WorldWideScience

Sample records for medical image databases

  1. 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.

  2. Constructing Benchmark Databases and Protocols for Medical Image Analysis: Diabetic Retinopathy

    Directory of Open Access Journals (Sweden)

    Tomi Kauppi

    2013-01-01

    Full Text Available We address the performance evaluation practices for developing medical image analysis methods, in particular, how to establish and share databases of medical images with verified ground truth and solid evaluation protocols. Such databases support the development of better algorithms, execution of profound method comparisons, and, consequently, technology transfer from research laboratories to clinical practice. For this purpose, we propose a framework consisting of reusable methods and tools for the laborious task of constructing a benchmark database. We provide a software tool for medical image annotation helping to collect class label, spatial span, and expert's confidence on lesions and a method to appropriately combine the manual segmentations from multiple experts. The tool and all necessary functionality for method evaluation are provided as public software packages. As a case study, we utilized the framework and tools to establish the DiaRetDB1 V2.1 database for benchmarking diabetic retinopathy detection algorithms. The database contains a set of retinal images, ground truth based on information from multiple experts, and a baseline algorithm for the detection of retinopathy lesions.

  3. Quantitative imaging features: extension of the oncology medical image database

    Science.gov (United States)

    Patel, M. N.; Looney, P. T.; Young, K. C.; Halling-Brown, M. D.

    2015-03-01

    Radiological imaging is fundamental within the healthcare industry and has become routinely adopted for diagnosis, disease monitoring and treatment planning. With the advent of digital imaging modalities and the rapid growth in both diagnostic and therapeutic imaging, the ability to be able to harness this large influx of data is of paramount importance. The Oncology Medical Image Database (OMI-DB) was created to provide a centralized, fully annotated dataset for research. The database contains both processed and unprocessed images, associated data, and annotations and where applicable expert determined ground truths describing features of interest. Medical imaging provides the ability to detect and localize many changes that are important to determine whether a disease is present or a therapy is effective by depicting alterations in anatomic, physiologic, biochemical or molecular processes. Quantitative imaging features are sensitive, specific, accurate and reproducible imaging measures of these changes. Here, we describe an extension to the OMI-DB whereby a range of imaging features and descriptors are pre-calculated using a high throughput approach. The ability to calculate multiple imaging features and data from the acquired images would be valuable and facilitate further research applications investigating detection, prognosis, and classification. The resultant data store contains more than 10 million quantitative features as well as features derived from CAD predictions. Theses data can be used to build predictive models to aid image classification, treatment response assessment as well as to identify prognostic imaging biomarkers.

  4. Multimodality medical image database for temporal lobe epilepsy

    Science.gov (United States)

    Siadat, Mohammad-Reza; Soltanian-Zadeh, Hamid; Fotouhi, Farshad A.; Elisevich, Kost

    2003-05-01

    This paper presents the development of a human brain multi-modality database for surgical candidacy determination in temporal lobe epilepsy. The focus of the paper is on content-based image management, navigation and retrieval. Several medical image-processing methods including our newly developed segmentation method are utilized for information extraction/correlation and indexing. The input data includes T1-, T2-Weighted and FLAIR MRI and ictal/interictal SPECT modalities with associated clinical data and EEG data analysis. The database can answer queries regarding issues such as the correlation between the attribute X of the entity Y and the outcome of a temporal lobe epilepsy surgery. The entity Y can be a brain anatomical structure such as the hippocampus. The attribute X can be either a functionality feature of the anatomical structure Y, calculated with SPECT modalities, such as signal average, or a volumetric/morphological feature of the entity Y such as volume or average curvature. The outcome of the surgery can be any surgery assessment such as non-verbal Wechsler memory quotient. A determination is made regarding surgical candidacy by analysis of both textual and image data. The current database system suggests a surgical determination for the cases with relatively small hippocampus and high signal intensity average on FLAIR images within the hippocampus. This indication matches the neurosurgeons expectations/observations. Moreover, as the database gets more populated with patient profiles and individual surgical outcomes, using data mining methods one may discover partially invisible correlations between the contents of different modalities of data and the outcome of the surgery.

  5. Development of educational image databases and e-books for medical physics training.

    Science.gov (United States)

    Tabakov, S; Roberts, V C; Jonsson, B-A; Ljungberg, M; Lewis, C A; Wirestam, R; Strand, S-E; Lamm, I-L; Milano, F; Simmons, A; Deane, C; Goss, D; Aitken, V; Noel, A; Giraud, J-Y; Sherriff, S; Smith, P; Clarke, G; Almqvist, M; Jansson, T

    2005-09-01

    Medical physics education and training requires the use of extensive imaging material and specific explanations. These requirements provide an excellent background for application of e-Learning. The EU projects Consortia EMERALD and EMIT developed five volumes of such materials, now used in 65 countries. EMERALD developed e-Learning materials in three areas of medical physics (X-ray diagnostic radiology, nuclear medicine and radiotherapy). EMIT developed e-Learning materials in two further areas: ultrasound and magnetic resonance imaging. This paper describes the development of these e-Learning materials (consisting of e-books and educational image databases). The e-books include tasks helping studying of various equipment and methods. The text of these PDF e-books is hyperlinked with respective images. The e-books are used through the readers' own Internet browser. Each Image Database (IDB) includes a browser, which displays hundreds of images of equipment, block diagrams and graphs, image quality examples, artefacts, etc. Both the e-books and IDB are engraved on five separate CD-ROMs. Demo of these materials can be taken from www.emerald2.net.

  6. Combined semantic and similarity search in medical image databases

    Science.gov (United States)

    Seifert, Sascha; Thoma, Marisa; Stegmaier, Florian; Hammon, Matthias; Kramer, Martin; Huber, Martin; Kriegel, Hans-Peter; Cavallaro, Alexander; Comaniciu, Dorin

    2011-03-01

    The current diagnostic process at hospitals is mainly based on reviewing and comparing images coming from multiple time points and modalities in order to monitor disease progression over a period of time. However, for ambiguous cases the radiologist deeply relies on reference literature or second opinion. Although there is a vast amount of acquired images stored in PACS systems which could be reused for decision support, these data sets suffer from weak search capabilities. Thus, we present a search methodology which enables the physician to fulfill intelligent search scenarios on medical image databases combining ontology-based semantic and appearance-based similarity search. It enabled the elimination of 12% of the top ten hits which would arise without taking the semantic context into account.

  7. Intelligent distributed medical image management

    Science.gov (United States)

    Garcia, Hong-Mei C.; Yun, David Y.

    1995-05-01

    The rapid advancements in high performance global communication have accelerated cooperative image-based medical services to a new frontier. Traditional image-based medical services such as radiology and diagnostic consultation can now fully utilize multimedia technologies in order to provide novel services, including remote cooperative medical triage, distributed virtual simulation of operations, as well as cross-country collaborative medical research and training. Fast (efficient) and easy (flexible) retrieval of relevant images remains a critical requirement for the provision of remote medical services. This paper describes the database system requirements, identifies technological building blocks for meeting the requirements, and presents a system architecture for our target image database system, MISSION-DBS, which has been designed to fulfill the goals of Project MISSION (medical imaging support via satellite integrated optical network) -- an experimental high performance gigabit satellite communication network with access to remote supercomputing power, medical image databases, and 3D visualization capabilities in addition to medical expertise anywhere and anytime around the country. The MISSION-DBS design employs a synergistic fusion of techniques in distributed databases (DDB) and artificial intelligence (AI) for storing, migrating, accessing, and exploring images. The efficient storage and retrieval of voluminous image information is achieved by integrating DDB modeling and AI techniques for image processing while the flexible retrieval mechanisms are accomplished by combining attribute- based and content-based retrievals.

  8. A Medical Image Backup Architecture Based on a NoSQL Database and Cloud Computing Services.

    Science.gov (United States)

    Santos Simões de Almeida, Luan Henrique; Costa Oliveira, Marcelo

    2015-01-01

    The use of digital systems for storing medical images generates a huge volume of data. Digital images are commonly stored and managed on a Picture Archiving and Communication System (PACS), under the DICOM standard. However, PACS is limited because it is strongly dependent on the server's physical space. Alternatively, Cloud Computing arises as an extensive, low cost, and reconfigurable resource. However, medical images contain patient information that can not be made available in a public cloud. Therefore, a mechanism to anonymize these images is needed. This poster presents a solution for this issue by taking digital images from PACS, converting the information contained in each image file to a NoSQL database, and using cloud computing to store digital images.

  9. The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): A Completed Reference Database of Lung Nodules on CT Scans

    International Nuclear Information System (INIS)

    2011-01-01

    Purpose: The development of computer-aided diagnostic (CAD) methods for lung nodule detection, classification, and quantitative assessment can be facilitated through a well-characterized repository of computed tomography (CT) scans. The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI) completed such a database, establishing a publicly available reference for the medical imaging research community. Initiated by the National Cancer Institute (NCI), further advanced by the Foundation for the National Institutes of Health (FNIH), and accompanied by the Food and Drug Administration (FDA) through active participation, this public-private partnership demonstrates the success of a consortium founded on a consensus-based process. Methods: Seven academic centers and eight medical imaging companies collaborated to identify, address, and resolve challenging organizational, technical, and clinical issues to provide a solid foundation for a robust database. The LIDC/IDRI Database contains 1018 cases, each of which includes images from a clinical thoracic CT scan and an associated XML file that records the results of a two-phase image annotation process performed by four experienced thoracic radiologists. In the initial blinded-read phase, each radiologist independently reviewed each CT scan and marked lesions belonging to one of three categories (''nodule≥3 mm,''''nodule<3 mm,'' and ''non-nodule≥3 mm''). In the subsequent unblinded-read phase, each radiologist independently reviewed their own marks along with the anonymized marks of the three other radiologists to render a final opinion. The goal of this process was to identify as completely as possible all lung nodules in each CT scan without requiring forced consensus. Results: The Database contains 7371 lesions marked ''nodule'' by at least one radiologist. 2669 of these lesions were marked ''nodule≥3 mm'' by at least one radiologist, of which 928 (34.7%) received such marks from all

  10. The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): A Completed Reference Database of Lung Nodules on CT Scans

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2011-02-15

    Purpose: The development of computer-aided diagnostic (CAD) methods for lung nodule detection, classification, and quantitative assessment can be facilitated through a well-characterized repository of computed tomography (CT) scans. The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI) completed such a database, establishing a publicly available reference for the medical imaging research community. Initiated by the National Cancer Institute (NCI), further advanced by the Foundation for the National Institutes of Health (FNIH), and accompanied by the Food and Drug Administration (FDA) through active participation, this public-private partnership demonstrates the success of a consortium founded on a consensus-based process. Methods: Seven academic centers and eight medical imaging companies collaborated to identify, address, and resolve challenging organizational, technical, and clinical issues to provide a solid foundation for a robust database. The LIDC/IDRI Database contains 1018 cases, each of which includes images from a clinical thoracic CT scan and an associated XML file that records the results of a two-phase image annotation process performed by four experienced thoracic radiologists. In the initial blinded-read phase, each radiologist independently reviewed each CT scan and marked lesions belonging to one of three categories (''nodule{>=}3 mm,''''nodule<3 mm,'' and ''non-nodule{>=}3 mm''). In the subsequent unblinded-read phase, each radiologist independently reviewed their own marks along with the anonymized marks of the three other radiologists to render a final opinion. The goal of this process was to identify as completely as possible all lung nodules in each CT scan without requiring forced consensus. Results: The Database contains 7371 lesions marked ''nodule'' by at least one radiologist. 2669 of these lesions were marked &apos

  11. A digital library for medical imaging activities

    Science.gov (United States)

    dos Santos, Marcelo; Furuie, Sérgio S.

    2007-03-01

    This work presents the development of an electronic infrastructure to make available a free, online, multipurpose and multimodality medical image database. The proposed infrastructure implements a distributed architecture for medical image database, authoring tools, and a repository for multimedia documents. Also it includes a peer-reviewed model that assures quality of dataset. This public repository provides a single point of access for medical images and related information to facilitate retrieval tasks. The proposed approach has been used as an electronic teaching system in Radiology as well.

  12. Topics in medical image processing and computational vision

    CERN Document Server

    Jorge, Renato

    2013-01-01

      The sixteen chapters included in this book were written by invited experts of international recognition and address important issues in Medical Image Processing and Computational Vision, including: Object Recognition, Object Detection, Object Tracking, Pose Estimation, Facial Expression Recognition, Image Retrieval, Data Mining, Automatic Video Understanding and Management, Edges Detection, Image Segmentation, Modelling and Simulation, Medical thermography, Database Systems, Synthetic Aperture Radar and Satellite Imagery.   Different applications are addressed and described throughout the book, comprising: Object Recognition and Tracking, Facial Expression Recognition, Image Database, Plant Disease Classification, Video Understanding and Management, Image Processing, Image Segmentation, Bio-structure Modelling and Simulation, Medical Imaging, Image Classification, Medical Diagnosis, Urban Areas Classification, Land Map Generation.   The book brings together the current state-of-the-art in the various mul...

  13. Draft secure medical database standard.

    Science.gov (United States)

    Pangalos, George

    2002-01-01

    Medical database security is a particularly important issue for all Healthcare establishments. Medical information systems are intended to support a wide range of pertinent health issues today, for example: assure the quality of care, support effective management of the health services institutions, monitor and contain the cost of care, implement technology into care without violating social values, ensure the equity and availability of care, preserve humanity despite the proliferation of technology etc.. In this context, medical database security aims primarily to support: high availability, accuracy and consistency of the stored data, the medical professional secrecy and confidentiality, and the protection of the privacy of the patient. These properties, though of technical nature, basically require that the system is actually helpful for medical care and not harmful to patients. These later properties require in turn not only that fundamental ethical principles are not violated by employing database systems, but instead, are effectively enforced by technical means. This document reviews the existing and emerging work on the security of medical database systems. It presents in detail the related problems and requirements related to medical database security. It addresses the problems of medical database security policies, secure design methodologies and implementation techniques. It also describes the current legal framework and regulatory requirements for medical database security. The issue of medical database security guidelines is also examined in detailed. The current national and international efforts in the area are studied. It also gives an overview of the research work in the area. The document also presents in detail the most complete to our knowledge set of security guidelines for the development and operation of medical database systems.

  14. A cloud collaborative medical image platform oriented by social network

    Science.gov (United States)

    Muniz, Frederico B.; Araújo, Luciano V.; Nunes, Fátima L. S.

    2017-03-01

    Computer-aided diagnosis systems using medical images and three-dimensional models as input data have greatly expanded and developed, but in terms of building suitable image databases to assess them, the challenge remains. Although there are some image databases available for this purpose, they are generally limited to certain types of exams or contain a limited number of medical cases. The objective of this work is to present the concepts and the development of a collaborative platform for sharing medical images and three-dimensional models, providing a resource to share and increase the number of images available for researchers. The collaborative cloud platform, called CATALYZER, aims to increase the availability and sharing of graphic objects, including 3D images, and their reports that are essential for research related to medical images. A survey conducted with researchers and health professionals indicated that this could be an innovative approach in the creation of medical image databases, providing a wider variety of cases together with a considerable amount of shared information among its users.

  15. Low dose CT image restoration using a database of image patches

    Science.gov (United States)

    Ha, Sungsoo; Mueller, Klaus

    2015-01-01

    Reducing the radiation dose in CT imaging has become an active research topic and many solutions have been proposed to remove the significant noise and streak artifacts in the reconstructed images. Most of these methods operate within the domain of the image that is subject to restoration. This, however, poses limitations on the extent of filtering possible. We advocate to take into consideration the vast body of external knowledge that exists in the domain of already acquired medical CT images, since after all, this is what radiologists do when they examine these low quality images. We can incorporate this knowledge by creating a database of prior scans, either of the same patient or a diverse corpus of different patients, to assist in the restoration process. Our paper follows up on our previous work that used a database of images. Using images, however, is challenging since it requires tedious and error prone registration and alignment. Our new method eliminates these problems by storing a diverse set of small image patches in conjunction with a localized similarity matching scheme. We also empirically show that it is sufficient to store these patches without anatomical tags since their statistics are sufficiently strong to yield good similarity matches from the database and as a direct effect, produce image restorations of high quality. A final experiment demonstrates that our global database approach can recover image features that are difficult to preserve with conventional denoising approaches.

  16. Internet-accessible radiographic database of Vietnam War casualties for medical student education.

    Science.gov (United States)

    Critchley, Eric P; Smirniotopoulos, James G

    2003-04-01

    The purpose of this study was to determine the feasibility of archiving radiographic images from Vietnam era conflict casualties into a personal computer-based electronic database of text and images and displaying the data using an Internet-accessible database for preservation and educational purposes. Thirty-two patient cases were selected at random from a pool of 1,000 autopsy reports in which radiographs were available. A total of 74 radiographs from these cases were digitized using a commercial image scanner and then uploaded into an Internet accessible database. The quality of the digitized images was assessed by administering an image-based test to a group of 12 medical students. No statistically significant (p > 0.05) differences were found between test scores when using the original radiographs versus using the digitized radiographs on the Internet-accessible database. An Internet-accessible database is capable of effectively archiving Vietnam era casualty radiographs for educational purposes.

  17. Medical imaging and the Internet

    International Nuclear Information System (INIS)

    Jones, D.N.; Carr, P.

    1995-01-01

    A brief introduction to the INTERNET and its benefits for those involved in nuclear medical imaging is given. In Australia, depending on the type of institution/department involved, connection to the INTERNET may be obtained via the Australian Academic and Research Network or through a commercial provider. The recent proliferation of WWW servers has also resulted in multiple medical imaging databases and teaching resources becoming available to the user. Some Newsgroups and WWW addresses related to radiology are provided. 3 refs

  18. An XCT image database system

    International Nuclear Information System (INIS)

    Komori, Masaru; Minato, Kotaro; Koide, Harutoshi; Hirakawa, Akina; Nakano, Yoshihisa; Itoh, Harumi; Torizuka, Kanji; Yamasaki, Tetsuo; Kuwahara, Michiyoshi.

    1984-01-01

    In this paper, an expansion of X-ray CT (XCT) examination history database to XCT image database is discussed. The XCT examination history database has been constructed and used for daily examination and investigation in our hospital. This database consists of alpha-numeric information (locations, diagnosis and so on) of more than 15,000 cases, and for some of them, we add tree structured image data which has a flexibility for various types of image data. This database system is written by MUMPS database manipulation language. (author)

  19. Medical image informatics infrastructure design and applications.

    Science.gov (United States)

    Huang, H K; Wong, S T; Pietka, E

    1997-01-01

    Picture archiving and communication systems (PACS) is a system integration of multimodality images and health information systems designed for improving the operation of a radiology department. As it evolves, PACS becomes a hospital image document management system with a voluminous image and related data file repository. A medical image informatics infrastructure can be designed to take advantage of existing data, providing PACS with add-on value for health care service, research, and education. A medical image informatics infrastructure (MIII) consists of the following components: medical images and associated data (including PACS database), image processing, data/knowledge base management, visualization, graphic user interface, communication networking, and application oriented software. This paper describes these components and their logical connection, and illustrates some applications based on the concept of the MIII.

  20. Large-Scale medical image analytics: Recent methodologies, applications and Future directions.

    Science.gov (United States)

    Zhang, Shaoting; Metaxas, Dimitris

    2016-10-01

    Despite the ever-increasing amount and complexity of annotated medical image data, the development of large-scale medical image analysis algorithms has not kept pace with the need for methods that bridge the semantic gap between images and diagnoses. The goal of this position paper is to discuss and explore innovative and large-scale data science techniques in medical image analytics, which will benefit clinical decision-making and facilitate efficient medical data management. Particularly, we advocate that the scale of image retrieval systems should be significantly increased at which interactive systems can be effective for knowledge discovery in potentially large databases of medical images. For clinical relevance, such systems should return results in real-time, incorporate expert feedback, and be able to cope with the size, quality, and variety of the medical images and their associated metadata for a particular domain. The design, development, and testing of the such framework can significantly impact interactive mining in medical image databases that are growing rapidly in size and complexity and enable novel methods of analysis at much larger scales in an efficient, integrated fashion. Copyright © 2016. Published by Elsevier B.V.

  1. The Orthanc Ecosystem for Medical Imaging.

    Science.gov (United States)

    Jodogne, Sébastien

    2018-05-03

    This paper reviews the components of Orthanc, a free and open-source, highly versatile ecosystem for medical imaging. At the core of the Orthanc ecosystem, the Orthanc server is a lightweight vendor neutral archive that provides PACS managers with a powerful environment to automate and optimize the imaging flows that are very specific to each hospital. The Orthanc server can be extended with plugins that provide solutions for teleradiology, digital pathology, or enterprise-ready databases. It is shown how software developers and research engineers can easily develop external software or Web portals dealing with medical images, with minimal knowledge of the DICOM standard, thanks to the advanced programming interface of the Orthanc server. The paper concludes by introducing the Stone of Orthanc, an innovative toolkit for the cross-platform rendering of medical images.

  2. Medical emergencies in the imaging department of a university hospital: event and imaging characteristics.

    Science.gov (United States)

    van Tonder, F C; Sutherland, T; Smith, R J; Chock, J M E; Santamaria, J D

    2013-01-01

    We aimed to describe the characteristics of medical emergencies that occurred in the medical imaging department (MID) of a university hospital in Melbourne, Australia. A database of 'Respond Medical Emergency Team (MET)' and 'Respond Blue' calls was retrospectively examined for the period June 2003 to November 2010 in relation to events that occurred in the MID. The hospital medical imaging database was also examined in relation to these events and, where necessary, patients' notes were reviewed. Ethics approval was granted by the hospital ethics review board. There were 124 medical emergency calls in the MID during the study period, 28% Respond Blue and 72% Respond MET. Of these 124 calls, 26% occurred outside of usual work hours and 12% involved cardiac arrest. The most common reasons for the emergency calls were seizures (14%) and altered conscious state (13%). Contrast anaphylaxis precipitated the emergency in 4% of cases. In 83% of cases the emergency calls were for patients attending the MID for diagnostic imaging, the remainder being for a procedure. Of the scheduled imaging techniques, 45% were for computed tomography. The scheduled imaging was abandoned due to the emergency in 12% of cases. When performed, imaging informed patient management in 34% of cases in diagnostic imaging and in all cases in the context of image-guided procedures. Medical emergency calls in the MID often occurred outside usual work hours and were attributed to a range of medical problems. The emergencies occurred in relation to all imaging techniques and imaging informed patient management in many cases. Crown Copyright © 2012. Published by Elsevier Ireland Ltd. All rights reserved.

  3. Development of a personalized training system using the Lung Image Database Consortium and Image Database resource Initiative Database.

    Science.gov (United States)

    Lin, Hongli; Wang, Weisheng; Luo, Jiawei; Yang, Xuedong

    2014-12-01

    The aim of this study was to develop a personalized training system using the Lung Image Database Consortium (LIDC) and Image Database resource Initiative (IDRI) Database, because collecting, annotating, and marking a large number of appropriate computed tomography (CT) scans, and providing the capability of dynamically selecting suitable training cases based on the performance levels of trainees and the characteristics of cases are critical for developing a efficient training system. A novel approach is proposed to develop a personalized radiology training system for the interpretation of lung nodules in CT scans using the Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI) database, which provides a Content-Boosted Collaborative Filtering (CBCF) algorithm for predicting the difficulty level of each case of each trainee when selecting suitable cases to meet individual needs, and a diagnostic simulation tool to enable trainees to analyze and diagnose lung nodules with the help of an image processing tool and a nodule retrieval tool. Preliminary evaluation of the system shows that developing a personalized training system for interpretation of lung nodules is needed and useful to enhance the professional skills of trainees. The approach of developing personalized training systems using the LIDC/IDRL database is a feasible solution to the challenges of constructing specific training program in terms of cost and training efficiency. Copyright © 2014 AUR. Published by Elsevier Inc. All rights reserved.

  4. Establishing an international reference image database for research and development in medical image processing

    NARCIS (Netherlands)

    Horsch, A.D.; Prinz, M.; Schneider, S.; Sipilä, O; Spinnler, K.; Vallée, J-P; Verdonck-de Leeuw, I; Vogl, R.; Wittenberg, T.; Zahlmann, G.

    2004-01-01

    INTRODUCTION: The lack of comparability of evaluation results is one of the major obstacles of research and development in Medical Image Processing (MIP). The main reason for that is the usage of different image datasets with different quality, size and Gold standard. OBJECTIVES: Therefore, one of

  5. REVIEW OF MATHEMATICAL METHODS AND ALGORITHMS OF MEDICAL IMAGE PROCESSING ON THE EXAMPLE OF TECHNOLOGY OF MEDICAL IMAGE PROCESSING FROM WOLFRAM MATHEMATICA

    Directory of Open Access Journals (Sweden)

    О. E. Prokopchenko

    2015-09-01

    Full Text Available The article analyzes the basic methods and algorithms of mathematical processing of medical images as objects of computer mathematics. The presented methods and computer algorithms of mathematics relevant and may find application in the field of medical imaging - automated processing of images; as a tool for measurement and determination the optical parameters; identification and formation of medical images database. Methods and computer algorithms presented in the article & based on Wolfram Mathematica are also relevant to the problem of modern medical education. As an example of Wolfram Mathematica may be considered appropriate demonstration, such as recognition of special radiographs and morphological imaging. These methods are used to improve the diagnostic significance and value of medical (clinical research and can serve as an educational interactive demonstration. Implementation submitted individual methods and algorithms of computer Wolfram Mathematics contributes, in general, the optimization process of practical processing and presentation of medical images.

  6. 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

  7. Radiology and Enterprise Medical Imaging Extensions (REMIX).

    Science.gov (United States)

    Erdal, Barbaros S; Prevedello, Luciano M; Qian, Songyue; Demirer, Mutlu; Little, Kevin; Ryu, John; O'Donnell, Thomas; White, Richard D

    2018-02-01

    Radiology and Enterprise Medical Imaging Extensions (REMIX) is a platform originally designed to both support the medical imaging-driven clinical and clinical research operational needs of Department of Radiology of The Ohio State University Wexner Medical Center. REMIX accommodates the storage and handling of "big imaging data," as needed for large multi-disciplinary cancer-focused programs. The evolving REMIX platform contains an array of integrated tools/software packages for the following: (1) server and storage management; (2) image reconstruction; (3) digital pathology; (4) de-identification; (5) business intelligence; (6) texture analysis; and (7) artificial intelligence. These capabilities, along with documentation and guidance, explaining how to interact with a commercial system (e.g., PACS, EHR, commercial database) that currently exists in clinical environments, are to be made freely available.

  8. REVIEW OF MATHEMATICAL METHODS AND ALGORITHMS OF MEDICAL IMAGE PROCESSING ON THE EXAMPLE OF TECHNOLOGY OF MEDICAL IMAGE PROCESSING FROM WOLFRAM MATHEMATICS

    Directory of Open Access Journals (Sweden)

    O. Ye. Prokopchenko

    2015-10-01

    Full Text Available The article analyzes the basic methods and algorithms of mathematical processing of medical images as objects of computer mathematics. The presented methods and computer algorithms of mathematics relevant and may find application in the field of medical imaging - automated processing of images; as a tool for measurement and determination the optical parameters; identification and formation of medical images database. Methods and computer algorithms presented in the article and based on Wolfram Mathematica are also relevant to the problem of modern medical education. As an example of Wolfram Mathematics may be considered appropriate demonstration, such as recognition of special radiographs and morphological imaging. These methods are used to improve  the diagnostic significance and value of medical (clinical research and can serve as an educational interactive demonstration. Implementation submitted individual methods and algorithms of computer Wolfram Mathematics contributes, in general, the optimization process of practical processing and presentation of medical images.

  9. Database Description - Open TG-GATEs Pathological Image Database | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available List Contact us Open TG-GATEs Pathological Image Database Database Description General information of database Database... name Open TG-GATEs Pathological Image Database Alternative name - DOI 10.18908/lsdba.nbdc00954-0...iomedical Innovation 7-6-8, Saito-asagi, Ibaraki-city, Osaka 567-0085, Japan TEL:81-72-641-9826 Email: Database... classification Toxicogenomics Database Organism Taxonomy Name: Rattus norvegi... Article title: Author name(s): Journal: External Links: Original website information Database

  10. Review of interdisciplinary online-image-databases and their usability in medical education

    Directory of Open Access Journals (Sweden)

    Kammerer, Ferdinand J.

    2006-11-01

    Full Text Available Images play a significant role in medical teaching. They can get prospective physicians acquainted with specific pathological changes as early as possible and they support training their diagnostic eye. The latest improvements in Web-Based-Training offer extensive features for cost-effective studying adjustable to the individual student's requirements. However, many web-sites provide only qualitatively heterogeneous data and a limited inventory of images. This generally complicates any systematic access to the information the student requires.During the last years, several projects were initiated trying to overcome these difficulties. Web-Portals should provide access to large sets of images in a centralized manner while encompassing several medical subjects. For five of these portals their applicability for medical education was investigated considering structure, navigation and search mechanisms. Some notable approaches to implementing the various search functions were observed. However, some sites have room for improvement concerning quality of content as well as clarity of presentation and navigation. Based on the problems discovered and the approaches found, a catalogue of requirements was compiled for creating a Web-Portal to optimally support medical education.

  11. Access database application in medical treatment management platform

    International Nuclear Information System (INIS)

    Wu Qingming

    2014-01-01

    For timely, accurate and flexible access to medical expenses data, we applied Microsoft Access 2003 database management software, and we finished the establishment of a management platform for medical expenses. By developing management platform for medical expenses, overall hospital costs for medical expenses can be controlled to achieve a real-time monitoring of medical expenses. Using the Access database management platform for medical expenses not only changes the management model, but also promotes a sound management system for medical expenses. (authors)

  12. Diagnostic information management system for the evaluation of medical images

    Energy Technology Data Exchange (ETDEWEB)

    Higa, Toshiaki; Torizuka, Kanji; Minato, Kotaro; Komori, Masaru; Hirakawa, Akina

    1985-04-01

    A practical, small and low-cost diagnostic information management system has been developed for a comparative study of various medical imaging procedures, including ordinary radiography, X-ray computed tomography, emission computed tomography, and so forth. The purpose of the system is to effectively manage the original image data files and diagnostic descriptions during the various imaging procedures. A diagnostic description of each imaging procedure for each patient is made on a hand-sort punched-card with line-drawings and ordinary medical terminology and then coded and computerized using Index for Roentgen Diagnoses (American College of Radiology). A database management software (DB Master) on a personal computer (Apple II) is used for searching for patients' records on hand-sort punched-cards and finally original medical images. Discussed are realistic use of medical images and an effective form of diagnostic descriptions.

  13. Diagnostic information management system for the evaluation of medical images

    International Nuclear Information System (INIS)

    Higa, Toshiaki; Torizuka, Kanji; Minato, Kotaro; Komori, Masaru; Hirakawa, Akina.

    1985-01-01

    A practical, small and low-cost diagnostic information management system has been developed for a comparative study of various medical imaging procedures, including ordinary radiography, X-ray computed tomography, emission computed tomography, and so forth. The purpose of the system is to effectively manage the original image data files and diagnostic descriptions during the various imaging procedures. A diagnostic description of each imaging procedure for each patient is made on a hand-sort punched-card with line-drawings and ordinary medical terminology and then coded and computerized using Index for Roentgen Diagnoses (American College of Radiology). A database management software (DB Master) on a personal computer (Apple II) is used for searching for patients' records on hand-sort punched-cards and finally original medical images. Discussed are realistic use of medical images and an effective form of diagnostic descriptions. (author)

  14. A hierarchical SVG image abstraction layer for medical imaging

    Science.gov (United States)

    Kim, Edward; Huang, Xiaolei; Tan, Gang; Long, L. Rodney; Antani, Sameer

    2010-03-01

    As medical imaging rapidly expands, there is an increasing need to structure and organize image data for efficient analysis, storage and retrieval. In response, a large fraction of research in the areas of content-based image retrieval (CBIR) and picture archiving and communication systems (PACS) has focused on structuring information to bridge the "semantic gap", a disparity between machine and human image understanding. An additional consideration in medical images is the organization and integration of clinical diagnostic information. As a step towards bridging the semantic gap, we design and implement a hierarchical image abstraction layer using an XML based language, Scalable Vector Graphics (SVG). Our method encodes features from the raw image and clinical information into an extensible "layer" that can be stored in a SVG document and efficiently searched. Any feature extracted from the raw image including, color, texture, orientation, size, neighbor information, etc., can be combined in our abstraction with high level descriptions or classifications. And our representation can natively characterize an image in a hierarchical tree structure to support multiple levels of segmentation. Furthermore, being a world wide web consortium (W3C) standard, SVG is able to be displayed by most web browsers, interacted with by ECMAScript (standardized scripting language, e.g. JavaScript, JScript), and indexed and retrieved by XML databases and XQuery. Using these open source technologies enables straightforward integration into existing systems. From our results, we show that the flexibility and extensibility of our abstraction facilitates effective storage and retrieval of medical images.

  15. Unique identification code for medical fundus images using blood vessel pattern for tele-ophthalmology applications.

    Science.gov (United States)

    Singh, Anushikha; Dutta, Malay Kishore; Sharma, Dilip Kumar

    2016-10-01

    Identification of fundus images during transmission and storage in database for tele-ophthalmology applications is an important issue in modern era. The proposed work presents a novel accurate method for generation of unique identification code for identification of fundus images for tele-ophthalmology applications and storage in databases. Unlike existing methods of steganography and watermarking, this method does not tamper the medical image as nothing is embedded in this approach and there is no loss of medical information. Strategic combination of unique blood vessel pattern and patient ID is considered for generation of unique identification code for the digital fundus images. Segmented blood vessel pattern near the optic disc is strategically combined with patient ID for generation of a unique identification code for the image. The proposed method of medical image identification is tested on the publically available DRIVE and MESSIDOR database of fundus image and results are encouraging. Experimental results indicate the uniqueness of identification code and lossless recovery of patient identity from unique identification code for integrity verification of fundus images. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  16. [Research and development of medical case database: a novel medical case information system integrating with biospecimen management].

    Science.gov (United States)

    Pan, Shiyang; Mu, Yuan; Wang, Hong; Wang, Tong; Huang, Peijun; Ma, Jianfeng; Jiang, Li; Zhang, Jie; Gu, Bing; Yi, Lujiang

    2010-04-01

    To meet the needs of management of medical case information and biospecimen simultaneously, we developed a novel medical case information system integrating with biospecimen management. The database established by MS SQL Server 2000 covered, basic information, clinical diagnosis, imaging diagnosis, pathological diagnosis and clinical treatment of patient; physicochemical property, inventory management and laboratory analysis of biospecimen; users log and data maintenance. The client application developed by Visual C++ 6.0 was used to implement medical case and biospecimen management, which was based on Client/Server model. This system can perform input, browse, inquest, summary of case and related biospecimen information, and can automatically synthesize case-records based on the database. Management of not only a long-term follow-up on individual, but also of grouped cases organized according to the aim of research can be achieved by the system. This system can improve the efficiency and quality of clinical researches while biospecimens are used coordinately. It realizes synthesized and dynamic management of medical case and biospecimen, which may be considered as a new management platform.

  17. System for digitalization of medical images based on DICOM standard

    Directory of Open Access Journals (Sweden)

    Čabarkapa Slobodan

    2009-01-01

    Full Text Available According to DICOM standard, which defines both medical image information and user information, a new system for digitalizing medical images is involved as a part of the main system for archiving and retrieving medical databases. The basic characteristics of this system are described in this paper. Furthermore, the analysis of some important DICOM header's tags which are used in this system, are presented, too. Having chosen the appropriate tags in order to preserve important information, the efficient system has been created. .

  18. A review of m-health in medical imaging.

    Science.gov (United States)

    Perera, Chandrashan Mahendra; Chakrabarti, Rahul

    2015-02-01

    The increasing capabilities of camera-equipped mobile phones have led to a growing body of evidence regarding their use in medical imaging across a broad range of medical specialties. This article reviews the current evidence for the use of mobile health (m-health) in medical imaging. We performed a structured review of the published literature regarding m-health in medical imaging using the Medline, PubMed, and Web of Science databases (January 2002-August 2013). The two authors independently extracted data regarding type of specialty, purpose, and study design of publications. In total, 235 articles were identified. The majority of studies were case reports or noncomparative product validation studies. The greatest volume of publications originated in the fields of radiology (21%), dermatology (15%), laboratory techniques (15%), and plastic surgery (12%). Among these studies, m-health was used as diagnostic aids, for patient monitoring, and to improve communication between health practitioners. With the growing use of mobile phones for medical imaging, considerations need to be given to informed consent, privacy, image storage and transfer, and guidelines for healthcare workers and patients. There are several novel uses of mobile devices for medical imaging that show promise across a variety of areas and subspecialties of healthcare. Currently, studies are mostly exploratory in nature. To validate these devices, studies with higher methodological rigor are required.

  19. Animal Detection in Natural Images: Effects of Color and Image Database

    Science.gov (United States)

    Zhu, Weina; Drewes, Jan; Gegenfurtner, Karl R.

    2013-01-01

    The visual system has a remarkable ability to extract categorical information from complex natural scenes. In order to elucidate the role of low-level image features for the recognition of objects in natural scenes, we recorded saccadic eye movements and event-related potentials (ERPs) in two experiments, in which human subjects had to detect animals in previously unseen natural images. We used a new natural image database (ANID) that is free of some of the potential artifacts that have plagued the widely used COREL images. Color and grayscale images picked from the ANID and COREL databases were used. In all experiments, color images induced a greater N1 EEG component at earlier time points than grayscale images. We suggest that this influence of color in animal detection may be masked by later processes when measuring reation times. The ERP results of go/nogo and forced choice tasks were similar to those reported earlier. The non-animal stimuli induced bigger N1 than animal stimuli both in the COREL and ANID databases. This result indicates ultra-fast processing of animal images is possible irrespective of the particular database. With the ANID images, the difference between color and grayscale images is more pronounced than with the COREL images. The earlier use of the COREL images might have led to an underestimation of the contribution of color. Therefore, we conclude that the ANID image database is better suited for the investigation of the processing of natural scenes than other databases commonly used. PMID:24130744

  20. Animal detection in natural images: effects of color and image database.

    Directory of Open Access Journals (Sweden)

    Weina Zhu

    Full Text Available The visual system has a remarkable ability to extract categorical information from complex natural scenes. In order to elucidate the role of low-level image features for the recognition of objects in natural scenes, we recorded saccadic eye movements and event-related potentials (ERPs in two experiments, in which human subjects had to detect animals in previously unseen natural images. We used a new natural image database (ANID that is free of some of the potential artifacts that have plagued the widely used COREL images. Color and grayscale images picked from the ANID and COREL databases were used. In all experiments, color images induced a greater N1 EEG component at earlier time points than grayscale images. We suggest that this influence of color in animal detection may be masked by later processes when measuring reation times. The ERP results of go/nogo and forced choice tasks were similar to those reported earlier. The non-animal stimuli induced bigger N1 than animal stimuli both in the COREL and ANID databases. This result indicates ultra-fast processing of animal images is possible irrespective of the particular database. With the ANID images, the difference between color and grayscale images is more pronounced than with the COREL images. The earlier use of the COREL images might have led to an underestimation of the contribution of color. Therefore, we conclude that the ANID image database is better suited for the investigation of the processing of natural scenes than other databases commonly used.

  1. 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.

  2. Medical databases in studies of drug teratogenicity: methodological issues

    Directory of Open Access Journals (Sweden)

    Vera Ehrenstein

    2010-03-01

    Full Text Available Vera Ehrenstein1, Henrik T Sørensen1, Leiv S Bakketeig1,2, Lars Pedersen11Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark; 2Norwegian Institute of Public Health, Oslo, NorwayAbstract: More than half of all pregnant women take prescription medications, raising concerns about fetal safety. Medical databases routinely collecting data from large populations are potentially valuable resources for cohort studies addressing teratogenicity of drugs. These include electronic medical records, administrative databases, population health registries, and teratogenicity information services. Medical databases allow estimation of prevalences of birth defects with enhanced precision, but systematic error remains a potentially serious problem. In this review, we first provide a brief description of types of North American and European medical databases suitable for studying teratogenicity of drugs and then discuss manifestation of systematic errors in teratogenicity studies based on such databases. Selection bias stems primarily from the inability to ascertain all reproductive outcomes. Information bias (misclassification may be caused by paucity of recorded clinical details or incomplete documentation of medication use. Confounding, particularly confounding by indication, can rarely be ruled out. Bias that either masks teratogenicity or creates false appearance thereof, may have adverse consequences for the health of the child and the mother. Biases should be quantified and their potential impact on the study results should be assessed. Both theory and software are available for such estimation. Provided that methodological problems are understood and effectively handled, computerized medical databases are a valuable source of data for studies of teratogenicity of drugs.Keywords: databases, birth defects, epidemiologic methods, pharmacoepidemiology

  3. The state of the art of medical imaging technology: from creation to archive and back.

    Science.gov (United States)

    Gao, Xiaohong W; Qian, Yu; Hui, Rui

    2011-01-01

    Medical imaging has learnt itself well into modern medicine and revolutionized medical industry in the last 30 years. Stemming from the discovery of X-ray by Nobel laureate Wilhelm Roentgen, radiology was born, leading to the creation of large quantities of digital images as opposed to film-based medium. While this rich supply of images provides immeasurable information that would otherwise not be possible to obtain, medical images pose great challenges in archiving them safe from corrupted, lost and misuse, retrievable from databases of huge sizes with varying forms of metadata, and reusable when new tools for data mining and new media for data storing become available. This paper provides a summative account on the creation of medical imaging tomography, the development of image archiving systems and the innovation from the existing acquired image data pools. The focus of this paper is on content-based image retrieval (CBIR), in particular, for 3D images, which is exemplified by our developed online e-learning system, MIRAGE, home to a repository of medical images with variety of domains and different dimensions. In terms of novelties, the facilities of CBIR for 3D images coupled with image annotation in a fully automatic fashion have been developed and implemented in the system, resonating with future versatile, flexible and sustainable medical image databases that can reap new innovations.

