invasive nature and the cost-effectiveness of photonic modalities in medical diagnostics and therapy. The second edition of the Biomedical Photonics Handbook presents fundamental developments as well as important applications of biomedical photonics of interest to scientists, engineers, manufacturers, teachers, studen

  5. COLOR IMAGE RETRIEVAL BASED ON FEATURE FUSION THROUGH MULTIPLE LINEAR REGRESSION ANALYSIS

    Directory of Open Access Journals (Sweden)

    K. Seetharaman

    2015-08-01

    Full Text Available This paper proposes a novel technique based on feature fusion using multiple linear regression analysis, and the least-square estimation method is employed to estimate the parameters. The given input query image is segmented into various regions according to the structure of the image. The color and texture features are extracted on each region of the query image, and the features are fused together using the multiple linear regression model. The estimated parameters of the model, which is modeled based on the features, are formed as a vector called a feature vector. The Canberra distance measure is adopted to compare the feature vectors of the query and target images. The F-measure is applied to evaluate the performance of the proposed technique. The obtained results expose that the proposed technique is comparable to the other existing techniques.

  6. Estimation of cloud optical thickness by processing SEVIRI images and implementing a semi analytical cloud property retrieval algorithm

    Science.gov (United States)

    Pandey, P.; De Ridder, K.; van Lipzig, N.

    2009-04-01

    Clouds play a very important role in the Earth's climate system, as they form an intermediate layer between Sun and the Earth. Satellite remote sensing systems are the only means to provide information about clouds on large scales. The geostationary satellite, Meteosat Second Generation (MSG) has onboard an imaging radiometer, the Spinning Enhanced Visible and Infrared Imager (SEVIRI). SEVIRI is a 12 channel imager, with 11 channels observing the earth's full disk with a temporal resolution of 15 min and spatial resolution of 3 km at nadir, and a high resolution visible (HRV) channel. The visible channels (0.6 µm and 0.81 µm) and near infrared channel (1.6µm) of SEVIRI are being used to retrieve the cloud optical thickness (COT). The study domain is over Europe covering the region between 35°N - 70°N and 10°W - 30°E. SEVIRI level 1.5 images over this domain are being acquired from the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) archive. The processing of this imagery, involves a number of steps before estimating the COT. The steps involved in pre-processing are as follows. First, the digital count number is acquired from the imagery. Image geo-coding is performed in order to relate the pixel positions to the corresponding longitude and latitude. Solar zenith angle is determined as a function of latitude and time. The radiometric conversion is done using the values of offsets and slopes of each band. The values of radiance obtained are then used to calculate the reflectance for channels in the visible spectrum using the information of solar zenith angle. An attempt is made to estimate the COT from the observed radiances. A semi analytical algorithm [Kokhanovsky et al., 2003] is implemented for the estimation of cloud optical thickness from the visible spectrum of light intensity reflected from clouds. The asymptotical solution of the radiative transfer equation, for clouds with large optical thickness, is the basis of

  7. Informatics in radiology: An open-source and open-access cancer biomedical informatics grid annotation and image markup template builder.

    Science.gov (United States)

    Mongkolwat, Pattanasak; Channin, David S; Kleper, Vladimir; Rubin, Daniel L

    2012-01-01

    In a routine clinical environment or clinical trial, a case report form or structured reporting template can be used to quickly generate uniform and consistent reports. Annotation and image markup (AIM), a project supported by the National Cancer Institute's cancer biomedical informatics grid, can be used to collect information for a case report form or structured reporting template. AIM is designed to store, in a single information source, (a) the description of pixel data with use of markups or graphical drawings placed on the image, (b) calculation results (which may or may not be directly related to the markups), and (c) supplemental information. To facilitate the creation of AIM annotations with data entry templates, an AIM template schema and an open-source template creation application were developed to assist clinicians, image researchers, and designers of clinical trials to quickly create a set of data collection items, thereby ultimately making image information more readily accessible.

  8. Content-based retrieval of brain tumor in contrast-enhanced MRI images using tumor margin information and learned distance metric.