  4. Interactive searching of facial image databases

    Science.gov (United States)

    Nicholls, Robert A.; Shepherd, John W.; Shepherd, Jean

    1995-09-01

    A set of psychological facial descriptors has been devised to enable computerized searching of criminal photograph albums. The descriptors have been used to encode image databased of up to twelve thousand images. Using a system called FACES, the databases are searched by translating a witness' verbal description into corresponding facial descriptors. Trials of FACES have shown that this coding scheme is more productive and efficient than searching traditional photograph albums. An alternative method of searching the encoded database using a genetic algorithm is currenly being tested. The genetic search method does not require the witness to verbalize a description of the target but merely to indicate a degree of similarity between the target and a limited selection of images from the database. The major drawback of FACES is that is requires a manual encoding of images. Research is being undertaken to automate the process, however, it will require an algorithm which can predict human descriptive values. Alternatives to human derived coding schemes exist using statistical classifications of images. Since databases encoded using statistical classifiers do not have an obvious direct mapping to human derived descriptors, a search method which does not require the entry of human descriptors is required. A genetic search algorithm is being tested for such a purpose.

  5. [Development and evaluation of the medical imaging distribution system with dynamic web application and clustering technology].

    Science.gov (United States)

    Yokohama, Noriya; Tsuchimoto, Tadashi; Oishi, Masamichi; Itou, Katsuya

    2007-01-20

    It has been noted that the downtime of medical informatics systems is often long. Many systems encounter downtimes of hours or even days, which can have a critical effect on daily operations. Such systems remain especially weak in the areas of database and medical imaging data. The scheme design shows the three-layer architecture of the system: application, database, and storage layers. The application layer uses the DICOM protocol (Digital Imaging and Communication in Medicine) and HTTP (Hyper Text Transport Protocol) with AJAX (Asynchronous JavaScript+XML). The database is designed to decentralize in parallel using cluster technology. Consequently, restoration of the database can be done not only with ease but also with improved retrieval speed. In the storage layer, a network RAID (Redundant Array of Independent Disks) system, it is possible to construct exabyte-scale parallel file systems that exploit storage spread. Development and evaluation of the test-bed has been successful in medical information data backup and recovery in a network environment. This paper presents a schematic design of the new medical informatics system that can be accommodated from a recovery and the dynamic Web application for medical imaging distribution using AJAX.

  6. 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.

  7. Teaching medical anatomy: what is the role of imaging today?

    Science.gov (United States)

    Grignon, Bruno; Oldrini, Guillaume; Walter, Frédéric

    2016-03-01

    Medical anatomy instruction has been an important issue of debate for many years and imaging anatomy has become an increasingly important component in the field, the role of which has not yet been clearly defined. The aim of the paper was to assess the current deployment of medical imaging in the teaching of anatomy by means of a review of the literature. A systematic search was performed using the electronic database PubMed, ScienceDirect and various publisher databases, with combinations of the relevant MeSH terms. A manual research was added. In most academic curricula, imaging anatomy has been integrated as a part of anatomical education, taught using a very wide variety of strategies. Considerable variation in the time allocation, content and delivery of medical imaging in teaching human anatomy was identified. Given this considerable variation, an objective assessment remains quite difficult. In most publications, students' perceptions regarding anatomical courses including imaging anatomy were investigated by means of questionnaires and, regardless of the method of teaching, it was globally concluded that imaging anatomy enhanced the quality and efficiency of instruction in human anatomy. More objective evaluation based on an increase in students' performance on course examinations or on specific tests performed before and after teaching sessions showed positive results in numerous cases, while mixed results were also indicated by other studies. A relative standardization could be useful in improving the teaching of imaging anatomy, to facilitate its assessment and reinforce its effectiveness.

  8. Automation of PCXMC and ImPACT for NASA Astronaut Medical Imaging Dose and Risk Tracking

    Science.gov (United States)

    Bahadori, Amir; Picco, Charles; Flores-McLaughlin, John; Shavers, Mark; Semones, Edward

    2011-01-01

    To automate astronaut organ and effective dose calculations from occupational X-ray and computed tomography (CT) examinations incorporating PCXMC and ImPACT tools and to estimate the associated lifetime cancer risk per the National Council on Radiation Protection & Measurements (NCRP) using MATLAB(R). Methods: NASA follows guidance from the NCRP on its operational radiation safety program for astronauts. NCRP Report 142 recommends that astronauts be informed of the cancer risks from reported exposures to ionizing radiation from medical imaging. MATLAB(R) code was written to retrieve exam parameters for medical imaging procedures from a NASA database, calculate associated dose and risk, and return results to the database, using the Microsoft .NET Framework. This code interfaces with the PCXMC executable and emulates the ImPACT Excel spreadsheet to calculate organ doses from X-rays and CTs, respectively, eliminating the need to utilize the PCXMC graphical user interface (except for a few special cases) and the ImPACT spreadsheet. Results: Using MATLAB(R) code to interface with PCXMC and replicate ImPACT dose calculation allowed for rapid evaluation of multiple medical imaging exams. The user inputs the exam parameter data into the database and runs the code. Based on the imaging modality and input parameters, the organ doses are calculated. Output files are created for record, and organ doses, effective dose, and cancer risks associated with each exam are written to the database. Annual and post-flight exposure reports, which are used by the flight surgeon to brief the astronaut, are generated from the database. Conclusions: Automating PCXMC and ImPACT for evaluation of NASA astronaut medical imaging radiation procedures allowed for a traceable and rapid method for tracking projected cancer risks associated with over 12,000 exposures. This code will be used to evaluate future medical radiation exposures, and can easily be modified to accommodate changes to the risk

  9. Design and implementation of typical target image database system

    International Nuclear Information System (INIS)

    Qin Kai; Zhao Yingjun

    2010-01-01

    It is necessary to provide essential background data and thematic data timely in image processing and application. In fact, application is an integrating and analyzing procedure with different kinds of data. In this paper, the authors describe an image database system which classifies, stores, manages and analyzes database of different types, such as image database, vector database, spatial database, spatial target characteristics database, its design and structure. (authors)

  10. 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

  11. DEIMOS – an Open Source Image Database

    Directory of Open Access Journals (Sweden)

    M. Blazek

    2011-12-01

    Full Text Available The DEIMOS (DatabasE of Images: Open Source is created as an open-source database of images and videos for testing, verification and comparing of various image and/or video processing techniques such as enhancing, compression and reconstruction. The main advantage of DEIMOS is its orientation to various application fields – multimedia, television, security, assistive technology, biomedicine, astronomy etc. The DEIMOS is/will be created gradually step-by-step based upon the contributions of team members. The paper is describing basic parameters of DEIMOS database including application examples.

  12. 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.

  13. Common hyperspectral image database design

    Science.gov (United States)

    Tian, Lixun; Liao, Ningfang; Chai, Ali

    2009-11-01

    This paper is to introduce Common hyperspectral image database with a demand-oriented Database design method (CHIDB), which comprehensively set ground-based spectra, standardized hyperspectral cube, spectral analysis together to meet some applications. The paper presents an integrated approach to retrieving spectral and spatial patterns from remotely sensed imagery using state-of-the-art data mining and advanced database technologies, some data mining ideas and functions were associated into CHIDB to make it more suitable to serve in agriculture, geological and environmental areas. A broad range of data from multiple regions of the electromagnetic spectrum is supported, including ultraviolet, visible, near-infrared, thermal infrared, and fluorescence. CHIDB is based on dotnet framework and designed by MVC architecture including five main functional modules: Data importer/exporter, Image/spectrum Viewer, Data Processor, Parameter Extractor, and On-line Analyzer. The original data were all stored in SQL server2008 for efficient search, query and update, and some advance Spectral image data Processing technology are used such as Parallel processing in C#; Finally an application case is presented in agricultural disease detecting area.

  14. CANDID: Comparison algorithm for navigating digital image databases

    Energy Technology Data Exchange (ETDEWEB)

    Kelly, P.M.; Cannon, T.M.

    1994-02-21

    In this paper, we propose a method for calculating the similarity between two digital images. A global signature describing the texture, shape, or color content is first computed for every image stored in a database, and a normalized distance between probability density functions of feature vectors is used to match signatures. This method can be used to retrieve images from a database that are similar to an example target image. This algorithm is applied to the problem of search and retrieval for database containing pulmonary CT imagery, and experimental results are provided.

  15. Solutions for medical databases optimal exploitation.

    Science.gov (United States)

    Branescu, I; Purcarea, V L; Dobrescu, R

    2014-03-15

    The paper discusses the methods to apply OLAP techniques for multidimensional databases that leverage the existing, performance-enhancing technique, known as practical pre-aggregation, by making this technique relevant to a much wider range of medical applications, as a logistic support to the data warehousing techniques. The transformations have practically low computational complexity and they may be implemented using standard relational database technology. The paper also describes how to integrate the transformed hierarchies in current OLAP systems, transparently to the user and proposes a flexible, "multimodel" federated system for extending OLAP querying to external object databases.

  16. Kingfisher: a system for remote sensing image database management

    Science.gov (United States)

    Bruzzo, Michele; Giordano, Ferdinando; Dellepiane, Silvana G.

    2003-04-01

    At present retrieval methods in remote sensing image database are mainly based on spatial-temporal information. The increasing amount of images to be collected by the ground station of earth observing systems emphasizes the need for database management with intelligent data retrieval capabilities. The purpose of the proposed method is to realize a new content based retrieval system for remote sensing images database with an innovative search tool based on image similarity. This methodology is quite innovative for this application, at present many systems exist for photographic images, as for example QBIC and IKONA, but they are not able to extract and describe properly remote image content. The target database is set by an archive of images originated from an X-SAR sensor (spaceborne mission, 1994). The best content descriptors, mainly texture parameters, guarantees high retrieval performances and can be extracted without losses independently of image resolution. The latter property allows DBMS (Database Management System) to process low amount of information, as in the case of quick-look images, improving time performance and memory access without reducing retrieval accuracy. The matching technique has been designed to enable image management (database population and retrieval) independently of dimensions (width and height). Local and global content descriptors are compared, during retrieval phase, with the query image and results seem to be very encouraging.

  17. Medical Care Cost Recovery National Database (MCCR NDB)

    Data.gov (United States)

    Department of Veterans Affairs — The Medical Care Cost Recovery National Database (MCCR NDB) provides a repository of summary Medical Care Collections Fund (MCCF) billing and collection information...

  18. An image database structure for pediatric radiology

    International Nuclear Information System (INIS)

    Mankovich, N.J.

    1987-01-01

    The operation of the Clinical Radiology Imaging System (CRIS) in Pediatric Radiology at UCLA relies on the orderly flow of text and image data among the three basic subsystems including acquisition, storage, and display. CRIS provides the radiologist, clinician, and technician with data at clinical image workstations by maintaining comprehensive database. CRIS is made up of sub-systems, each composed of one more programs or tasks which operate in parallel on a VAX-11/750 microcomputer in Pediatric Radiology. Tasks are coordinated through dynamic data structures that include system event flags and disk-resident queues. This report outlines: (1) the CRIS data model, (2) the flow of information among CRIS components, (3) the underlying database structures which support the acquisition, display, and storage of text and image information, and (4) current database statistics

  19. Datamining on distributed medical databases

    DEFF Research Database (Denmark)

    Have, Anna Szynkowiak

    2004-01-01

    This Ph.D. thesis focuses on clustering techniques for Knowledge Discovery in Databases. Various data mining tasks relevant for medical applications are described and discussed. A general framework which combines data projection and data mining and interpretation is presented. An overview...... is available. If data is unlabeled, then it is possible to generate keywords (in case of textual data) or key-patterns, as an informative representation of the obtained clusters. The methods are applied on simple artificial data sets, as well as collections of textual and medical data. In Danish: Denne ph...

  20. Document image database indexing with pictorial dictionary

    Science.gov (United States)

    Akbari, Mohammad; Azimi, Reza

    2010-02-01

    In this paper we introduce a new approach for information retrieval from Persian document image database without using Optical Character Recognition (OCR).At first an attribute called subword upper contour label is defined then, a pictorial dictionary is constructed based on this attribute for the subwords. By this approach we address two issues in document image retrieval: keyword spotting and retrieval according to the document similarities. The proposed methods have been evaluated on a Persian document image database. The results have proved the ability of this approach in document image information retrieval.

  1. Development of a networked four-million-pixel pathological and radiological digital image presentation system and its application to medical conferences

    Science.gov (United States)

    Sakano, Toshikazu; Furukawa, Isao; Okumura, Akira; Yamaguchi, Takahiro; Fujii, Tetsuro; Ono, Sadayasu; Suzuki, Junji; Matsuya, Shoji; Ishihara, Teruo

    2001-08-01

    The wide spread of digital technology in the medical field has led to a demand for the high-quality, high-speed, and user-friendly digital image presentation system in the daily medical conferences. To fulfill this demand, we developed a presentation system for radiological and pathological images. It is composed of a super-high-definition (SHD) imaging system, a radiological image database (R-DB), a pathological image database (P-DB), and the network interconnecting these three. The R-DB consists of a 270GB RAID, a database server workstation, and a film digitizer. The P-DB includes an optical microscope, a four-million-pixel digital camera, a 90GB RAID, and a database server workstation. A 100Mbps Ethernet LAN interconnects all the sub-systems. The Web-based system operation software was developed for easy operation. We installed the whole system in NTT East Kanto Hospital to evaluate it in the weekly case conferences. The SHD system could display digital full-color images of 2048 x 2048 pixels on a 28-inch CRT monitor. The doctors evaluated the image quality and size, and found them applicable to the actual medical diagnosis. They also appreciated short image switching time that contributed to smooth presentation. Thus, we confirmed that its characteristics met the requirements.

  2. [Discussion of the implementation of MIMIC database in emergency medical study].

    Science.gov (United States)

    Li, Kaiyuan; Feng, Cong; Jia, Lijing; Chen, Li; Pan, Fei; Li, Tanshi

    2018-05-01

    To introduce Medical Information Mart for Intensive Care (MIMIC) database and elaborate the approach of critically emergent research with big data based on the feature of MIMIC and updated studies both domestic and overseas, we put forward the feasibility and necessity of introducing medical big data to research in emergency. Then we discuss the role of MIMIC database in emergency clinical study, as well as the principles and key notes of experimental design and implementation under the medical big data circumstance. The implementation of MIMIC database in emergency medical research provides a brand new field for the early diagnosis, risk warning and prognosis of critical illness, however there are also limitations. To meet the era of big data, emergency medical database which is in accordance with our national condition is needed, which will provide new energy to the development of emergency medicine.

  3. Medical ultrasound imaging

    DEFF Research Database (Denmark)

    Jensen, Jørgen Arendt

    2007-01-01

    The paper gives an introduction to current medical ultrasound imaging systems. The basics of anatomic and blood flow imaging are described. The properties of medical ultrasound and its focusing are described, and the various methods for two- and three-dimensional imaging of the human anatomy...

  4. Medical Image Registration by means of a Bio-Inspired Optimization Strategy

    Directory of Open Access Journals (Sweden)

    Hariton Costin

    2012-07-01

    Full Text Available Medical imaging mainly treats and processes missing, ambiguous, complementary, redundant and distorted data. Biomedical image registration is the process of geometric overlaying or alignment of two or more 2D/3D images of the same scene, taken at different time slots, from different angles, and/or by different acquisition systems. In medical practice, it is becoming increasingly important in diagnosis, treatment planning, functional studies, computer-guided therapies, and in biomedical research. Technically, image registration implies a complex optimization of different parameters, performed at local or/and global levels. Local optimization methods frequently fail because functions of the involved metrics with respect to transformation parameters are generally nonconvex and irregular. Therefore, global methods are often required, at least at the beginning of the procedure. In this paper, a new evolutionary and bio-inspired approach -- bacterial foraging optimization -- is adapted for single-slice to 3-D PET and CT multimodal image registration. Preliminary results of optimizing the normalized mutual information similarity metric validated the efficacy of the proposed method by using a freely available medical image database.

  5. Medical image registration for analysis

    International Nuclear Information System (INIS)

    Petrovic, V.

    2006-01-01

    Full text: Image registration techniques represent a rich family of image processing and analysis tools that aim to provide spatial correspondences across sets of medical images of similar and disparate anatomies and modalities. Image registration is a fundamental and usually the first step in medical image analysis and this paper presents a number of advanced techniques as well as demonstrates some of the advanced medical image analysis techniques they make possible. A number of both rigid and non-rigid medical image alignment algorithms of equivalent and merely consistent anatomical structures respectively are presented. The algorithms are compared in terms of their practical aims, inputs, computational complexity and level of operator (e.g. diagnostician) interaction. In particular, the focus of the methods discussion is placed on the applications and practical benefits of medical image registration. Results of medical image registration on a number of different imaging modalities and anatomies are presented demonstrating the accuracy and robustness of their application. Medical image registration is quickly becoming ubiquitous in medical imaging departments with the results of such algorithms increasingly used in complex medical image analysis and diagnostics. This paper aims to demonstrate at least part of the reason why

  6. Medical Imaging System

    Science.gov (United States)

    1991-01-01

    The MD Image System, a true-color image processing system that serves as a diagnostic aid and tool for storage and distribution of images, was developed by Medical Image Management Systems, Huntsville, AL, as a "spinoff from a spinoff." The original spinoff, Geostar 8800, developed by Crystal Image Technologies, Huntsville, incorporates advanced UNIX versions of ELAS (developed by NASA's Earth Resources Laboratory for analysis of Landsat images) for general purpose image processing. The MD Image System is an application of this technology to a medical system that aids in the diagnosis of cancer, and can accept, store and analyze images from other sources such as Magnetic Resonance Imaging.

  7. Data Mining on Distributed Medical Databases: Recent Trends and Future Directions

    Science.gov (United States)

    Atilgan, Yasemin; Dogan, Firat

    As computerization in healthcare services increase, the amount of available digital data is growing at an unprecedented rate and as a result healthcare organizations are much more able to store data than to extract knowledge from it. Today the major challenge is to transform these data into useful information and knowledge. It is important for healthcare organizations to use stored data to improve quality while reducing cost. This paper first investigates the data mining applications on centralized medical databases, and how they are used for diagnostic and population health, then introduces distributed databases. The integration needs and issues of distributed medical databases are described. Finally the paper focuses on data mining studies on distributed medical databases.

  8. Database for radiation therapy images

    International Nuclear Information System (INIS)

    Shalev, S.; Cosby, S.; Leszczynski, K.; Chu, T.

    1989-01-01

    The authors have developed a database for images acquired during simulation and verification of radiation treatments. Simulation images originate as planning films that are digitized with a video camera, or through direct digitization of fluoroscopic images. Verification images may also be digitized from portal films or acquired with an on-line portal imaging system. Images are classified by the patient, the fraction, the field direction, static or dynamic (movie) sequences, and the type of processing applied. Additional parameters indicate whether the source is a simulation or treatment, whether images are digitized film or real-time acquisitions, and whether treatment is portal or double exposure for beam localization. Examples are presented for images acquired, processed, stored, and displayed with on-line portal imaging system (OPIUM) and digital simulation system (FLIP)

  9. Image Reference Database in Teleradiology: Migrating to WWW

    Science.gov (United States)

    Pasqui, Valdo

    The paper presents a multimedia Image Reference Data Base (IRDB) used in Teleradiology. The application was developed at the University of Florence in the framework of the European Community TELEMED Project. TELEMED overall goals and IRDB requirements are outlined and the resulting architecture is described. IRDB is a multisite database containing radiological images, selected because their scientific interest, and their related information. The architecture consists of a set of IRDB Installations which are accessed from Viewing Stations (VS) located at different medical sites. The interaction between VS and IRDB Installations follows the client-server paradigm and uses an OSI level-7 protocol, named Telemed Communication Language. After reviewing Florence prototype implementation and experimentation, IRDB migration to World Wide Web (WWW) is discussed. A possible scenery to implement IRDB on the basis of WWW model is depicted in order to exploit WWW servers and browsers capabilities. Finally, the advantages of this conversion are outlined.

  10. Frontiers in medical imaging technology

    International Nuclear Information System (INIS)

    Iinuma, Takeshi

    1992-01-01

    At present many medical images are used for diagnostics and treatment. After the advent of X-ray computer tomography (XCT), the violent development of medical images has continued. Medical imaging technology can be defined as the field of technology that deals with the production, processing, display, transmission, evaluation and so on of medical images, and it can be said that the present development of medical imaging diagnostics has been led by medical imaging technology. In this report, the most advanced technology of medical imaging is explained. The principle of XCT is shown. The feature of XCT is that it can image the delicate difference in the X-ray absorption factor of the cross section being measured. The technical development has been advanced to reduce the time for imaging and to heighten the resolution. The technology which brings about a large impact to future imaging diagnostics is computed radiography. Magnetic resonance imaging is the method of imaging the distribution of protons in human bodies. Positron CT is the method of measurement by injecting a positron-emitting RI. These methods are explained. (K.I.)

  11. The reference ballistic imaging database revisited.

    Science.gov (United States)

    De Ceuster, Jan; Dujardin, Sylvain

    2015-03-01

    A reference ballistic image database (RBID) contains images of cartridge cases fired in firearms that are in circulation: a ballistic fingerprint database. The performance of an RBID was investigated a decade ago by De Kinder et al. using IBIS(®) Heritage™ technology. The results of that study were published in this journal, issue 214. Since then, technologies have evolved quite significantly and novel apparatus have become available on the market. The current research article investigates the efficiency of another automated ballistic imaging system, Evofinder(®) using the same database as used by De Kinder et al. The results demonstrate a significant increase in correlation efficiency: 38% of all matches were on first position of the Evofinder correlation list in comparison to IBIS(®) Heritage™ where only 19% were on the first position. Average correlation times are comparable to the IBIS(®) Heritage™ system. While Evofinder(®) demonstrates specific improvement for mutually correlating different ammunition brands, ammunition dependence of the markings is still strongly influencing the correlation result because the markings may vary considerably. As a consequence a great deal of potential hits (36%) was still far down in the correlation lists (positions 31 and lower). The large database was used to examine the probability of finding a match as a function of correlation list verification. As an example, the RBID study on Evofinder(®) demonstrates that to find at least 90% of all potential matches, at least 43% of the items in the database need to be compared on screen and this for breech face markings and firing pin impression separately. These results, although a clear improvement to the original RBID study, indicate that the implementation of such a database should still not be considered nowadays. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  12. Medication errors detected in non-traditional databases

    DEFF Research Database (Denmark)

    Perregaard, Helene; Aronson, Jeffrey K; Dalhoff, Kim

    2015-01-01

    AIMS: We have looked for medication errors involving the use of low-dose methotrexate, by extracting information from Danish sources other than traditional pharmacovigilance databases. We used the data to establish the relative frequencies of different types of errors. METHODS: We searched four...... errors, whereas knowledge-based errors more often resulted in near misses. CONCLUSIONS: The medication errors in this survey were most often action-based (50%) and knowledge-based (34%), suggesting that greater attention should be paid to education and surveillance of medical personnel who prescribe...

  13. Machine learning and medical imaging

    CERN Document Server

    Shen, Dinggang; Sabuncu, Mert

    2016-01-01

    Machine Learning and Medical Imaging presents state-of- the-art machine learning methods in medical image analysis. It first summarizes cutting-edge machine learning algorithms in medical imaging, including not only classical probabilistic modeling and learning methods, but also recent breakthroughs in deep learning, sparse representation/coding, and big data hashing. In the second part leading research groups around the world present a wide spectrum of machine learning methods with application to different medical imaging modalities, clinical domains, and organs. The biomedical imaging modalities include ultrasound, magnetic resonance imaging (MRI), computed tomography (CT), histology, and microscopy images. The targeted organs span the lung, liver, brain, and prostate, while there is also a treatment of examining genetic associations. Machine Learning and Medical Imaging is an ideal reference for medical imaging researchers, industry scientists and engineers, advanced undergraduate and graduate students, a...

  14. Digital medical imaging

    International Nuclear Information System (INIS)

    Goeringer, F.; Mun, S.K.; Kerlin, B.D.

    1989-01-01

    In formulating an implementation strategy for digital medical imaging, three interrelated thrusts have emerged for the defense medical establishment. These thrusts: totally filmless medical imaging on the battlefield, teleradiology, and DIN/PACS for peacetime military health care are discussed. They have implications in their fully developed form as resource savers and quality improvers for the unique aspects of military health care

  15. EMITEL: E-Encyclopaedia and E-Dictionary of Medical Imaging Technologies

    International Nuclear Information System (INIS)

    Medvedec, M.; Kovacevic, N.; Magjarevic, R.

    2011-01-01

    EMITEL (European Medical Imaging Technology e-Encyclopaedia for Lifelong Learning) is an electronic encyclopaedia and multilingual dictionary related to medical imaging technologies. It is a result of the multi-annual international project which involved more than 250 contributors from 35 countries, aiming to foster development of medical physics and biomedical/clinical engineering by a lifelong e-learning web tool for all interested individuals or groups. Currently, the encyclopaedia is equivalent to about 2100 hard copy pages and includes about 3300 terms with an explanatory article for each term. The dictionary provides bidirectional cross-translation of terms between any two among 28 languages from its current database. Dictionary entries are divided into seven groups: diagnostic radiology, nuclear medicine, radiotherapy, magnetic resonance imaging, ultrasound imaging, radiation protection and general terms. Croatian language was implemented in EMITEL dictionary in April 2010. There were 17 Croatian translators and reviewers from 8 institutions and 3 cities, ranging from medical physics experts to linguist. The basic terminological principles of translation were final intelligibility of terms, desirable Croatian origin and linguistic appropriateness. Croatian contribution in the actual phase of EMITEL project attempted to improve the quality and efficiency of the specific professional, scientific and teaching terminology. A sort of novel, consistent and verified pool of terms of emerging medical imaging technologies was built up, as a one small part of the process of developing information technologies and socio-cultural transition from the industrial society into the society of knowledge. (author)

  16. Advances in medical image computing.

    Science.gov (United States)

    Tolxdorff, T; Deserno, T M; Handels, H; Meinzer, H-P

    2009-01-01

    Medical image computing has become a key technology in high-tech applications in medicine and an ubiquitous part of modern imaging systems and the related processes of clinical diagnosis and intervention. Over the past years significant progress has been made in the field, both on methodological and on application level. Despite this progress there are still big challenges to meet in order to establish image processing routinely in health care. In this issue, selected contributions of the German Conference on Medical Image Processing (BVM) are assembled to present latest advances in the field of medical image computing. The winners of scientific awards of the German Conference on Medical Image Processing (BVM) 2008 were invited to submit a manuscript on their latest developments and results for possible publication in Methods of Information in Medicine. Finally, seven excellent papers were selected to describe important aspects of recent advances in the field of medical image processing. The selected papers give an impression of the breadth and heterogeneity of new developments. New methods for improved image segmentation, non-linear image registration and modeling of organs are presented together with applications of image analysis methods in different medical disciplines. Furthermore, state-of-the-art tools and techniques to support the development and evaluation of medical image processing systems in practice are described. The selected articles describe different aspects of the intense development in medical image computing. The image processing methods presented enable new insights into the patient's image data and have the future potential to improve medical diagnostics and patient treatment.

  17. Integrating heterogeneous databases in clustered medic care environments using object-oriented technology

    Science.gov (United States)

    Thakore, Arun K.; Sauer, Frank

    1994-05-01

    The organization of modern medical care environments into disease-related clusters, such as a cancer center, a diabetes clinic, etc., has the side-effect of introducing multiple heterogeneous databases, often containing similar information, within the same organization. This heterogeneity fosters incompatibility and prevents the effective sharing of data amongst applications at different sites. Although integration of heterogeneous databases is now feasible, in the medical arena this is often an ad hoc process, not founded on proven database technology or formal methods. In this paper we illustrate the use of a high-level object- oriented semantic association method to model information found in different databases into an integrated conceptual global model that integrates the databases. We provide examples from the medical domain to illustrate an integration approach resulting in a consistent global view, without attacking the autonomy of the underlying databases.

  18. Experience with CANDID: Comparison algorithm for navigating digital image databases

    Energy Technology Data Exchange (ETDEWEB)

    Kelly, P.; Cannon, M.

    1994-10-01

    This paper presents results from the authors experience with CANDID (Comparison Algorithm for Navigating Digital Image Databases), which was designed to facilitate image retrieval by content using a query-by-example methodology. A global signature describing the texture, shape, or color content is first computed for every image stored in a database, and a normalized similarity measure between probability density functions of feature vectors is used to match signatures. This method can be used to retrieve images from a database that are similar to a user-provided example image. Results for three test applications are included.

  19. Medical Imaging.

    Science.gov (United States)

    Barker, M. C. J.

    1996-01-01

    Discusses four main types of medical imaging (x-ray, radionuclide, ultrasound, and magnetic resonance) and considers their relative merits. Describes important recent and possible future developments in image processing. (Author/MKR)

  20. Medical Image Tamper Detection Based on Passive Image Authentication.

    Science.gov (United States)

    Ulutas, Guzin; Ustubioglu, Arda; Ustubioglu, Beste; V Nabiyev, Vasif; Ulutas, Mustafa

    2017-12-01

    Telemedicine has gained popularity in recent years. Medical images can be transferred over the Internet to enable the telediagnosis between medical staffs and to make the patient's history accessible to medical staff from anywhere. Therefore, integrity protection of the medical image is a serious concern due to the broadcast nature of the Internet. Some watermarking techniques are proposed to control the integrity of medical images. However, they require embedding of extra information (watermark) into image before transmission. It decreases visual quality of the medical image and can cause false diagnosis. The proposed method uses passive image authentication mechanism to detect the tampered regions on medical images. Structural texture information is obtained from the medical image by using local binary pattern rotation invariant (LBPROT) to make the keypoint extraction techniques more successful. Keypoints on the texture image are obtained with scale invariant feature transform (SIFT). Tampered regions are detected by the method by matching the keypoints. The method improves the keypoint-based passive image authentication mechanism (they do not detect tampering when the smooth region is used for covering an object) by using LBPROT before keypoint extraction because smooth regions also have texture information. Experimental results show that the method detects tampered regions on the medical images even if the forged image has undergone some attacks (Gaussian blurring/additive white Gaussian noise) or the forged regions are scaled/rotated before pasting.

  1. Construction of image database for newspapaer articles using CTS

    Science.gov (United States)

    Kamio, Tatsuo

    Nihon Keizai Shimbun, Inc. developed a system of making articles' image database automatically by use of CTS (Computer Typesetting System). Besides the articles and the headlines inputted in CTS, it reproduces the image of elements of such as photography and graphs by article in accordance with information of position on the paper. So to speak, computer itself clips the articles out of the newspaper. Image database is accumulated in magnetic file and optical file and is output to the facsimile of users. With diffusion of CTS, newspaper companies which start to have structure of articles database are increased rapidly, the said system is the first attempt to make database automatically. This paper describes the device of CTS which supports this system and outline.

  2. ASTER 2002-2003 Kansas Satellite Image Database (KSID)

    Data.gov (United States)

    Kansas Data Access and Support Center — The Kansas Satellite Image Database (KSID):2002-2003 consists of image data gathered by three sensors. The first image data are terrain-corrected, precision...

  3. MODIS 2002-2003 Kansas Satellite Image Database (KSID)

    Data.gov (United States)

    Kansas Data Access and Support Center — The Kansas Satellite Image Database (KSID):2002-2003 consists of image data gathered by three sensors. The first image data are terrain-corrected, precision...

  4. Wavelet versus DCT-based spread spectrum watermarking of image databases

    Science.gov (United States)

    Mitrea, Mihai P.; Zaharia, Titus B.; Preteux, Francoise J.; Vlad, Adriana

    2004-05-01

    This paper addresses the issue of oblivious robust watermarking, within the framework of colour still image database protection. We present an original method which complies with all the requirements nowadays imposed to watermarking applications: robustness (e.g. low-pass filtering, print & scan, StirMark), transparency (both quality and fidelity), low probability of false alarm, obliviousness and multiple bit recovering. The mark is generated from a 64 bit message (be it a logo, a serial number, etc.) by means of a Spread Spectrum technique and is embedded into DWT (Discrete Wavelet Transform) domain, into certain low frequency coefficients, selected according to the hierarchy of their absolute values. The best results were provided by the (9,7) bi-orthogonal transform. The experiments were carried out on 1200 image sequences, each of them of 32 images. Note that these sequences represented several types of images: natural, synthetic, medical, etc. and each time we obtained the same good results. These results are compared with those we already obtained for the DCT domain, the differences being pointed out and discussed.

  5. The use of web internet technologies to distribute medical images

    International Nuclear Information System (INIS)

    Deller, A.L.; Cheal, D.; Field, J.

    1999-01-01

    Full text: In the past, internet browsers were considered ineffective for image distribution. Today we have the technology to use internet standards for picture archive and communication systems (PACS) and teleradiology effectively. Advanced wavelet compression and state-of-the-art JAVA software allows us to distribute images on normal computer hardware. The use of vendor and database neutral software and industry-standard hardware has many advantages. This standards base approach avoids the costly rapid obsolescence of proprietary PACS and is cheaper to purchase and maintain. Images can be distributed around a hospital site, as well as outside the campus, quickly and inexpensively. It also allows integration between the Hospital Information System (HIS) and the Radiology Information System (RIS). Being able to utilize standard internet technologies and computer hardware for PACS is a cost-effective alternative. A system based on this technology can be used for image distribution, archiving, teleradiology and RIS integration. This can be done without expensive specialized imaging workstations and telecommunication systems. Web distribution of images allows you to send images to multiple places concurrently. A study can be within your Medical Imaging Department, as well as in the ward and on the desktop of referring clinicians - with a report. As long as there is a computer with an internet access account, high-quality images can be at your disposal 24 h a day. The importance of medical images for patient management makes them a valuable component of the patient's medical record. Therefore, an efficient system for displaying and distributing images can improve patient management and make your workplace more effective

  6. Recent progress in medical imaging technology

    International Nuclear Information System (INIS)

    Endo, Masahiro

    2004-01-01

    Medical imaging is name of methods for diagnosis and therapy, which make visible with physical media such as X-ray, structures and functions of man's inside those are usually invisible. These methods are classified by the physical media into ultrasound imaging, magnetic resonance imaging, nuclear medicine imaging and X-ray imaging etc. Having characteristics different from one another, these are used complementarily in medical fields though in some case being competitive. Medical imaging is supported by highly progressed technology, which is called medical imaging technology. This paper describes a survey of recent progress of medical imaging technology in magnetic resonance imaging, nuclear medicine imaging and X-ray imaging. (author)

  7. Roles of medical image processing in medical physics

    International Nuclear Information System (INIS)

    Arimura, Hidetaka

    2011-01-01

    Image processing techniques including pattern recognition techniques play important roles in high precision diagnosis and radiation therapy. The author reviews a symposium on medical image information, which was held in the 100th Memorial Annual Meeting of the Japan Society of Medical Physics from September 23rd to 25th. In this symposium, we had three invited speakers, Dr. Akinobu Shimizu, Dr. Hideaki Haneishi, and Dr. Hirohito Mekata, who are active engineering researchers of segmentation, image registration, and pattern recognition, respectively. In this paper, the author reviews the roles of the medical imaging processing in medical physics field, and the talks of the three invited speakers. (author)

  8. Medical imaging

    International Nuclear Information System (INIS)

    Elliott, Alex

    2005-01-01

    Diagnostic medical imaging is a fundamental part of the practice of modern medicine and is responsible for the expenditure of considerable amounts of capital and revenue monies in healthcare systems around the world. Much research and development work is carried out, both by commercial companies and the academic community. This paper reviews briefly each of the major diagnostic medical imaging techniques-X-ray (planar and CT), ultrasound, nuclear medicine (planar, SPECT and PET) and magnetic resonance. The technical challenges facing each are highlighted, with some of the most recent developments. In terms of the future, interventional/peri-operative imaging, the advancement of molecular medicine and gene therapy are identified as potential areas of expansion

  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. Medical imaging informatics simulators: a tutorial.

    Science.gov (United States)

    Huang, H K; Deshpande, Ruchi; Documet, Jorge; Le, Anh H; Lee, Jasper; Ma, Kevin; Liu, Brent J

    2014-05-01

    A medical imaging informatics infrastructure (MIII) platform is an organized method of selecting tools and synthesizing data from HIS/RIS/PACS/ePR systems with the aim of developing an imaging-based diagnosis or treatment system. Evaluation and analysis of these systems can be made more efficient by designing and implementing imaging informatics simulators. This tutorial introduces the MIII platform and provides the definition of treatment/diagnosis systems, while primarily focusing on the development of the related simulators. A medical imaging informatics (MII) simulator in this context is defined as a system integration of many selected imaging and data components from the MIII platform and clinical treatment protocols, which can be used to simulate patient workflow and data flow starting from diagnostic procedures to the completion of treatment. In these processes, DICOM and HL-7 standards, IHE workflow profiles, and Web-based tools are emphasized. From the information collected in the database of a specific simulator, evidence-based medicine can be hypothesized to choose and integrate optimal clinical decision support components. Other relevant, selected clinical resources in addition to data and tools from the HIS/RIS/PACS and ePRs platform may also be tailored to develop the simulator. These resources can include image content indexing, 3D rendering with visualization, data grid and cloud computing, computer-aided diagnosis (CAD) methods, specialized image-assisted surgical, and radiation therapy technologies. Five simulators will be discussed in this tutorial. The PACS-ePR simulator with image distribution is the cradle of the other simulators. It supplies the necessary PACS-based ingredients and data security for the development of four other simulators: the data grid simulator for molecular imaging, CAD-PACS, radiation therapy simulator, and image-assisted surgery simulator. The purpose and benefits of each simulator with respect to its clinical relevance

  11. Medical imaging

    CERN Document Server

    Townsend, David W

    1996-01-01

    Since the introduction of the X-ray scanner into radiology almost 25 years ago, non-invasive imaging has become firmly established as an essential tool in the diagnosis of disease. Fully three-dimensional imaging of internal organs is now possible, b and for studies which explore the functional status of the body. Powerful techniques to correlate anatomy and function are available, and scanners which combine anatomical and functional imaging in a single device are under development. Such techniques have been made possible through r ecent technological and mathematical advances. This series of lectures will review both the physical basis of medical imaging techniques using X-rays, gamma and positron emitting radiosiotopes, and nuclear magnetic resonance, and the mathematical methods used to reconstruct three-dimentional distributions from projection data. The lectures will trace the development of medical imaging from simple radiographs to the present-day non-invasive measurement of in vivo biochemistry. They ...

  12. Drug interaction databases in medical literature

    DEFF Research Database (Denmark)

    Kongsholm, Gertrud Gansmo; Nielsen, Anna Katrine Toft; Damkier, Per

    2015-01-01

    PURPOSE: It is well documented that drug-drug interaction databases (DIDs) differ substantially with respect to classification of drug-drug interactions (DDIs). The aim of this study was to study online available transparency of ownership, funding, information, classifications, staff training...... available transparency of ownership, funding, information, classifications, staff training, and underlying documentation varies substantially among various DIDs. Open access DIDs had a statistically lower score on parameters assessed....... and the three most commonly used subscription DIDs in the medical literature. The following parameters were assessed for each of the databases: Ownership, classification of interactions, primary information sources, and staff qualification. We compared the overall proportion of yes/no answers from open access...

  13. An implementation of wireless medical image transmission system on mobile devices.

    Science.gov (United States)

    Lee, SangBock; Lee, Taesoo; Jin, Gyehwan; Hong, Juhyun

    2008-12-01

    The advanced technology of computing system was followed by the rapid improvement of medical instrumentation and patient record management system. The typical examples are hospital information system (HIS) and picture archiving and communication system (PACS), which computerized the management procedure of medical records and images in hospital. Because these systems were built and used in hospitals, doctors out of hospital have problems to access them immediately on emergent cases. To solve these problems, this paper addressed the realization of system that could transmit the images acquired by medical imaging systems in hospital to the remote doctors' handheld PDA's using CDMA cellular phone network. The system consists of server and PDA. The server was developed to manage the accounts of doctors and patients and allocate the patient images to each doctor. The PDA was developed to display patient images through remote server connection. To authenticate the personal user, remote data access (RDA) method was used in PDA accessing the server database and file transfer protocol (FTP) was used to download patient images from the remove server. In laboratory experiments, it was calculated to take ninety seconds to transmit thirty images with 832 x 488 resolution and 24 bit depth and 0.37 Mb size. This result showed that the developed system has no problems for remote doctors to receive and review the patient images immediately on emergent cases.

  14. Automated collection of medical images for research from heterogeneous systems: trials and tribulations

    Science.gov (United States)

    Patel, M. N.; Looney, P.; Young, K.; Halling-Brown, M. D.

    2014-03-01

    Radiological imaging is fundamental within the healthcare industry and has become routinely adopted for diagnosis, disease monitoring and treatment planning. Over the past two decades both diagnostic and therapeutic imaging have undergone a rapid growth, the ability to be able to harness this large influx of medical images can provide an essential resource for research and training. Traditionally, the systematic collection of medical images for research from heterogeneous sites has not been commonplace within the NHS and is fraught with challenges including; data acquisition, storage, secure transfer and correct anonymisation. Here, we describe a semi-automated system, which comprehensively oversees the collection of both unprocessed and processed medical images from acquisition to a centralised database. The provision of unprocessed images within our repository enables a multitude of potential research possibilities that utilise the images. Furthermore, we have developed systems and software to integrate these data with their associated clinical data and annotations providing a centralised dataset for research. Currently we regularly collect digital mammography images from two sites and partially collect from a further three, with efforts to expand into other modalities and sites currently ongoing. At present we have collected 34,014 2D images from 2623 individuals. In this paper we describe our medical image collection system for research and discuss the wide spectrum of challenges faced during the design and implementation of such systems.

  15. Grid Databases for Shared Image Analysis in the MammoGrid Project

    CERN Document Server

    Amendolia, S R; Hauer, T; Manset, D; McClatchey, R; Odeh, M; Reading, T; Rogulin, D; Schottlander, D; Solomonides, T

    2004-01-01

    The MammoGrid project aims to prove that Grid infrastructures can be used for collaborative clinical analysis of database-resident but geographically distributed medical images. This requires: a) the provision of a clinician-facing front-end workstation and b) the ability to service real-world clinician queries across a distributed and federated database. The MammoGrid project will prove the viability of the Grid by harnessing its power to enable radiologists from geographically dispersed hospitals to share standardized mammograms, to compare diagnoses (with and without computer aided detection of tumours) and to perform sophisticated epidemiological studies across national boundaries. This paper outlines the approach taken in MammoGrid to seamlessly connect radiologist workstations across a Grid using an "information infrastructure" and a DICOM-compliant object model residing in multiple distributed data stores in Italy and the UK

  16. Visual servoing in medical robotics: a survey. Part II: tomographic imaging modalities--techniques and applications.

    Science.gov (United States)

    Azizian, Mahdi; Najmaei, Nima; Khoshnam, Mahta; Patel, Rajni

    2015-03-01

    Intraoperative application of tomographic imaging techniques provides a means of visual servoing for objects beneath the surface of organs. The focus of this survey is on therapeutic and diagnostic medical applications where tomographic imaging is used in visual servoing. To this end, a comprehensive search of the electronic databases was completed for the period 2000-2013. Existing techniques and products are categorized and studied, based on the imaging modality and their medical applications. This part complements Part I of the survey, which covers visual servoing techniques using endoscopic imaging and direct vision. The main challenges in using visual servoing based on tomographic images have been identified. 'Supervised automation of medical robotics' is found to be a major trend in this field and ultrasound is the most commonly used tomographic modality for visual servoing. Copyright © 2014 John Wiley & Sons, Ltd.

  17. Genetic databases and consent for use of medical records

    NARCIS (Netherlands)

    Gevers, J. K. M.

    2004-01-01

    The legislation on the Icelandic genetic database provides for an opting-out system for the collection of encoded medical information from individual medical records. From the beginning this has raised criticism, in Iceland itself and abroad. The Supreme Court has now decided that this approach of

  18. The Application of Use Case Modeling in Designing Medical Imaging Information Systems

    International Nuclear Information System (INIS)

    Safdari, Reza; Farzi, Jebraeil; Ghazisaeidi, Marjan; Mirzaee, Mahboobeh; Goodini, Azadeh

    2013-01-01

    Introduction. The essay at hand is aimed at examining the application of use case modeling in analyzing and designing information systems to support Medical Imaging services. Methods. The application of use case modeling in analyzing and designing health information systems was examined using electronic databases (Pubmed, Google scholar) resources and the characteristics of the modeling system and its effect on the development and design of the health information systems were analyzed. Results. Analyzing the subject indicated that Provident modeling of health information systems should provide for quick access to many health data resources in a way that patients' data can be used in order to expand distant services and comprehensive Medical Imaging advices. Also these experiences show that progress in the infrastructure development stages through gradual and repeated evolution process of user requirements is stronger and this can lead to a decline in the cycle of requirements engineering process in the design of Medical Imaging information systems. Conclusion. Use case modeling approach can be effective in directing the problems of health and Medical Imaging information systems towards understanding, focusing on the start and analysis, better planning, repetition, and control

  19. Image processing in medical ultrasound

    DEFF Research Database (Denmark)

    Hemmsen, Martin Christian

    This Ph.D project addresses image processing in medical ultrasound and seeks to achieve two major scientific goals: First to develop an understanding of the most significant factors influencing image quality in medical ultrasound, and secondly to use this knowledge to develop image processing...... multiple imaging setups. This makes the system well suited for development of new processing methods and for clinical evaluations, where acquisition of the exact same scan location for multiple methods is important. The second project addressed implementation, development and evaluation of SASB using...... methods for enhancing the diagnostic value of medical ultrasound. The project is an industrial Ph.D project co-sponsored by BK Medical ApS., with the commercial goal to improve the image quality of BK Medicals scanners. Currently BK Medical employ a simple conventional delay-and-sum beamformer to generate...

  20. MedXViewer: an extensible web-enabled software package for medical imaging

    Science.gov (United States)

    Looney, P. T.; Young, K. C.; Mackenzie, Alistair; Halling-Brown, Mark D.

    2014-03-01

    MedXViewer (Medical eXtensible Viewer) is an application designed to allow workstation-independent, PACS-less viewing and interaction with anonymised medical images (e.g. observer studies). The application was initially implemented for use in digital mammography and tomosynthesis but the flexible software design allows it to be easily extended to other imaging modalities. Regions of interest can be identified by a user and any associated information about a mark, an image or a study can be added. The questions and settings can be easily configured depending on the need of the research allowing both ROC and FROC studies to be performed. The extensible nature of the design allows for other functionality and hanging protocols to be available for each study. Panning, windowing, zooming and moving through slices are all available while modality-specific features can be easily enabled e.g. quadrant zooming in mammographic studies. MedXViewer can integrate with a web-based image database allowing results and images to be stored centrally. The software and images can be downloaded remotely from this centralised data-store. Alternatively, the software can run without a network connection where the images and results can be encrypted and stored locally on a machine or external drive. Due to the advanced workstation-style functionality, the simple deployment on heterogeneous systems over the internet without a requirement for administrative access and the ability to utilise a centralised database, MedXViewer has been used for running remote paper-less observer studies and is capable of providing a training infrastructure and co-ordinating remote collaborative viewing sessions (e.g. cancer reviews, interesting cases).

  1. A generic method for improving the spatial interoperability of medical and ecological databases.

    Science.gov (United States)

    Ghenassia, A; Beuscart, J B; Ficheur, G; Occelli, F; Babykina, E; Chazard, E; Genin, M

    2017-10-03

    The availability of big data in healthcare and the intensive development of data reuse and georeferencing have opened up perspectives for health spatial analysis. However, fine-scale spatial studies of ecological and medical databases are limited by the change of support problem and thus a lack of spatial unit interoperability. The use of spatial disaggregation methods to solve this problem introduces errors into the spatial estimations. Here, we present a generic, two-step method for merging medical and ecological databases that avoids the use of spatial disaggregation methods, while maximizing the spatial resolution. Firstly, a mapping table is created after one or more transition matrices have been defined. The latter link the spatial units of the original databases to the spatial units of the final database. Secondly, the mapping table is validated by (1) comparing the covariates contained in the two original databases, and (2) checking the spatial validity with a spatial continuity criterion and a spatial resolution index. We used our novel method to merge a medical database (the French national diagnosis-related group database, containing 5644 spatial units) with an ecological database (produced by the French National Institute of Statistics and Economic Studies, and containing with 36,594 spatial units). The mapping table yielded 5632 final spatial units. The mapping table's validity was evaluated by comparing the number of births in the medical database and the ecological databases in each final spatial unit. The median [interquartile range] relative difference was 2.3% [0; 5.7]. The spatial continuity criterion was low (2.4%), and the spatial resolution index was greater than for most French administrative areas. Our innovative approach improves interoperability between medical and ecological databases and facilitates fine-scale spatial analyses. We have shown that disaggregation models and large aggregation techniques are not necessarily the best ways to

  2. Supporting ontology-based keyword search over medical databases.

    Science.gov (United States)

    Kementsietsidis, Anastasios; Lim, Lipyeow; Wang, Min

    2008-11-06

    The proliferation of medical terms poses a number of challenges in the sharing of medical information among different stakeholders. Ontologies are commonly used to establish relationships between different terms, yet their role in querying has not been investigated in detail. In this paper, we study the problem of supporting ontology-based keyword search queries on a database of electronic medical records. We present several approaches to support this type of queries, study the advantages and limitations of each approach, and summarize the lessons learned as best practices.

  3. Exploring Human Cognition Using Large Image Databases.

    Science.gov (United States)

    Griffiths, Thomas L; Abbott, Joshua T; Hsu, Anne S

    2016-07-01

    Most cognitive psychology experiments evaluate models of human cognition using a relatively small, well-controlled set of stimuli. This approach stands in contrast to current work in neuroscience, perception, and computer vision, which have begun to focus on using large databases of natural images. We argue that natural images provide a powerful tool for characterizing the statistical environment in which people operate, for better evaluating psychological theories, and for bringing the insights of cognitive science closer to real applications. We discuss how some of the challenges of using natural images as stimuli in experiments can be addressed through increased sample sizes, using representations from computer vision, and developing new experimental methods. Finally, we illustrate these points by summarizing recent work using large image databases to explore questions about human cognition in four different domains: modeling subjective randomness, defining a quantitative measure of representativeness, identifying prior knowledge used in word learning, and determining the structure of natural categories. Copyright © 2016 Cognitive Science Society, Inc.

  4. 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...

  5. Computer-aided diagnosis workstation and database system for chest diagnosis based on multi-helical CT images

    Science.gov (United States)

    Satoh, Hitoshi; Niki, Noboru; Mori, Kiyoshi; Eguchi, Kenji; Kaneko, Masahiro; Kakinuma, Ryutarou; Moriyama, Noriyuki; Ohmatsu, Hironobu; Masuda, Hideo; Machida, Suguru; Sasagawa, Michizou

    2006-03-01

    Multi-helical CT scanner advanced remarkably at the speed at which the chest CT images were acquired for mass screening. Mass screening based on multi-helical CT images requires a considerable number of images to be read. It is this time-consuming step that makes the use of helical CT for mass screening impractical at present. To overcome this problem, we have provided diagnostic assistance methods to medical screening specialists by developing a lung cancer screening algorithm that automatically detects suspected lung cancers in helical CT images and a coronary artery calcification screening algorithm that automatically detects suspected coronary artery calcification. We also have developed electronic medical recording system and prototype internet system for the community health in two or more regions by using the Virtual Private Network router and Biometric fingerprint authentication system and Biometric face authentication system for safety of medical information. Based on these diagnostic assistance methods, we have now developed a new computer-aided workstation and database that can display suspected lesions three-dimensionally in a short time. This paper describes basic studies that have been conducted to evaluate this new system. The results of this study indicate that our computer-aided diagnosis workstation and network system can increase diagnostic speed, diagnostic accuracy and safety of medical information.

  6. 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....

  7. Structure of the medical digital image

    International Nuclear Information System (INIS)

    Baltadzhiev, D.

    1997-01-01

    In up-to-date medical practice diagnostic imaging techniques are the most powerful tools available to clinicians. The modern medical equipment is entirely based on digital technology. In this article the principle of generating medical images is presented. The concept for gray scale where medical images are commonly presented is described. The patterns of gray images transformation into colour scale are likewise outlined. Basic notions from medical imaging terminology such as image matrix, pixel, spatial and contrast resolution power, bit, byte and the like are explained. Also an example is given of how the binary system treats images. On the basis of digital technology the obtained medical images lend themselves readily to additional processing, reconstruction (including 3D) and storage for subsequent utilization. The ceaseless progress of computerized communications promote easy and prompt access for clinicians to the diagnostic images needed as well as realization of expert consultations by teleconference contact (author)

  8. Improvement of medication event interventions through use of an electronic database.

    Science.gov (United States)

    Merandi, Jenna; Morvay, Shelly; Lewe, Dorcas; Stewart, Barb; Catt, Char; Chanthasene, Phillip P; McClead, Richard; Kappeler, Karl; Mirtallo, Jay M

    2013-10-01

    Patient safety enhancements achieved through the use of an electronic Web-based system for responding to adverse drug events (ADEs) are described. A two-phase initiative was carried out at an academic pediatric hospital to improve processes related to "medication event huddles" (interdisciplinary meetings focused on ADE interventions). Phase 1 of the initiative entailed a review of huddles and interventions over a 16-month baseline period during which multiple databases were used to manage the huddle process and staff interventions were assigned via manually generated e-mail reminders. Phase 1 data collection included ADE details (e.g., medications and staff involved, location and date of event) and the types and frequencies of interventions. Based on the phase 1 analysis, an electronic database was created to eliminate the use of multiple systems for huddle scheduling and documentation and to automatically generate e-mail reminders on assigned interventions. In phase 2 of the initiative, the impact of the database during a 5-month period was evaluated; the primary outcome was the percentage of interventions documented as completed after database implementation. During the postimplementation period, 44.7% of assigned interventions were completed, compared with a completion rate of 21% during the preimplementation period, and interventions documented as incomplete decreased from 77% to 43.7% (p Process changes, education, and medication order improvements were the most frequently documented categories of interventions. Implementation of a user-friendly electronic database improved intervention completion and documentation after medication event huddles.

  9. Standardizing terminology and definitions of medication adherence and persistence in research employing electronic databases.

    Science.gov (United States)

    Raebel, Marsha A; Schmittdiel, Julie; Karter, Andrew J; Konieczny, Jennifer L; Steiner, John F

    2013-08-01

    To propose a unifying set of definitions for prescription adherence research utilizing electronic health record prescribing databases, prescription dispensing databases, and pharmacy claims databases and to provide a conceptual framework to operationalize these definitions consistently across studies. We reviewed recent literature to identify definitions in electronic database studies of prescription-filling patterns for chronic oral medications. We then develop a conceptual model and propose standardized terminology and definitions to describe prescription-filling behavior from electronic databases. The conceptual model we propose defines 2 separate constructs: medication adherence and persistence. We define primary and secondary adherence as distinct subtypes of adherence. Metrics for estimating secondary adherence are discussed and critiqued, including a newer metric (New Prescription Medication Gap measure) that enables estimation of both primary and secondary adherence. Terminology currently used in prescription adherence research employing electronic databases lacks consistency. We propose a clear, consistent, broadly applicable conceptual model and terminology for such studies. The model and definitions facilitate research utilizing electronic medication prescribing, dispensing, and/or claims databases and encompasses the entire continuum of prescription-filling behavior. Employing conceptually clear and consistent terminology to define medication adherence and persistence will facilitate future comparative effectiveness research and meta-analytic studies that utilize electronic prescription and dispensing records.

  10. A comparative study of six European databases of medically oriented Web resources.

    Science.gov (United States)

    Abad García, Francisca; González Teruel, Aurora; Bayo Calduch, Patricia; de Ramón Frias, Rosa; Castillo Blasco, Lourdes

    2005-10-01

    The paper describes six European medically oriented databases of Web resources, pertaining to five quality-controlled subject gateways, and compares their performance. The characteristics, coverage, procedure for selecting Web resources, record structure, searching possibilities, and existence of user assistance were described for each database. Performance indicators for each database were obtained by means of searches carried out using the key words, "myocardial infarction." Most of the databases originated in the 1990s in an academic or library context and include all types of Web resources of an international nature. Five databases use Medical Subject Headings. The number of fields per record varies between three and nineteen. The language of the search interfaces is mostly English, and some of them allow searches in other languages. In some databases, the search can be extended to Pubmed. Organizing Medical Networked Information, Catalogue et Index des Sites Médicaux Francophones, and Diseases, Disorders and Related Topics produced the best results. The usefulness of these databases as quick reference resources is clear. In addition, their lack of content overlap means that, for the user, they complement each other. Their continued survival faces three challenges: the instability of the Internet, maintenance costs, and lack of use in spite of their potential usefulness.

  11. Med-records: an ADD database of AAEC medical records since 1966

    International Nuclear Information System (INIS)

    Barry, J.M.; Pollard, J.P.; Tucker, A.D.

    1986-08-01

    Since its inception in 1958 most of the staff of the AAEC Research Establishment at Lucas Heights have had annual medical examinations. Medical information accrued since 1966 has been collected as an ADD database to allow ad hoc enquiries to be made against the data. Details are given of the database schema and numerous support routines ranging from the integrity checking of input data to analysis and plotting of the summary results

  12. Processing of medical images

    International Nuclear Information System (INIS)

    Restrepo, A.

    1998-01-01

    Thanks to the innovations in the technology for the processing of medical images, to the high development of better and cheaper computers, and, additionally, to the advances in the systems of communications of medical images, the acquisition, storage and handling of digital images has acquired great importance in all the branches of the medicine. It is sought in this article to introduce some fundamental ideas of prosecution of digital images that include such aspects as their representation, storage, improvement, visualization and understanding

  13. An end to end secure CBIR over encrypted medical database.

    Science.gov (United States)

    Bellafqira, Reda; Coatrieux, Gouenou; Bouslimi, Dalel; Quellec, Gwenole

    2016-08-01

    In this paper, we propose a new secure content based image retrieval (SCBIR) system adapted to the cloud framework. This solution allows a physician to retrieve images of similar content within an outsourced and encrypted image database, without decrypting them. Contrarily to actual CBIR approaches in the encrypted domain, the originality of the proposed scheme stands on the fact that the features extracted from the encrypted images are themselves encrypted. This is achieved by means of homomorphic encryption and two non-colluding servers, we however both consider as honest but curious. In that way an end to end secure CBIR process is ensured. Experimental results carried out on a diabetic retinopathy database encrypted with the Paillier cryptosystem indicate that our SCBIR achieves retrieval performance as good as if images were processed in their non-encrypted form.

  14. Towards adapting a normal patient database for SPECT brain perfusion imaging

    International Nuclear Information System (INIS)

    Smith, N D; Soleimani, M; Mitchell, C N; Holmes, R B; Evans, M J; Cade, S C

    2012-01-01

    Single-photon emission computerized tomography (SPECT) is a tool which can be used to image perfusion in the brain. Clinicians can use such images to help diagnose dementias such as Alzheimer's disease. Due to the intrinsic stochasticity in the photon imaging system, some form of statistical comparison of an individual image with a 'normal' patient database gives a clinician additional confidence in interpreting the image. Due to the variations between SPECT camera systems, ideally a normal patient database is required for each individual system. However, cost or ethical considerations often prohibit the collection of such a database for each new camera system. Some method of adapting existing normal patient databases to new camera systems would be beneficial. This paper introduces a method which may be regarded as a 'first-pass' attempt based on 2-norm regularization and a codebook of discrete spatially stationary convolutional kernels. Some preliminary illustrative results are presented, together with discussion on limitations and possible improvements

  15. Images - RPSD | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available switchLanguage; BLAST Search Image Search Home About Archive Update History Data ...ta file File name: rpsd_images.zip File URL: ftp://ftp.biosciencedbc.jp/archive/rpsd/LATEST/rpsd_images.zip ... History of This Database Site Policy | Contact Us Images - RPSD | LSDB Archive ...

  16. A study on the optimization of referring method about medical images using MIH (Medical Image History)

    International Nuclear Information System (INIS)

    Kim, Sun Chil; Kim, Jung Min

    2002-01-01

    The recent development of embodiment technology of the medical images makes most medical institutions introduce PACS (Picture Archiving and Communication System) in haste. However lots of PACS solutions, currently developed and distributed, haven't been able to serve the convenience of users and to satisfy user's demand because of economic limitations and administrator-oriented con-siderations in the process of development. So we have developed MIH (Medical Image History), by which we can search and refer to the patient's medical images and information with few restrictions of time and space for diagnosis and treatment. The program will contribute to the improvement in the medical environment and meet the clients' need. We'll make more effort to develop the application which insures the better quality of medical images. MIH manages the patient's image files and medical records like film chart in connection with time. This trial will contribute to the reduction of the economical loss caused by unnecessary references and improve the quality in the medical services. The demand on the development of the program which refers to the medical data quickly and keeps them stable will be continued by the medical institute. This will satisfy the client's demand and improve the service to the patients in that the program will be modified from the standpoint of the users. MIH is trying to keep user-oriented policy and to apply the benefit of the analog system to the digital environment. It is necessary to lead the public to the better understanding that the systematic management and referring of the medical images is as important as the quality of the images

  17. Evaluating parallel relational databases for medical data analysis.

    Energy Technology Data Exchange (ETDEWEB)

    Rintoul, Mark Daniel; Wilson, Andrew T.

    2012-03-01

    Hospitals have always generated and consumed large amounts of data concerning patients, treatment and outcomes. As computers and networks have permeated the hospital environment it has become feasible to collect and organize all of this data. This raises naturally the question of how to deal with the resulting mountain of information. In this report we detail a proof-of-concept test using two commercially available parallel database systems to analyze a set of real, de-identified medical records. We examine database scalability as data sizes increase as well as responsiveness under load from multiple users.

  18. A data model and database for high-resolution pathology analytical image informatics.

    Science.gov (United States)

    Wang, Fusheng; Kong, Jun; Cooper, Lee; Pan, Tony; Kurc, Tahsin; Chen, Wenjin; Sharma, Ashish; Niedermayr, Cristobal; Oh, Tae W; Brat, Daniel; Farris, Alton B; Foran, David J; Saltz, Joel

    2011-01-01

    The systematic analysis of imaged pathology specimens often results in a vast amount of morphological information at both the cellular and sub-cellular scales. While microscopy scanners and computerized analysis are capable of capturing and analyzing data rapidly, microscopy image data remain underutilized in research and clinical settings. One major obstacle which tends to reduce wider adoption of these new technologies throughout the clinical and scientific communities is the challenge of managing, querying, and integrating the vast amounts of data resulting from the analysis of large digital pathology datasets. This paper presents a data model, which addresses these challenges, and demonstrates its implementation in a relational database system. This paper describes a data model, referred to as Pathology Analytic Imaging Standards (PAIS), and a database implementation, which are designed to support the data management and query requirements of detailed characterization of micro-anatomic morphology through many interrelated analysis pipelines on whole-slide images and tissue microarrays (TMAs). (1) Development of a data model capable of efficiently representing and storing virtual slide related image, annotation, markup, and feature information. (2) Development of a database, based on the data model, capable of supporting queries for data retrieval based on analysis and image metadata, queries for comparison of results from different analyses, and spatial queries on segmented regions, features, and classified objects. The work described in this paper is motivated by the challenges associated with characterization of micro-scale features for comparative and correlative analyses involving whole-slides tissue images and TMAs. Technologies for digitizing tissues have advanced significantly in the past decade. Slide scanners are capable of producing high-magnification, high-resolution images from whole slides and TMAs within several minutes. Hence, it is becoming

  19. A data model and database for high-resolution pathology analytical image informatics

    Directory of Open Access Journals (Sweden)

    Fusheng Wang

    2011-01-01

    Full Text Available Background: The systematic analysis of imaged pathology specimens often results in a vast amount of morphological information at both the cellular and sub-cellular scales. While microscopy scanners and computerized analysis are capable of capturing and analyzing data rapidly, microscopy image data remain underutilized in research and clinical settings. One major obstacle which tends to reduce wider adoption of these new technologies throughout the clinical and scientific communities is the challenge of managing, querying, and integrating the vast amounts of data resulting from the analysis of large digital pathology datasets. This paper presents a data model, which addresses these challenges, and demonstrates its implementation in a relational database system. Context: This paper describes a data model, referred to as Pathology Analytic Imaging Standards (PAIS, and a database implementation, which are designed to support the data management and query requirements of detailed characterization of micro-anatomic morphology through many interrelated analysis pipelines on whole-slide images and tissue microarrays (TMAs. Aims: (1 Development of a data model capable of efficiently representing and storing virtual slide related image, annotation, markup, and feature information. (2 Development of a database, based on the data model, capable of supporting queries for data retrieval based on analysis and image metadata, queries for comparison of results from different analyses, and spatial queries on segmented regions, features, and classified objects. Settings and Design: The work described in this paper is motivated by the challenges associated with characterization of micro-scale features for comparative and correlative analyses involving whole-slides tissue images and TMAs. Technologies for digitizing tissues have advanced significantly in the past decade. Slide scanners are capable of producing high-magnification, high-resolution images from whole

  20. Kansas Satellite Image Database (KSID) 2004-2005

    Data.gov (United States)

    Kansas Data Access and Support Center — The Kansas Satellite Image Database (KSID) 2004-2005 consists of terrain-corrected, precision rectified spring, summer, and fall Landsat 5 Thematic Mapper (TM)...

  1. Luminescence in medical image science

    Energy Technology Data Exchange (ETDEWEB)

    Kandarakis, I.S., E-mail: kandarakis@teiath.gr

    2016-01-15

    Radiation detection in Medical Imaging is mostly based on the use of luminescent materials (scintillators and phosphors) coupled to optical sensors. Materials are employed in the form of granular screens, structured (needle-like) crystals and single crystal transparent blocks. Storage phosphors are also incorporated in some x-ray imaging plates. Description of detector performance is currently based on quality metrics, such as the Luminescence efficiency, the Modulation Transfer Function (MTF), the Noise Power Spectrum (NPS) and the Detective Quantum Efficiency (DQE) can be defined and evaluated. The aforementioned metrics are experimental evaluated for various materials in the form of screens. A software was designed (MINORE v1) to present image quality measurements in a graphical user interface (GUI) environment. Luminescence efficiency, signal and noise analysis are valuable tools for the evaluation of luminescent materials as candidates for medical imaging detectors. - Highlights: • Luminescence based medical imaging detectors. • Image science: MTF, NPS, DQE. • Phosphors screens light emission efficiency experimental evaluation. • Theoretical models for estimation of phosphor screen properties. • Software for medical image quality metrics.

  2. Medical X-ray Image Hierarchical Classification Using a Merging and Splitting Scheme in Feature Space.

    Science.gov (United States)

    Fesharaki, Nooshin Jafari; Pourghassem, Hossein

    2013-07-01

    Due to the daily mass production and the widespread variation of medical X-ray images, it is necessary to classify these for searching and retrieving proposes, especially for content-based medical image retrieval systems. In this paper, a medical X-ray image hierarchical classification structure based on a novel merging and splitting scheme and using shape and texture features is proposed. In the first level of the proposed structure, to improve the classification performance, similar classes with regard to shape contents are grouped based on merging measures and shape features into the general overlapped classes. In the next levels of this structure, the overlapped classes split in smaller classes based on the classification performance of combination of shape and texture features or texture features only. Ultimately, in the last levels, this procedure is also continued forming all the classes, separately. Moreover, to optimize the feature vector in the proposed structure, we use orthogonal forward selection algorithm according to Mahalanobis class separability measure as a feature selection and reduction algorithm. In other words, according to the complexity and inter-class distance of each class, a sub-space of the feature space is selected in each level and then a supervised merging and splitting scheme is applied to form the hierarchical classification. The proposed structure is evaluated on a database consisting of 2158 medical X-ray images of 18 classes (IMAGECLEF 2005 database) and accuracy rate of 93.6% in the last level of the hierarchical structure for an 18-class classification problem is obtained.

  3. Cloud Engineering Principles and Technology Enablers for Medical Image Processing-as-a-Service

    Science.gov (United States)

    Bao, Shunxing; Plassard, Andrew J.; Landman, Bennett A.; Gokhale, Aniruddha

    2017-01-01

    Traditional in-house, laboratory-based medical imaging studies use hierarchical data structures (e.g., NFS file stores) or databases (e.g., COINS, XNAT) for storage and retrieval. The resulting performance from these approaches is, however, impeded by standard network switches since they can saturate network bandwidth during transfer from storage to processing nodes for even moderate-sized studies. To that end, a cloud-based “medical image processing-as-a-service” offers promise in utilizing the ecosystem of Apache Hadoop, which is a flexible framework providing distributed, scalable, fault tolerant storage and parallel computational modules, and HBase, which is a NoSQL database built atop Hadoop’s distributed file system. Despite this promise, HBase’s load distribution strategy of region split and merge is detrimental to the hierarchical organization of imaging data (e.g., project, subject, session, scan, slice). This paper makes two contributions to address these concerns by describing key cloud engineering principles and technology enhancements we made to the Apache Hadoop ecosystem for medical imaging applications. First, we propose a row-key design for HBase, which is a necessary step that is driven by the hierarchical organization of imaging data. Second, we propose a novel data allocation policy within HBase to strongly enforce collocation of hierarchically related imaging data. The proposed enhancements accelerate data processing by minimizing network usage and localizing processing to machines where the data already exist. Moreover, our approach is amenable to the traditional scan, subject, and project-level analysis procedures, and is compatible with standard command line/scriptable image processing software. Experimental results for an illustrative sample of imaging data reveals that our new HBase policy results in a three-fold time improvement in conversion of classic DICOM to NiFTI file formats when compared with the default HBase region split

  4. Cloud Engineering Principles and Technology Enablers for Medical Image Processing-as-a-Service.

    Science.gov (United States)

    Bao, Shunxing; Plassard, Andrew J; Landman, Bennett A; Gokhale, Aniruddha

    2017-04-01

    Traditional in-house, laboratory-based medical imaging studies use hierarchical data structures (e.g., NFS file stores) or databases (e.g., COINS, XNAT) for storage and retrieval. The resulting performance from these approaches is, however, impeded by standard network switches since they can saturate network bandwidth during transfer from storage to processing nodes for even moderate-sized studies. To that end, a cloud-based "medical image processing-as-a-service" offers promise in utilizing the ecosystem of Apache Hadoop, which is a flexible framework providing distributed, scalable, fault tolerant storage and parallel computational modules, and HBase, which is a NoSQL database built atop Hadoop's distributed file system. Despite this promise, HBase's load distribution strategy of region split and merge is detrimental to the hierarchical organization of imaging data (e.g., project, subject, session, scan, slice). This paper makes two contributions to address these concerns by describing key cloud engineering principles and technology enhancements we made to the Apache Hadoop ecosystem for medical imaging applications. First, we propose a row-key design for HBase, which is a necessary step that is driven by the hierarchical organization of imaging data. Second, we propose a novel data allocation policy within HBase to strongly enforce collocation of hierarchically related imaging data. The proposed enhancements accelerate data processing by minimizing network usage and localizing processing to machines where the data already exist. Moreover, our approach is amenable to the traditional scan, subject, and project-level analysis procedures, and is compatible with standard command line/scriptable image processing software. Experimental results for an illustrative sample of imaging data reveals that our new HBase policy results in a three-fold time improvement in conversion of classic DICOM to NiFTI file formats when compared with the default HBase region split policy

  5. A study on the optimization of referring method about medical images using MIH (Medical Image History)

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Sun Chil; Kim, Jung Min [College of Health Sciences, Korea University, Seoul (Korea, Republic of)

    2002-09-15

    The recent development of embodiment technology of the medical images makes most medical institutions introduce PACS (Picture Archiving and Communication System) in haste. However lots of PACS solutions, currently developed and distributed, haven't been able to serve the convenience of users and to satisfy user's demand because of economic limitations and administrator-oriented con-siderations in the process of development. So we have developed MIH (Medical Image History), by which we can search and refer to the patient's medical images and information with few restrictions of time and space for diagnosis and treatment. The program will contribute to the improvement in the medical environment and meet the clients' need. We'll make more effort to develop the application which insures the better quality of medical images. MIH manages the patient's image files and medical records like film chart in connection with time. This trial will contribute to the reduction of the economical loss caused by unnecessary references and improve the quality in the medical services. The demand on the development of the program which refers to the medical data quickly and keeps them stable will be continued by the medical institute. This will satisfy the client's demand and improve the service to the patients in that the program will be modified from the standpoint of the users. MIH is trying to keep user-oriented policy and to apply the benefit of the analog system to the digital environment. It is necessary to lead the public to the better understanding that the systematic management and referring of the medical images is as important as the quality of the images.

  6. Medical imaging

    International Nuclear Information System (INIS)

    Loshkajian, A.

    2000-01-01

    This didactical book presents the medical imaging techniques: radiography, scanner, nuclear magnetic resonance (NMR). Examples are given for the most common pathologies in all domains of medicine. (J.S.)

  7. Image-based query-by-example for big databases of galaxy images

    Science.gov (United States)

    Shamir, Lior; Kuminski, Evan

    2017-01-01

    Very large astronomical databases containing millions or even billions of galaxy images have been becoming increasingly important tools in astronomy research. However, in many cases the very large size makes it more difficult to analyze these data manually, reinforcing the need for computer algorithms that can automate the data analysis process. An example of such task is the identification of galaxies of a certain morphology of interest. For instance, if a rare galaxy is identified it is reasonable to expect that more galaxies of similar morphology exist in the database, but it is virtually impossible to manually search these databases to identify such galaxies. Here we describe computer vision and pattern recognition methodology that receives a galaxy image as an input, and searches automatically a large dataset of galaxies to return a list of galaxies that are visually similar to the query galaxy. The returned list is not necessarily complete or clean, but it provides a substantial reduction of the original database into a smaller dataset, in which the frequency of objects visually similar to the query galaxy is much higher. Experimental results show that the algorithm can identify rare galaxies such as ring galaxies among datasets of 10,000 astronomical objects.

  8. Java advanced medical image toolkit

    International Nuclear Information System (INIS)

    Saunder, T.H.C.; O'Keefe, G.J.; Scott, A.M.

    2002-01-01

    Full text: The Java Advanced Medical Image Toolkit (jAMIT) has been developed at the Center for PET and Department of Nuclear Medicine in an effort to provide a suite of tools that can be utilised in applications required to perform analysis, processing and visualisation of medical images. jAMIT uses Java Advanced Imaging (JAI) to combine the platform independent nature of Java with the speed benefits associated with native code. The object-orientated nature of Java allows the production of an extensible and robust package which is easily maintained. In addition to jAMIT, a Medical Image VO API called Sushi has been developed to provide access to many commonly used image formats. These include DICOM, Analyze, MINC/NetCDF, Trionix, Beat 6.4, Interfile 3.2/3.3 and Odyssey. This allows jAMIT to access data and study information contained in different medical image formats transparently. Additional formats can be added at any time without any modification to the jAMIT package. Tools available in jAMIT include 2D ROI Analysis, Palette Thresholding, Image Groping, Image Transposition, Scaling, Maximum Intensity Projection, Image Fusion, Image Annotation and Format Conversion. Future tools may include 2D Linear and Non-linear Registration, PET SUV Calculation, 3D Rendering and 3D ROI Analysis. Applications currently using JAMIT include Antibody Dosimetry Analysis, Mean Hemispheric Blood Flow Analysis, QuickViewing of PET Studies for Clinical Training, Pharamcodynamic Modelling based on Planar Imaging, and Medical Image Format Conversion. The use of jAMIT and Sushi for scripting and analysis in Matlab v6.1 and Jython is currently being explored. Copyright (2002) The Australian and New Zealand Society of Nuclear Medicine Inc

  9. A broadband multimedia collaborative system for advanced teleradiology and medical imaging diagnosis.

    Science.gov (United States)

    Gómez, E J; del Pozo, F; Ortiz, E J; Malpica, N; Rahms, H

    1998-09-01

    This paper presents a new telemedicine system currently in routine clinical usage, developed within the European Union (EU) ACTS BONAPARTE project (1). The telemedicine system is developed on an asynchronous transfer mode (ATM) multimedia hardware/software platform comprising the following set of telemedicine services: synchronous cooperative work, high-quality video conference, multimedia mail, medical image digitizing, processing, storing and printing, and local and remote transparent database access. The medical information handled by the platform conforms to the Digital Imaging and Communications in Medicine (DICOM) 3.0 medical imaging standard. The telemedicine system has been installed for clinical routines in three Spanish hospitals since November 1997 and has been used in an average of one/two clinical sessions per week. At each clinical session, a usability and clinical evaluation of the system was carried out. Evaluation is carried out through direct observation of interactions and questionnaire-based subjective data. The usability evaluation methodology and the results of the system usability study are also presented in this article. The experience gained from the design, development, and evaluation of the telemedicine system is providing an indepth knowledge of the benefits and difficulties involved in the installation and clinical usage of this type of high-usability and advanced multimedia telemedicine system in the field of teleradiology and collaborative medical imaging diagnosis.

  10. Compressive sensing in medical imaging.

    Science.gov (United States)

    Graff, Christian G; Sidky, Emil Y

    2015-03-10

    The promise of compressive sensing, exploitation of compressibility to achieve high quality image reconstructions with less data, has attracted a great deal of attention in the medical imaging community. At the Compressed Sensing Incubator meeting held in April 2014 at OSA Headquarters in Washington, DC, presentations were given summarizing some of the research efforts ongoing in compressive sensing for x-ray computed tomography and magnetic resonance imaging systems. This article provides an expanded version of these presentations. Sparsity-exploiting reconstruction algorithms that have gained popularity in the medical imaging community are studied, and examples of clinical applications that could benefit from compressive sensing ideas are provided. The current and potential future impact of compressive sensing on the medical imaging field is discussed.

  11. Medical Imaging Informatics in Nuclear Medicine

    NARCIS (Netherlands)

    van Ooijen, Peter; Glaudemans, Andor W.J.M.; Medema, Jitze; van Zanten, Annie K.; Dierckx, Rudi A.J.O.; Ahaus, C.T.B. (Kees)

    2016-01-01

    Medical imaging informatics is gaining importance in medicine both in clinical practice and in scientific research. Besides radiology, nuclear medicine is also a major stakeholder in medical imaging informatics because of the variety of available imaging modalities and the imaging-oriented operation

  12. Nuclear imaging in the realm of medical imaging

    International Nuclear Information System (INIS)

    Deconinck, Frank

    2003-01-01

    In medical imaging, information concerning the anatomy or biological processes of a patient is detected and presented on film or screen for interpretation by a reader. The information flow from patient to reader optimally implies: - the emission, transmission or reflection of information carriers, typically photons or sound waves, which have to be correctly modulated by patient information through interactions in the patient; - their detection by adequate imaging equipment preserving essential spectral, spatial and/or temporal information; - the presentation of the information in the most perceivable way; - the observation by an unbiased and trained expert. In reality, only an approximation to this optimal situation is achieved. It is the goal of R and D in the medical imaging field to approach the optimum as much as possible within societal constraints such as patient risk and comfort, economics, etc. First, the basic physical concepts underlying the imaging process will be introduced. Different imaging modalities will then be situated in the realm of medical imaging with some emphasis on nuclear imaging

  13. Distributed data collection for a database of radiological image interpretations

    Science.gov (United States)

    Long, L. Rodney; Ostchega, Yechiam; Goh, Gin-Hua; Thoma, George R.

    1997-01-01

    The National Library of Medicine, in collaboration with the National Center for Health Statistics and the National Institute for Arthritis and Musculoskeletal and Skin Diseases, has built a system for collecting radiological interpretations for a large set of x-ray images acquired as part of the data gathered in the second National Health and Nutrition Examination Survey. This system is capable of delivering across the Internet 5- and 10-megabyte x-ray images to Sun workstations equipped with X Window based 2048 X 2560 image displays, for the purpose of having these images interpreted for the degree of presence of particular osteoarthritic conditions in the cervical and lumbar spines. The collected interpretations can then be stored in a database at the National Library of Medicine, under control of the Illustra DBMS. This system is a client/server database application which integrates (1) distributed server processing of client requests, (2) a customized image transmission method for faster Internet data delivery, (3) distributed client workstations with high resolution displays, image processing functions and an on-line digital atlas, and (4) relational database management of the collected data.

  14. Machine Learning for Medical Imaging.

    Science.gov (United States)

    Erickson, Bradley J; Korfiatis, Panagiotis; Akkus, Zeynettin; Kline, Timothy L

    2017-01-01

    Machine learning is a technique for recognizing patterns that can be applied to medical images. Although it is a powerful tool that can help in rendering medical diagnoses, it can be misapplied. Machine learning typically begins with the machine learning algorithm system computing the image features that are believed to be of importance in making the prediction or diagnosis of interest. The machine learning algorithm system then identifies the best combination of these image features for classifying the image or computing some metric for the given image region. There are several methods that can be used, each with different strengths and weaknesses. There are open-source versions of most of these machine learning methods that make them easy to try and apply to images. Several metrics for measuring the performance of an algorithm exist; however, one must be aware of the possible associated pitfalls that can result in misleading metrics. More recently, deep learning has started to be used; this method has the benefit that it does not require image feature identification and calculation as a first step; rather, features are identified as part of the learning process. Machine learning has been used in medical imaging and will have a greater influence in the future. Those working in medical imaging must be aware of how machine learning works. © RSNA, 2017.

  15. Automated medical image segmentation techniques

    Directory of Open Access Journals (Sweden)

    Sharma Neeraj

    2010-01-01

    Full Text Available Accurate segmentation of medical images is a key step in contouring during radiotherapy planning. Computed topography (CT and Magnetic resonance (MR imaging are the most widely used radiographic techniques in diagnosis, clinical studies and treatment planning. This review provides details of automated segmentation methods, specifically discussed in the context of CT and MR images. The motive is to discuss the problems encountered in segmentation of CT and MR images, and the relative merits and limitations of methods currently available for segmentation of medical images.

  16. Visual servoing in medical robotics: a survey. Part I: endoscopic and direct vision imaging - techniques and applications.

    Science.gov (United States)

    Azizian, Mahdi; Khoshnam, Mahta; Najmaei, Nima; Patel, Rajni V

    2014-09-01

    Intra-operative imaging is widely used to provide visual feedback to a clinician when he/she performs a procedure. In visual servoing, surgical instruments and parts of tissue/body are tracked by processing the acquired images. This information is then used within a control loop to manoeuvre a robotic manipulator during a procedure. A comprehensive search of electronic databases was completed for the period 2000-2013 to provide a survey of the visual servoing applications in medical robotics. The focus is on medical applications where image-based tracking is used for closed-loop control of a robotic system. Detailed classification and comparative study of various contributions in visual servoing using endoscopic or direct visual images are presented and summarized in tables and diagrams. The main challenges in using visual servoing for medical robotic applications are identified and potential future directions are suggested. 'Supervised automation of medical robotics' is found to be a major trend in this field. Copyright © 2013 John Wiley & Sons, Ltd.

  17. Medical image information system 2001. Development of the medical image information system to risk management- Medical exposure management

    International Nuclear Information System (INIS)

    Kuranishi, Makoto; Kumagai, Michitomo; Shintani, Mitsuo

    2000-01-01

    This paper discusses the methods and systems for optimizing the following supplements 10 and 17 for national health and medical care. The supplements 10 and 17 of DICOM (digital imaging and communications in medicine) system, which is now under progress for the purpose to keep compatibility within medical image information system as an international standard, are important for making the cooperation between HIS (hospital information system)/RIS (radiation information system) and modality (imaging instruments). Supplement 10 concerns the system to send the information of patients and their orders through HIS/RIS to modality and 17, the information of modality performed procedure step (MPPS) to HIS/RIS. The latter defines to document patients' exposure, a part of which has not been recognized in Japan. Thus the medical information system can be useful for risk-management of medical exposure in future. (K.H.)