    Science.gov (United States)

    Yang, Wei; Feng, Qianjin; Yu, Mei; Lu, Zhentai; Gao, Yang; Xu, Yikai; Chen, Wufan

    2012-11-01

    A content-based image retrieval (CBIR) method for T1-weighted contrast-enhanced MRI (CE-MRI) images of brain tumors is presented for diagnosis aid. The method is thoroughly evaluated on a large image dataset. Using the tumor region as a query, the authors' CBIR system attempts to retrieve tumors of the same pathological category. Aside from commonly used features such as intensity, texture, and shape features, the authors use a margin information descriptor (MID), which is capable of describing the characteristics of tissue surrounding a tumor, for representing image contents. In addition, the authors designed a distance metric learning algorithm called Maximum mean average Precision Projection (MPP) to maximize the smooth approximated mean average precision (mAP) to optimize retrieval performance. The effectiveness of MID and MPP algorithms was evaluated using a brain CE-MRI dataset consisting of 3108 2D scans acquired from 235 patients with three categories of brain tumors (meningioma, glioma, and pituitary tumor). By combining MID and other features, the mAP of retrieval increased by more than 6% with the learned distance metrics. The distance metric learned by MPP significantly outperformed the other two existing distance metric learning methods in terms of mAP. The CBIR system using the proposed strategies achieved a mAP of 87.3% and a precision of 89.3% when top 10 images were returned by the system. Compared with scale-invariant feature transform, the MID, which uses the intensity profile as descriptor, achieves better retrieval performance. Incorporating tumor margin information represented by MID with the distance metric learned by the MPP algorithm can substantially improve the retrieval performance for brain tumors in CE-MRI.

  9. Efficient random access high resolution region-of-interest (ROI) image retrieval using backward coding of wavelet trees (BCWT)

    Science.gov (United States)

    Corona, Enrique; Nutter, Brian; Mitra, Sunanda; Guo, Jiangling; Karp, Tanja

    2008-03-01

    Efficient retrieval of high quality Regions-Of-Interest (ROI) from high resolution medical images is essential for reliable interpretation and accurate diagnosis. Random access to high quality ROI from codestreams is becoming an essential feature in many still image compression applications, particularly in viewing diseased areas from large medical images. This feature is easier to implement in block based codecs because of the inherent spatial independency of the code blocks. This independency implies that the decoding order of the blocks is unimportant as long as the position for each is properly identified. In contrast, wavelet-tree based codecs naturally use some interdependency that exploits the decaying spectrum model of the wavelet coefficients. Thus one must keep track of the decoding order from level to level with such codecs. We have developed an innovative multi-rate image subband coding scheme using "Backward Coding of Wavelet Trees (BCWT)" which is fast, memory efficient, and resolution scalable. It offers far less complexity than many other existing codecs including both, wavelet-tree, and block based algorithms. The ROI feature in BCWT is implemented through a transcoder stage that generates a new BCWT codestream containing only the information associated with the user-defined ROI. This paper presents an efficient technique that locates a particular ROI within the BCWT coded domain, and decodes it back to the spatial domain. This technique allows better access and proper identification of pathologies in high resolution images since only a small fraction of the codestream is required to be transmitted and analyzed.

  10. Physical retrieval of precipitation water contents from Special Sensor Microwave/Imager (SSM/I) data. Part 2: Retrieval method and applications (report version)

    Science.gov (United States)

    Olson, William S.

    1990-01-01

    A physical retrieval method for estimating precipitating water distributions and other geophysical parameters based upon measurements from the DMSP-F8 SSM/I is developed. Three unique features of the retrieval method are (1) sensor antenna patterns are explicitly included to accommodate varying channel resolution; (2) precipitation-brightness temperature relationships are quantified using the cloud ensemble/radiative parameterization; and (3) spatial constraints are imposed for certain background parameters, such as humidity, which vary more slowly in the horizontal than the cloud and precipitation water contents. The general framework of the method will facilitate the incorporation of measurements from the SSMJT, SSM/T-2 and geostationary infrared measurements, as well as information from conventional sources (e.g., radiosondes) or numerical forecast model fields.

  11. Designing an image retrieval interface for abstract concepts within the domain of journalism

    NARCIS (Netherlands)

    R. Besseling (Ron)

    2011-01-01

    htmlabstractResearch has shown that users have difficulties finding images which illustrate abstract concepts. We carried out a user study that confirms the finding that the selection of search terms is perceived difficult and that users find the subjectivity of abstract concepts problematic. In

  12. Multimedia human brain database system for surgical candid