  18. Medical image information system 2001. Development of the medical image information system to risk management- Medical exposure management

    Energy Technology Data Exchange (ETDEWEB)

    Kuranishi, Makoto; Kumagai, Michitomo; Shintani, Mitsuo [Toyama Medical and Pharmaceutical Univ. (Japan). Hospital

    2000-12-01

    This paper discusses the methods and systems for optimizing the following supplements 10 and 17 for national health and medical care. The supplements 10 and 17 of DICOM (digital imaging and communications in medicine) system, which is now under progress for the purpose to keep compatibility within medical image information system as an international standard, are important for making the cooperation between HIS (hospital information system)/RIS (radiation information system) and modality (imaging instruments). Supplement 10 concerns the system to send the information of patients and their orders through HIS/RIS to modality and 17, the information of modality performed procedure step (MPPS) to HIS/RIS. The latter defines to document patients' exposure, a part of which has not been recognized in Japan. Thus the medical information system can be useful for risk-management of medical exposure in future. (K.H.)

  19. Medical imaging systems

    Science.gov (United States)

    Frangioni, John V

    2013-06-25

    A medical imaging system provides simultaneous rendering of visible light and diagnostic or functional images. The system may be portable, and may include adapters for connecting various light sources and cameras in open surgical environments or laparascopic or endoscopic environments. A user interface provides control over the functionality of the integrated imaging system. In one embodiment, the system provides a tool for surgical pathology.

  20. Medical Imaging with Neural Networks

    International Nuclear Information System (INIS)

    Pattichis, C.; Cnstantinides, A.

    1994-01-01

    The objective of this paper is to provide an overview of the recent developments in the use of artificial neural networks in medical imaging. The areas of medical imaging that are covered include : ultrasound, magnetic resonance, nuclear medicine and radiological (including computerized tomography). (authors)

  1. Medical image registration algorithms assesment Bronze Standard application enactment on grids using the MOTEUR workflow engine

    CERN Document Server

    Glatard, T; Pennec, X

    2006-01-01

    Medical image registration is pre-processing needed for many medical image analysis procedures. A very large number of registration algorithms are available today, but their performance is often not known and very difficult to assess due to the lack of gold standard. The Bronze Standard algorithm is a very data and compute intensive statistical approach for quantifying registration algorithms accuracy. In this paper, we describe the Bronze Standard application and we discuss the need for grids to tackle such computations on medical image databases. We demonstrate MOTEUR, a service-based workflow engine optimized for dealing with data intensive applications. MOTEUR eases the enactment of the Bronze Standard and similar applications on the EGEE production grid infrastructure. It is a generic workflow engine, based on current standards and freely available, that can be used to instrument legacy application code at low cost.

  2. Medical imaging and augmented reality. Proceedings

    International Nuclear Information System (INIS)

    Dohi, Takeyoshi; Sakuma, Ichiro; Liao, Hongen

    2008-01-01

    This book constitutes the refereed proceedings of the 4th International Workshop on Medical Imaging and Augmented Reality, MIAR 2008, held in Tokyo, Japan, in August 2008. The 44 revised full papers presented together with 3 invited papers were carefully reviewed and selected from 90 submissions. The papers are organized in topical sections on surgical planning and simulation, medical image computing, image analysis, shape modeling and morphometry, image-guided robotics, image-guided intervention, interventional imaging, image registration, augmented reality, and image segmentation. (orig.)

  3. Medical imaging and augmented reality. Proceedings

    Energy Technology Data Exchange (ETDEWEB)

    Dohi, Takeyoshi [Tokyo Univ. (Japan). Dept. of Mechano-Informatics; Sakuma, Ichiro [Tokyo Univ. (Japan). Dept. of Precision Engineering; Liao, Hongen (eds.) [Tokyo Univ. (Japan). Dept. of Bioengineering

    2008-07-01

    This book constitutes the refereed proceedings of the 4th International Workshop on Medical Imaging and Augmented Reality, MIAR 2008, held in Tokyo, Japan, in August 2008. The 44 revised full papers presented together with 3 invited papers were carefully reviewed and selected from 90 submissions. The papers are organized in topical sections on surgical planning and simulation, medical image computing, image analysis, shape modeling and morphometry, image-guided robotics, image-guided intervention, interventional imaging, image registration, augmented reality, and image segmentation. (orig.)

  4. [Medical image compression: a review].

    Science.gov (United States)

    Noreña, Tatiana; Romero, Eduardo

    2013-01-01

    Modern medicine is an increasingly complex activity , based on the evidence ; it consists of information from multiple sources : medical record text , sound recordings , images and videos generated by a large number of devices . Medical imaging is one of the most important sources of information since they offer comprehensive support of medical procedures for diagnosis and follow-up . However , the amount of information generated by image capturing gadgets quickly exceeds storage availability in radiology services , generating additional costs in devices with greater storage capacity . Besides , the current trend of developing applications in cloud computing has limitations, even though virtual storage is available from anywhere, connections are made through internet . In these scenarios the optimal use of information necessarily requires powerful compression algorithms adapted to medical activity needs . In this paper we present a review of compression techniques used for image storage , and a critical analysis of them from the point of view of their use in clinical settings.

  5. Generative Interpretation of Medical Images

    DEFF Research Database (Denmark)

    Stegmann, Mikkel Bille

    2004-01-01

    This thesis describes, proposes and evaluates methods for automated analysis and quantification of medical images. A common theme is the usage of generative methods, which draw inference from unknown images by synthesising new images having shape, pose and appearance similar to the analysed images......, handling of non-Gaussian variation by means of cluster analysis, correction of respiratory noise in cardiac MRI, and the extensions to multi-slice two-dimensional time-series and bi-temporal three-dimensional models. The medical applications include automated estimation of: left ventricular ejection...

  6. Medical Imaging with Neural Networks

    Energy Technology Data Exchange (ETDEWEB)

    Pattichis, C [Department of Computer Science, University of Cyprus, Kallipoleos 75, P.O.Box 537, Nicosia (Cyprus); Cnstantinides, A [Department of Electrical Engineering, Imperial College of Science, Technology and Medicine, London SW7 2BT (United Kingdom)

    1994-12-31

    The objective of this paper is to provide an overview of the recent developments in the use of artificial neural networks in medical imaging. The areas of medical imaging that are covered include : ultrasound, magnetic resonance, nuclear medicine and radiological (including computerized tomography). (authors). 61 refs, 4 tabs.

  7. 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.

  8. Image analysis and modeling in medical image computing. Recent developments and advances.

    Science.gov (United States)

    Handels, H; Deserno, T M; Meinzer, H-P; Tolxdorff, T

    2012-01-01

    Medical image computing is of growing importance in medical diagnostics and image-guided therapy. Nowadays, image analysis systems integrating advanced image computing methods are used in practice e.g. to extract quantitative image parameters or to support the surgeon during a navigated intervention. However, the grade of automation, accuracy, reproducibility and robustness of medical image computing methods has to be increased to meet the requirements in clinical routine. In the focus theme, recent developments and advances in the field of modeling and model-based image analysis are described. The introduction of models in the image analysis process enables improvements of image analysis algorithms in terms of automation, accuracy, reproducibility and robustness. Furthermore, model-based image computing techniques open up new perspectives for prediction of organ changes and risk analysis of patients. Selected contributions are assembled to present latest advances in the field. The authors were invited to present their recent work and results based on their outstanding contributions to the Conference on Medical Image Computing BVM 2011 held at the University of Lübeck, Germany. All manuscripts had to pass a comprehensive peer review. Modeling approaches and model-based image analysis methods showing new trends and perspectives in model-based medical image computing are described. Complex models are used in different medical applications and medical images like radiographic images, dual-energy CT images, MR images, diffusion tensor images as well as microscopic images are analyzed. The applications emphasize the high potential and the wide application range of these methods. The use of model-based image analysis methods can improve segmentation quality as well as the accuracy and reproducibility of quantitative image analysis. Furthermore, image-based models enable new insights and can lead to a deeper understanding of complex dynamic mechanisms in the human body

  9. Quantitative information in medical imaging

    International Nuclear Information System (INIS)

    Deconinck, F.

    1985-01-01

    When developing new imaging or image processing techniques, one constantly has in mind that the new technique should provide a better, or more optimal answer to medical tasks than existing techniques do 'Better' or 'more optimal' imply some kind of standard by which one can measure imaging or image processing performance. The choice of a particular imaging modality to answer a diagnostic task, such as the detection of coronary artery stenosis is also based on an implicit optimalisation of performance criteria. Performance is measured by the ability to provide information about an object (patient) to the person (referring doctor) who ordered a particular task. In medical imaging the task is generally to find quantitative information on bodily function (biochemistry, physiology) and structure (histology, anatomy). In medical imaging, a wide range of techniques is available. Each technique has it's own characteristics. The techniques discussed in this paper are: nuclear magnetic resonance, X-ray fluorescence, scintigraphy, positron emission tomography, applied potential tomography, computerized tomography, and compton tomography. This paper provides a framework for the comparison of imaging performance, based on the way the quantitative information flow is altered by the characteristics of the modality

  10. 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

  11. Evidence based medical imaging (EBMI)

    International Nuclear Information System (INIS)

    Smith, Tony

    2008-01-01

    Background: The evidence based paradigm was first described about a decade ago. Previous authors have described a framework for the application of evidence based medicine which can be readily adapted to medical imaging practice. Purpose: This paper promotes the application of the evidence based framework in both the justification of the choice of examination type and the optimisation of the imaging technique used. Methods: The framework includes five integrated steps: framing a concise clinical question; searching for evidence to answer that question; critically appraising the evidence; applying the evidence in clinical practice; and, evaluating the use of revised practices. Results: This paper illustrates the use of the evidence based framework in medical imaging (that is, evidence based medical imaging) using the examples of two clinically relevant case studies. In doing so, a range of information technology and other resources available to medical imaging practitioners are identified with the intention of encouraging the application of the evidence based paradigm in radiography and radiology. Conclusion: There is a perceived need for radiographers and radiologists to make greater use of valid research evidence from the literature to inform their clinical practice and thus provide better quality services

  12. Medical imaging technology

    CERN Document Server

    Haidekker, Mark A

    2013-01-01

    Biomedical imaging is a relatively young discipline that started with Conrad Wilhelm Roentgen’s discovery of the x-ray in 1885. X-ray imaging was rapidly adopted in hospitals around the world. However, it was the advent of computerized data and image processing that made revolutionary new imaging modalities possible. Today, cross-sections and three-dimensional reconstructions of the organs inside the human body is possible with unprecedented speed, detail and quality. This book provides an introduction into the principles of image formation of key medical imaging modalities: X-ray projection imaging, x-ray computed tomography, magnetic resonance imaging, ultrasound imaging, and radionuclide imaging. Recent developments in optical imaging are also covered. For each imaging modality, the introduction into the physical principles and sources of contrast is provided, followed by the methods of image formation, engineering aspects of the imaging devices, and a discussion of strengths and limitations of the modal...

  13. A high-performance spatial database based approach for pathology imaging algorithm evaluation.

    Science.gov (United States)

    Wang, Fusheng; Kong, Jun; Gao, Jingjing; Cooper, Lee A D; Kurc, Tahsin; Zhou, Zhengwen; Adler, David; Vergara-Niedermayr, Cristobal; Katigbak, Bryan; Brat, Daniel J; Saltz, Joel H

    2013-01-01

    Algorithm evaluation provides a means to characterize variability across image analysis algorithms, validate algorithms by comparison with human annotations, combine results from multiple algorithms for performance improvement, and facilitate algorithm sensitivity studies. The sizes of images and image analysis results in pathology image analysis pose significant challenges in algorithm evaluation. We present an efficient parallel spatial database approach to model, normalize, manage, and query large volumes of analytical image result data. This provides an efficient platform for algorithm evaluation. Our experiments with a set of brain tumor images demonstrate the application, scalability, and effectiveness of the platform. The paper describes an approach and platform for evaluation of pathology image analysis algorithms. The platform facilitates algorithm evaluation through a high-performance database built on the Pathology Analytic Imaging Standards (PAIS) data model. (1) Develop a framework to support algorithm evaluation by modeling and managing analytical results and human annotations from pathology images; (2) Create a robust data normalization tool for converting, validating, and fixing spatial data from algorithm or human annotations; (3) Develop a set of queries to support data sampling and result comparisons; (4) Achieve high performance computation capacity via a parallel data management infrastructure, parallel data loading and spatial indexing optimizations in this infrastructure. WE HAVE CONSIDERED TWO SCENARIOS FOR ALGORITHM EVALUATION: (1) algorithm comparison where multiple result sets from different methods are compared and consolidated; and (2) algorithm validation where algorithm results are compared with human annotations. We have developed a spatial normalization toolkit to validate and normalize spatial boundaries produced by image analysis algorithms or human annotations. The validated data were formatted based on the PAIS data model and

  14. Visual perception and medical imaging

    International Nuclear Information System (INIS)

    Jaffe, C.C.

    1985-01-01

    Medical imaging represents a particularly distinct discipline for image processing since it uniquely depends on the ''expert observer'' and yet models of the human visual system are totally inadequate at the complex level to allow satisfactory prediction of observer response to a given image modification. An illustration of the difficulties in assessing observer performance is shown by a series of optical illustrations which demonstrate that net cognitive behavior is not readily predictable. Although many of these phenomena are often considered as exceptional visual events, the setting of complex images makes it difficult to entirely exclude at least partial operation of these impairments during performance of the diagnostic medical imaging task

  15. Medical hyperspectral imaging: a review

    Science.gov (United States)

    Lu, Guolan; Fei, Baowei

    2014-01-01

    Abstract. Hyperspectral imaging (HSI) is an emerging imaging modality for medical applications, especially in disease diagnosis and image-guided surgery. HSI acquires a three-dimensional dataset called hypercube, with two spatial dimensions and one spectral dimension. Spatially resolved spectral imaging obtained by HSI provides diagnostic information about the tissue physiology, morphology, and composition. This review paper presents an overview of the literature on medical hyperspectral imaging technology and its applications. The aim of the survey is threefold: an introduction for those new to the field, an overview for those working in the field, and a reference for those searching for literature on a specific application. PMID:24441941

  16. Landsat TM and ETM+ 2002-2003 Kansas Satellite Image Database (KSID)

    Data.gov (United States)

    Kansas Data Access and Support Center — The Kansas Satellite Image Database (KSID):2002-2003 consists of image data gathered by three sensors. The first image data are terrain-corrected, precision...

  17. An overview of medical image data base

    International Nuclear Information System (INIS)

    Nishihara, Eitaro

    1992-01-01

    Recently, the systematization using computers in medical institutions has advanced, and the introduction of hospital information system has been almost completed in the large hospitals with more than 500 beds. But the objects of the management of the hospital information system are text information, and do not include the management of images of enormous quantity. By the progress of image diagnostic equipment, the digitization of medical images has advanced, but the management of images in hospitals does not utilize the merits of digital images. For the purpose of solving these problems, the picture archiving and communication system (PACS) was proposed about ten years ago, which makes medical images into a data base, and enables the on-line access to images from various places in hospitals. The studies have been continued to realize it. The features of medical image data, the present status of utilizing medical image data, the outline of the PACS, the image data base for the PACS, the problems in the realization of the data base and the technical trend, and the state of actual construction of the PACS are reported. (K.I.)

  18. Multimedia human brain database system for surgical candidacy determination in temporal lobe epilepsy with content-based image retrieval

    Science.gov (United States)

    Siadat, Mohammad-Reza; Soltanian-Zadeh, Hamid; Fotouhi, Farshad A.; Elisevich, Kost

    2003-01-01

    This paper presents the development of a human brain multimedia database for surgical candidacy determination in temporal lobe epilepsy. The focus of the paper is on content-based image management, navigation and retrieval. Several medical image-processing methods including our newly developed segmentation method are utilized for information extraction/correlation and indexing. The input data includes T1-, T2-Weighted MRI and FLAIR MRI and ictal and interictal SPECT modalities with associated clinical data and EEG data analysis. The database can answer queries regarding issues such as the correlation between the attribute X of the entity Y and the outcome of a temporal lobe epilepsy surgery. The entity Y can be a brain anatomical structure such as the hippocampus. The attribute X can be either a functionality feature of the anatomical structure Y, calculated with SPECT modalities, such as signal average, or a volumetric/morphological feature of the entity Y such as volume or average curvature. The outcome of the surgery can be any surgery assessment such as memory quotient. A determination is made regarding surgical candidacy by analysis of both textual and image data. The current database system suggests a surgical determination for the cases with relatively small hippocampus and high signal intensity average on FLAIR images within the hippocampus. This indication pretty much fits with the surgeons" expectations/observations. Moreover, as the database gets more populated with patient profiles and individual surgical outcomes, using data mining methods one may discover partially invisible correlations between the contents of different modalities of data and the outcome of the surgery.

  19. HVS-based medical image compression

    Energy Technology Data Exchange (ETDEWEB)

    Kai Xie [Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, 200030 Shanghai (China)]. E-mail: xie_kai2001@sjtu.edu.cn; Jie Yang [Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, 200030 Shanghai (China); Min Zhuyue [CREATIS-CNRS Research Unit 5515 and INSERM Unit 630, 69621 Villeurbanne (France); Liang Lixiao [Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, 200030 Shanghai (China)

    2005-07-01

    Introduction: With the promotion and application of digital imaging technology in the medical domain, the amount of medical images has grown rapidly. However, the commonly used compression methods cannot acquire satisfying results. Methods: In this paper, according to the existed and stated experiments and conclusions, the lifting step approach is used for wavelet decomposition. The physical and anatomic structure of human vision is combined and the contrast sensitivity function (CSF) is introduced as the main research issue in human vision system (HVS), and then the main designing points of HVS model are presented. On the basis of multi-resolution analyses of wavelet transform, the paper applies HVS including the CSF characteristics to the inner correlation-removed transform and quantization in image and proposes a new HVS-based medical image compression model. Results: The experiments are done on the medical images including computed tomography (CT) and magnetic resonance imaging (MRI). At the same bit rate, the performance of SPIHT, with respect to the PSNR metric, is significantly higher than that of our algorithm. But the visual quality of the SPIHT-compressed image is roughly the same as that of the image compressed with our approach. Our algorithm obtains the same visual quality at lower bit rates and the coding/decoding time is less than that of SPIHT. Conclusions: The results show that under common objective conditions, our compression algorithm can achieve better subjective visual quality, and performs better than that of SPIHT in the aspects of compression ratios and coding/decoding time.

  20. HVS-based medical image compression

    International Nuclear Information System (INIS)

    Kai Xie; Jie Yang; Min Zhuyue; Liang Lixiao

    2005-01-01

    Introduction: With the promotion and application of digital imaging technology in the medical domain, the amount of medical images has grown rapidly. However, the commonly used compression methods cannot acquire satisfying results. Methods: In this paper, according to the existed and stated experiments and conclusions, the lifting step approach is used for wavelet decomposition. The physical and anatomic structure of human vision is combined and the contrast sensitivity function (CSF) is introduced as the main research issue in human vision system (HVS), and then the main designing points of HVS model are presented. On the basis of multi-resolution analyses of wavelet transform, the paper applies HVS including the CSF characteristics to the inner correlation-removed transform and quantization in image and proposes a new HVS-based medical image compression model. Results: The experiments are done on the medical images including computed tomography (CT) and magnetic resonance imaging (MRI). At the same bit rate, the performance of SPIHT, with respect to the PSNR metric, is significantly higher than that of our algorithm. But the visual quality of the SPIHT-compressed image is roughly the same as that of the image compressed with our approach. Our algorithm obtains the same visual quality at lower bit rates and the coding/decoding time is less than that of SPIHT. Conclusions: The results show that under common objective conditions, our compression algorithm can achieve better subjective visual quality, and performs better than that of SPIHT in the aspects of compression ratios and coding/decoding time

  1. Interpretation of medical imaging data with a mobile application: a mobile digital imaging processing environment

    Directory of Open Access Journals (Sweden)

    Meng Kuan eLin

    2013-07-01

    Full Text Available Digital Imaging Processing (DIP requires data extraction and output from a visualization tool to be consistent. Data handling and transmission between the server and a user is a systematic process in service interpretation. The use of integrated medical services for management and viewing of imaging data in combination with a mobile visualization tool can be greatly facilitated by data analysis and interpretation. This paper presents an integrated mobile application and digital imaging processing service, called M-DIP. The objective of the system is to (1 automate the direct data tiling, conversion, pre-tiling of brain images from Medical Imaging NetCDF (MINC, Neuroimaging Informatics Technology Initiative (NIFTI to RAW formats; (2 speed up querying of imaging measurement; and (3 display high level of images with three dimensions in real world coordinates. In addition, M-DIP provides the ability to work on a mobile or tablet device without any software installation using web-based protocols. M-DIP implements three levels of architecture with a relational middle- layer database, a stand-alone DIP server and a mobile application logic middle level realizing user interpretation for direct querying and communication. This imaging software has the ability to display biological imaging data a multiple zoom levels and to increase its quality to meet users expectations. Interpretation of bioimaging data is facilitated by an interface analogous to online mapping services using real world coordinate browsing. This allows mobile devices to display multiple datasets simultaneously from a remote site. M-DIP can be used as a measurement repository that can be accessed by any network environment, such as a portable mobile or tablet device. In addition, this system and combination with mobile applications are establishing a virtualization tool in the neuroinformatics field to speed interpretation services.

  2. Application of stereo-imaging technology to medical field.

    Science.gov (United States)

    Nam, Kyoung Won; Park, Jeongyun; Kim, In Young; Kim, Kwang Gi

    2012-09-01

    There has been continuous development in the area of stereoscopic medical imaging devices, and many stereoscopic imaging devices have been realized and applied in the medical field. In this article, we review past and current trends pertaining to the application stereo-imaging technologies in the medical field. We describe the basic principles of stereo vision and visual issues related to it, including visual discomfort, binocular disparities, vergence-accommodation mismatch, and visual fatigue. We also present a brief history of medical applications of stereo-imaging techniques, examples of recently developed stereoscopic medical devices, and patent application trends as they pertain to stereo-imaging medical devices. Three-dimensional (3D) stereo-imaging technology can provide more realistic depth perception to the viewer than conventional two-dimensional imaging technology. Therefore, it allows for a more accurate understanding and analysis of the morphology of an object. Based on these advantages, the significance of stereoscopic imaging in the medical field increases in accordance with the increase in the number of laparoscopic surgeries, and stereo-imaging technology plays a key role in the diagnoses of the detailed morphologies of small biological specimens. The application of 3D stereo-imaging technology to the medical field will help improve surgical accuracy, reduce operation times, and enhance patient safety. Therefore, it is important to develop more enhanced stereoscopic medical devices.

  3. Developments in medical imaging techniques

    International Nuclear Information System (INIS)

    Kramer, Cornelis

    1979-01-01

    A review of the developments in medical imaging in the past 25 years shows a strong increase in the number of physical methods which have become available for obtaining images of diagnostic value. It is shown that despite this proliferation of methods the equipment used for obtaining the images can be based on a common structure. Also the resulting images can be characterized by a few relevant parameters which indicate their information content. On the basis of this common architecture a study is made of the potential capabilities of the large number of medical imaging techniques available now and in the future. Also the requirements and possibilities for handling the images obtained and for controlling the diagnostic systems are investigated [fr

  4. 21 CFR 892.2040 - Medical image hardcopy device.

    Science.gov (United States)

    2010-04-01

    ... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Medical image hardcopy device. 892.2040 Section... (CONTINUED) MEDICAL DEVICES RADIOLOGY DEVICES Diagnostic Devices § 892.2040 Medical image hardcopy device. (a) Identification. A medical image hardcopy device is a device that produces a visible printed record of a medical...

  5. On the Perceptual Organization of Image Databases Using Cognitive Discriminative Biplots

    Directory of Open Access Journals (Sweden)

    Spiros Fotopoulos

    2007-01-01

    Full Text Available A human-centered approach to image database organization is presented in this study. The management of a generic image database is pursued using a standard psychophysical experimental procedure followed by a well-suited data analysis methodology that is based on simple geometrical concepts. The end result is a cognitive discriminative biplot, which is a visualization of the intrinsic organization of the image database best reflecting the user's perception. The discriminating power of the introduced cognitive biplot constitutes an appealing tool for image retrieval and a flexible interface for visual data mining tasks. These ideas were evaluated in two ways. First, the separability of semantically distinct image classes was measured according to their reduced representations on the biplot. Then, a nearest-neighbor retrieval scheme was run on the emerged low-dimensional terrain to measure the suitability of the biplot for performing content-based image retrieval (CBIR. The achieved organization performance when compared with the performance of a contemporary system was found superior. This promoted the further discussion of packing these ideas into a realizable algorithmic procedure for an efficient and effective personalized CBIR system.

  6. Stereoscopic medical imaging collaboration system

    Science.gov (United States)

    Okuyama, Fumio; Hirano, Takenori; Nakabayasi, Yuusuke; Minoura, Hirohito; Tsuruoka, Shinji

    2007-02-01

    The computerization of the clinical record and the realization of the multimedia have brought improvement of the medical service in medical facilities. It is very important for the patients to obtain comprehensible informed consent. Therefore, the doctor should plainly explain the purpose and the content of the diagnoses and treatments for the patient. We propose and design a Telemedicine Imaging Collaboration System which presents a three dimensional medical image as X-ray CT, MRI with stereoscopic image by using virtual common information space and operating the image from a remote location. This system is composed of two personal computers, two 15 inches stereoscopic parallax barrier type LCD display (LL-151D, Sharp), one 1Gbps router and 1000base LAN cables. The software is composed of a DICOM format data transfer program, an operation program of the images, the communication program between two personal computers and a real time rendering program. Two identical images of 512×768 pixcels are displayed on two stereoscopic LCD display, and both images show an expansion, reduction by mouse operation. This system can offer a comprehensible three-dimensional image of the diseased part. Therefore, the doctor and the patient can easily understand it, depending on their needs.

  7. A review on the application of medical infrared thermal imaging in hands

    Science.gov (United States)

    Sousa, Elsa; Vardasca, Ricardo; Teixeira, Sérgio; Seixas, Adérito; Mendes, Joaquim; Costa-Ferreira, António

    2017-09-01

    Infrared Thermal (IRT) imaging is a medical imaging modality to study skin temperature in real time, providing physiological information about the underlining structures. One of the most accessible body sites to be investigated using such imaging method is the hands, which can reflect valuable information about conditions affecting the upper limbs. The aim of this review is to acquaint the successful applications of IRT in the hands with a medical scope, opening horizons for future applications based in the achieved results. A systematic literature review was performed in order to assess in which applications medical IRT imaging was applied to the hands. The literature search was conducted in the reference databases: PubMed, Scopus and ISI Web of Science, making use of keywords (hand, thermography, infrared imaging, thermal imaging) combination that were present at the title and abstract. No temporal restriction was made. As a result, 4260 articles were identified, after removal of duplicates, 3224 articles remained and from first title and abstract filtering, a total of 388 articles were considered. After application of exclusion criteria (non-availability, non-clinical applications, reviews, case studies, written in other languages than English and using liquid crystal thermography), 146 articles were considered for this review. It can be verified that thermography provides useful diagnostic and monitoring information of conditions that directly or indirectly related to hands, as well as aiding in the treatment assessment. Trends and future challenges for IRT applications on hands are provided to stimulate researchers and clinicians to explore and address them.

  8. A comparative study on medical image segmentation methods

    Directory of Open Access Journals (Sweden)

    Praylin Selva Blessy SELVARAJ ASSLEY

    2014-03-01

    Full Text Available Image segmentation plays an important role in medical images. It has been a relevant research area in computer vision and image analysis. Many segmentation algorithms have been proposed for medical images. This paper makes a review on segmentation methods for medical images. In this survey, segmentation methods are divided into five categories: region based, boundary based, model based, hybrid based and atlas based. The five different categories with their principle ideas, advantages and disadvantages in segmenting different medical images are discussed.

  9. Classification in Medical Imaging

    DEFF Research Database (Denmark)

    Chen, Chen

    Classification is extensively used in the context of medical image analysis for the purpose of diagnosis or prognosis. In order to classify image content correctly, one needs to extract efficient features with discriminative properties and build classifiers based on these features. In addition...... on characterizing human faces and emphysema disease in lung CT images....

  10. Improved medical image modality classification using a combination of visual and textual features.

    Science.gov (United States)

    Dimitrovski, Ivica; Kocev, Dragi; Kitanovski, Ivan; Loskovska, Suzana; Džeroski, Sašo

    2015-01-01

    In this paper, we present the approach that we applied to the medical modality classification tasks at the ImageCLEF evaluation forum. More specifically, we used the modality classification databases from the ImageCLEF competitions in 2011, 2012 and 2013, described by four visual and one textual types of features, and combinations thereof. We used local binary patterns, color and edge directivity descriptors, fuzzy color and texture histogram and scale-invariant feature transform (and its variant opponentSIFT) as visual features and the standard bag-of-words textual representation coupled with TF-IDF weighting. The results from the extensive experimental evaluation identify the SIFT and opponentSIFT features as the best performing features for modality classification. Next, the low-level fusion of the visual features improves the predictive performance of the classifiers. This is because the different features are able to capture different aspects of an image, their combination offering a more complete representation of the visual content in an image. Moreover, adding textual features further increases the predictive performance. Finally, the results obtained with our approach are the best results reported on these databases so far. Copyright © 2014 Elsevier Ltd. All rights reserved.

  11. Reducing noise component on medical images

    Science.gov (United States)

    Semenishchev, Evgeny; Voronin, Viacheslav; Dub, Vladimir; Balabaeva, Oksana

    2018-04-01

    Medical visualization and analysis of medical data is an actual direction. Medical images are used in microbiology, genetics, roentgenology, oncology, surgery, ophthalmology, etc. Initial data processing is a major step towards obtaining a good diagnostic result. The paper considers the approach allows an image filtering with preservation of objects borders. The algorithm proposed in this paper is based on sequential data processing. At the first stage, local areas are determined, for this purpose the method of threshold processing, as well as the classical ICI algorithm, is applied. The second stage uses a method based on based on two criteria, namely, L2 norm and the first order square difference. To preserve the boundaries of objects, we will process the transition boundary and local neighborhood the filtering algorithm with a fixed-coefficient. For example, reconstructed images of CT, x-ray, and microbiological studies are shown. The test images show the effectiveness of the proposed algorithm. This shows the applicability of analysis many medical imaging applications.

  12. Medical Imaging and Infertility.

    Science.gov (United States)

    Peterson, Rebecca

    2016-11-01

    Infertility affects many couples, and medical imaging plays a vital role in its diagnosis and treatment. Radiologic technologists benefit from having a broad understanding of infertility risk factors and causes. This article describes the typical structure and function of the male and female reproductive systems, as well as congenital and acquired conditions that could lead to a couple's inability to conceive. Medical imaging procedures performed for infertility diagnosis are discussed, as well as common interventional options available to patients. © 2016 American Society of Radiologic Technologists.

  13. Digital Signal Processing for Medical Imaging Using Matlab

    CERN Document Server

    Gopi, E S

    2013-01-01

    This book describes medical imaging systems, such as X-ray, Computed tomography, MRI, etc. from the point of view of digital signal processing. Readers will see techniques applied to medical imaging such as Radon transformation, image reconstruction, image rendering, image enhancement and restoration, and more. This book also outlines the physics behind medical imaging required to understand the techniques being described. The presentation is designed to be accessible to beginners who are doing research in DSP for medical imaging. Matlab programs and illustrations are used wherever possible to reinforce the concepts being discussed.  ·         Acts as a “starter kit” for beginners doing research in DSP for medical imaging; ·         Uses Matlab programs and illustrations throughout to make content accessible, particularly with techniques such as Radon transformation and image rendering; ·         Includes discussion of the basic principles behind the various medical imaging tec...

  14. A high-performance spatial database based approach for pathology imaging algorithm evaluation

    Directory of Open Access Journals (Sweden)

    Fusheng Wang

    2013-01-01

    Full Text Available Background: Algorithm evaluation provides a means to characterize variability across image analysis algorithms, validate algorithms by comparison with human annotations, combine results from multiple algorithms for performance improvement, and facilitate algorithm sensitivity studies. The sizes of images and image analysis results in pathology image analysis pose significant challenges in algorithm evaluation. We present an efficient parallel spatial database approach to model, normalize, manage, and query large volumes of analytical image result data. This provides an efficient platform for algorithm evaluation. Our experiments with a set of brain tumor images demonstrate the application, scalability, and effectiveness of the platform. Context: The paper describes an approach and platform for evaluation of pathology image analysis algorithms. The platform facilitates algorithm evaluation through a high-performance database built on the Pathology Analytic Imaging Standards (PAIS data model. Aims: (1 Develop a framework to support algorithm evaluation by modeling and managing analytical results and human annotations from pathology images; (2 Create a robust data normalization tool for converting, validating, and fixing spatial data from algorithm or human annotations; (3 Develop a set of queries to support data sampling and result comparisons; (4 Achieve high performance computation capacity via a parallel data management infrastructure, parallel data loading and spatial indexing optimizations in this infrastructure. Materials and Methods: We have considered two scenarios for algorithm evaluation: (1 algorithm comparison where multiple result sets from different methods are compared and consolidated; and (2 algorithm validation where algorithm results are compared with human annotations. We have developed a spatial normalization toolkit to validate and normalize spatial boundaries produced by image analysis algorithms or human annotations. The

  15. High Bit-Depth Medical Image Compression With HEVC.

    Science.gov (United States)

    Parikh, Saurin S; Ruiz, Damian; Kalva, Hari; Fernandez-Escribano, Gerardo; Adzic, Velibor

    2018-03-01

    Efficient storing and retrieval of medical images has direct impact on reducing costs and improving access in cloud-based health care services. JPEG 2000 is currently the commonly used compression format for medical images shared using the DICOM standard. However, new formats such as high efficiency video coding (HEVC) can provide better compression efficiency compared to JPEG 2000. Furthermore, JPEG 2000 is not suitable for efficiently storing image series and 3-D imagery. Using HEVC, a single format can support all forms of medical images. This paper presents the use of HEVC for diagnostically acceptable medical image compression, focusing on compression efficiency compared to JPEG 2000. Diagnostically acceptable lossy compression and complexity of high bit-depth medical image compression are studied. Based on an established medically acceptable compression range for JPEG 2000, this paper establishes acceptable HEVC compression range for medical imaging applications. Experimental results show that using HEVC can increase the compression performance, compared to JPEG 2000, by over 54%. Along with this, a new method for reducing computational complexity of HEVC encoding for medical images is proposed. Results show that HEVC intra encoding complexity can be reduced by over 55% with negligible increase in file size.

  16. Open Availability of Patient Medical Photographs in Google Images Search Results: Cross-Sectional Study of Transgender Research.

    Science.gov (United States)

    Marshall, Zack; Brunger, Fern; Welch, Vivian; Asghari, Shabnam; Kaposy, Chris

    2018-02-26

    This paper focuses on the collision of three factors: a growing emphasis on sharing research through open access publication, an increasing awareness of big data and its potential uses, and an engaged public interested in the privacy and confidentiality of their personal health information. One conceptual space where this collision is brought into sharp relief is with the open availability of patient medical photographs from peer-reviewed journal articles in the search results of online image databases such as Google Images. The aim of this study was to assess the availability of patient medical photographs from published journal articles in Google Images search results and the factors impacting this availability. We conducted a cross-sectional study using data from an evidence map of research with transgender, gender non-binary, and other gender diverse (trans) participants. For the original evidence map, a comprehensive search of 15 academic databases was developed in collaboration with a health sciences librarian. Initial search results produced 25,230 references after duplicates were removed. Eligibility criteria were established to include empirical research of any design that included trans participants or their personal information and that was published in English in peer-reviewed journals. We identified all articles published between 2008 and 2015 with medical photographs of trans participants. For each reference, images were individually numbered in order to track the total number of medical photographs. We used odds ratios (OR) to assess the association between availability of the clinical photograph on Google Images and the following factors: whether the article was openly available online (open access, Researchgate.net, or Academia.edu), whether the article included genital images, if the photographs were published in color, and whether the photographs were located on the journal article landing page. We identified 94 articles with medical photographs

  17. Image files - RPD | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available switchLanguage; BLAST Search Image Search Home About Archive Update History Data ...ftp://ftp.biosciencedbc.jp/archive/rpd/LATEST/rpd_gel_image.zip File size: 38.5 MB Simple search URL - Data ... License Update History of This Database Site Policy | Contact Us Image files - RPD | LSDB Archive ...

  18. A survey of medical diagnostic imaging technologies

    Energy Technology Data Exchange (ETDEWEB)

    Heese, V.; Gmuer, N.; Thomlinson, W.

    1991-10-01

    The fields of medical imaging and medical imaging instrumentation are increasingly important. The state-of-the-art continues to advance at a very rapid pace. In fact, various medical imaging modalities are under development at the National Synchrotron Light Source (such as MECT and Transvenous Angiography.) It is important to understand how these techniques compare with today`s more conventional imaging modalities. The purpose of this report is to provide some basic information about the various medical imaging technologies currently in use and their potential developments as a basis for this comparison. This report is by no means an in-depth study of the physics and instrumentation of the various imaging modalities; instead, it is an attempt to provide an explanation of the physical bases of these techniques and their principal clinical and research capabilities.

  19. A survey of medical diagnostic imaging technologies

    International Nuclear Information System (INIS)

    Heese, V.; Gmuer, N.; Thomlinson, W.

    1991-10-01

    The fields of medical imaging and medical imaging instrumentation are increasingly important. The state-of-the-art continues to advance at a very rapid pace. In fact, various medical imaging modalities are under development at the National Synchrotron Light Source (such as MECT and Transvenous Angiography.) It is important to understand how these techniques compare with today's more conventional imaging modalities. The purpose of this report is to provide some basic information about the various medical imaging technologies currently in use and their potential developments as a basis for this comparison. This report is by no means an in-depth study of the physics and instrumentation of the various imaging modalities; instead, it is an attempt to provide an explanation of the physical bases of these techniques and their principal clinical and research capabilities

  20. Interpretation of medical imaging data with a mobile application: a mobile digital imaging processing environment.

    Science.gov (United States)

    Lin, Meng Kuan; Nicolini, Oliver; Waxenegger, Harald; Galloway, Graham J; Ullmann, Jeremy F P; Janke, Andrew L

    2013-01-01

    Digital Imaging Processing (DIP) requires data extraction and output from a visualization tool to be consistent. Data handling and transmission between the server and a user is a systematic process in service interpretation. The use of integrated medical services for management and viewing of imaging data in combination with a mobile visualization tool can be greatly facilitated by data analysis and interpretation. This paper presents an integrated mobile application and DIP service, called M-DIP. The objective of the system is to (1) automate the direct data tiling, conversion, pre-tiling of brain images from Medical Imaging NetCDF (MINC), Neuroimaging Informatics Technology Initiative (NIFTI) to RAW formats; (2) speed up querying of imaging measurement; and (3) display high-level of images with three dimensions in real world coordinates. In addition, M-DIP provides the ability to work on a mobile or tablet device without any software installation using web-based protocols. M-DIP implements three levels of architecture with a relational middle-layer database, a stand-alone DIP server, and a mobile application logic middle level realizing user interpretation for direct querying and communication. This imaging software has the ability to display biological imaging data at multiple zoom levels and to increase its quality to meet users' expectations. Interpretation of bioimaging data is facilitated by an interface analogous to online mapping services using real world coordinate browsing. This allows mobile devices to display multiple datasets simultaneously from a remote site. M-DIP can be used as a measurement repository that can be accessed by any network environment, such as a portable mobile or tablet device. In addition, this system and combination with mobile applications are establishing a virtualization tool in the neuroinformatics field to speed interpretation services.

  1. The patient experience of high technology medical imaging: A systematic review of the qualitative evidence

    International Nuclear Information System (INIS)

    Munn, Zachary; Jordan, Zoe

    2011-01-01

    Background: When presenting to an imaging department, the person who is to be imaged is often in a vulnerable state, and can experience the scan in a number of ways. It is the role of the radiographer to produce a high quality image and facilitate patient care throughout the imaging process. A qualitative systematic review was performed to synthesise the existent evidence on the patient experience of high technology medical imaging. Only papers relating to Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) were identified. Inclusion criteria: Studies that were of a qualitative design that explored the phenomenon of interest, the patient experience of high technology medical imaging. Participants included anyone who had undergone one of these procedures. Methods: A systematic search of medical and allied health databases was conducted. Articles identified during the search process that met the inclusion criteria were then critically appraised for methodological quality independently by two reviewers. Results: During the search and inclusion process, 15 studies were found that were deemed of suitable quality to be included in the review. From the 15 studies, 127 findings were extracted from the included studies. These were analysed in more detail to observe common themes, and then grouped into 33 categories. From these 33 categories, 11 synthesised findings were produced. The 11 synthesised findings highlight the diverse, unique and challenging ways in which people experience imaging with MRI and CT scanners. Conclusion: The results of the review demonstrate the diverse ways in which people experience medical imaging. All health professionals involved in imaging need to be aware of the different ways each patient may experience imaging.

  2. Overview of deep learning in medical imaging.

    Science.gov (United States)

    Suzuki, Kenji

    2017-09-01

    The use of machine learning (ML) has been increasing rapidly in the medical imaging field, including computer-aided diagnosis (CAD), radiomics, and medical image analysis. Recently, an ML area called deep learning emerged in the computer vision field and became very popular in many fields. It started from an event in late 2012, when a deep-learning approach based on a convolutional neural network (CNN) won an overwhelming victory in the best-known worldwide computer vision competition, ImageNet Classification. Since then, researchers in virtually all fields, including medical imaging, have started actively participating in the explosively growing field of deep learning. In this paper, the area of deep learning in medical imaging is overviewed, including (1) what was changed in machine learning before and after the introduction of deep learning, (2) what is the source of the power of deep learning, (3) two major deep-learning models: a massive-training artificial neural network (MTANN) and a convolutional neural network (CNN), (4) similarities and differences between the two models, and (5) their applications to medical imaging. This review shows that ML with feature input (or feature-based ML) was dominant before the introduction of deep learning, and that the major and essential difference between ML before and after deep learning is the learning of image data directly without object segmentation or feature extraction; thus, it is the source of the power of deep learning, although the depth of the model is an important attribute. The class of ML with image input (or image-based ML) including deep learning has a long history, but recently gained popularity due to the use of the new terminology, deep learning. There are two major models in this class of ML in medical imaging, MTANN and CNN, which have similarities as well as several differences. In our experience, MTANNs were substantially more efficient in their development, had a higher performance, and required a

  3. Radioisotopes and medical imaging in Sri Lanka

    International Nuclear Information System (INIS)

    Jayasinghe, J.M.A.C.

    1993-01-01

    The article deals with the use of X-rays and magnetic resonance imaging in medical diagnosis in its introduction. Then it elaborates on the facilities in the field of medical imaging for diagnosis, in Sri Lanka. The use of Technetium-99m in diagnostic medicine as well as the future of medical imaging in Sri Lanka is also dealt with

  4. Medical image segmentation using genetic algorithms.

    Science.gov (United States)

    Maulik, Ujjwal

    2009-03-01

    Genetic algorithms (GAs) have been found to be effective in the domain of medical image segmentation, since the problem can often be mapped to one of search in a complex and multimodal landscape. The challenges in medical image segmentation arise due to poor image contrast and artifacts that result in missing or diffuse organ/tissue boundaries. The resulting search space is therefore often noisy with a multitude of local optima. Not only does the genetic algorithmic framework prove to be effective in coming out of local optima, it also brings considerable flexibility into the segmentation procedure. In this paper, an attempt has been made to review the major applications of GAs to the domain of medical image segmentation.

  5. A survey of medical diagnostic imaging technologies

    Energy Technology Data Exchange (ETDEWEB)

    Heese, V.; Gmuer, N.; Thomlinson, W.

    1991-10-01

    The fields of medical imaging and medical imaging instrumentation are increasingly important. The state-of-the-art continues to advance at a very rapid pace. In fact, various medical imaging modalities are under development at the National Synchrotron Light Source (such as MECT and Transvenous Angiography.) It is important to understand how these techniques compare with today's more conventional imaging modalities. The purpose of this report is to provide some basic information about the various medical imaging technologies currently in use and their potential developments as a basis for this comparison. This report is by no means an in-depth study of the physics and instrumentation of the various imaging modalities; instead, it is an attempt to provide an explanation of the physical bases of these techniques and their principal clinical and research capabilities.

  6. Medical image segmentation using improved FCM

    Institute of Scientific and Technical Information of China (English)

    ZHANG XiaoFeng; ZHANG CaiMing; TANG WenJing; WEI ZhenWen

    2012-01-01

    Image segmentation is one of the most important problems in medical image processing,and the existence of partial volume effect and other phenomena makes the problem much more complex. Fuzzy Cmeans,as an effective tool to deal with PVE,however,is faced with great challenges in efficiency.Aiming at this,this paper proposes one improved FCM algorithm based on the histogram of the given image,which will be denoted as HisFCM and divided into two phases.The first phase will retrieve several intervals on which to compute cluster centroids,and the second one will perform image segmentation based on improved FCM algorithm.Compared with FCM and other improved algorithms,HisFCM is of much higher efficiency with satisfying results.Experiments on medical images show that HisFCM can achieve good segmentation results in less than 0.1 second,and can satisfy real-time requirements of medical image processing.

  7. Medical imaging, PACS, and imaging informatics: retrospective.

    Science.gov (United States)

    Huang, H K

    2014-01-01

    Historical reviews of PACS (picture archiving and communication system) and imaging informatics development from different points of view have been published in the past (Huang in Euro J Radiol 78:163-176, 2011; Lemke in Euro J Radiol 78:177-183, 2011; Inamura and Jong in Euro J Radiol 78:184-189, 2011). This retrospective attempts to look at the topic from a different angle by identifying certain basic medical imaging inventions in the 1960s and 1970s which had conceptually defined basic components of PACS guiding its course of development in the 1980s and 1990s, as well as subsequent imaging informatics research in the 2000s. In medical imaging, the emphasis was on the innovations at Georgetown University in Washington, DC, in the 1960s and 1970s. During the 1980s and 1990s, research and training support from US government agencies and public and private medical imaging manufacturers became available for training of young talents in biomedical physics and for developing the key components required for PACS development. In the 2000s, computer hardware and software as well as communication networks advanced by leaps and bounds, opening the door for medical imaging informatics to flourish. Because many key components required for the PACS operation were developed by the UCLA PACS Team and its collaborative partners in the 1980s, this presentation is centered on that aspect. During this period, substantial collaborative research efforts by many individual teams in the US and in Japan were highlighted. Credits are due particularly to the Pattern Recognition Laboratory at Georgetown University, and the computed radiography (CR) development at the Fuji Electric Corp. in collaboration with Stanford University in the 1970s; the Image Processing Laboratory at UCLA in the 1980s-1990s; as well as the early PACS development at the Hokkaido University, Sapporo, Japan, in the late 1970s, and film scanner and digital radiography developed by Konishiroku Photo Ind. Co. Ltd

  8. 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.

  9. The present and future of medical imaging physics

    International Nuclear Information System (INIS)

    Bao Shanglian; Zhang Huailing; Huang Feizeng

    2004-01-01

    The physics of medical imaging is one of the main branches of medical physics, which trains medical physicists for the R and D of medical imaging equipment, clinical application of this equipment as well as R and D in medical physics. The development of medical imaging physics is one of the biggest programs aimed at making China a world manufacturer both in hardware and software. However, there is no formal medical physics in China as yet. The scale of education and training, and the level of manufacture of medical imaging equipment are very low compared with developed countries. It is therefore imperative for China to accelerate the rate of development to satisfy her requirements. Amongst other priorities, building up the education and training system in medical physics and setting up a staff of medical physicists in hospitals is the most urgent thing

  10. Appropriateness of the food-pics image database for experimental eating and appetite research with adolescents.

    Science.gov (United States)

    Jensen, Chad D; Duraccio, Kara M; Barnett, Kimberly A; Stevens, Kimberly S

    2016-12-01

    Research examining effects of visual food cues on appetite-related brain processes and eating behavior has proliferated. Recently investigators have developed food image databases for use across experimental studies examining appetite and eating behavior. The food-pics image database represents a standardized, freely available image library originally validated in a large sample primarily comprised of adults. The suitability of the images for use with adolescents has not been investigated. The aim of the present study was to evaluate the appropriateness of the food-pics image library for appetite and eating research with adolescents. Three hundred and seven adolescents (ages 12-17) provided ratings of recognizability, palatability, and desire to eat, for images from the food-pics database. Moreover, participants rated the caloric content (high vs. low) and healthiness (healthy vs. unhealthy) of each image. Adolescents rated approximately 75% of the food images as recognizable. Approximately 65% of recognizable images were correctly categorized as high vs. low calorie and 63% were correctly classified as healthy vs. unhealthy in 80% or more of image ratings. These results suggest that a smaller subset of the food-pics image database is appropriate for use with adolescents. With some modifications to included images, the food-pics image database appears to be appropriate for use in experimental appetite and eating-related research conducted with adolescents. Copyright © 2016 Elsevier Ltd. All rights reserved.

  11. Viewpoints on Medical Image Processing: From Science to Application

    Science.gov (United States)

    Deserno (né Lehmann), Thomas M.; Handels, Heinz; Maier-Hein (né Fritzsche), Klaus H.; Mersmann, Sven; Palm, Christoph; Tolxdorff, Thomas; Wagenknecht, Gudrun; Wittenberg, Thomas

    2013-01-01

    Medical image processing provides core innovation for medical imaging. This paper is focused on recent developments from science to applications analyzing the past fifteen years of history of the proceedings of the German annual meeting on medical image processing (BVM). Furthermore, some members of the program committee present their personal points of views: (i) multi-modality for imaging and diagnosis, (ii) analysis of diffusion-weighted imaging, (iii) model-based image analysis, (iv) registration of section images, (v) from images to information in digital endoscopy, and (vi) virtual reality and robotics. Medical imaging and medical image computing is seen as field of rapid development with clear trends to integrated applications in diagnostics, treatment planning and treatment. PMID:24078804

  12. Viewpoints on Medical Image Processing: From Science to Application.

    Science.gov (United States)

    Deserno Né Lehmann, Thomas M; Handels, Heinz; Maier-Hein Né Fritzsche, Klaus H; Mersmann, Sven; Palm, Christoph; Tolxdorff, Thomas; Wagenknecht, Gudrun; Wittenberg, Thomas

    2013-05-01

    Medical image processing provides core innovation for medical imaging. This paper is focused on recent developments from science to applications analyzing the past fifteen years of history of the proceedings of the German annual meeting on medical image processing (BVM). Furthermore, some members of the program committee present their personal points of views: (i) multi-modality for imaging and diagnosis, (ii) analysis of diffusion-weighted imaging, (iii) model-based image analysis, (iv) registration of section images, (v) from images to information in digital endoscopy, and (vi) virtual reality and robotics. Medical imaging and medical image computing is seen as field of rapid development with clear trends to integrated applications in diagnostics, treatment planning and treatment.

  13. A Study of NetCDF as an Approach for High Performance Medical Image Storage

    International Nuclear Information System (INIS)

    Magnus, Marcone; Prado, Thiago Coelho; Von Wangenhein, Aldo; De Macedo, Douglas D J; Dantas, M A R

    2012-01-01

    The spread of telemedicine systems increases every day. The systems and PACS based on DICOM images has become common. This rise reflects the need to develop new storage systems, more efficient and with lower computational costs. With this in mind, this article discusses a study for application in NetCDF data format as the basic platform for storage of DICOM images. The study case comparison adopts an ordinary database, the HDF5 and the NetCDF to storage the medical images. Empirical results, using a real set of images, indicate that the time to retrieve images from the NetCDF for large scale images has a higher latency compared to the other two methods. In addition, the latency is proportional to the file size, which represents a drawback to a telemedicine system that is characterized by a large amount of large image files.

  14. The Establishment of the SAR images database System Based on Oracle and ArcSDE

    International Nuclear Information System (INIS)

    Zhou, Jijin; Li, Zhen; Chen, Quan; Tian, Bangsen

    2014-01-01

    Synthetic aperture radar is a kind of microwave imaging system, and has the advantages of multi-band, multi-polarization and multi-angle. At present, there is no SAR images database system based on typical features. For solving problems in interpretation and identification, a new SAR images database system of the typical features is urgent in the current development need. In this article, a SAR images database system based on Oracle and ArcSDE was constructed. The main works involving are as follows: (1) SAR image data was calibrated and corrected geometrically and geometrically. Besides, the fully polarimetric image was processed as the coherency matrix[T] to preserve the polarimetric information. (2) After analyzing multiple space borne SAR images, the metadata table was defined as: IMAGEID; Name of features; Latitude and Longitude; Sensor name; Range and Azimuth resolution etc. (3) Through the comparison between GeoRaster and ArcSDE, result showed ArcSDE is a more appropriate technology to store images in a central database. The System stores and manages multisource SAR image data well, reflects scattering, geometry, polarization, band and angle characteristics, and combines with analysis of the managed objects and service objects of the database as well as focuses on constructing SAR image system in the aspects of data browse and data retrieval. According the analysis of characteristics of SAR images such as scattering, polarization, incident angle and wave band information, different weights can be given to these characteristics. Then an interpreted tool is formed to provide an efficient platform for interpretation

  15. Medical image diagnosis of liver cancer using artificial intelligence

    International Nuclear Information System (INIS)

    Kondo, Tadashi; Ueno, Junji; Takao, Shoichiro

    2010-01-01

    A revised Group Method of Data Handling (GMDH)-type neural network algorithm using artificial intelligence technology for medical image diagnosis is proposed and is applied to medical image diagnosis of liver cancer. In this algorithm, the knowledge base for medical image diagnosis are used for organizing the neural network architecture for medical image diagnosis. Furthermore, the revised GMDH-type neural network algorithm has a feedback loop and can identify the characteristics of the medical images accurately using feedback loop calculations. The optimum neural network architecture fitting the complexity of the medical images is automatically organized so as to minimize the prediction error criterion defined as Prediction Sum of Squares (PSS). It is shown that the revised GMDH-type neural network can be easily applied to the medical image diagnosis. (author)

  16. Diagnostic imaging in undergraduate medical education: an expanding role

    International Nuclear Information System (INIS)

    Miles, K.A.

    2005-01-01

    Radiologists have been involved in anatomy instruction for medical students for decades. However, recent technical advances in radiology, such as multiplanar imaging, 'virtual endoscopy', functional and molecular imaging, and spectroscopy, offer new ways in which to use imaging for teaching basic sciences to medical students. The broad dissemination of picture archiving and communications systems is making such images readily available to medical schools, providing new opportunities for the incorporation of diagnostic imaging into the undergraduate medical curriculum. Current reforms in the medical curriculum and the establishment of new medical schools in the UK further underline the prospects for an expanding role for imaging in medical education. This article reviews the methods by which diagnostic imaging can be used to support the learning of anatomy and other basic sciences

  17. Applications of VLSI circuits to medical imaging

    International Nuclear Information System (INIS)

    O'Donnell, M.

    1988-01-01

    In this paper the application of advanced VLSI circuits to medical imaging is explored. The relationship of both general purpose signal processing chips and custom devices to medical imaging is discussed using examples of fabricated chips. In addition, advanced CAD tools for silicon compilation are presented. Devices built with these tools represent a possible alternative to custom devices and general purpose signal processors for the next generation of medical imaging systems

  18. Army medical imaging system: ARMIS

    International Nuclear Information System (INIS)

    Siedband, M.P.; Kramp, D.C.

    1987-01-01

    Recent advances of stimulable phosphor screens, data cards using optical storage means, and new personal computers with image processing capability have made possible the design of economical filmless medical imaging systems. The addition of communication links means that remote interpretation of images is also possible. The Army Medical Imaging System uses stimulable phosphor screens, digital readout, a small computer, an optical digital data card device, and a DIN/PACS link. Up to 200 images can be stored in the computer hard disk for rapid recall and reading by the radiologist. The computer permits image processing, annotation, insertion of text, and control of the system. Each device contains an image storage RAM and communicates with the computer via the small computer systems interface. Data compression is used to reduce the required storage capacity and transmission times of the 1-mB images. The credit card-size optical data cards replace film and can store 12 or more images. The data cards can be read on an independent viewer. The research is supported by the U.S. Army Biomedical Research and Development Laboratory

  19. Lossless medical image compression with a hybrid coder

    Science.gov (United States)

    Way, Jing-Dar; Cheng, Po-Yuen

    1998-10-01

    The volume of medical image data is expected to increase dramatically in the next decade due to the large use of radiological image for medical diagnosis. The economics of distributing the medical image dictate that data compression is essential. While there is lossy image compression, the medical image must be recorded and transmitted lossless before it reaches the users to avoid wrong diagnosis due to the image data lost. Therefore, a low complexity, high performance lossless compression schematic that can approach the theoretic bound and operate in near real-time is needed. In this paper, we propose a hybrid image coder to compress the digitized medical image without any data loss. The hybrid coder is constituted of two key components: an embedded wavelet coder and a lossless run-length coder. In this system, the medical image is compressed with the lossy wavelet coder first, and the residual image between the original and the compressed ones is further compressed with the run-length coder. Several optimization schemes have been used in these coders to increase the coding performance. It is shown that the proposed algorithm is with higher compression ratio than run-length entropy coders such as arithmetic, Huffman and Lempel-Ziv coders.

  20. 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.

  1. Remote consultation and diagnosis in medical imaging using a global PACS backbone network

    Science.gov (United States)

    Martinez, Ralph; Sutaria, Bijal N.; Kim, Jinman; Nam, Jiseung

    1993-10-01

    A Global PACS is a national network which interconnects several PACS networks at medical and hospital complexes using a national backbone network. A Global PACS environment enables new and beneficial operations between radiologists and physicians, when they are located in different geographical locations. One operation allows the radiologist to view the same image folder at both Local and Remote sites so that a diagnosis can be performed. The paper describes the user interface, database management, and network communication software which has been developed in the Computer Engineering Research Laboratory and Radiology Research Laboratory. Specifically, a design for a file management system in a distributed environment is presented. In the remote consultation and diagnosis operation, a set of images is requested from the database archive system and sent to the Local and Remote workstation sites on the Global PACS network. Viewing the same images, the radiologists use pointing overlay commands, or frames to point out features on the images. Each workstation transfers these frames, to the other workstation, so that an interactive session for diagnosis takes place. In this phase, we use fixed frames and variable size frames, used to outline an object. The data pockets for these frames traverses the national backbone in real-time. We accomplish this feature by using TCP/IP protocol sockets for communications. The remote consultation and diagnosis operation has been tested in real-time between the University Medical Center and the Bowman Gray School of Medicine at Wake Forest University, over the Internet. In this paper, we show the feasibility of the operation in a Global PACS environment. Future improvements to the system will include real-time voice and interactive compressed video scenarios.

  2. A special designed library for medical imaging applications

    International Nuclear Information System (INIS)

    Lymberopoulos, D.; Kotsopoulos, S.; Zoupas, V.; Yoldassis, N.; Spyropoulos, C.

    1994-01-01

    The present paper deals with a sophisticated and flexible library of medical purpose image processing routines. It contains modules for simple as well as advanced gray or colour image processing. This library offers powerful features for medical image processing and analysis applications, thus providing the physician with a means of analyzing and estimating medical images in order to accomplish their diagnostic procedures

  3. A special designed library for medical imaging applications

    Energy Technology Data Exchange (ETDEWEB)

    Lymberopoulos, D; Kotsopoulos, S; Zoupas, V; Yoldassis, N [Departmeent of Electrical Engineering, University of Patras, Patras 26 110 Greece (Greece); Spyropoulos, C [School of Medicine, Regional University Hospital, University of Patras, Patras 26 110 Greece (Greece)

    1994-12-31

    The present paper deals with a sophisticated and flexible library of medical purpose image processing routines. It contains modules for simple as well as advanced gray or colour image processing. This library offers powerful features for medical image processing and analysis applications, thus providing the physician with a means of analyzing and estimating medical images in order to accomplish their diagnostic procedures. 6 refs, 1 figs.

  4. Desktop publishing and medical imaging: paper as hardcopy medium for digital images.

    Science.gov (United States)

    Denslow, S

    1994-08-01

    Desktop-publishing software and hardware has progressed to the point that many widely used word-processing programs are capable of printing high-quality digital images with many shades of gray from black to white. Accordingly, it should be relatively easy to print digital medical images on paper for reports, instructional materials, and in research notes. Components were assembled that were necessary for extracting image data from medical imaging devices and converting the data to a form usable by word-processing software. A system incorporating these components was implemented in a medical setting and has been operating for 18 months. The use of this system by medical staff has been monitored.

  5. The image database management system of teaching file using personal computer

    International Nuclear Information System (INIS)

    Shin, M. J.; Kim, G. W.; Chun, T. J.; Ahn, W. H.; Baik, S. K.; Choi, H. Y.; Kim, B. G.

    1995-01-01

    For the systemic management and easy using of teaching file in radiology department, the authors tried to do the setup of a database management system of teaching file using personal computer. We used a personal computer (IBM PC compatible, 486DX2) including a image capture card(Window vision, Dooin Elect, Seoul, Korea) and video camera recorder (8mm, CCD-TR105, Sony, Tokyo, Japan) for the acquisition and storage of images. We developed the database program by using Foxpro for Window 2.6(Microsoft, Seattle, USA) executed in the Window 3.1 (Microsoft, Seattle, USA). Each datum consisted of hospital number, name, sex, age, examination date, keyword, radiologic examination modalities, final diagnosis, radiologic findings, references and representative images. The images were acquired and stored as bitmap format (8 bitmap, 540 X 390 ∼ 545 X 414, 256 gray scale) and displayed on the 17 inch-flat monitor(1024 X 768, Samtron, Seoul, Korea). Without special devices, the images acquisition and storage could be done on the reading viewbox, simply. The image quality on the computer's monitor was less than the one of original film on the viewbox, but generally the characteristics of each lesions could be differentiated. Easy retrieval of data was possible for the purpose of teaching file system. Without high cost appliances, we could consummate the image database system of teaching file using personal computer with relatively inexpensive method

  6. Deep Learning in Medical Image Analysis.

    Science.gov (United States)

    Shen, Dinggang; Wu, Guorong; Suk, Heung-Il

    2017-06-21

    This review covers computer-assisted analysis of images in the field of medical imaging. Recent advances in machine learning, especially with regard to deep learning, are helping to identify, classify, and quantify patterns in medical images. At the core of these advances is the ability to exploit hierarchical feature representations learned solely from data, instead of features designed by hand according to domain-specific knowledge. Deep learning is rapidly becoming the state of the art, leading to enhanced performance in various medical applications. We introduce the fundamentals of deep learning methods and review their successes in image registration, detection of anatomical and cellular structures, tissue segmentation, computer-aided disease diagnosis and prognosis, and so on. We conclude by discussing research issues and suggesting future directions for further improvement.

  7. Landsat TM and ETM+ Kansas Satellite Image Database (KSID)

    Data.gov (United States)

    Kansas Data Access and Support Center — The Kansas Satellite Image Database (KSID):2000-2001 consists of terrain-corrected, precision rectified spring, summer, and fall Landsat 5 Thematic Mapper (TM) and...

  8. 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

  9. A high performance parallel approach to medical imaging

    International Nuclear Information System (INIS)

    Frieder, G.; Frieder, O.; Stytz, M.R.

    1988-01-01

    Research into medical imaging using general purpose parallel processing architectures is described and a review of the performance of previous medical imaging machines is provided. Results demonstrating that general purpose parallel architectures can achieve performance comparable to other, specialized, medical imaging machine architectures is presented. A new back-to-front hidden-surface removal algorithm is described. Results demonstrating the computational savings obtained by using the modified back-to-front hidden-surface removal algorithm are presented. Performance figures for forming a full-scale medical image on a mesh interconnected multiprocessor are presented

  10. Hybrid Imaging: A New Frontier in Medical Imaging

    OpenAIRE

    Bijan Bijan

    2010-01-01

    Introduction of hybrid imaging in the arena of medical imaging calls for re-strategizing in current practice. Operating PET-CT and upcoming PET-MRI is a turf battle between Radiologists, Nuclear Medicine Physicians, Oncologists, Cardiologists and other related fields.

  11. Contributions to HEVC Prediction for Medical Image Compression

    OpenAIRE

    Guarda, André Filipe Rodrigues

    2016-01-01

    Medical imaging technology and applications are continuously evolving, dealing with images of increasing spatial and temporal resolutions, which allow easier and more accurate medical diagnosis. However, this increase in resolution demands a growing amount of data to be stored and transmitted. Despite the high coding efficiency achieved by the most recent image and video coding standards in lossy compression, they are not well suited for quality-critical medical image compressi...

  12. 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.

  13. Imaging techniques for medical diagnosis

    International Nuclear Information System (INIS)

    Gudden, F.

    1982-01-01

    In the last few decades, science, engineering and medicine have combinded to improve the quality of our lives to a level previously unimagined. Within the framework of medical engineering - the field of activity of the Medical Engineering Group of Siemens AG - diagnostic image-generating systems have played an important role in effecting these changes and improvements. The importance of these systems to the success of the Group is clearly evident. Diagnostic imaging systems account for 65% of the sales achieved by this Group. In this article an overview is presented of the major innovations and the aims of developments in the field of imaging systems. (orig.)

  14. A Data Colocation Grid Framework for Big Data Medical Image Processing: Backend Design

    Science.gov (United States)

    Huo, Yuankai; Parvathaneni, Prasanna; Plassard, Andrew J.; Bermudez, Camilo; Yao, Yuang; Lyu, Ilwoo; Gokhale, Aniruddha; Landman, Bennett A.

    2018-01-01

    When processing large medical imaging studies, adopting high performance grid computing resources rapidly becomes important. We recently presented a "medical image processing-as-a-service" grid framework that offers promise in utilizing the Apache Hadoop ecosystem and HBase for data colocation by moving computation close to medical image storage. However, the framework has not yet proven to be easy to use in a heterogeneous hardware environment. Furthermore, the system has not yet validated when considering variety of multi-level analysis in medical imaging. Our target design criteria are (1) improving the framework’s performance in a heterogeneous cluster, (2) performing population based summary statistics on large datasets, and (3) introducing a table design scheme for rapid NoSQL query. In this paper, we present a heuristic backend interface application program interface (API) design for Hadoop & HBase for Medical Image Processing (HadoopBase-MIP). The API includes: Upload, Retrieve, Remove, Load balancer (for heterogeneous cluster) and MapReduce templates. A dataset summary statistic model is discussed and implemented by MapReduce paradigm. We introduce a HBase table scheme for fast data query to better utilize the MapReduce model. Briefly, 5153 T1 images were retrieved from a university secure, shared web database and used to empirically access an in-house grid with 224 heterogeneous CPU cores. Three empirical experiments results are presented and discussed: (1) load balancer wall-time improvement of 1.5-fold compared with a framework with built-in data allocation strategy, (2) a summary statistic model is empirically verified on grid framework and is compared with the cluster when deployed with a standard Sun Grid Engine (SGE), which reduces 8-fold of wall clock time and 14-fold of resource time, and (3) the proposed HBase table scheme improves MapReduce computation with 7 fold reduction of wall time compare with a naïve scheme when datasets are relative

  15. The semiotics of medical image Segmentation.

    Science.gov (United States)

    Baxter, John S H; Gibson, Eli; Eagleson, Roy; Peters, Terry M

    2018-02-01

    As the interaction between clinicians and computational processes increases in complexity, more nuanced mechanisms are required to describe how their communication is mediated. Medical image segmentation in particular affords a large number of distinct loci for interaction which can act on a deep, knowledge-driven level which complicates the naive interpretation of the computer as a symbol processing machine. Using the perspective of the computer as dialogue partner, we can motivate the semiotic understanding of medical image segmentation. Taking advantage of Peircean semiotic traditions and new philosophical inquiry into the structure and quality of metaphors, we can construct a unified framework for the interpretation of medical image segmentation as a sign exchange in which each sign acts as an interface metaphor. This allows for a notion of finite semiosis, described through a schematic medium, that can rigorously describe how clinicians and computers interpret the signs mediating their interaction. Altogether, this framework provides a unified approach to the understanding and development of medical image segmentation interfaces. Copyright © 2017 Elsevier B.V. All rights reserved.

  16. Trends in medical image processing

    International Nuclear Information System (INIS)

    Robilotta, C.C.

    1987-01-01

    The function of medical image processing is analysed, mentioning the developments, the physical agents, and the main categories, as conection of distortion in image formation, detectability increase, parameters quantification, etc. (C.G.C.) [pt

  17. Medical imaging systems

    Science.gov (United States)

    Frangioni, John V [Wayland, MA

    2012-07-24

    A medical imaging system provides simultaneous rendering of visible light and fluorescent images. The system may employ dyes in a small-molecule form that remains in a subject's blood stream for several minutes, allowing real-time imaging of the subject's circulatory system superimposed upon a conventional, visible light image of the subject. The system may also employ dyes or other fluorescent substances associated with antibodies, antibody fragments, or ligands that accumulate within a region of diagnostic significance. In one embodiment, the system provides an excitation light source to excite the fluorescent substance and a visible light source for general illumination within the same optical guide that is used to capture images. In another embodiment, the system is configured for use in open surgical procedures by providing an operating area that is closed to ambient light. More broadly, the systems described herein may be used in imaging applications where a visible light image may be usefully supplemented by an image formed from fluorescent emissions from a fluorescent substance that marks areas of functional interest.

  18. Nonreference Medical Image Edge Map Measure

    Directory of Open Access Journals (Sweden)

    Karen Panetta

    2014-01-01

    Full Text Available Edge detection is a key step in medical image processing. It is widely used to extract features, perform segmentation, and further assist in diagnosis. A poor quality edge map can result in false alarms and misses in cancer detection algorithms. Therefore, it is necessary to have a reliable edge measure to assist in selecting the optimal edge map. Existing reference based edge measures require a ground truth edge map to evaluate the similarity between the generated edge map and the ground truth. However, the ground truth images are not available for medical images. Therefore, a nonreference edge measure is ideal for medical image processing applications. In this paper, a nonreference reconstruction based edge map evaluation (NREM is proposed. The theoretical basis is that a good edge map keeps the structure and details of the original image thus would yield a good reconstructed image. The NREM is based on comparing the similarity between the reconstructed image with the original image using this concept. The edge measure is used for selecting the optimal edge detection algorithm and optimal parameters for the algorithm. Experimental results show that the quantitative evaluations given by the edge measure have good correlations with human visual analysis.

  19. Database Capture of Natural Language Echocardiographic Reports: A Unified Medical Language System Approach

    OpenAIRE

    Canfield, K.; Bray, B.; Huff, S.; Warner, H.

    1989-01-01

    We describe a prototype system for semi-automatic database capture of free-text echocardiography reports. The system is very simple and uses a Unified Medical Language System compatible architecture. We use this system and a large body of texts to create a patient database and develop a comprehensive hierarchical dictionary for echocardiography.

  20. Feature Detector and Descriptor for Medical Images

    Science.gov (United States)

    Sargent, Dusty; Chen, Chao-I.; Tsai, Chang-Ming; Wang, Yuan-Fang; Koppel, Daniel

    2009-02-01

    The ability to detect and match features across multiple views of a scene is a crucial first step in many computer vision algorithms for dynamic scene analysis. State-of-the-art methods such as SIFT and SURF perform successfully when applied to typical images taken by a digital camera or camcorder. However, these methods often fail to generate an acceptable number of features when applied to medical images, because such images usually contain large homogeneous regions with little color and intensity variation. As a result, tasks like image registration and 3D structure recovery become difficult or impossible in the medical domain. This paper presents a scale, rotation and color/illumination invariant feature detector and descriptor for medical applications. The method incorporates elements of SIFT and SURF while optimizing their performance on medical data. Based on experiments with various types of medical images, we combined, adjusted, and built on methods and parameter settings employed in both algorithms. An approximate Hessian based detector is used to locate scale invariant keypoints and a dominant orientation is assigned to each keypoint using a gradient orientation histogram, providing rotation invariance. Finally, keypoints are described with an orientation-normalized distribution of gradient responses at the assigned scale, and the feature vector is normalized for contrast invariance. Experiments show that the algorithm detects and matches far more features than SIFT and SURF on medical images, with similar error levels.

  1. A framework for integration of heterogeneous medical imaging networks.

    Science.gov (United States)

    Viana-Ferreira, Carlos; Ribeiro, Luís S; Costa, Carlos

    2014-01-01

    Medical imaging is increasing its importance in matters of medical diagnosis and in treatment support. Much is due to computers that have revolutionized medical imaging not only in acquisition process but also in the way it is visualized, stored, exchanged and managed. Picture Archiving and Communication Systems (PACS) is an example of how medical imaging takes advantage of computers. To solve problems of interoperability of PACS and medical imaging equipment, the Digital Imaging and Communications in Medicine (DICOM) standard was defined and widely implemented in current solutions. More recently, the need to exchange medical data between distinct institutions resulted in Integrating the Healthcare Enterprise (IHE) initiative that contains a content profile especially conceived for medical imaging exchange: Cross Enterprise Document Sharing for imaging (XDS-i). Moreover, due to application requirements, many solutions developed private networks to support their services. For instance, some applications support enhanced query and retrieve over DICOM objects metadata. This paper proposes anintegration framework to medical imaging networks that provides protocols interoperability and data federation services. It is an extensible plugin system that supports standard approaches (DICOM and XDS-I), but is also capable of supporting private protocols. The framework is being used in the Dicoogle Open Source PACS.

  2. Semi-Automated Annotation of Biobank Data Using Standard Medical Terminologies in a Graph Database.

    Science.gov (United States)

    Hofer, Philipp; Neururer, Sabrina; Goebel, Georg

    2016-01-01

    Data describing biobank resources frequently contains unstructured free-text information or insufficient coding standards. (Bio-) medical ontologies like Orphanet Rare Diseases Ontology (ORDO) or the Human Disease Ontology (DOID) provide a high number of concepts, synonyms and entity relationship properties. Such standard terminologies increase quality and granularity of input data by adding comprehensive semantic background knowledge from validated entity relationships. Moreover, cross-references between terminology concepts facilitate data integration across databases using different coding standards. In order to encourage the use of standard terminologies, our aim is to identify and link relevant concepts with free-text diagnosis inputs within a biobank registry. Relevant concepts are selected automatically by lexical matching and SPARQL queries against a RDF triplestore. To ensure correctness of annotations, proposed concepts have to be confirmed by medical data administration experts before they are entered into the registry database. Relevant (bio-) medical terminologies describing diseases and phenotypes were identified and stored in a graph database which was tied to a local biobank registry. Concept recommendations during data input trigger a structured description of medical data and facilitate data linkage between heterogeneous systems.

  3. Development of prostate cancer research database with the clinical data warehouse technology for direct linkage with electronic medical record system.

    Science.gov (United States)

    Choi, In Young; Park, Seungho; Park, Bumjoon; Chung, Byung Ha; Kim, Choung-Soo; Lee, Hyun Moo; Byun, Seok-Soo; Lee, Ji Youl

    2013-01-01

    In spite of increased prostate cancer patients, little is known about the impact of treatments for prostate cancer patients and outcome of different treatments based on nationwide data. In order to obtain more comprehensive information for Korean prostate cancer patients, many professionals urged to have national system to monitor the quality of prostate cancer care. To gain its objective, the prostate cancer database system was planned and cautiously accommodated different views from various professions. This prostate cancer research database system incorporates information about a prostate cancer research including demographics, medical history, operation information, laboratory, and quality of life surveys. And, this system includes three different ways of clinical data collection to produce a comprehensive data base; direct data extraction from electronic medical record (EMR) system, manual data entry after linking EMR documents like magnetic resonance imaging findings and paper-based data collection for survey from patients. We implemented clinical data warehouse technology to test direct EMR link method with St. Mary's Hospital system. Using this method, total number of eligible patients were 2,300 from 1997 until 2012. Among them, 538 patients conducted surgery and others have different treatments. Our database system could provide the infrastructure for collecting error free data to support various retrospective and prospective studies.

  4. MedXViewer: providing a web-enabled workstation environment for collaborative and remote medical imaging viewing, perception studies and reader training

    International Nuclear Information System (INIS)

    Looney, P.T.; Young, K.C.; Halling-Brown, M.D.

    2016-01-01

    MedXViewer (Medical extensible Viewer) has been developed to address the need for workstation-independent, picture archiving and communication system (PACS)-less viewing and interaction with anonymised medical images. The aim of this paper is to describe the design and features of MedXViewer as well as to introduce the new features available in the latest release (version 1.2). MedXViewer currently supports digital mammography and tomosynthesis. The flexible software design used to develop MedXViewer allows it to be easily extended to support other imaging modalities. Regions of interest can be drawn by a user, and any associated information about a mark, an image or a study can be added. The questions and settings can be easily configured depending on the need of the research allowing both ROC and FROC studies to be performed. Complex tree-like questions can be asked where a given answer presents the user to new questions. The hanging protocol can be specified for each study. Panning, windowing, zooming and moving through slices are all available while modality-specific features can be easily enabled, e.g. quadrant zooming in digital mammography and tomosynthesis studies. MedXViewer can integrate with a web-based image database OPTIMAM Medical Image Database allowing results and images to be stored centrally. The software can, alternatively, run without a network connection where the images and results can be encrypted and stored locally on a machine or external drive. MedXViewer has been used for running remote paper-less observer studies and is capable of providing a training infrastructure and coordinating remote collaborative viewing sessions. (authors)

  5. Application of the STOPP/START criteria to a medical record database.

    Science.gov (United States)

    Nauta, Katinka J; Groenhof, Feikje; Schuling, Jan; Hugtenburg, Jacqueline G; van Hout, Hein P J; Haaijer-Ruskamp, Flora M; Denig, Petra

    2017-10-01

    The STOPP/START criteria are increasingly used to assess prescribing quality in elderly patients at practice level. Our aim was to test computerized algorithms for applying these criteria to a medical record database. STOPP/START criteria-based computerized algorithms were defined using Anatomical-Therapeutic-Chemical (ATC) codes for medication and International Classification of Primary Care (ICPC) codes for diagnoses. The algorithms were applied to a Dutch primary care database, including patients aged ≥65 years using ≥5 chronic drugs. We tested for associations with patient characteristics that have previously shown a relationship with the original STOPP/START criteria, using multivariate logistic regression models. Included were 1187 patients with a median age of 75 years. In total, 39 of the 62 STOPP and 18 of the 26 START criteria could be converted to a computerized algorithm. The main reasons for inapplicability were lack of information on the severity of a condition and insufficient covering of ICPC-codes. We confirmed a positive association between the occurrence of both the STOPP and the START criteria and the number of chronic drugs (adjusted OR ranging from 1.37, 95% CI 1.04-1.82 to 3.19, 95% CI 2.33-4.36) as well as the patient's age (adjusted OR for STOPP 1.30, 95% CI 1.01-1.67; for START 1.73, 95% CI 1.35-2.21), and also between female gender and the occurrence of STOPP criteria (adjusted OR 1.41, 95% CI 1.09-1.82). Sixty-five percent of the STOPP/START criteria could be applied with computerized algorithms to a medical record database with ATC-coded medication and ICPC-coded diagnoses. Copyright © 2017 John Wiley & Sons, Ltd.

  6. Developments in medical image processing and computational vision

    CERN Document Server

    Jorge, Renato

    2015-01-01

    This book presents novel and advanced topics in Medical Image Processing and Computational Vision in order to solidify knowledge in the related fields and define their key stakeholders. It contains extended versions of selected papers presented in VipIMAGE 2013 – IV International ECCOMAS Thematic Conference on Computational Vision and Medical Image, which took place in Funchal, Madeira, Portugal, 14-16 October 2013.  The twenty-two chapters were written by invited experts of international recognition and address important issues in medical image processing and computational vision, including: 3D vision, 3D visualization, colour quantisation, continuum mechanics, data fusion, data mining, face recognition, GPU parallelisation, image acquisition and reconstruction, image and video analysis, image clustering, image registration, image restoring, image segmentation, machine learning, modelling and simulation, object detection, object recognition, object tracking, optical flow, pattern recognition, pose estimat...

  7. Machine Learning Interface for Medical Image Analysis.

    Science.gov (United States)

    Zhang, Yi C; Kagen, Alexander C

    2017-10-01

    TensorFlow is a second-generation open-source machine learning software library with a built-in framework for implementing neural networks in wide variety of perceptual tasks. Although TensorFlow usage is well established with computer vision datasets, the TensorFlow interface with DICOM formats for medical imaging remains to be established. Our goal is to extend the TensorFlow API to accept raw DICOM images as input; 1513 DaTscan DICOM images were obtained from the Parkinson's Progression Markers Initiative (PPMI) database. DICOM pixel intensities were extracted and shaped into tensors, or n-dimensional arrays, to populate the training, validation, and test input datasets for machine learning. A simple neural network was constructed in TensorFlow to classify images into normal or Parkinson's disease groups. Training was executed over 1000 iterations for each cross-validation set. The gradient descent optimization and Adagrad optimization algorithms were used to minimize cross-entropy between the predicted and ground-truth labels. Cross-validation was performed ten times to produce a mean accuracy of 0.938 ± 0.047 (95 % CI 0.908-0.967). The mean sensitivity was 0.974 ± 0.043 (95 % CI 0.947-1.00) and mean specificity was 0.822 ± 0.207 (95 % CI 0.694-0.950). We extended the TensorFlow API to enable DICOM compatibility in the context of DaTscan image analysis. We implemented a neural network classifier that produces diagnostic accuracies on par with excellent results from previous machine learning models. These results indicate the potential role of TensorFlow as a useful adjunct diagnostic tool in the clinical setting.

  8. Applied medical image processing a basic course

    CERN Document Server

    Birkfellner, Wolfgang

    2014-01-01

    A widely used, classroom-tested text, Applied Medical Image Processing: A Basic Course delivers an ideal introduction to image processing in medicine, emphasizing the clinical relevance and special requirements of the field. Avoiding excessive mathematical formalisms, the book presents key principles by implementing algorithms from scratch and using simple MATLAB®/Octave scripts with image data and illustrations on an accompanying CD-ROM or companion website. Organized as a complete textbook, it provides an overview of the physics of medical image processing and discusses image formats and data storage, intensity transforms, filtering of images and applications of the Fourier transform, three-dimensional spatial transforms, volume rendering, image registration, and tomographic reconstruction.

  9. [Role and management of cancer clinical database in the application of gastric cancer precision medicine].

    Science.gov (United States)

    Li, Yuanfang; Zhou, Zhiwei

    2016-02-01

    Precision medicine is a new medical concept and medical model, which is based on personalized medicine, rapid progress of genome sequencing technology and cross application of biological information and big data science. Precision medicine improves the diagnosis and treatment of gastric cancer to provide more convenience through more profound analyses of characteristics, pathogenesis and other core issues in gastric cancer. Cancer clinical database is important to promote the development of precision medicine. Therefore, it is necessary to pay close attention to the construction and management of the database. The clinical database of Sun Yat-sen University Cancer Center is composed of medical record database, blood specimen bank, tissue bank and medical imaging database. In order to ensure the good quality of the database, the design and management of the database should follow the strict standard operation procedure(SOP) model. Data sharing is an important way to improve medical research in the era of medical big data. The construction and management of clinical database must also be strengthened and innovated.

  10. Future of X-ray phase imaging in medical imaging technology

    International Nuclear Information System (INIS)

    Momose, Atsushi

    2007-01-01

    Weakly absorbing materials, such as biological, soft tissues, can be imaged by generating contrast due to the phase shift of X-rays. In the past decade, several methods for X-ray phase imaging were proposed and demonstrated. The performance of X-ray phase imaging is attractive in the field of medical imaging technology, and its development for practical use is expected. Many methods, however, have been developed under the assumption of the use of synchrotron radiation, which is an obstacle to practical use. The method based on Talbot (-Lau) interferometry enables us to use a compact X-ray source, and its development is expected as a breakthrough for medical applications. (author)

  11. Computerized comprehensive data analysis of Lung Imaging Database Consortium (LIDC)

    International Nuclear Information System (INIS)

    Tan Jun; Pu Jiantao; Zheng Bin; Wang Xingwei; Leader, Joseph K.

    2010-01-01

    Purpose: Lung Image Database Consortium (LIDC) is the largest public CT image database of lung nodules. In this study, the authors present a comprehensive and the most updated analysis of this dynamically growing database under the help of a computerized tool, aiming to assist researchers to optimally use this database for lung cancer related investigations. Methods: The authors developed a computer scheme to automatically match the nodule outlines marked manually by radiologists on CT images. A large variety of characteristics regarding the annotated nodules in the database including volume, spiculation level, elongation, interobserver variability, as well as the intersection of delineated nodule voxels and overlapping ratio between the same nodules marked by different radiologists are automatically calculated and summarized. The scheme was applied to analyze all 157 examinations with complete annotation data currently available in LIDC dataset. Results: The scheme summarizes the statistical distributions of the abovementioned geometric and diagnosis features. Among the 391 nodules, (1) 365 (93.35%) have principal axis length ≤20 mm; (2) 120, 75, 76, and 120 were marked by one, two, three, and four radiologists, respectively; and (3) 122 (32.48%) have the maximum volume overlapping ratios ≥80% for the delineations of two radiologists, while 198 (50.64%) have the maximum volume overlapping ratios <60%. The results also showed that 72.89% of the nodules were assessed with malignancy score between 2 and 4, and only 7.93% of these nodules were considered as severely malignant (malignancy ≥4). Conclusions: This study demonstrates that LIDC contains examinations covering a diverse distribution of nodule characteristics and it can be a useful resource to assess the performance of the nodule detection and/or segmentation schemes.

  12. MEDXVIEWER: PROVIDING A WEB-ENABLED WORKSTATION ENVIRONMENT FOR COLLABORATIVE AND REMOTE MEDICAL IMAGING VIEWING, PERCEPTION STUDIES AND READER TRAINING.

    Science.gov (United States)

    Looney, P T; Young, K C; Halling-Brown, M D

    2016-06-01

    MedXViewer (Medical eXtensible Viewer) has been developed to address the need for workstation-independent, picture archiving and communication system (PACS)-less viewing and interaction with anonymised medical images. The aim of this paper is to describe the design and features of MedXViewer as well as to introduce the new features available in the latest release (version 1.2). MedXViewer currently supports digital mammography and tomosynthesis. The flexible software design used to develop MedXViewer allows it to be easily extended to support other imaging modalities. Regions of interest can be drawn by a user, and any associated information about a mark, an image or a study can be added. The questions and settings can be easily configured depending on the need of the research allowing both ROC and FROC studies to be performed. Complex tree-like questions can be asked where a given answer presents the user to new questions. The hanging protocol can be specified for each study. Panning, windowing, zooming and moving through slices are all available while modality-specific features can be easily enabled, e.g. quadrant zooming in digital mammography and tomosynthesis studies. MedXViewer can integrate with a web-based image database OPTIMAM Medical Image Database allowing results and images to be stored centrally. The software can, alternatively, run without a network connection where the images and results can be encrypted and stored locally on a machine or external drive. MedXViewer has been used for running remote paper-less observer studies and is capable of providing a training infrastructure and coordinating remote collaborative viewing sessions. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  13. Physics and engineering of medical imaging

    International Nuclear Information System (INIS)

    Guzzardi, R.

    1987-01-01

    The ever-developing technology of medical imaging has a continuous and significant impact on the practice of medicine as well as on clinical research activity. The information and level of accuracy obtained by an imaging methodology is a complex result of a multidisciplinary effort of physics, engineering, electronics, chemistry and medicine. In this book, the state of the art is described for NMR, ultrasound, X-ray CT, nuclear medicine, positron tomography and other imaging modalities. For every imaging modality, the most important clinical applications are described together with the delineation of problems and future needs. Furthermore, specific sections of the book are devoted to general aspects of medical imaging, such as reconstruction techniques, 2-D and 3-D display, quality control, archiving, market trends and correlative assessment

  14. An interactive medical image segmentation framework using iterative refinement.

    Science.gov (United States)

    Kalshetti, Pratik; Bundele, Manas; Rahangdale, Parag; Jangra, Dinesh; Chattopadhyay, Chiranjoy; Harit, Gaurav; Elhence, Abhay

    2017-04-01

    Segmentation is often performed on medical images for identifying diseases in clinical evaluation. Hence it has become one of the major research areas. Conventional image segmentation techniques are unable to provide satisfactory segmentation results for medical images as they contain irregularities. They need to be pre-processed before segmentation. In order to obtain the most suitable method for medical image segmentation, we propose MIST (Medical Image Segmentation Tool), a two stage algorithm. The first stage automatically generates a binary marker image of the region of interest using mathematical morphology. This marker serves as the mask image for the second stage which uses GrabCut to yield an efficient segmented result. The obtained result can be further refined by user interaction, which can be done using the proposed Graphical User Interface (GUI). Experimental results show that the proposed method is accurate and provides satisfactory segmentation results with minimum user interaction on medical as well as natural images. Copyright © 2017 Elsevier Ltd. All rights reserved.

  15. Infant feeding practices within a large electronic medical record database.

    Science.gov (United States)

    Bartsch, Emily; Park, Alison L; Young, Jacqueline; Ray, Joel G; Tu, Karen

    2018-01-02

    The emerging adoption of the electronic medical record (EMR) in primary care enables clinicians and researchers to efficiently examine epidemiological trends in child health, including infant feeding practices. We completed a population-based retrospective cohort study of 8815 singleton infants born at term in Ontario, Canada, April 2002 to March 2013. Newborn records were linked to the Electronic Medical Record Administrative data Linked Database (EMRALD™), which uses patient-level information from participating family practice EMRs across Ontario. We assessed exclusive breastfeeding patterns using an automated electronic search algorithm, with manual review of EMRs when the latter was not possible. We examined the rate of breastfeeding at visits corresponding to 2, 4 and 6 months of age, as well as sociodemographic factors associated with exclusive breastfeeding. Of the 8815 newborns, 1044 (11.8%) lacked breastfeeding information in their EMR. Rates of exclusive breastfeeding were 39.5% at 2 months, 32.4% at 4 months and 25.1% at 6 months. At age 6 months, exclusive breastfeeding rates were highest among mothers aged ≥40 vs. database.

  16. 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.

  17. Wavelets in medical imaging

    International Nuclear Information System (INIS)

    Zahra, Noor e; Sevindir, Huliya A.; Aslan, Zafar; Siddiqi, A. H.

    2012-01-01

    The aim of this study is to provide emerging applications of wavelet methods to medical signals and images, such as electrocardiogram, electroencephalogram, functional magnetic resonance imaging, computer tomography, X-ray and mammography. Interpretation of these signals and images are quite important. Nowadays wavelet methods have a significant impact on the science of medical imaging and the diagnosis of disease and screening protocols. Based on our initial investigations, future directions include neurosurgical planning and improved assessment of risk for individual patients, improved assessment and strategies for the treatment of chronic pain, improved seizure localization, and improved understanding of the physiology of neurological disorders. We look ahead to these and other emerging applications as the benefits of this technology become incorporated into current and future patient care. In this chapter by applying Fourier transform and wavelet transform, analysis and denoising of one of the important biomedical signals like EEG is carried out. The presence of rhythm, template matching, and correlation is discussed by various method. Energy of EEG signal is used to detect seizure in an epileptic patient. We have also performed denoising of EEG signals by SWT.

  18. Wavelets in medical imaging

    Energy Technology Data Exchange (ETDEWEB)

    Zahra, Noor e; Sevindir, Huliya A.; Aslan, Zafar; Siddiqi, A. H. [Sharda University, SET, Department of Electronics and Communication, Knowledge Park 3rd, Gr. Noida (India); University of Kocaeli, Department of Mathematics, 41380 Kocaeli (Turkey); Istanbul Aydin University, Department of Computer Engineering, 34295 Istanbul (Turkey); Sharda University, SET, Department of Mathematics, 32-34 Knowledge Park 3rd, Greater Noida (India)

    2012-07-17

    The aim of this study is to provide emerging applications of wavelet methods to medical signals and images, such as electrocardiogram, electroencephalogram, functional magnetic resonance imaging, computer tomography, X-ray and mammography. Interpretation of these signals and images are quite important. Nowadays wavelet methods have a significant impact on the science of medical imaging and the diagnosis of disease and screening protocols. Based on our initial investigations, future directions include neurosurgical planning and improved assessment of risk for individual patients, improved assessment and strategies for the treatment of chronic pain, improved seizure localization, and improved understanding of the physiology of neurological disorders. We look ahead to these and other emerging applications as the benefits of this technology become incorporated into current and future patient care. In this chapter by applying Fourier transform and wavelet transform, analysis and denoising of one of the important biomedical signals like EEG is carried out. The presence of rhythm, template matching, and correlation is discussed by various method. Energy of EEG signal is used to detect seizure in an epileptic patient. We have also performed denoising of EEG signals by SWT.

  19. Moonshot Acceleration Factor: Medical Imaging.

    Science.gov (United States)

    Sevick-Muraca, Eva M; Frank, Richard A; Giger, Maryellen L; Mulshine, James L

    2017-11-01

    Medical imaging is essential to screening, early diagnosis, and monitoring responses to cancer treatments and, when used with other diagnostics, provides guidance for clinicians in choosing the most effective patient management plan that maximizes survivorship and quality of life. At a gathering of agency officials, patient advocacy organizations, industry/professional stakeholder groups, and clinical/basic science academicians, recommendations were made on why and how one should build a "cancer knowledge network" that includes imaging. Steps to accelerate the translation and clinical adoption of cancer discoveries to meet the goals of the Cancer Moonshot include harnessing computational power and architectures, developing data sharing policies, and standardizing medical imaging and in vitro diagnostics. Cancer Res; 77(21); 5717-20. ©2017 AACR . ©2017 American Association for Cancer Research.

  20. DisFace: A Database of Human Facial Disorders

    Directory of Open Access Journals (Sweden)

    Paramjit Kaur

    2017-10-01

    Full Text Available Face is an integral part of human body by which an individual communicates in the society. Its importance can be highlighted by the fact that a person deprived of face cannot sustain in the living world. In the past few decades, human face has gained attention of several researchers, whether it is related to facial anthropometry, facial disorder, face transplantation or face reconstruction. Several researches have also shown the correlation between neuropsychiatry disorders and human face and also that how face recognition abilities are correlated with these disorders. Currently, several databases exist which contain the facial images of several individuals captured from different sources. The advantage of these databases is that the images in these databases can be used for testing and training purpose. However, in current date no such database exists which would provide not only facial images of individuals; but also the literature concerning the human face, list of several genes controlling human face, list of facial disorders and various tools which work on facial images. Thus, the current research aims at developing a database of human facial disorders using bioinformatics approach. The database will contain information about facial diseases, medications, symptoms, findings, etc. The information will be extracted from several other databases like OMIM, PubChem, Radiopedia, Medline Plus, FDA, etc. and links to them will also be provided. Initially, the diseases specific for human face have been obtained from already created published corpora of literature using text mining approach. Becas tool was used to obtain the specific task.  A dataset will be created and stored in the form of database. It will be a database containing cross-referenced index of human facial diseases, medications, symptoms, signs, etc. Thus, a database on human face with complete existing information about human facial disorders will be developed. The novelty of the

  1. Resolution enhancement in medical ultrasound imaging.

    Science.gov (United States)

    Ploquin, Marie; Basarab, Adrian; Kouamé, Denis

    2015-01-01

    Image resolution enhancement is a problem of considerable interest in all medical imaging modalities. Unlike general purpose imaging or video processing, for a very long time, medical image resolution enhancement has been based on optimization of the imaging devices. Although some recent works purport to deal with image postprocessing, much remains to be done regarding medical image enhancement via postprocessing, especially in ultrasound imaging. We face a resolution improvement issue in the case of medical ultrasound imaging. We propose to investigate this problem using multidimensional autoregressive (AR) models. Noting that the estimation of the envelope of an ultrasound radio frequency (RF) signal is very similar to the estimation of classical Fourier-based power spectrum estimation, we theoretically show that a domain change and a multidimensional AR model can be used to achieve super-resolution in ultrasound imaging provided the order is estimated correctly. Here, this is done by means of a technique that simultaneously estimates the order and the parameters of a multidimensional model using relevant regression matrix factorization. Doing so, the proposed method specifically fits ultrasound imaging and provides an estimated envelope. Moreover, an expression that links the theoretical image resolution to both the image acquisition features (such as the point spread function) and a postprocessing feature (the AR model) order is derived. The overall contribution of this work is threefold. First, it allows for automatic resolution improvement. Through a simple model and without any specific manual algorithmic parameter tuning, as is used in common methods, the proposed technique simply and exclusively uses the ultrasound RF signal as input and provides the improved B-mode as output. Second, it allows for the a priori prediction of the improvement in resolution via the knowledge of the parametric model order before actual processing. Finally, to achieve the

  2. Shape analysis in medical image analysis

    CERN Document Server

    Tavares, João

    2014-01-01

    This book contains thirteen contributions from invited experts of international recognition addressing important issues in shape analysis in medical image analysis, including techniques for image segmentation, registration, modelling and classification, and applications in biology, as well as in cardiac, brain, spine, chest, lung and clinical practice. This volume treats topics such as, anatomic and functional shape representation and matching; shape-based medical image segmentation; shape registration; statistical shape analysis; shape deformation; shape-based abnormity detection; shape tracking and longitudinal shape analysis; machine learning for shape modeling and analysis; shape-based computer-aided-diagnosis; shape-based medical navigation; benchmark and validation of shape representation, analysis and modeling algorithms. This work will be of interest to researchers, students, and manufacturers in the fields of artificial intelligence, bioengineering, biomechanics, computational mechanics, computationa...

  3. A Public Image Database for Benchmark of Plant Seedling Classification Algorithms

    DEFF Research Database (Denmark)

    Giselsson, Thomas Mosgaard; Nyholm Jørgensen, Rasmus; Jensen, Peter Kryger

    A database of images of approximately 960 unique plants belonging to 12 species at several growth stages is made publicly available. It comprises annotated RGB images with a physical resolution of roughly 10 pixels per mm. To standardise the evaluation of classification results obtained...

  4. Medical Students? Confidence Judgments Using a Factual Database and Personal Memory: A Comparison.

    Science.gov (United States)

    O'Keefe, Karen M.; Wildemuth, Barbara M.; Friedman, Charles P.

    1999-01-01

    This study examined the quality of medical students' confidence estimates in answering questions in bacteriology based on personal knowledge alone and what they retrieved from a factual database in microbiology, in order to determine whether medical students can recognize when an information need has been fulfilled and when it has not. (Author/LRW)

  5. Software for Distributed Computation on Medical Databases: A Demonstration Project

    Directory of Open Access Journals (Sweden)

    Balasubramanian Narasimhan

    2017-05-01

    Full Text Available Bringing together the information latent in distributed medical databases promises to personalize medical care by enabling reliable, stable modeling of outcomes with rich feature sets (including patient characteristics and treatments received. However, there are barriers to aggregation of medical data, due to lack of standardization of ontologies, privacy concerns, proprietary attitudes toward data, and a reluctance to give up control over end use. Aggregation of data is not always necessary for model fitting. In models based on maximizing a likelihood, the computations can be distributed, with aggregation limited to the intermediate results of calculations on local data, rather than raw data. Distributed fitting is also possible for singular value decomposition. There has been work on the technical aspects of shared computation for particular applications, but little has been published on the software needed to support the "social networking" aspect of shared computing, to reduce the barriers to collaboration. We describe a set of software tools that allow the rapid assembly of a collaborative computational project, based on the flexible and extensible R statistical software and other open source packages, that can work across a heterogeneous collection of database environments, with full transparency to allow local officials concerned with privacy protections to validate the safety of the method. We describe the principles, architecture, and successful test results for the site-stratified Cox model and rank-k singular value decomposition.

  6. Signal Processing in Medical Ultrasound B-mode Imaging

    International Nuclear Information System (INIS)

    Song, Tai Kyong

    2000-01-01

    Ultrasonic imaging is the most widely used modality among modern imaging device for medical diagnosis and the system performance has been improved dramatically since early 90's due to the rapid advances in DSP performance and VLSI technology that made it possible to employ more sophisticated algorithms. This paper describes 'main stream' digital signal processing functions along with the associated implementation considerations in modern medical ultrasound imaging systems. Topics covered include signal processing methods for resolution improvement, ultrasound imaging system architectures, roles and necessity of the applications of DSP and VLSI technology in the development of the medical ultrasound imaging systems, and array signal processing techniques for ultrasound focusing

  7. 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)

  8. Functional Principal Component Analysis and Randomized Sparse Clustering Algorithm for Medical Image Analysis

    Science.gov (United States)

    Lin, Nan; Jiang, Junhai; Guo, Shicheng; Xiong, Momiao

    2015-01-01

    Due to the advancement in sensor technology, the growing large medical image data have the ability to visualize the anatomical changes in biological tissues. As a consequence, the medical images have the potential to enhance the diagnosis of disease, the prediction of clinical outcomes and the characterization of disease progression. But in the meantime, the growing data dimensions pose great methodological and computational challenges for the representation and selection of features in image cluster analysis. To address these challenges, we first extend the functional principal component analysis (FPCA) from one dimension to two dimensions to fully capture the space variation of image the signals. The image signals contain a large number of redundant features which provide no additional information for clustering analysis. The widely used methods for removing the irrelevant features are sparse clustering algorithms using a lasso-type penalty to select the features. However, the accuracy of clustering using a lasso-type penalty depends on the selection of the penalty parameters and the threshold value. In practice, they are difficult to determine. Recently, randomized algorithms have received a great deal of attentions in big data analysis. This paper presents a randomized algorithm for accurate feature selection in image clustering analysis. The proposed method is applied to both the liver and kidney cancer histology image data from the TCGA database. The results demonstrate that the randomized feature selection method coupled with functional principal component analysis substantially outperforms the current sparse clustering algorithms in image cluster analysis. PMID:26196383

  9. 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.

  10. The future of three-dimensional medical imaging

    International Nuclear Information System (INIS)

    Peter, T.M.

    1996-01-01

    The past 15 years have witnessed an explosion in medical imaging technology, and none more so than in the tomographic imaging modalities of CT and MRI. Prior to 1975, 3-D imaging was largely performed in the minds of radiologists and surgeons, assisted by the modalities of conventional x-ray tomography and stereoscopic radiography. However today, with the advent of imaging techniques which ower their existence to computer technology, three-dimensional image acquisition is fast becoming the norm and the clinician finally has access to sets of data that represent the entire imaged volume. Stereoscopic image visualization has already begun to reappear as a viable means of visualizing 3 D medical images. The future of 3-D imaging is exciting and will undoubtedly move further in the direction of virtual reality. (author)

  11. From Roentgen to magnetic resonance imaging: the history of medical imaging.

    Science.gov (United States)

    Scatliff, James H; Morris, Peter J

    2014-01-01

    Medical imaging has advanced in remarkable ways since the discovery of x-rays 120 years ago. Today's radiologists can image the human body in intricate detail using computed tomography, magnetic resonance imaging, positron emission tomography, ultrasound, and various other modalities. Such technology allows for improved screening, diagnosis, and monitoring of disease, but it also comes with risks. Many imaging modalities expose patients to ionizing radiation, which potentially increases their risk of developing cancer in the future, and imaging may also be associated with possible allergic reactions or risks related to the use of intravenous contrast agents. In addition, the financial costs of imaging are taxing our health care system, and incidental findings can trigger anxiety and further testing. This issue of the NCMJ addresses the pros and cons of medical imaging and discusses in detail the following uses of medical imaging: screening for breast cancer with mammography, screening for osteoporosis and monitoring of bone mineral density with dual-energy x-ray absorptiometry, screening for congenital hip dysplasia in infants with ultrasound, and evaluation of various heart conditions with cardiac imaging. Together, these articles show the challenges that must be met as we seek to harness the power of today's imaging technologies, as well as the potential benefits that can be achieved when these hurdles are overcome.

  12. Physics instrumentation for medical imaging

    International Nuclear Information System (INIS)

    Townsend, D.W.

    1993-01-01

    The first Nobel Physics Prize, awarded in 1901, went to Wilhelm Röntgen for his discovery of X-rays in 1895. This, and the most recent physics Nobel, to Georges Charpak last year for his detector developments, span several generations of applied science. As well as helping to launch the science of atomic physics, Röntgen's discovery also marked the dawn of a medical science - radiography - using beams of various kinds to image what otherwise cannot be seen. Ever since, physicists and radiologists have worked hand in hand to improve imaging techniques and widen their medical applications

  13. Physics instrumentation for medical imaging

    Energy Technology Data Exchange (ETDEWEB)

    Townsend, D. W. [Geneva University Hospital, Geneva (Switzerland)

    1993-04-15

    The first Nobel Physics Prize, awarded in 1901, went to Wilhelm Röntgen for his discovery of X-rays in 1895. This, and the most recent physics Nobel, to Georges Charpak last year for his detector developments, span several generations of applied science. As well as helping to launch the science of atomic physics, Röntgen's discovery also marked the dawn of a medical science - radiography - using beams of various kinds to image what otherwise cannot be seen. Ever since, physicists and radiologists have worked hand in hand to improve imaging techniques and widen their medical applications.

  14. Medical Image Registration and Surgery Simulation

    DEFF Research Database (Denmark)

    Bro-Nielsen, Morten

    1996-01-01

    This thesis explores the application of physical models in medical image registration and surgery simulation. The continuum models of elasticity and viscous fluids are described in detail, and this knowledge is used as a basis for most of the methods described here. Real-time deformable models......, and the use of selective matrix vector multiplication. Fluid medical image registration A new and faster algorithm for non-rigid registration using viscous fluid models is presented. This algorithm replaces the core part of the original algorithm with multi-resolution convolution using a new filter, which...... growth is also presented. Using medical knowledge about the growth processes of the mandibular bone, a registration algorithm for time sequence images of the mandible is developed. Since this registration algorithm models the actual development of the mandible, it is possible to simulate the development...

  15. Radically Reducing Radiation Exposure during Routine Medical Imaging

    Science.gov (United States)

    Exposure to radiation from medical imaging in the United States has increased dramatically. NCI and several partner organizations sponsored a 2011 summit to promote efforts to reduce radiation exposure from medical imaging.

  16. A Kalman filter technique applied for medical image reconstruction

    International Nuclear Information System (INIS)

    Goliaei, S.; Ghorshi, S.; Manzuri, M. T.; Mortazavi, M.

    2011-01-01

    Medical images contain information about vital organic tissues inside of human body and are widely used for diagnoses of disease or for surgical purposes. Image reconstruction is essential for medical images for some applications such as suppression of noise or de-blurring the image in order to provide images with better quality and contrast. Due to vital rule of image reconstruction in medical sciences the corresponding algorithms with better efficiency and higher speed is desirable. Most algorithms in image reconstruction are operated on frequency domain such as the most popular one known as filtered back projection. In this paper we introduce a Kalman filter technique which is operated in time domain for medical image reconstruction. Results indicated that as the number of projection increases in both normal collected ray sum and the collected ray sum corrupted by noise the quality of reconstructed image becomes better in terms of contract and transparency. It is also seen that as the number of projection increases the error index decreases.

  17. 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.

  18. SCEGRAM: An image database for semantic and syntactic inconsistencies in scenes.

    Science.gov (United States)

    Öhlschläger, Sabine; Võ, Melissa Le-Hoa

    2017-10-01

    Our visual environment is not random, but follows compositional rules according to what objects are usually found where. Despite the growing interest in how such semantic and syntactic rules - a scene grammar - enable effective attentional guidance and object perception, no common image database containing highly-controlled object-scene modifications has been publically available. Such a database is essential in minimizing the risk that low-level features drive high-level effects of interest, which is being discussed as possible source of controversial study results. To generate the first database of this kind - SCEGRAM - we took photographs of 62 real-world indoor scenes in six consistency conditions that contain semantic and syntactic (both mild and extreme) violations as well as their combinations. Importantly, always two scenes were paired, so that an object was semantically consistent in one scene (e.g., ketchup in kitchen) and inconsistent in the other (e.g., ketchup in bathroom). Low-level salience did not differ between object-scene conditions and was generally moderate. Additionally, SCEGRAM contains consistency ratings for every object-scene condition, as well as object-absent scenes and object-only images. Finally, a cross-validation using eye-movements replicated previous results of longer dwell times for both semantic and syntactic inconsistencies compared to consistent controls. In sum, the SCEGRAM image database is the first to contain well-controlled semantic and syntactic object-scene inconsistencies that can be used in a broad range of cognitive paradigms (e.g., verbal and pictorial priming, change detection, object identification, etc.) including paradigms addressing developmental aspects of scene grammar. SCEGRAM can be retrieved for research purposes from http://www.scenegrammarlab.com/research/scegram-database/ .

  19. Tissues segmentation based on multi spectral medical images

    Science.gov (United States)

    Li, Ya; Wang, Ying

    2017-11-01

    Each band image contains the most obvious tissue feature according to the optical characteristics of different tissues in different specific bands for multispectral medical images. In this paper, the tissues were segmented by their spectral information at each multispectral medical images. Four Local Binary Patter descriptors were constructed to extract blood vessels based on the gray difference between the blood vessels and their neighbors. The segmented tissue in each band image was merged to a clear image.

  20. 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...

  1. Invitation to medical image processing

    International Nuclear Information System (INIS)

    Kitasaka, Takayuki; Suenaga, Yasuhito; Mori, Kensaku

    2010-01-01

    This medical essay explains the present state of CT image processing technology about its recognition, acquisition and visualization for computer-assisted diagnosis (CAD) and surgery (CAS), and future view. Medical image processing has a series of history of its original start from the discovery of X-ray to its application to diagnostic radiography, its combination with the computer for CT, multi-detector raw CT, leading to 3D/4D images for CAD and CAS. CAD is performed based on the recognition of normal anatomical structure of human body, detection of possible abnormal lesion and visualization of its numerical figure into image. Actual instances of CAD images are presented here for chest (lung cancer), abdomen (colorectal cancer) and future body atlas (models of organs and diseases for imaging), a recent national project: computer anatomy. CAS involves the surgical planning technology based on 3D images, navigation of the actual procedure and of endoscopy. As guidance to beginning technological image processing, described are the national and international community like related academic societies, regularly conducting congresses, textbooks and workshops, and topics in the field like computed anatomy of an individual patient for CAD and CAS, its data security and standardization. In future, protective medicine is in authors' view based on the imaging technology, e.g., daily life CAD of individuals ultimately, as exemplified in the present body thermometer and home sphygmometer, to monitor one's routine physical conditions. (T.T.)

  2. 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.

  3. Patients radiation protection in medical imaging. Conference proceedings

    International Nuclear Information System (INIS)

    2011-12-01

    This document brings together the available presentations given at the conference organised by the French society of radiation protection about patients radiation protection in medical imaging. Twelve presentations (slides) are compiled in this document and deal with: 1 - Medical exposure of the French population: methodology and results (Bernard Aubert, IRSN); 2 - What indicators for the medical exposure? (Cecile Etard, IRSN); 3 - Guidebook of correct usage of medical imaging examination (Philippe Grenier, Pitie-Salpetriere hospital); 4 - Radiation protection optimization in pediatric imaging (Hubert Ducou-Le-Pointe, Aurelien Bouette (Armand-Trousseau children hospital); 5 - Children's exposure to image scanners: epidemiological survey (Marie-Odile Bernier, IRSN); 6 - Management of patient's irradiation: from image quality to good practice (Thierry Solaire, General Electric); 7 - Dose optimization in radiology (Cecile Salvat (Lariboisiere hospital); 8 - Cancer detection in the breast cancer planned screening program - 2004-2009 era (Agnes Rogel, InVS); 9 - Mammographic exposures - radiobiological effects - radio-induced DNA damages (Catherine Colin, Lyon Sud hospital); 10 - Breast cancer screening program - importance of non-irradiating techniques (Anne Tardivon, Institut Curie); 11 - Radiation protection justification for the medical imaging of patients over the age of 50 (Michel Bourguignon, ASN); 12 - Search for a molecular imprint for the discrimination between radio-induced and sporadic tumors (Sylvie Chevillard, CEA)

  4. Segmentation of medical images using explicit anatomical knowledge

    Science.gov (United States)

    Wilson, Laurie S.; Brown, Stephen; Brown, Matthew S.; Young, Jeanne; Li, Rongxin; Luo, Suhuai; Brandt, Lee

    1999-07-01

    Knowledge-based image segmentation is defined in terms of the separation of image analysis procedures and representation of knowledge. Such architecture is particularly suitable for medical image segmentation, because of the large amount of structured domain knowledge. A general methodology for the application of knowledge-based methods to medical image segmentation is described. This includes frames for knowledge representation, fuzzy logic for anatomical variations, and a strategy for determining the order of segmentation from the modal specification. This method has been applied to three separate problems, 3D thoracic CT, chest X-rays and CT angiography. The application of the same methodology to such a range of applications suggests a major role in medical imaging for segmentation methods incorporating representation of anatomical knowledge.

  5. Mesh Processing in Medical Image Analysis

    DEFF Research Database (Denmark)

    The following topics are dealt with: mesh processing; medical image analysis; interactive freeform modeling; statistical shape analysis; clinical CT images; statistical surface recovery; automated segmentation; cerebral aneurysms; and real-time particle-based representation....

  6. Practical guide to quality assurance in medical imaging

    International Nuclear Information System (INIS)

    Moores, M.; Watkinson, S.; Pearcy, J.; Henshaw, E.T.

    1987-01-01

    This volume forms an important part of the response to a growing need to ensure the same and cost-effective use of ionizing radiations for the benefit of both staff and patients. The authors provide guidance to implementing and running quality assurance programs in medical imaging departments. The treatment provides an overview of all the tests which need to be carried out in medical imaging, and the text contains step-by-step guidance as to how to perform and interpret the results of medical imaging

  7. Introduction to Medical Image Analysis

    DEFF Research Database (Denmark)

    Paulsen, Rasmus Reinhold; Moeslund, Thomas B.

    of the book is to present the fascinating world of medical image analysis in an easy and interesting way. Compared to many standard books on image analysis, the approach we have chosen is less mathematical and more casual. Some of the key algorithms are exemplified in C-code. Please note that the code...

  8. Evaluation Of Medical Fluoroscopy Imaging

    International Nuclear Information System (INIS)

    Hartana, Budi; Santoso

    2000-01-01

    It has been done to evaluate image system of medical fluoroscopic machine by Leeds Test Object (LTO). Two x-ray potentials of 70 kV and 40-60 kV were used to evaluate image by LTO on monitor and oscilloscope. Performance of imaging system decreased for some parameters of video signal, linearity of television scan, contras threshold of 4.5%, distortion integral of 65.1%, and focus uniformity decrease to edge image. Comparison of field diameter of television image to intensifier field vertically and horizontally were respectively 221:230 and 205:230, symmetrically vignetting, spatial resolution limit is 1.26 lp/mm

  9. Improved Interactive Medical-Imaging System

    Science.gov (United States)

    Ross, Muriel D.; Twombly, Ian A.; Senger, Steven

    2003-01-01

    An improved computational-simulation system for interactive medical imaging has been invented. The system displays high-resolution, three-dimensional-appearing images of anatomical objects based on data acquired by such techniques as computed tomography (CT) and magnetic-resonance imaging (MRI). The system enables users to manipulate the data to obtain a variety of views for example, to display cross sections in specified planes or to rotate images about specified axes. Relative to prior such systems, this system offers enhanced capabilities for synthesizing images of surgical cuts and for collaboration by users at multiple, remote computing sites.

  10. Artificial intelligence and medical imaging. Expert systems and image analysis

    International Nuclear Information System (INIS)

    Wackenheim, A.; Zoellner, G.; Horviller, S.; Jacqmain, T.

    1987-01-01

    This paper gives an overview on the existing systems for automated image analysis and interpretation in medical imaging, especially in radiology. The example of ORFEVRE, the system for the analysis of CAT-scan images of the cervical triplet (c3-c5) by image analysis and subsequent expert-system is given and discussed in detail. Possible extensions are described [fr

  11. Ontology modularization to improve semantic medical image annotation.

    Science.gov (United States)

    Wennerberg, Pinar; Schulz, Klaus; Buitelaar, Paul

    2011-02-01

    Searching for medical images and patient reports is a significant challenge in a clinical setting. The contents of such documents are often not described in sufficient detail thus making it difficult to utilize the inherent wealth of information contained within them. Semantic image annotation addresses this problem by describing the contents of images and reports using medical ontologies. Medical images and patient reports are then linked to each other through common annotations. Subsequently, search algorithms can more effectively find related sets of documents on the basis of these semantic descriptions. A prerequisite to realizing such a semantic search engine is that the data contained within should have been previously annotated with concepts from medical ontologies. One major challenge in this regard is the size and complexity of medical ontologies as annotation sources. Manual annotation is particularly time consuming labor intensive in a clinical environment. In this article we propose an approach to reducing the size of clinical ontologies for more efficient manual image and text annotation. More precisely, our goal is to identify smaller fragments of a large anatomy ontology that are relevant for annotating medical images from patients suffering from lymphoma. Our work is in the area of ontology modularization, which is a recent and active field of research. We describe our approach, methods and data set in detail and we discuss our results. Copyright © 2010 Elsevier Inc. All rights reserved.

  12. Development of 3-D Medical Image VIsualization System

    African Journals Online (AJOL)

    User

    uses standard 2-D medical imaging inputs and generates medical images of human body parts ... light wave from points on the 3-D object(s) in ... tools, and communication bandwidth cannot .... locations along the track that correspond with.

  13. Leadership and power in medical imaging

    Energy Technology Data Exchange (ETDEWEB)

    Yielder, Jill [School of Health and Community Studies, Unitec New Zealand, Private Bag 92 025, Mt Albert, Auckland (New Zealand)]. E-mail: jyielder@unitec.ac.nz

    2006-11-15

    This article examines the concept of professional leadership in medical imaging. It explores the context of power issues in which such leadership is located, the differences between leadership and management, the qualities needed for effective leadership and how an individual's psychology may affect it. The article concludes that in the current climate of change and development, the medical imaging profession needs strong and appropriate leadership to profile the profession effectively and to lead it through to a more autonomous future.

  14. Leadership and power in medical imaging

    International Nuclear Information System (INIS)

    Yielder, Jill

    2006-01-01

    This article examines the concept of professional leadership in medical imaging. It explores the context of power issues in which such leadership is located, the differences between leadership and management, the qualities needed for effective leadership and how an individual's psychology may affect it. The article concludes that in the current climate of change and development, the medical imaging profession needs strong and appropriate leadership to profile the profession effectively and to lead it through to a more autonomous future

  15. A new concept for medical imaging centered on cellular phone technology.

    Directory of Open Access Journals (Sweden)

    Yair Granot

    2008-04-01

    Full Text Available According to World Health Organization reports, some three quarters of the world population does not have access to medical imaging. In addition, in developing countries over 50% of medical equipment that is available is not being used because it is too sophisticated or in disrepair or because the health personnel are not trained to use it. The goal of this study is to introduce and demonstrate the feasibility of a new concept in medical imaging that is centered on cellular phone technology and which may provide a solution to medical imaging in underserved areas. The new system replaces the conventional stand-alone medical imaging device with a new medical imaging system made of two independent components connected through cellular phone technology. The independent units are: a a data acquisition device (DAD at a remote patient site that is simple, with limited controls and no image display capability and b an advanced image reconstruction and hardware control multiserver unit at a central site. The cellular phone technology transmits unprocessed raw data from the patient site DAD and receives and displays the processed image from the central site. (This is different from conventional telemedicine where the image reconstruction and control is at the patient site and telecommunication is used to transmit processed images from the patient site. The primary goal of this study is to demonstrate that the cellular phone technology can function in the proposed mode. The feasibility of the concept is demonstrated using a new frequency division multiplexing electrical impedance tomography system, which we have developed for dynamic medical imaging, as the medical imaging modality. The system is used to image through a cellular phone a simulation of breast cancer tumors in a medical imaging diagnostic mode and to image minimally invasive tissue ablation with irreversible electroporation in a medical imaging interventional mode.

  16. Database Description - SKIP Stemcell Database | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available List Contact us SKIP Stemcell Database Database Description General information of database Database name SKIP Stemcell Database...rsity Journal Search: Contact address http://www.skip.med.keio.ac.jp/en/contact/ Database classification Human Genes and Diseases Dat...abase classification Stemcell Article Organism Taxonomy Name: Homo sapiens Taxonomy ID: 9606 Database...ks: Original website information Database maintenance site Center for Medical Genetics, School of medicine, ...lable Web services Not available URL of Web services - Need for user registration Not available About This Database Database

  17. Hello World Deep Learning in Medical Imaging.

    Science.gov (United States)

    Lakhani, Paras; Gray, Daniel L; Pett, Carl R; Nagy, Paul; Shih, George

    2018-05-03

    There is recent popularity in applying machine learning to medical imaging, notably deep learning, which has achieved state-of-the-art performance in image analysis and processing. The rapid adoption of deep learning may be attributed to the availability of machine learning frameworks and libraries to simplify their use. In this tutorial, we provide a high-level overview of how to build a deep neural network for medical image classification, and provide code that can help those new to the field begin their informatics projects.

  18. Image Format Conversion to DICOM and Lookup Table Conversion to Presentation Value of the Japanese Society of Radiological Technology (JSRT) Standard Digital Image Database.

    Science.gov (United States)

    Yanagita, Satoshi; Imahana, Masato; Suwa, Kazuaki; Sugimura, Hitomi; Nishiki, Masayuki

    2016-01-01

    Japanese Society of Radiological Technology (JSRT) standard digital image database contains many useful cases of chest X-ray images, and has been used in many state-of-the-art researches. However, the pixel values of all the images are simply digitized as relative density values by utilizing a scanned film digitizer. As a result, the pixel values are completely different from the standardized display system input value of digital imaging and communications in medicine (DICOM), called presentation value (P-value), which can maintain a visual consistency when observing images using different display luminance. Therefore, we converted all the images from JSRT standard digital image database to DICOM format followed by the conversion of the pixel values to P-value using an original program developed by ourselves. Consequently, JSRT standard digital image database has been modified so that the visual consistency of images is maintained among different luminance displays.

  19. Use of mobile devices for medical imaging.

    Science.gov (United States)

    Hirschorn, David S; Choudhri, Asim F; Shih, George; Kim, Woojin

    2014-12-01

    Mobile devices have fundamentally changed personal computing, with many people forgoing the desktop and even laptop computer altogether in favor of a smaller, lighter, and cheaper device with a touch screen. Doctors and patients are beginning to expect medical images to be available on these devices for consultative viewing, if not actual diagnosis. However, this raises serious concerns with regard to the ability of existing mobile devices and networks to quickly and securely move these images. Medical images often come in large sets, which can bog down a network if not conveyed in an intelligent manner, and downloaded data on a mobile device are highly vulnerable to a breach of patient confidentiality should that device become lost or stolen. Some degree of regulation is needed to ensure that the software used to view these images allows all relevant medical information to be visible and manipulated in a clinically acceptable manner. There also needs to be a quality control mechanism to ensure that a device's display accurately conveys the image content without loss of contrast detail. Furthermore, not all mobile displays are appropriate for all types of images. The smaller displays of smart phones, for example, are not well suited for viewing entire chest radiographs, no matter how small and numerous the pixels of the display may be. All of these factors should be taken into account when deciding where, when, and how to use mobile devices for the display of medical images. Copyright © 2014 American College of Radiology. Published by Elsevier Inc. All rights reserved.

  20. Neural networks: Application to medical imaging

    Science.gov (United States)

    Clarke, Laurence P.

    1994-01-01

    The research mission is the development of computer assisted diagnostic (CAD) methods for improved diagnosis of medical images including digital x-ray sensors and tomographic imaging modalities. The CAD algorithms include advanced methods for adaptive nonlinear filters for image noise suppression, hybrid wavelet methods for feature segmentation and enhancement, and high convergence neural networks for feature detection and VLSI implementation of neural networks for real time analysis. Other missions include (1) implementation of CAD methods on hospital based picture archiving computer systems (PACS) and information networks for central and remote diagnosis and (2) collaboration with defense and medical industry, NASA, and federal laboratories in the area of dual use technology conversion from defense or aerospace to medicine.

  1. NiftyNet: a deep-learning platform for medical imaging.

    Science.gov (United States)

    Gibson, Eli; Li, Wenqi; Sudre, Carole; Fidon, Lucas; Shakir, Dzhoshkun I; Wang, Guotai; Eaton-Rosen, Zach; Gray, Robert; Doel, Tom; Hu, Yipeng; Whyntie, Tom; Nachev, Parashkev; Modat, Marc; Barratt, Dean C; Ourselin, Sébastien; Cardoso, M Jorge; Vercauteren, Tom

    2018-05-01

    Medical image analysis and computer-assisted intervention problems are increasingly being addressed with deep-learning-based solutions. Established deep-learning platforms are flexible but do not provide specific functionality for medical image analysis and adapting them for this domain of application requires substantial implementation effort. Consequently, there has been substantial duplication of effort and incompatible infrastructure developed across many research groups. This work presents the open-source NiftyNet platform for deep learning in medical imaging. The ambition of NiftyNet is to accelerate and simplify the development of these solutions, and to provide a common mechanism for disseminating research outputs for the community to use, adapt and build upon. The NiftyNet infrastructure provides a modular deep-learning pipeline for a range of medical imaging applications including segmentation, regression, image generation and representation learning applications. Components of the NiftyNet pipeline including data loading, data augmentation, network architectures, loss functions and evaluation metrics are tailored to, and take advantage of, the idiosyncracies of medical image analysis and computer-assisted intervention. NiftyNet is built on the TensorFlow framework and supports features such as TensorBoard visualization of 2D and 3D images and computational graphs by default. We present three illustrative medical image analysis applications built using NiftyNet infrastructure: (1) segmentation of multiple abdominal organs from computed tomography; (2) image regression to predict computed tomography attenuation maps from brain magnetic resonance images; and (3) generation of simulated ultrasound images for specified anatomical poses. The NiftyNet infrastructure enables researchers to rapidly develop and distribute deep learning solutions for segmentation, regression, image generation and representation learning applications, or extend the platform to new

  2. Physics and engineering of medical imaging

    International Nuclear Information System (INIS)

    Guzzardi, R.

    1987-01-01

    The ever-growing development in the technology of Medical Imaging has a continuous and significant impact in the practice of Medicine as well as in the clinical research activity. The information and accuracy obtained by whatever imaging methodology is a complex result of a multidisciplinary effort of several sciences, such as Physics, Engineering, Electronics, Chemistry and Medicine. In this book, the state-of-the-art is described of the technology at the base of NMR, Ultrasound, X-ray CT, Nuclear Medicine, Positron Tomography and other Imaging Modalities such as Thermography or Biomagnetism, considering both the research and industrial point of view. For every imaging modality the most important clinical applications are described, together with the delineation of problems and future needs. Furthermore, specific sections of the book are devoted to general aspects of Medical Imaging, such as Reconstruction Techniques, 2-D and 3-D Display, Quality Control, Archiving, Market Trends and Correlative Assessment. (Auth.)

  3. Data Analysis Strategies in Medical Imaging.

    Science.gov (United States)

    Parmar, Chintan; Barry, Joseph D; Hosny, Ahmed; Quackenbush, John; Aerts, Hugo Jwl

    2018-03-26

    Radiographic imaging continues to be one of the most effective and clinically useful tools within oncology. Sophistication of artificial intelligence (AI) has allowed for detailed quantification of radiographic characteristics of tissues using predefined engineered algorithms or deep learning methods. Precedents in radiology as well as a wealth of research studies hint at the clinical relevance of these characteristics. However, there are critical challenges associated with the analysis of medical imaging data. While some of these challenges are specific to the imaging field, many others like reproducibility and batch effects are generic and have already been addressed in other quantitative fields such as genomics. Here, we identify these pitfalls and provide recommendations for analysis strategies of medical imaging data including data normalization, development of robust models, and rigorous statistical analyses. Adhering to these recommendations will not only improve analysis quality, but will also enhance precision medicine by allowing better integration of imaging data with other biomedical data sources. Copyright ©2018, American Association for Cancer Research.

  4. Medical image transmission via communication satellite: evaluation of ultrasonographic images.

    Science.gov (United States)

    Suzuki, H; Horikoshi, H; Shiba, H; Shimamoto, S

    1996-01-01

    As compared with terrestrial circuits, communication satellites possess superior characteristics such as wide area coverage, broadcasting functions, high capacity, and resistance to disasters. Utilizing the narrow band channel (64 kbps) of the stationary communication satellite JCSAT1 located at an altitude of 36,000 km above the equator, we investigated satelliterelayed dynamic medical images transmitted by video signals, using hepatic ultrasonography as a model. We conclude that the "variable playing speed transmission scheme" proposed by us is effective for the transmission of dynamic images in the narrow band channel. This promises to permit diverse utilization and applications for purposes such as the transmission of other types of ultrasonic images as well as remotely directed medical diagnosis and treatment.

  5. Detecting medication errors in the New Zealand pharmacovigilance database: a retrospective analysis.

    Science.gov (United States)

    Kunac, Desireé L; Tatley, Michael V

    2011-01-01

    Despite the traditional focus being adverse drug reactions (ADRs), pharmacovigilance centres have recently been identified as a potentially rich and important source of medication error data. To identify medication errors in the New Zealand Pharmacovigilance database (Centre for Adverse Reactions Monitoring [CARM]), and to describe the frequency and characteristics of these events. A retrospective analysis of the CARM pharmacovigilance database operated by the New Zealand Pharmacovigilance Centre was undertaken for the year 1 January-31 December 2007. All reports, excluding those relating to vaccines, clinical trials and pharmaceutical company reports, underwent a preventability assessment using predetermined criteria. Those events deemed preventable were subsequently classified to identify the degree of patient harm, type of error, stage of medication use process where the error occurred and origin of the error. A total of 1412 reports met the inclusion criteria and were reviewed, of which 4.3% (61/1412) were deemed preventable. Not all errors resulted in patient harm: 29.5% (18/61) were 'no harm' errors but 65.5% (40/61) of errors were deemed to have been associated with some degree of patient harm (preventable adverse drug events [ADEs]). For 5.0% (3/61) of events, the degree of patient harm was unable to be determined as the patient outcome was unknown. The majority of preventable ADEs (62.5% [25/40]) occurred in adults aged 65 years and older. The medication classes most involved in preventable ADEs were antibacterials for systemic use and anti-inflammatory agents, with gastrointestinal and respiratory system disorders the most common adverse events reported. For both preventable ADEs and 'no harm' events, most errors were incorrect dose and drug therapy monitoring problems consisting of failures in detection of significant drug interactions, past allergies or lack of necessary clinical monitoring. Preventable events were mostly related to the prescribing and

  6. Energy functionals for medical image segmentation: choices and consequences

    OpenAIRE

    McIntosh, Christopher

    2011-01-01

    Medical imaging continues to permeate the practice of medicine, but automated yet accurate segmentation and labeling of anatomical structures continues to be a major obstacle to computerized medical image analysis. Though there exists numerous approaches for medical image segmentation, one in particular has gained increasing popularity: energy minimization-based techniques, and the large set of methods encompassed therein. With these techniques an energy function must be chosen, segmentations...

  7. Novel medical image enhancement algorithms

    Science.gov (United States)

    Agaian, Sos; McClendon, Stephen A.

    2010-01-01

    In this paper, we present two novel medical image enhancement algorithms. The first, a global image enhancement algorithm, utilizes an alpha-trimmed mean filter as its backbone to sharpen images. The second algorithm uses a cascaded unsharp masking technique to separate the high frequency components of an image in order for them to be enhanced using a modified adaptive contrast enhancement algorithm. Experimental results from enhancing electron microscopy, radiological, CT scan and MRI scan images, using the MATLAB environment, are then compared to the original images as well as other enhancement methods, such as histogram equalization and two forms of adaptive contrast enhancement. An image processing scheme for electron microscopy images of Purkinje cells will also be implemented and utilized as a comparison tool to evaluate the performance of our algorithm.

  8. Gadgetron: An Open Source Framework for Medical Image Reconstruction

    DEFF Research Database (Denmark)

    Hansen, Michael Schacht; Sørensen, Thomas Sangild

    2013-01-01

    This work presents a new open source framework for medical image reconstruction called the “Gadgetron.” The framework implements a flexible system for creating streaming data processing pipelines where data pass through a series of modules or “Gadgets” from raw data to reconstructed images...... with a set of dedicated toolboxes in shared libraries for medical image reconstruction. This includes generic toolboxes for data-parallel (e.g., GPU-based) execution of compute-intensive components. The basic framework architecture is independent of medical imaging modality, but this article focuses on its...

  9. Driving change in rural workforce planning: the medical schools outcomes database.

    Science.gov (United States)

    Gerber, Jonathan P; Landau, Louis I

    2010-01-01

    The Medical Schools Outcomes Database (MSOD) is an ongoing longitudinal tracking project ofmedical students from all medical schools in Australia and New Zealand. It was established in 2005 to track the career trajectories of medical students and will directly help develop models of workforce flow, particularly with respect to rural and remote shortages. This paper briefly outlines the MSOD project and reports on key methodological factors in tracking medical students. Finally, the potential impact of the MSOD on understanding changes in rural practice intentions is illustrated using data from the 2005 pilot cohort (n = 112). Rural placements were associated with a shift towards rural practice intentions, while those who intended to practice rurally at both the start and end of medical school tended to be older and interested in a generalist career. Continuing work will track these and future students as they progress through the workforce, as well as exploring issues such as the career trajectories of international fee-paying students, workforce succession planning, and the evaluation of medical education initiatives.

  10. An open architecture for medical image workstation

    Science.gov (United States)

    Liang, Liang; Hu, Zhiqiang; Wang, Xiangyun

    2005-04-01

    Dealing with the difficulties of integrating various medical image viewing and processing technologies with a variety of clinical and departmental information systems and, in the meantime, overcoming the performance constraints in transferring and processing large-scale and ever-increasing image data in healthcare enterprise, we design and implement a flexible, usable and high-performance architecture for medical image workstations. This architecture is not developed for radiology only, but for any workstations in any application environments that may need medical image retrieving, viewing, and post-processing. This architecture contains an infrastructure named Memory PACS and different kinds of image applications built on it. The Memory PACS is in charge of image data caching, pre-fetching and management. It provides image applications with a high speed image data access and a very reliable DICOM network I/O. In dealing with the image applications, we use dynamic component technology to separate the performance-constrained modules from the flexibility-constrained modules so that different image viewing or processing technologies can be developed and maintained independently. We also develop a weakly coupled collaboration service, through which these image applications can communicate with each other or with third party applications. We applied this architecture in developing our product line and it works well. In our clinical sites, this architecture is applied not only in Radiology Department, but also in Ultrasonic, Surgery, Clinics, and Consultation Center. Giving that each concerned department has its particular requirements and business routines along with the facts that they all have different image processing technologies and image display devices, our workstations are still able to maintain high performance and high usability.

  11. 47 CFR 15.513 - Technical requirements for medical imaging systems.

    Science.gov (United States)

    2010-10-01

    ... 47 Telecommunication 1 2010-10-01 2010-10-01 false Technical requirements for medical imaging... DEVICES Ultra-Wideband Operation § 15.513 Technical requirements for medical imaging systems. (a) The UWB... MHz and 10,600 MHz. (b) Operation under the provisions of this section is limited to medical imaging...

  12. Rice8987 Array: Gel images - RMOS | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available List Contact us RMOS Rice8987 Array: Gel images Data detail Data name Rice8987 Array: Gel images DOI 10.1890...e by Wako), was used to other Dplate. Gel images were scanned by scanner (Molecular Dynamics Co.). Number of...Database Site Policy | Contact Us Rice8987 Array: Gel images - RMOS | LSDB Archive ...

  13. Use of medical imaging as an epidemiologic tracer

    International Nuclear Information System (INIS)

    Dartigues, J.F.

    1987-01-01

    Medical imaging is a source of data for clinical and epidemiological research just like any other factual information obtained during medical treatment. Medical imaging data, like any other information, are not really useful unless they are obtained in rigorously controlled and determined conditions, defined a priori in the research protocol. In order to be use as an epidemiologic tracer (that is, as a meaning of finding a given pathology in a given population and during a given time period), the imaging data have to be valid, reliable, and representative, of easy access and obtained at a low cost [fr

  14. 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.

  15. An Integrated Dictionary-Learning Entropy-Based Medical Image Fusion Framework

    Directory of Open Access Journals (Sweden)

    Guanqiu Qi

    2017-10-01

    Full Text Available Image fusion is widely used in different areas and can integrate complementary and relevant information of source images captured by multiple sensors into a unitary synthetic image. Medical image fusion, as an important image fusion application, can extract the details of multiple images from different imaging modalities and combine them into an image that contains complete and non-redundant information for increasing the accuracy of medical diagnosis and assessment. The quality of the fused image directly affects medical diagnosis and assessment. However, existing solutions have some drawbacks in contrast, sharpness, brightness, blur and details. This paper proposes an integrated dictionary-learning and entropy-based medical image-fusion framework that consists of three steps. First, the input image information is decomposed into low-frequency and high-frequency components by using a Gaussian filter. Second, low-frequency components are fused by weighted average algorithm and high-frequency components are fused by the dictionary-learning based algorithm. In the dictionary-learning process of high-frequency components, an entropy-based algorithm is used for informative blocks selection. Third, the fused low-frequency and high-frequency components are combined to obtain the final fusion results. The results and analyses of comparative experiments demonstrate that the proposed medical image fusion framework has better performance than existing solutions.

  16. Relative accuracy and availability of an Irish National Database of dispensed medication as a source of medication history information: observational study and retrospective record analysis.

    LENUS (Irish Health Repository)

    Grimes, T

    2013-01-27

    WHAT IS KNOWN AND OBJECTIVE: The medication reconciliation process begins by identifying which medicines a patient used before presentation to hospital. This is time-consuming, labour intensive and may involve interruption of clinicians. We sought to identify the availability and accuracy of data held in a national dispensing database, relative to other sources of medication history information. METHODS: For patients admitted to two acute hospitals in Ireland, a Gold Standard Pre-Admission Medication List (GSPAML) was identified and corroborated with the patient or carer. The GSPAML was compared for accuracy and availability to PAMLs from other sources, including the Health Service Executive Primary Care Reimbursement Scheme (HSE-PCRS) dispensing database. RESULTS: Some 1111 medication were assessed for 97 patients, who were median age 74 years (range 18-92 years), median four co-morbidities (range 1-9), used median 10 medications (range 3-25) and half (52%) were male. The HSE-PCRS PAML was the most accurate source compared to lists provided by the general practitioner, community pharmacist or cited in previous hospital documentation: the list agreed for 74% of the medications the patients actually used, representing complete agreement for all medications in 17% of patients. It was equally contemporaneous to other sources, but was less reliable for male than female patients, those using increasing numbers of medications and those using one or more item that was not reimbursable by the HSE. WHAT IS NEW AND CONCLUSION: The HSE-PCRS database is a relatively accurate, available and contemporaneous source of medication history information and could support acute hospital medication reconciliation.

  17. Real-time image mosaicing for medical applications.

    Science.gov (United States)

    Loewke, Kevin E; Camarillo, David B; Jobst, Christopher A; Salisbury, J Kenneth

    2007-01-01

    In this paper we describe the development of a robotically-assisted image mosaicing system for medical applications. The processing occurs in real-time due to a fast initial image alignment provided by robotic position sensing. Near-field imaging, defined by relatively large camera motion, requires translations as well as pan and tilt orientations to be measured. To capture these measurements we use 5-d.o.f. sensing along with a hand-eye calibration to account for sensor offset. This sensor-based approach speeds up the mosaicing, eliminates cumulative errors, and readily handles arbitrary camera motions. Our results have produced visually satisfactory mosaics on a dental model but can be extended to other medical images.

  18. Use of organoboranes in modern medical imaging

    International Nuclear Information System (INIS)

    Kabalka, G.W.

    1991-01-01

    Isotopically labeled materials have proven to be invaluable in chemical, medical, and biological research. Organoboranes are beginning to play a significant role in the synthesis of medically important materials which contain both stable and short-lived isotopes. The organic compounds of boron possess characteristics which make them ideal intermediates in radiopharmaceutical pathways; these include the facts that boron reactions tolerate a wide variety of physiologically active functionality and that the reactions proceed rapidly and in high yields. Boranes have found important applications in modern medical imaging techniques such as positron emission tomography (PET) and magnetic resonance imaging (MRI). (author)

  19. HOMED-homicides eastern Denmark: an introduction to a forensic medical homicide database.

    Science.gov (United States)

    Colville-Ebeling, Bonnie; Frisch, Morten; Lynnerup, Niels; Theilade, Peter

    2014-11-01

    An introduction to a forensic medical homicide database established at the Department of Forensic Medicine in Copenhagen. The database contains substantial clinical and demographic data obtained in conjunction with medico-legal autopsies of victims and forensic clinical examinations of perpetrators in homicide cases in eastern Denmark. The database contains information on all homicide cases investigated at the Department of Forensic Medicine in Copenhagen since 1971. Coverage for the catchment area of the department is assumed to be very good because of a medico-legal homicide autopsy rate close to 100%. Regional differences might exist however, due to the fact that the catchment area of the department is dominated by the city of Copenhagen. The strength of the database includes a long running time, near complete regional coverage and an exhaustive list of registered variables it is useful for research purposes, although specific data limitations apply. © 2014 the Nordic Societies of Public Health.

  20. Image processing for medical diagnosis using CNN

    International Nuclear Information System (INIS)

    Arena, Paolo; Basile, Adriano; Bucolo, Maide; Fortuna, Luigi

    2003-01-01

    Medical diagnosis is one of the most important area in which image processing procedures are usefully applied. Image processing is an important phase in order to improve the accuracy both for diagnosis procedure and for surgical operation. One of these fields is tumor/cancer detection by using Microarray analysis. The research studies in the Cancer Genetics Branch are mainly involved in a range of experiments including the identification of inherited mutations predisposing family members to malignant melanoma, prostate and breast cancer. In bio-medical field the real-time processing is very important, but often image processing is a quite time-consuming phase. Therefore techniques able to speed up the elaboration play an important rule. From this point of view, in this work a novel approach to image processing has been developed. The new idea is to use the Cellular Neural Networks to investigate on diagnostic images, like: Magnetic Resonance Imaging, Computed Tomography, and fluorescent cDNA microarray images

  1. Multi-channel medical imaging system

    Science.gov (United States)

    Frangioni, John V

    2013-12-31

    A medical imaging system provides simultaneous rendering of visible light and fluorescent images. The system may employ dyes in a small-molecule form that remain in the subject's blood stream for several minutes, allowing real-time imaging of the subject's circulatory system superimposed upon a conventional, visible light image of the subject. The system may provide an excitation light source to excite the fluorescent substance and a visible light source for general illumination within the same optical guide used to capture images. The system may be configured for use in open surgical procedures by providing an operating area that is closed to ambient light. The systems described herein provide two or more diagnostic imaging channels for capture of multiple, concurrent diagnostic images and may be used where a visible light image may be usefully supplemented by two or more images that are independently marked for functional interest.

  2. FUZZY BASED CONTRAST STRETCHING FOR MEDICAL IMAGE ENHANCEMENT

    Directory of Open Access Journals (Sweden)

    T.C. Raja Kumar

    2011-07-01

    Full Text Available Contrast Stretching is an important part in medical image processing applications. Contrast is the difference between two adjacent pixels. Fuzzy statistical values are analyzed and better results are produced in the spatial domain of the input image. The histogram mapping produces the resultant image with less impulsive noise and smooth nature. The probabilities of gray values are generated and the fuzzy set is determined from the position of the input image pixel. The result indicates the good performance of the proposed fuzzy based stretching. The inverse transform of the real values are mapped with the input image to generate the fuzzy statistics. This approach gives a flexible image enhancement for medical images in the presence of noises.

  3. A facial expression image database and norm for Asian population: a preliminary report

    Science.gov (United States)

    Chen, Chien-Chung; Cho, Shu-ling; Horszowska, Katarzyna; Chen, Mei-Yen; Wu, Chia-Ching; Chen, Hsueh-Chih; Yeh, Yi-Yu; Cheng, Chao-Min

    2009-01-01

    We collected 6604 images of 30 models in eight types of facial expression: happiness, anger, sadness, disgust, fear, surprise, contempt and neutral. Among them, 406 most representative images from 12 models were rated by more than 200 human raters for perceived emotion category and intensity. Such large number of emotion categories, models and raters is sufficient for most serious expression recognition research both in psychology and in computer science. All the models and raters are of Asian background. Hence, this database can also be used when the culture background is a concern. In addition, 43 landmarks each of the 291 rated frontal view images were identified and recorded. This information should facilitate feature based research of facial expression. Overall, the diversity in images and richness in information should make our database and norm useful for a wide range of research.

  4. Machine Learning in Medical Imaging.

    Science.gov (United States)

    Giger, Maryellen L

    2018-03-01

    Advances in both imaging and computers have synergistically led to a rapid rise in the potential use of artificial intelligence in various radiological imaging tasks, such as risk assessment, detection, diagnosis, prognosis, and therapy response, as well as in multi-omics disease discovery. A brief overview of the field is given here, allowing the reader to recognize the terminology, the various subfields, and components of machine learning, as well as the clinical potential. Radiomics, an expansion of computer-aided diagnosis, has been defined as the conversion of images to minable data. The ultimate benefit of quantitative radiomics is to (1) yield predictive image-based phenotypes of disease for precision medicine or (2) yield quantitative image-based phenotypes for data mining with other -omics for discovery (ie, imaging genomics). For deep learning in radiology to succeed, note that well-annotated large data sets are needed since deep networks are complex, computer software and hardware are evolving constantly, and subtle differences in disease states are more difficult to perceive than differences in everyday objects. In the future, machine learning in radiology is expected to have a substantial clinical impact with imaging examinations being routinely obtained in clinical practice, providing an opportunity to improve decision support in medical image interpretation. The term of note is decision support, indicating that computers will augment human decision making, making it more effective and efficient. The clinical impact of having computers in the routine clinical practice may allow radiologists to further integrate their knowledge with their clinical colleagues in other medical specialties and allow for precision medicine. Copyright © 2018. Published by Elsevier Inc.

  5. Aliphatic polyesters for medical imaging and theranostic applications.

    Science.gov (United States)

    Nottelet, Benjamin; Darcos, Vincent; Coudane, Jean

    2015-11-01

    Medical imaging is a cornerstone of modern medicine. In that context the development of innovative imaging systems combining biomaterials and contrast agents (CAs)/imaging probes (IPs) for improved diagnostic and theranostic applications focuses intense research efforts. In particular, the classical aliphatic (co)polyesters poly(lactide) (PLA), poly(lactide-co-glycolide) (PLGA) and poly(ɛ-caprolactone) (PCL), attract much attention due to their long track record in the medical field. This review aims therefore at providing a state-of-the-art of polyester-based imaging systems. In a first section a rapid description of the various imaging modalities, including magnetic resonance imaging (MRI), optical imaging, computed tomography (CT), ultrasound (US) and radionuclide imaging (SPECT, PET) will be given. Then, the two main strategies used to combine the CAs/IPs and the polyesters will be discussed. In more detail we will first present the strategies relying on CAs/IPs encapsulation in nanoparticles, micelles, dendrimers or capsules. We will then present chemical modifications of polyesters backbones and/or polyester surfaces to yield macromolecular imaging agents. Finally, opportunities offered by these innovative systems will be illustrated with some recent examples in the fields of cell labeling, diagnostic or theranostic applications and medical devices. Copyright © 2015 Elsevier B.V. All rights reserved.

  6. Brain medical image diagnosis based on corners with importance-values.

    Science.gov (United States)

    Gao, Linlin; Pan, Haiwei; Li, Qing; Xie, Xiaoqin; Zhang, Zhiqiang; Han, Jinming; Zhai, Xiao

    2017-11-21

    Brain disorders are one of the top causes of human death. Generally, neurologists analyze brain medical images for diagnosis. In the image analysis field, corners are one of the most important features, which makes corner detection and matching studies essential. However, existing corner detection studies do not consider the domain information of brain. This leads to many useless corners and the loss of significant information. Regarding corner matching, the uncertainty and structure of brain are not employed in existing methods. Moreover, most corner matching studies are used for 3D image registration. They are inapplicable for 2D brain image diagnosis because of the different mechanisms. To address these problems, we propose a novel corner-based brain medical image classification method. Specifically, we automatically extract multilayer texture images (MTIs) which embody diagnostic information from neurologists. Moreover, we present a corner matching method utilizing the uncertainty and structure of brain medical images and a bipartite graph model. Finally, we propose a similarity calculation method for diagnosis. Brain CT and MRI image sets are utilized to evaluate the proposed method. First, classifiers are trained in N-fold cross-validation analysis to produce the best θ and K. Then independent brain image sets are tested to evaluate the classifiers. Moreover, the classifiers are also compared with advanced brain image classification studies. For the brain CT image set, the proposed classifier outperforms the comparison methods by at least 8% on accuracy and 2.4% on F1-score. Regarding the brain MRI image set, the proposed classifier is superior to the comparison methods by more than 7.3% on accuracy and 4.9% on F1-score. Results also demonstrate that the proposed method is robust to different intensity ranges of brain medical image. In this study, we develop a robust corner-based brain medical image classifier. Specifically, we propose a corner detection

  7. Visualization index for image-enabled medical records

    Science.gov (United States)

    Dong, Wenjie; Zheng, Weilin; Sun, Jianyong; Zhang, Jianguo

    2011-03-01

    With the widely use of healthcare information technology in hospitals, the patients' medical records are more and more complex. To transform the text- or image-based medical information into easily understandable and acceptable form for human, we designed and developed an innovation indexing method which can be used to assign an anatomical 3D structure object to every patient visually to store indexes of the patients' basic information, historical examined image information and RIS report information. When a doctor wants to review patient historical records, he or she can first load the anatomical structure object and the view the 3D index of this object using a digital human model tool kit. This prototype system helps doctors to easily and visually obtain the complete historical healthcare status of patients, including large amounts of medical data, and quickly locate detailed information, including both reports and images, from medical information systems. In this way, doctors can save time that may be better used to understand information, obtain a more comprehensive understanding of their patients' situations, and provide better healthcare services to patients.

  8. Aligning Islamic Spirituality to Medical Imaging.

    Science.gov (United States)

    Zainuddin, Zainul Ibrahim

    2017-10-01

    This paper attempts to conceptualize Islamic spirituality in medical imaging that deals with the humanistic and technical dimensions. It begins with establishing an understanding concerning spirituality, an area that now accepted as part of patient-centred care. This is followed by discussions pertaining to Islamic spirituality, related to the practitioner, patient care and the practice. Possible avenues towards applying Islamic spirituality in medical imaging are proposed. It is hoped that the resultant harmonization between Islamic spirituality and the practice will trigger awareness and interests pertaining to the role of a Muslim practitioner in advocating and enhancing Islamic spirituality.

  9. An Improved FCM Medical Image Segmentation Algorithm Based on MMTD

    Directory of Open Access Journals (Sweden)

    Ningning Zhou

    2014-01-01

    Full Text Available Image segmentation plays an important role in medical image processing. Fuzzy c-means (FCM is one of the popular clustering algorithms for medical image segmentation. But FCM is highly vulnerable to noise due to not considering the spatial information in image segmentation. This paper introduces medium mathematics system which is employed to process fuzzy information for image segmentation. It establishes the medium similarity measure based on the measure of medium truth degree (MMTD and uses the correlation of the pixel and its neighbors to define the medium membership function. An improved FCM medical image segmentation algorithm based on MMTD which takes some spatial features into account is proposed in this paper. The experimental results show that the proposed algorithm is more antinoise than the standard FCM, with more certainty and less fuzziness. This will lead to its practicable and effective applications in medical image segmentation.

  10. Organization and visualization of medical images in radiotherapy

    International Nuclear Information System (INIS)

    Lorang, T.

    2001-05-01

    In modern radiotherapy, various imaging equipment is used to acquire views from inside human bodies. Tomographic imaging equipment is acquiring stacks of cross-sectional images, software implementations derive three-dimensional volumes from planar images to allow for visualization of reconstructed cross-sections at any orientation and location and higher-level visualization systems allow for transparent views and surface rendering. Of upcoming interest in radiotherapy is mutual information, the integration of information from multiple imaging equipment res. from the same imaging equipment at different time stamps and varying acquisition parameters. Huge amounts of images are acquired nowadays at radiotherapy centers, requiring organization of images with respect to patient, acquisition and equipment to allow for visualization of images in a comparative and integrative manner. Especially for integration of image information from different equipment, geometrical information is required to allow for registration of images res. volumes. DICOM 3.0 has been introduced as a standard for information interchange with respect to medical imaging. Geometric information of cross-sections, demographic information of patients and medical information of acquisitions and equipment are covered by this standard, allowing for a high-level automation with respect to organization and visualization of medical images. Reconstructing cross-sectional images from volumes at any orientation and location is required for the purpose of registration and multi-planar views. Resampling and addressing of discrete volume data need be implemented efficiently to allow for simultaneous visualization of multiple cross-sectional images, especially with respect to multiple, non-isotropy volume data sets. (author)

  11. Effective spatial database support for acquiring spatial information from remote sensing images

    Science.gov (United States)

    Jin, Peiquan; Wan, Shouhong; Yue, Lihua

    2009-12-01

    In this paper, a new approach to maintain spatial information acquiring from remote-sensing images is presented, which is based on Object-Relational DBMS. According to this approach, the detected and recognized results of targets are stored and able to be further accessed in an ORDBMS-based spatial database system, and users can access the spatial information using the standard SQL interface. This approach is different from the traditional ArcSDE-based method, because the spatial information management module is totally integrated into the DBMS and becomes one of the core modules in the DBMS. We focus on three issues, namely the general framework for the ORDBMS-based spatial database system, the definitions of the add-in spatial data types and operators, and the process to develop a spatial Datablade on Informix. The results show that the ORDBMS-based spatial database support for image-based target detecting and recognition is easy and practical to be implemented.

  12. Contributions in compression of 3D medical images and 2D images

    International Nuclear Information System (INIS)

    Gaudeau, Y.

    2006-12-01

    The huge amounts of volumetric data generated by current medical imaging techniques in the context of an increasing demand for long term archiving solutions, as well as the rapid development of distant radiology make the use of compression inevitable. Indeed, if the medical community has sided until now with compression without losses, most of applications suffer from compression ratios which are too low with this kind of compression. In this context, compression with acceptable losses could be the most appropriate answer. So, we propose a new loss coding scheme based on 3D (3 dimensional) Wavelet Transform and Dead Zone Lattice Vector Quantization 3D (DZLVQ) for medical images. Our algorithm has been evaluated on several computerized tomography (CT) and magnetic resonance image volumes. The main contribution of this work is the design of a multidimensional dead zone which enables to take into account correlations between neighbouring elementary volumes. At high compression ratios, we show that it can out-perform visually and numerically the best existing methods. These promising results are confirmed on head CT by two medical patricians. The second contribution of this document assesses the effect with-loss image compression on CAD (Computer-Aided Decision) detection performance of solid lung nodules. This work on 120 significant lungs images shows that detection did not suffer until 48:1 compression and still was robust at 96:1. The last contribution consists in the complexity reduction of our compression scheme. The first allocation dedicated to 2D DZLVQ uses an exponential of the rate-distortion (R-D) functions. The second allocation for 2D and 3D medical images is based on block statistical model to estimate the R-D curves. These R-D models are based on the joint distribution of wavelet vectors using a multidimensional mixture of generalized Gaussian (MMGG) densities. (author)

  13. MEDICAL IMAGE COMPRESSION USING HYBRID CODER WITH FUZZY EDGE DETECTION

    Directory of Open Access Journals (Sweden)

    K. Vidhya

    2011-02-01

    Full Text Available Medical imaging techniques produce prohibitive amounts of digitized clinical data. Compression of medical images is a must due to large memory space required for transmission and storage. This paper presents an effective algorithm to compress and to reconstruct medical images. The proposed algorithm first extracts edge information of medical images by using fuzzy edge detector. The images are decomposed using Cohen-Daubechies-Feauveau (CDF wavelet. The hybrid technique utilizes the efficient wavelet based compression algorithms such as JPEG2000 and Set Partitioning In Hierarchical Trees (SPIHT. The wavelet coefficients in the approximation sub band are encoded using tier 1 part of JPEG2000. The wavelet coefficients in the detailed sub bands are encoded using SPIHT. Consistent quality images are produced by this method at a lower bit rate compared to other standard compression algorithms. Two main approaches to assess image quality are objective testing and subjective testing. The image quality is evaluated by objective quality measures. Objective measures correlate well with the perceived image quality for the proposed compression algorithm.

  14. The Handbook of Medical Image Perception and Techniques

    Science.gov (United States)

    Samei, Ehsan; Krupinski, Elizabeth

    2014-07-01

    1. Medical image perception Ehsan Samei and Elizabeth Krupinski; Part I. Historical Reflections and Theoretical Foundations: 2. A short history of image perception in medical radiology Harold Kundel and Calvin Nodine; 3. Spatial vision research without noise Arthur Burgess; 4. Signal detection theory, a brief history Arthur Burgess; 5. Signal detection in radiology Arthur Burgess; 6. Lessons from dinners with the giants of modern image science Robert Wagner; Part II. Science of Image Perception: 7. Perceptual factors in reading medical images Elizabeth Krupinski; 8. Cognitive factors in reading medical images David Manning; 9. Satisfaction of search in traditional radiographic imaging Kevin Berbaum, Edmund Franken, Robert Caldwell and Kevin Schartz; 10. The role of expertise in radiologic image interpretation Calvin Nodine and Claudia Mello-Thoms; 11. A primer of image quality and its perceptual relevance Robert Saunders and Ehsan Samei; 12. Beyond the limitations of human vision Maria Petrou; Part III. Perception Metrology: 13. Logistical issues in designing perception experiments Ehsan Samei and Xiang Li; 14. ROC analysis: basic concepts and practical applications Georgia Tourassi; 15. Multi-reader ROC Steve Hillis; 16. Recent developments in FROC methodology Dev Chakraborty; 17. Observer models as a surrogate to perception experiments Craig Abbey and Miguel Eckstein; 18. Implementation of observer models Matthew Kupinski; Part IV. Decision Support and Computer Aided Detection: 19. CAD: an image perception perspective Maryellen Giger and Weijie Chen; 20. Common designs of CAD studies Yulei Jiang; 21. Perceptual effect of CAD in reading chest images Matthew Freedman and Teresa Osicka; 22. Perceptual issues in mammography and CAD Michael Ulissey; 23. How perceptual factors affect the use and accuracy of CAD for interpretation of CT images Ronald Summers; 24. CAD: risks and benefits for radiologists' decisions Eugenio Alberdi, Andrey Povyakalo, Lorenzo Strigini and

  15. Medical images storage using discrete cosine transform

    International Nuclear Information System (INIS)

    Arhouma, Ali M.; Ajaal, Tawfik; Marghani, Khaled

    2010-01-01

    The advances in technology during the last decades have made the use of digital images as one of the common things in everyday life. While the application of digital images in communicating information is very important, the cost of storing and transmitting images is much larger compared to storage and transmission of text. The main problem with all of the images was the fact that they take large size of memory space, large transmission bandwidth and long transmission time. Image data compression is needed to reduce the storage space,transmission bandwidth and transmission time. Medical image compression plays a key role as hospitals move towards filmless imaging and go completely digital. Image compression allows Picture Archiving and Communication Systems (PACS) to reduce the file size on their storage requirements while maintaining relevant diagnostic information. The reduced image file size yield reduced transmission times. Even as the capacity of storage media continues to increase, it is expected that the volume of uncompressed data produced by hospitals will exceed capacity of storage and drive up costs. This paper proposes a Discrete Cosine Transform (DCT) algorithm which can help to solve the image storage and transmission time problem in hospitals. Discrete cosine transform (DCT) has become the most popular technique for image compression over the past several years. One of the major reasons for its popularity is its selection as the standard for JPEG. DCTs are most commonly used for non-analytical applications such as image processing and digital signal-processing (DSP) applications such as video conferencing, fax systems, video disks, and high-definition television HDTV. They also can be used on a matrix of practically any dimension. The proposed (DCT) algorithm improves the performance of medical image compression while satisfying both the medical image quality, and the high compression ratio. Application of DCT coding algorithm to actual still images

  16. Medical imaging and augmented reality. Proceedings

    International Nuclear Information System (INIS)

    Yang Guang-Zhong; Jiang Tianzi; Shen Dinggang; Gu Lixu; Yang Jie

    2006-01-01

    This book constitutes the refereed proceedings of the Third International Workshop on Medical Imaging and Augmented Reality, MIAR 2006, held in Shanghai, China, in August 2006. The 45 revised full papers presented together with 4 invited papers were carefully reviewed and selected from 87 submissions. The papers are organized in topical sections on shape modeling and morphometry, patient specific modeling and quantification, surgical simulation and skills assessment, surgical guidance and navigation, image registration, PET image reconstruction, and image segmentation. (orig.)

  17. Adaptive Beamforming for Medical Ultrasound Imaging

    DEFF Research Database (Denmark)

    Holfort, Iben Kraglund

    This dissertation investigates the application of adaptive beamforming for medical ultrasound imaging. The investigations have been concentrated primarily on the Minimum Variance (MV) beamformer. A broadband implementation of theMV beamformer is described, and simulated data have been used...... to demonstrate the performance. The MV beamformer has been applied to different sets of ultrasound imaging sequences; synthetic aperture ultrasound imaging and plane wave ultrasound imaging. And an approach for applying MV optimized apodization weights on both the transmitting and the receiving apertures...

  18. [Managing digital medical imaging projects in healthcare services: lessons learned].

    Science.gov (United States)

    Rojas de la Escalera, D

    2013-01-01

    Medical imaging is one of the most important diagnostic instruments in clinical practice. The technological development of digital medical imaging has enabled healthcare services to undertake large scale projects that require the participation and collaboration of many professionals of varied backgrounds and interests as well as substantial investments in infrastructures. Rather than focusing on systems for dealing with digital medical images, this article deals with the management of projects for implementing these systems, reviewing various organizational, technological, and human factors that are critical to ensure the success of these projects and to guarantee the compatibility and integration of digital medical imaging systems with other health information systems. To this end, the author relates several lessons learned from a review of the literature and the author's own experience in the technical coordination of digital medical imaging projects. Copyright © 2012 SERAM. Published by Elsevier Espana. All rights reserved.

  19. Intelligent medical image processing by simulated annealing

    International Nuclear Information System (INIS)

    Ohyama, Nagaaki

    1992-01-01

    Image processing is being widely used in the medical field and already has become very important, especially when used for image reconstruction purposes. In this paper, it is shown that image processing can be classified into 4 categories; passive, active, intelligent and visual image processing. These 4 classes are explained at first through the use of several examples. The results show that the passive image processing does not give better results than the others. Intelligent image processing, then, is addressed, and the simulated annealing method is introduced. Due to the flexibility of the simulated annealing, formulated intelligence is shown to be easily introduced in an image reconstruction problem. As a practical example, 3D blood vessel reconstruction from a small number of projections, which is insufficient for conventional method to give good reconstruction, is proposed, and computer simulation clearly shows the effectiveness of simulated annealing method. Prior to the conclusion, medical file systems such as IS and C (Image Save and Carry) is pointed out to have potential for formulating knowledge, which is indispensable for intelligent image processing. This paper concludes by summarizing the advantages of simulated annealing. (author)

  20. Identifying regions of interest in medical images using self-organizing maps.

    Science.gov (United States)

    Teng, Wei-Guang; Chang, Ping-Lin

    2012-10-01

    Advances in data acquisition, processing and visualization techniques have had a tremendous impact on medical imaging in recent years. However, the interpretation of medical images is still almost always performed by radiologists. Developments in artificial intelligence and image processing have shown the increasingly great potential of computer-aided diagnosis (CAD). Nevertheless, it has remained challenging to develop a general approach to process various commonly used types of medical images (e.g., X-ray, MRI, and ultrasound images). To facilitate diagnosis, we recommend the use of image segmentation to discover regions of interest (ROI) using self-organizing maps (SOM). We devise a two-stage SOM approach that can be used to precisely identify the dominant colors of a medical image and then segment it into several small regions. In addition, by appropriately conducting the recursive merging steps to merge smaller regions into larger ones, radiologists can usually identify one or more ROIs within a medical image.

  1. Machine learning approaches in medical image analysis

    DEFF Research Database (Denmark)

    de Bruijne, Marleen

    2016-01-01

    Machine learning approaches are increasingly successful in image-based diagnosis, disease prognosis, and risk assessment. This paper highlights new research directions and discusses three main challenges related to machine learning in medical imaging: coping with variation in imaging protocols......, learning from weak labels, and interpretation and evaluation of results....

  2. Adaptable pattern recognition system for discriminating Melanocytic Nevi from Malignant Melanomas using plain photography images from different image databases.

    Science.gov (United States)

    Kostopoulos, Spiros A; Asvestas, Pantelis A; Kalatzis, Ioannis K; Sakellaropoulos, George C; Sakkis, Theofilos H; Cavouras, Dionisis A; Glotsos, Dimitris T

    2017-09-01

    The aim of this study was to propose features that evaluate pictorial differences between melanocytic nevus (mole) and melanoma lesions by computer-based analysis of plain photography images and to design a cross-platform, tunable, decision support system to discriminate with high accuracy moles from melanomas in different publicly available image databases. Digital plain photography images of verified mole and melanoma lesions were downloaded from (i) Edinburgh University Hospital, UK, (Dermofit, 330moles/70 melanomas, under signed agreement), from 5 different centers (Multicenter, 63moles/25 melanomas, publicly available), and from the Groningen University, Netherlands (Groningen, 100moles/70 melanomas, publicly available). Images were processed for outlining the lesion-border and isolating the lesion from the surrounding background. Fourteen features were generated from each lesion evaluating texture (4), structure (5), shape (4) and color (1). Features were subjected to statistical analysis for determining differences in pictorial properties between moles and melanomas. The Probabilistic Neural Network (PNN) classifier, the exhaustive search features selection, the leave-one-out (LOO), and the external cross-validation (ECV) methods were used to design the PR-system for discriminating between moles and melanomas. Statistical analysis revealed that melanomas as compared to moles were of lower intensity, of less homogenous surface, had more dark pixels with intensities spanning larger spectra of gray-values, contained more objects of different sizes and gray-levels, had more asymmetrical shapes and irregular outlines, had abrupt intensity transitions from lesion to background tissue, and had more distinct colors. The PR-system designed by the Dermofit images scored on the Dermofit images, using the ECV, 94.1%, 82.9%, 96.5% for overall accuracy, sensitivity, specificity, on the Multicenter Images 92.0%, 88%, 93.7% and on the Groningen Images 76.2%, 73.9%, 77

  3. The FoodCast Research Image Database (FRIDa

    Directory of Open Access Journals (Sweden)

    Francesco eForoni

    2013-03-01

    Full Text Available In recent years we have witnessed to an increasing interest in food processing and eating behaviors. This is probably due to several reasons. The biological relevance of food choices, the complexity of the food-rich environment in which we presently live (making food-intake regulation difficult, and the increasing health care cost due to illness associated with food (food hazards, food contamination, and aberrant food-intake. Despite the importance of the issues and the relevance of this research, comprehensive and validated databases of stimuli are rather limited, outdated, or not available for noncommercial purposes to independent researchers who aim at developing their own research program. The FoodCast Research Image Database (FRIDa we present here is comprised of 877 images from eight different categories: natural-food (e.g., strawberry, transformed-food (e.g., French fries, rotten-food (e.g., moldy banana, natural-nonfood items (e.g., pinecone, artificial food-related objects (e.g., teacup, artificial objects (e.g., guitar, animals (e.g., camel, and scenes (e.g., airport. FRIDa has been validated on a sample of healthy participants (N=73 on standard variables (e.g., valence, familiarity etc. as well as on other variables specifically related to food items (e.g., perceived calorie content; it also includes data on the visual features of the stimuli (e.g., brightness, high frequency power etc.. FRIDa is a well-controlled, flexible, validated, and freely available (http://foodcast.sissa.it/neuroscience/ tool for researchers in a wide range of academic fields and industry.

  4. Food-pics: an image database for experimental research on eating and appetite.

    Science.gov (United States)

    Blechert, Jens; Meule, Adrian; Busch, Niko A; Ohla, Kathrin

    2014-01-01

    Our current environment is characterized by the omnipresence of food cues. The sight and smell of real foods, but also graphically depictions of appetizing foods, can guide our eating behavior, for example, by eliciting food craving and influencing food choice. The relevance of visual food cues on human information processing has been demonstrated by a growing body of studies employing food images across the disciplines of psychology, medicine, and neuroscience. However, currently used food image sets vary considerably across laboratories and image characteristics (contrast, brightness, etc.) and food composition (calories, macronutrients, etc.) are often unspecified. These factors might have contributed to some of the inconsistencies of this research. To remedy this, we developed food-pics, a picture database comprising 568 food images and 315 non-food images along with detailed meta-data. A total of N = 1988 individuals with large variance in age and weight from German speaking countries and North America provided normative ratings of valence, arousal, palatability, desire to eat, recognizability and visual complexity. Furthermore, data on macronutrients (g), energy density (kcal), and physical image characteristics (color composition, contrast, brightness, size, complexity) are provided. The food-pics image database is freely available under the creative commons license with the hope that the set will facilitate standardization and comparability across studies and advance experimental research on the determinants of eating behavior.

  5. Personalizing Medicine Through Hybrid Imaging and Medical Big Data Analysis

    Directory of Open Access Journals (Sweden)

    Laszlo Papp

    2018-06-01

    Full Text Available Medical imaging has evolved from a pure visualization tool to representing a primary source of analytic approaches toward in vivo disease characterization. Hybrid imaging is an integral part of this approach, as it provides complementary visual and quantitative information in the form of morphological and functional insights into the living body. As such, non-invasive imaging modalities no longer provide images only, but data, as stated recently by pioneers in the field. Today, such information, together with other, non-imaging medical data creates highly heterogeneous data sets that underpin the concept of medical big data. While the exponential growth of medical big data challenges their processing, they inherently contain information that benefits a patient-centric personalized healthcare. Novel machine learning approaches combined with high-performance distributed cloud computing technologies help explore medical big data. Such exploration and subsequent generation of knowledge require a profound understanding of the technical challenges. These challenges increase in complexity when employing hybrid, aka dual- or even multi-modality image data as input to big data repositories. This paper provides a general insight into medical big data analysis in light of the use of hybrid imaging information. First, hybrid imaging is introduced (see further contributions to this special Research Topic, also in the context of medical big data, then the technological background of machine learning as well as state-of-the-art distributed cloud computing technologies are presented, followed by the discussion of data preservation and data sharing trends. Joint data exploration endeavors in the context of in vivo radiomics and hybrid imaging will be presented. Standardization challenges of imaging protocol, delineation, feature engineering, and machine learning evaluation will be detailed. Last, the paper will provide an outlook into the future role of hybrid

  6. ImageParser: a tool for finite element generation from three-dimensional medical images

    Directory of Open Access Journals (Sweden)

    Yamada T

    2004-10-01

    Full Text Available Abstract Background The finite element method (FEM is a powerful mathematical tool to simulate and visualize the mechanical deformation of tissues and organs during medical examinations or interventions. It is yet a challenge to build up an FEM mesh directly from a volumetric image partially because the regions (or structures of interest (ROIs may be irregular and fuzzy. Methods A software package, ImageParser, is developed to generate an FEM mesh from 3-D tomographic medical images. This software uses a semi-automatic method to detect ROIs from the context of image including neighboring tissues and organs, completes segmentation of different tissues, and meshes the organ into elements. Results The ImageParser is shown to build up an FEM model for simulating the mechanical responses of the breast based on 3-D CT images. The breast is compressed by two plate paddles under an overall displacement as large as 20% of the initial distance between the paddles. The strain and tangential Young's modulus distributions are specified for the biomechanical analysis of breast tissues. Conclusion The ImageParser can successfully exact the geometry of ROIs from a complex medical image and generate the FEM mesh with customer-defined segmentation information.

  7. Improved Software to Browse the Serial Medical Images for Learning.

    Science.gov (United States)

    Kwon, Koojoo; Chung, Min Suk; Park, Jin Seo; Shin, Byeong Seok; Chung, Beom Sun

    2017-07-01

    The thousands of serial images used for medical pedagogy cannot be included in a printed book; they also cannot be efficiently handled by ordinary image viewer software. The purpose of this study was to provide browsing software to grasp serial medical images efficiently. The primary function of the newly programmed software was to select images using 3 types of interfaces: buttons or a horizontal scroll bar, a vertical scroll bar, and a checkbox. The secondary function was to show the names of the structures that had been outlined on the images. To confirm the functions of the software, 3 different types of image data of cadavers (sectioned and outlined images, volume models of the stomach, and photos of the dissected knees) were inputted. The browsing software was downloadable for free from the homepage (anatomy.co.kr) and available off-line. The data sets provided could be replaced by any developers for their educational achievements. We anticipate that the software will contribute to medical education by allowing users to browse a variety of images. © 2017 The Korean Academy of Medical Sciences.

  8. Structural analysis in medical imaging

    International Nuclear Information System (INIS)

    Dellepiane, S.; Serpico, S.B.; Venzano, L.; Vernazza, G.

    1987-01-01

    The conventional techniques in Pattern Recognition (PR) have been greatly improved by the introduction of Artificial Intelligence (AI) approaches, in particular for knowledge representation, inference mechanism and control structure. The purpose of this paper is to describe an image understanding system, based on the integrated approach (AI - PR), developed in the author's Department to interpret Nuclear Magnetic Resonance (NMR) images. The system is characterized by a heterarchical control structure and a blackboard model for the global data-base. The major aspects of the system are pointed out, with particular reference to segmentation, knowledge representation and error recovery (backtracking). The eye slices obtained in the case of two patients have been analyzed and the related results are discussed

  9. An Imaging Sensor-Aided Vision Navigation Approach that Uses a Geo-Referenced Image Database.

    Science.gov (United States)

    Li, Yan; Hu, Qingwu; Wu, Meng; Gao, Yang

    2016-01-28

    In determining position and attitude, vision navigation via real-time image processing of data collected from imaging sensors is advanced without a high-performance global positioning system (GPS) and an inertial measurement unit (IMU). Vision navigation is widely used in indoor navigation, far space navigation, and multiple sensor-integrated mobile mapping. This paper proposes a novel vision navigation approach aided by imaging sensors and that uses a high-accuracy geo-referenced image database (GRID) for high-precision navigation of multiple sensor platforms in environments with poor GPS. First, the framework of GRID-aided vision navigation is developed with sequence images from land-based mobile mapping systems that integrate multiple sensors. Second, a highly efficient GRID storage management model is established based on the linear index of a road segment for fast image searches and retrieval. Third, a robust image matching algorithm is presented to search and match a real-time image with the GRID. Subsequently, the image matched with the real-time scene is considered to calculate the 3D navigation parameter of multiple sensor platforms. Experimental results show that the proposed approach retrieves images efficiently and has navigation accuracies of 1.2 m in a plane and 1.8 m in height under GPS loss in 5 min and within 1500 m.

  10. FAST: framework for heterogeneous medical image computing and visualization.

    Science.gov (United States)

    Smistad, Erik; Bozorgi, Mohammadmehdi; Lindseth, Frank

    2015-11-01

    Computer systems are becoming increasingly heterogeneous in the sense that they consist of different processors, such as multi-core CPUs and graphic processing units. As the amount of medical image data increases, it is crucial to exploit the computational power of these processors. However, this is currently difficult due to several factors, such as driver errors, processor differences, and the need for low-level memory handling. This paper presents a novel FrAmework for heterogeneouS medical image compuTing and visualization (FAST). The framework aims to make it easier to simultaneously process and visualize medical images efficiently on heterogeneous systems. FAST uses common image processing programming paradigms and hides the details of memory handling from the user, while enabling the use of all processors and cores on a system. The framework is open-source, cross-platform and available online. Code examples and performance measurements are presented to show the simplicity and efficiency of FAST. The results are compared to the insight toolkit (ITK) and the visualization toolkit (VTK) and show that the presented framework is faster with up to 20 times speedup on several common medical imaging algorithms. FAST enables efficient medical image computing and visualization on heterogeneous systems. Code examples and performance evaluations have demonstrated that the toolkit is both easy to use and performs better than existing frameworks, such as ITK and VTK.

  11. Introduction to Medical Image Analysis

    DEFF Research Database (Denmark)

    Paulsen, Rasmus Reinhold; Moeslund, Thomas B.

    This book is a result of a collaboration between DTU Informatics at the Technical University of Denmark and the Laboratory of Computer Vision and Media Technology at Aalborg University. It is partly based on the book ”Image and Video Processing”, second edition by Thomas Moeslund. The aim...... of the book is to present the fascinating world of medical image analysis in an easy and interesting way. Compared to many standard books on image analysis, the approach we have chosen is less mathematical and more casual. Some of the key algorithms are exemplified in C-code. Please note that the code...

  12. Medical Image Visual Appearance Improvement Using Bihistogram Bezier Curve Contrast Enhancement: Data from the Osteoarthritis Initiative

    Science.gov (United States)

    Gan, Hong-Seng; Swee, Tan Tian; Abdul Karim, Ahmad Helmy; Sayuti, Khairil Amir; Abdul Kadir, Mohammed Rafiq; Tham, Weng-Kit; Wong, Liang-Xuan; Chaudhary, Kashif T.; Yupapin, Preecha P.

    2014-01-01

    Well-defined image can assist user to identify region of interest during segmentation. However, complex medical image is usually characterized by poor tissue contrast and low background luminance. The contrast improvement can lift image visual quality, but the fundamental contrast enhancement methods often overlook the sudden jump problem. In this work, the proposed bihistogram Bezier curve contrast enhancement introduces the concept of “adequate contrast enhancement” to overcome sudden jump problem in knee magnetic resonance image. Since every image produces its own intensity distribution, the adequate contrast enhancement checks on the image's maximum intensity distortion and uses intensity discrepancy reduction to generate Bezier transform curve. The proposed method improves tissue contrast and preserves pertinent knee features without compromising natural image appearance. Besides, statistical results from Fisher's Least Significant Difference test and the Duncan test have consistently indicated that the proposed method outperforms fundamental contrast enhancement methods to exalt image visual quality. As the study is limited to relatively small image database, future works will include a larger dataset with osteoarthritic images to assess the clinical effectiveness of the proposed method to facilitate the image inspection. PMID:24977191

  13. A Survey on Deep Learning in Medical Image Analysis

    NARCIS (Netherlands)

    Litjens, G.J.; Kooi, T.; Ehteshami Bejnordi, B.; Setio, A.A.A.; Ciompi, F.; Ghafoorian, M.; Laak, J.A.W.M. van der; Ginneken, B. van; Sanchez, C.I.

    2017-01-01

    Deep learning algorithms, in particular convolutional networks, have rapidly become a methodology of choice for analyzing medical images. This paper reviews the major deep learning concepts pertinent to medical image analysis and summarizes over 300 contributions to the field, most of which appeared

  14. Noise removal for medical X-ray images in wavelet domain

    International Nuclear Information System (INIS)

    Wang, Ling; Lu, Jianming; Li, Yeqiu; Yahagi, Takashi; Okamoto, Takahide

    2006-01-01

    Many important problems in engineering and science are well-modeled by Poisson noise, the noise of medical X-ray image is Poisson noise. In this paper, we propose a method of noise removal for degraded medical X-ray image using improved preprocessing and improved BayesShrink (IBS) method in wavelet domain. Firstly, we pre-process the medical X-ray image, Secondly, we apply the Daubechies (db) wavelet transform to medical X-ray image to acquire scaling and wavelet coefficients. Thirdly, we apply the proposed IBS method to process wavelet coefficients. Finally, we compute the inverse wavelet transform for the thresholded coefficeints. Experimental results show that the proposed method always outperforms traditional methods. (author)

  15. Cascaded Window Memoization for Medical Imaging

    OpenAIRE

    Khalvati , Farzad; Kianpour , Mehdi; Tizhoosh , Hamid ,

    2011-01-01

    Part 12: Medical Applications of ANN and Ethics of AI; International audience; Window Memoization is a performance improvement technique for image processing algorithms. It is based on removing computational redundancy in an algorithm applied to a single image, which is inherited from data redundancy in the image. The technique employs a fuzzy reuse mechanism to eliminate unnecessary computations. This paper extends the window memoization technique such that in addition to exploiting the data...

  16. elastix: a toolbox for intensity-based medical image registration.

    Science.gov (United States)

    Klein, Stefan; Staring, Marius; Murphy, Keelin; Viergever, Max A; Pluim, Josien P W

    2010-01-01

    Medical image registration is an important task in medical image processing. It refers to the process of aligning data sets, possibly from different modalities (e.g., magnetic resonance and computed tomography), different time points (e.g., follow-up scans), and/or different subjects (in case of population studies). A large number of methods for image registration are described in the literature. Unfortunately, there is not one method that works for all applications. We have therefore developed elastix, a publicly available computer program for intensity-based medical image registration. The software consists of a collection of algorithms that are commonly used to solve medical image registration problems. The modular design of elastix allows the user to quickly configure, test, and compare different registration methods for a specific application. The command-line interface enables automated processing of large numbers of data sets, by means of scripting. The usage of elastix for comparing different registration methods is illustrated with three example experiments, in which individual components of the registration method are varied.

  17. Rapid development of medical imaging tools with open-source libraries.

    Science.gov (United States)

    Caban, Jesus J; Joshi, Alark; Nagy, Paul

    2007-11-01

    Rapid prototyping is an important element in researching new imaging analysis techniques and developing custom medical applications. In the last ten years, the open source community and the number of open source libraries and freely available frameworks for biomedical research have grown significantly. What they offer are now considered standards in medical image analysis, computer-aided diagnosis, and medical visualization. A cursory review of the peer-reviewed literature in imaging informatics (indeed, in almost any information technology-dependent scientific discipline) indicates the current reliance on open source libraries to accelerate development and validation of processes and techniques. In this survey paper, we review and compare a few of the most successful open source libraries and frameworks for medical application development. Our dual intentions are to provide evidence that these approaches already constitute a vital and essential part of medical image analysis, diagnosis, and visualization and to motivate the reader to use open source libraries and software for rapid prototyping of medical applications and tools.

  18. Mathematics and computer science in medical imaging

    International Nuclear Information System (INIS)

    Viergever, M.A.; Todd-Pokroper, A.E.

    1987-01-01

    The book is divided into two parts. Part 1 gives an introduction to and an overview of the field in ten tutorial chapters. Part 2 contains a selection of invited and proffered papers reporting on current research. Subjects covered in depth are: analytical image reconstruction, regularization, iterative methods, image structure, 3-D display, compression, architectures for image processing, statistical pattern recognition, and expert systems in medical imaging

  19. Medical imaging technology reviews and computational applications

    CERN Document Server

    Dewi, Dyah

    2015-01-01

    This book presents the latest research findings and reviews in the field of medical imaging technology, covering ultrasound diagnostics approaches for detecting osteoarthritis, breast carcinoma and cardiovascular conditions, image guided biopsy and segmentation techniques for detecting lung cancer, image fusion, and simulating fluid flows for cardiovascular applications. It offers a useful guide for students, lecturers and professional researchers in the fields of biomedical engineering and image processing.

  20. Anniversary Paper: History and status of CAD and quantitative image analysis: The role of Medical Physics and AAPM

    International Nuclear Information System (INIS)

    Giger, Maryellen L.; Chan, Heang-Ping; Boone, John

    2008-01-01

    The roles of physicists in medical imaging have expanded over the years, from the study of imaging systems (sources and detectors) and dose to the assessment of image quality and perception, the development of image processing techniques, and the development of image analysis methods to assist in detection and diagnosis. The latter is a natural extension of medical physicists' goals in developing imaging techniques to help physicians acquire diagnostic information and improve clinical decisions. Studies indicate that radiologists do not detect all abnormalities on images that are visible on retrospective review, and they do not always correctly characterize abnormalities that are found. Since the 1950s, the potential use of computers had been considered for analysis of radiographic abnormalities. In the mid-1980s, however, medical physicists and radiologists began major research efforts for computer-aided detection or computer-aided diagnosis (CAD), that is, using the computer output as an aid to radiologists--as opposed to a completely automatic computer interpretation--focusing initially on methods for the detection of lesions on chest radiographs and mammograms. Since then, extensive investigations of computerized image analysis for detection or diagnosis of abnormalities in a variety of 2D and 3D medical images have been conducted. The growth of CAD over the past 20 years has been tremendous--from the early days of time-consuming film digitization and CPU-intensive computations on a limited number of cases to its current status in which developed CAD approaches are evaluated rigorously on large clinically relevant databases. CAD research by medical physicists includes many aspects--collecting relevant normal and pathological cases; developing computer algorithms appropriate for the medical interpretation task including those for segmentation, feature extraction, and classifier design; developing methodology for assessing CAD performance; validating the

  1. Object-oriented design of medical imaging software.

    Science.gov (United States)

    Ligier, Y; Ratib, O; Logean, M; Girard, C; Perrier, R; Scherrer, J R

    1994-01-01

    A special software package for interactive display and manipulation of medical images was developed at the University Hospital of Geneva, as part of a hospital wide Picture Archiving and Communication System (PACS). This software package, called Osiris, was especially designed to be easily usable and adaptable to the needs of noncomputer-oriented physicians. The Osiris software has been developed to allow the visualization of medical images obtained from any imaging modality. It provides generic manipulation tools, processing tools, and analysis tools more specific to clinical applications. This software, based on an object-oriented paradigm, is portable and extensible. Osiris is available on two different operating systems: the Unix X-11/OSF-Motif based workstations, and the Macintosh family.

  2. Performance evaluation of emerging JPEGXR compression standard for medical images

    International Nuclear Information System (INIS)

    Basit, M.A.

    2012-01-01

    Medical images require loss less compression as a small error due to lossy compression may be considered as a diagnostic error. JPEG XR is the latest image compression standard designed for variety of applications and has a support for lossy and loss less modes. This paper provides in-depth performance evaluation of latest JPEGXR with existing image coding standards for medical images using loss less compression. Various medical images are used for evaluation and ten images of each organ are tested. Performance of JPEGXR is compared with JPEG2000 and JPEGLS using mean square error, peak signal to noise ratio, mean absolute error and structural similarity index. JPEGXR shows improvement of 20.73 dB and 5.98 dB over JPEGLS and JPEG2000 respectively for various test images used in experimentation. (author)

  3. Medical Image Visual Appearance Improvement Using Bihistogram Bezier Curve Contrast Enhancement: Data from the Osteoarthritis Initiative

    Directory of Open Access Journals (Sweden)

    Hong-Seng Gan

    2014-01-01

    Full Text Available Well-defined image can assist user to identify region of interest during segmentation. However, complex medical image is usually characterized by poor tissue contrast and low background luminance. The contrast improvement can lift image visual quality, but the fundamental contrast enhancement methods often overlook the sudden jump problem. In this work, the proposed bihistogram Bezier curve contrast enhancement introduces the concept of “adequate contrast enhancement” to overcome sudden jump problem in knee magnetic resonance image. Since every image produces its own intensity distribution, the adequate contrast enhancement checks on the image’s maximum intensity distortion and uses intensity discrepancy reduction to generate Bezier transform curve. The proposed method improves tissue contrast and preserves pertinent knee features without compromising natural image appearance. Besides, statistical results from Fisher’s Least Significant Difference test and the Duncan test have consistently indicated that the proposed method outperforms fundamental contrast enhancement methods to exalt image visual quality. As the study is limited to relatively small image database, future works will include a larger dataset with osteoarthritic images to assess the clinical effectiveness of the proposed method to facilitate the image inspection.

  4. iMAGE cloud: medical image processing as a service for regional healthcare in a hybrid cloud environment.

    Science.gov (United States)

    Liu, Li; Chen, Weiping; Nie, Min; Zhang, Fengjuan; Wang, Yu; He, Ailing; Wang, Xiaonan; Yan, Gen

    2016-11-01

    To handle the emergence of the regional healthcare ecosystem, physicians and surgeons in various departments and healthcare institutions must process medical images securely, conveniently, and efficiently, and must integrate them with electronic medical records (EMRs). In this manuscript, we propose a software as a service (SaaS) cloud called the iMAGE cloud. A three-layer hybrid cloud was created to provide medical image processing services in the smart city of Wuxi, China, in April 2015. In the first step, medical images and EMR data were received and integrated via the hybrid regional healthcare network. Then, traditional and advanced image processing functions were proposed and computed in a unified manner in the high-performance cloud units. Finally, the image processing results were delivered to regional users using the virtual desktop infrastructure (VDI) technology. Security infrastructure was also taken into consideration. Integrated information query and many advanced medical image processing functions-such as coronary extraction, pulmonary reconstruction, vascular extraction, intelligent detection of pulmonary nodules, image fusion, and 3D printing-were available to local physicians and surgeons in various departments and healthcare institutions. Implementation results indicate that the iMAGE cloud can provide convenient, efficient, compatible, and secure medical image processing services in regional healthcare networks. The iMAGE cloud has been proven to be valuable in applications in the regional healthcare system, and it could have a promising future in the healthcare system worldwide.

  5. Management of oral and maxillofacial radiological images

    International Nuclear Information System (INIS)

    Kim, Eun Kyung

    2002-01-01

    To implement the database system of oral and maxillofacial radiological images using a commercial medical image management software with personally developed classification code. The image database was built using a slightly modified commercial medical image management software, Dr. Image v.2.1 (Bit Computer Co., Korea). The function of wild card '*' was added to the search function of this program. Diagnosis classification codes were written as the number at the first three digits, and radiographic technique classification codes as the alphabet right after the diagnosis code. 449 radiological films of 218 cases from January, 2000 to December, 2000, which had been specially stored for the demonstration and education at Dept. of OMF Radiology of Dankook University Dental Hospital, were scanned with each patient information. Cases could be efficiently accessed and analyzed by using the classification code. Search and statistics results were easily obtained according to sex, age, disease diagnosis and radiographic technique. Efficient image management was possible with this image database system. Application of this system to other departments or personal image management can be made possible by utilizing the appropriate classification code system.

  6. Near-infrared spectroscopic tissue imaging for medical applications

    Science.gov (United States)

    Demos, Stavros [Livermore, CA; Staggs, Michael C [Tracy, CA

    2006-12-12

    Near infrared imaging using elastic light scattering and tissue autofluorescence are explored for medical applications. The approach involves imaging using cross-polarized elastic light scattering and tissue autofluorescence in the Near Infra-Red (NIR) coupled with image processing and inter-image operations to differentiate human tissue components.

  7. [Mobile phone-computer wireless interactive graphics transmission technology and its medical application].

    Science.gov (United States)

    Huang, Shuo; Liu, Jing

    2010-05-01

    Application of clinical digital medical imaging has raised many tough issues to tackle, such as data storage, management, and information sharing. Here we investigated a mobile phone based medical image management system which is capable of achieving personal medical imaging information storage, management and comprehensive health information analysis. The technologies related to the management system spanning the wireless transmission technology, the technical capabilities of phone in mobile health care and management of mobile medical database were discussed. Taking medical infrared images transmission between phone and computer as an example, the working principle of the present system was demonstrated.

  8. APES Beamforming Applied to Medical Ultrasound Imaging

    DEFF Research Database (Denmark)

    Blomberg, Ann E. A.; Holfort, Iben Kraglund; Austeng, Andreas

    2009-01-01

    Recently, adaptive beamformers have been introduced to medical ultrasound imaging. The primary focus has been on the minimum variance (MV) (or Capon) beamformer. This work investigates an alternative but closely related beamformer, the Amplitude and Phase Estimation (APES) beamformer. APES offers...... added robustness at the expense of a slightly lower resolution. The purpose of this study was to evaluate the performance of the APES beamformer on medical imaging data, since correct amplitude estimation often is just as important as spatial resolution. In our simulations we have used a 3.5 MHz, 96...... element linear transducer array. When imaging two closely spaced point targets, APES displays nearly the same resolution as the MV, and at the same time improved amplitude control. When imaging cysts in speckle, APES offers speckle statistics similar to that of the DAS, without the need for temporal...

  9. Automatic Image Alignment and Stitching of Medical Images with Seam Blending

    OpenAIRE

    Abhinav Kumar; Raja Sekhar Bandaru; B Madhusudan Rao; Saket Kulkarni; Nilesh Ghatpande

    2010-01-01

    This paper proposes an algorithm which automatically aligns and stitches the component medical images (fluoroscopic) with varying degrees of overlap into a single composite image. The alignment method is based on similarity measure between the component images. As applied here the technique is intensity based rather than feature based. It works well in domains where feature based methods have difficulty, yet more robust than traditional correlation. Component images are stitched together usin...

  10. Motion correction in medical imaging.

    OpenAIRE

    Smith, Rhodri

    2017-01-01

    It is estimated that over half of current adults within Great Britain under the age of 65 will be diagnosed with cancer at some point in their lifetime. Medical Imaging forms an essential part of cancer clinical protocols and is able to furnish morphological, metabolic and functional information. The imaging of molecular interactions of biological processes in vivo with Positron Emission Tomography (PET) is informative not only for disease detection but also therapeutic response. The qualitat...

  11. [Security specifications for electronic medical records on the Internet].

    Science.gov (United States)

    Mocanu, Mihai; Mocanu, Carmen

    2007-01-01

    The extension for the Web applications of the Electronic Medical Record seems both interesting and promising. Correlated with the expansion of Internet in our country, it allows the interconnection of physicians of different specialties and their collaboration for better treatment of patients. In this respect, the ophthalmologic medical applications consider the increased possibilities for monitoring chronic ocular diseases and for the identification of some elements for early diagnosis and risk factors supervision. We emphasize in this survey some possible solutions to the problems of interconnecting medical information systems to the Internet: the achievement of interoperability within medical organizations through the use of open standards, the automated input and processing for ocular imaging, the use of data reduction techniques in order to increase the speed of image retrieval in large databases, and, last but not least, the resolution of security and confidentiality problems in medical databases.

  12. Elastix : a toolbox for intensity-based medical image registration

    NARCIS (Netherlands)

    Klein, S.; Staring, M.; Murphy, K.; Viergever, M.A.; Pluim, J.P.W.

    2010-01-01

    Medical image registration is an important task in medical image processing. It refers to the process of aligning data sets, possibly from different modalities (e.g., magnetic resonance and computed tomography), different time points (e.g., follow-up scans), and/or different subjects (in case of

  13. Medical physics personnel for medical imaging: requirements, conditions of involvement and staffing levels-French recommendations

    International Nuclear Information System (INIS)

    Isambert, Aurelie; Valero, Marc; Rousse, Carole; Blanchard, Vincent; Le Du, Dominique; Guilhem, Marie-Therese; Dieudonne, Arnaud; Pierrat, Noelle; Salvat, Cecile

    2015-01-01

    The French regulations concerning the involvement of medical physicists in medical imaging procedures are relatively vague. In May 2013, the ASN and the SFPM issued recommendations regarding Medical Physics Personnel for Medical Imaging: Requirements, Conditions of Involvement and Staffing Levels. In these recommendations, the various areas of activity of medical physicists in radiology and nuclear medicine have been identified and described, and the time required to perform each task has been evaluated. Criteria for defining medical physics staffing levels are thus proposed. These criteria are defined according to the technical platform, the procedures and techniques practised on it, the number of patients treated and the number of persons in the medical and paramedical teams requiring periodic training. The result of this work is an aid available to each medical establishment to determine their own needs in terms of medical physics. (authors)

  14. General Ultrasound Imaging

    Medline Plus

    Full Text Available ... radiation oncology provider in your community, you can search the ACR-accredited facilities database . This website does not provide cost information. The costs for specific medical imaging tests, treatments ...

  15. Imaging requirements for medical applications of additive manufacturing.

    Science.gov (United States)

    Huotilainen, Eero; Paloheimo, Markku; Salmi, Mika; Paloheimo, Kaija-Stiina; Björkstrand, Roy; Tuomi, Jukka; Markkola, Antti; Mäkitie, Antti

    2014-02-01

    Additive manufacturing (AM), formerly known as rapid prototyping, is steadily shifting its focus from industrial prototyping to medical applications as AM processes, bioadaptive materials, and medical imaging technologies develop, and the benefits of the techniques gain wider knowledge among clinicians. This article gives an overview of the main requirements for medical imaging affected by needs of AM, as well as provides a brief literature review from existing clinical cases concentrating especially on the kind of radiology they required. As an example application, a pair of CT images of the facial skull base was turned into 3D models in order to illustrate the significance of suitable imaging parameters. Additionally, the model was printed into a preoperative medical model with a popular AM device. Successful clinical cases of AM are recognized to rely heavily on efficient collaboration between various disciplines - notably operating surgeons, radiologists, and engineers. The single main requirement separating tangible model creation from traditional imaging objectives such as diagnostics and preoperative planning is the increased need for anatomical accuracy in all three spatial dimensions, but depending on the application, other specific requirements may be present as well. This article essentially intends to narrow the potential communication gap between radiologists and engineers who work with projects involving AM by showcasing the overlap between the two disciplines.

  16. Segmentation of elongated structures in medical images

    NARCIS (Netherlands)

    Staal, Jozef Johannes

    2004-01-01

    The research described in this thesis concerns the automatic detection, recognition and segmentation of elongated structures in medical images. For this purpose techniques have been developed to detect subdimensional pointsets (e.g. ridges, edges) in images of arbitrary dimension. These

  17. Challenges for data storage in medical imaging research.

    Science.gov (United States)

    Langer, Steve G

    2011-04-01

    Researchers in medical imaging have multiple challenges for storing, indexing, maintaining viability, and sharing their data. Addressing all these concerns requires a constellation of tools, but not all of them need to be local to the site. In particular, the data storage challenges faced by researchers can begin to require professional information technology skills. With limited human resources and funds, the medical imaging researcher may be better served with an outsourcing strategy for some management aspects. This paper outlines an approach to manage the main objectives faced by medical imaging scientists whose work includes processing and data mining on non-standard file formats, and relating those files to the their DICOM standard descendents. The capacity of the approach scales as the researcher's need grows by leveraging the on-demand provisioning ability of cloud computing.

  18. The future of medical imaging

    International Nuclear Information System (INIS)

    Maidment, A. D. A.

    2010-01-01

    The organisers of this conference have kindly provided me with the forum to look forward and examine the future of medical imaging. My view of the future is informed by my own research directions; thus, I illustrate my vision of the future with results from my own research, and from the research that has motivated me over the last few years. As such, the results presented are specific to the field of breast imaging; however, I believe that the trends presented have general applicability, and hope that this discourse will motivate new research. My vision of the future can be summarised in accordance with three broad trends: (1) increased prevalence of low-dose tomographic X-ray imaging; (2) continuing advances in functional and molecular X-ray imaging; and (3) novel image-based bio-marker discovery. (authors)

  19. Medical image reconstruction. A conceptual tutorial

    International Nuclear Information System (INIS)

    Zeng, Gengsheng Lawrence

    2010-01-01

    ''Medical Image Reconstruction: A Conceptual Tutorial'' introduces the classical and modern image reconstruction technologies, such as two-dimensional (2D) parallel-beam and fan-beam imaging, three-dimensional (3D) parallel ray, parallel plane, and cone-beam imaging. This book presents both analytical and iterative methods of these technologies and their applications in X-ray CT (computed tomography), SPECT (single photon emission computed tomography), PET (positron emission tomography), and MRI (magnetic resonance imaging). Contemporary research results in exact region-of-interest (ROI) reconstruction with truncated projections, Katsevich's cone-beam filtered backprojection algorithm, and reconstruction with highly undersampled data with l 0 -minimization are also included. (orig.)

  20. Medical image processing on the GPU - past, present and future.

    Science.gov (United States)

    Eklund, Anders; Dufort, Paul; Forsberg, Daniel; LaConte, Stephen M

    2013-12-01

    Graphics processing units (GPUs) are used today in a wide range of applications, mainly because they can dramatically accelerate parallel computing, are affordable and energy efficient. In the field of medical imaging, GPUs are in some cases crucial for enabling practical use of computationally demanding algorithms. This review presents the past and present work on GPU accelerated medical image processing, and is meant to serve as an overview and introduction to existing GPU implementations. The review covers GPU acceleration of basic image processing operations (filtering, interpolation, histogram estimation and distance transforms), the most commonly used algorithms in medical imaging (image registration, image segmentation and image denoising) and algorithms that are specific to individual modalities (CT, PET, SPECT, MRI, fMRI, DTI, ultrasound, optical imaging and microscopy). The review ends by highlighting some future possibilities and challenges. Copyright © 2013 Elsevier B.V. All rights reserved.

  1. Analysis of the evidence-practice gap to facilitate proper medical care for the elderly: investigation, using databases, of utilization measures for National Database of Health Insurance Claims and Specific Health Checkups of Japan (NDB).

    Science.gov (United States)

    Nakayama, Takeo; Imanaka, Yuichi; Okuno, Yasushi; Kato, Genta; Kuroda, Tomohiro; Goto, Rei; Tanaka, Shiro; Tamura, Hiroshi; Fukuhara, Shunichi; Fukuma, Shingo; Muto, Manabu; Yanagita, Motoko; Yamamoto, Yosuke

    2017-06-06

    As Japan becomes a super-aging society, presentation of the best ways to provide medical care for the elderly, and the direction of that care, are important national issues. Elderly people have multi-morbidity with numerous medical conditions and use many medical resources for complex treatment patterns. This increases the likelihood of inappropriate medical practices and an evidence-practice gap. The present study aimed to: derive findings that are applicable to policy from an elucidation of the actual state of medical care for the elderly; establish a foundation for the utilization of National Database of Health Insurance Claims and Specific Health Checkups of Japan (NDB), and present measures for the utilization of existing databases in parallel with NDB validation.Cross-sectional and retrospective cohort studies were conducted using the NDB built by the Ministry of Health, Labor and Welfare of Japan, private health insurance claims databases, and the Kyoto University Hospital database (including related hospitals). Medical practices (drug prescription, interventional procedures, testing) related to four issues-potential inappropriate medication, cancer therapy, chronic kidney disease treatment, and end-of-life care-will be described. The relationships between these issues and clinical outcomes (death, initiation of dialysis and other adverse events) will be evaluated, if possible.

  2. Statistical physics of medical ultrasonic images

    International Nuclear Information System (INIS)

    Wagner, R.F.; Insana, M.F.; Brown, D.G.; Smith, S.W.

    1987-01-01

    The physical and statistical properties of backscattered signals in medical ultrasonic imaging are reviewed in terms of: 1) the radiofrequency signal; 2) the envelope (video or magnitude) signal; and 3) the density of samples in simple and in compounded images. There is a wealth of physical information in backscattered signals in medical ultrasound. This information is contained in the radiofrequency spectrum - which is not typically displayed to the viewer - as well as in the higher statistical moments of the envelope or video signal - which are not readily accessed by the human viewer of typical B-scans. This information may be extracted from the detected backscattered signals by straightforward signal processing techniques at low resolution

  3. Bayesian image restoration for medical images using radon transform

    International Nuclear Information System (INIS)

    Shouno, Hayaru; Okada, Masato

    2010-01-01

    We propose an image reconstruction algorithm using Bayesian inference for Radon transformed observation data, which often appears in the field of medical image reconstruction known as computed tomography (CT). In order to apply our Bayesian reconstruction method, we introduced several hyper-parameters that control the ratio between prior information and the fidelity of the observation process. Since the quality of the reconstructed image is influenced by the estimation accuracy of these hyper-parameters, we propose an inference method for them based on the marginal likelihood maximization principle as well as the image reconstruction method. We are able to demonstrate a reconstruction result superior to that obtained using the conventional filtered back projection method. (author)

  4. Medical Imaging Informatics: Towards a Personalized Computational Patient.

    Science.gov (United States)

    Ayache, N

    2016-05-20

    Medical Imaging Informatics has become a fast evolving discipline at the crossing of Informatics, Computational Sciences, and Medicine that is profoundly changing medical practices, for the patients' benefit.

  5. Mesh Processing in Medical-Image Analysis-a Tutorial

    DEFF Research Database (Denmark)

    Levine, Joshua A.; Paulsen, Rasmus Reinhold; Zhang, Yongjie

    2012-01-01

    Medical-image analysis requires an understanding of sophisticated scanning modalities, constructing geometric models, building meshes to represent domains, and downstream biological applications. These four steps form an image-to-mesh pipeline. For research in this field to progress, the imaging...

  6. [Current situations and problems of quality control for medical imaging display systems].

    Science.gov (United States)

    Shibutani, Takayuki; Setojima, Tsuyoshi; Ueda, Katsumi; Takada, Katsumi; Okuno, Teiichi; Onoguchi, Masahisa; Nakajima, Tadashi; Fujisawa, Ichiro

    2015-04-01

    Diagnostic imaging has been shifted rapidly from film to monitor diagnostic. Consequently, Japan medical imaging and radiological systems industries association (JIRA) have recommended methods of quality control (QC) for medical imaging display systems. However, in spite of its need by majority of people, executing rate is low. The purpose of this study was to validate the problem including check items about QC for medical imaging display systems. We performed acceptance test of medical imaging display monitors based on Japanese engineering standards of radiological apparatus (JESRA) X-0093*A-2005 to 2009, and performed constancy test based on JESRA X-0093*A-2010 from 2010 to 2012. Furthermore, we investigated the cause of trouble and repaired number. Medical imaging display monitors had 23 inappropriate monitors about visual estimation, and all these monitors were not criteria of JESRA about luminance uniformity. Max luminance was significantly lower year-by-year about measurement estimation, and the 29 monitors did not meet the criteria of JESRA about luminance deviation. Repaired number of medical imaging display monitors had 25, and the cause was failure liquid crystal panel. We suggested the problems about medical imaging display systems.

  7. Medical images fusion for application in treatment planning systems in radiotherapy

    International Nuclear Information System (INIS)

    Ros, Renato Assenci

    2006-01-01

    Software for medical images fusion was developed for utilization in CAT3D radiotherapy and MNPS radiosurgery treatment planning systems. A mutual information maximization methodology was used to make the image registration of different modalities by measure of the statistical dependence between the voxels pairs. The alignment by references points makes an initial approximation to the non linear optimization process by downhill simplex method for estimation of the joint histogram. The coordinates transformation function use a trilinear interpolation and search for the global maximum value in a 6 dimensional space, with 3 degree of freedom for translation and 3 degree of freedom for rotation, by making use of the rigid body model. This method was evaluated with CT, MR and PET images from Vanderbilt University database to verify its accuracy by comparison of transformation coordinates of each images fusion with gold-standard values. The median of images alignment error values was 1.6 mm for CT-MR fusion and 3.5 mm for PET-MR fusion, with gold-standard accuracy estimated as 0.4 mm for CT-MR fusion and 1.7 mm for PET-MR fusion. The maximum error values were 5.3 mm for CT-MR fusion and 7.4 mm for PET-MR fusion, and 99.1% of alignment errors were images subvoxels values. The mean computing time was 24 s. The software was successfully finished and implemented in 59 radiotherapy routine services, of which 42 are in Brazil and 17 are in Latin America. This method does not have limitation about different resolutions from images, pixels sizes and slice thickness. Besides, the alignment may be accomplished by axial, coronal or sagittal images. (author)

  8. Superconductors and medical imaging

    International Nuclear Information System (INIS)

    Aubert, Guy

    2011-01-01

    After difficult beginnings in the 1970's, magnetic resonance imaging (MRI) has evolved to become nowadays the jewel in the crown of medical technology. Superconductors have been a key factor for the extraordinary expansion of MRI which in turn represents about 75 % of their total market. After recalling some basic principles, this article traces their common history and refers to future developments. (author)

  9. Compression-Based Tools for Navigation with an Image Database

    Directory of Open Access Journals (Sweden)

    Giovanni Motta

    2012-01-01

    Full Text Available We present tools that can be used within a larger system referred to as a passive assistant. The system receives information from a mobile device, as well as information from an image database such as Google Street View, and employs image processing to provide useful information about a local urban environment to a user who is visually impaired. The first stage acquires and computes accurate location information, the second stage performs texture and color analysis of a scene, and the third stage provides specific object recognition and navigation information. These second and third stages rely on compression-based tools (dimensionality reduction, vector quantization, and coding that are enhanced by knowledge of (approximate location of objects.

  10. User Oriented Platform for Data Analytics in Medical Imaging Repositories.

    Science.gov (United States)

    Valerio, Miguel; Godinho, Tiago Marques; Costa, Carlos

    2016-01-01

    The production of medical imaging studies and associated data has been growing in the last decades. Their primary use is to support medical diagnosis and treatment processes. However, the secondary use of the tremendous amount of stored data is generally more limited. Nowadays, medical imaging repositories have turned into rich databanks holding not only the images themselves, but also a wide range of metadata related to the medical practice. Exploring these repositories through data analysis and business intelligence techniques has the potential of increasing the efficiency and quality of the medical practice. Nevertheless, the continuous production of tremendous amounts of data makes their analysis difficult by conventional approaches. This article proposes a novel automated methodology to derive knowledge from medical imaging repositories that does not disrupt the regular medical practice. Our method is able to apply statistical analysis and business intelligence techniques directly on top of live institutional repositories. It is a Web-based solution that provides extensive dashboard capabilities, including complete charting and reporting options, combined with data mining components. Moreover, it enables the operator to set a wide multitude of query parameters and operators through the use of an intuitive graphical interface.

  11. The UBIRIS.v2: a database of visible wavelength iris images captured on-the-move and at-a-distance.

    Science.gov (United States)

    Proença, Hugo; Filipe, Sílvio; Santos, Ricardo; Oliveira, João; Alexandre, Luís A

    2010-08-01

    The iris is regarded as one of the most useful traits for biometric recognition and the dissemination of nationwide iris-based recognition systems is imminent. However, currently deployed systems rely on heavy imaging constraints to capture near infrared images with enough quality. Also, all of the publicly available iris image databases contain data correspondent to such imaging constraints and therefore are exclusively suitable to evaluate methods thought to operate on these type of environments. The main purpose of this paper is to announce the availability of the UBIRIS.v2 database, a multisession iris images database which singularly contains data captured in the visible wavelength, at-a-distance (between four and eight meters) and on on-the-move. This database is freely available for researchers concerned about visible wavelength iris recognition and will be useful in accessing the feasibility and specifying the constraints of this type of biometric recognition.

  12. Assessment of COPD-related outcomes via a national electronic medical record database.

    Science.gov (United States)

    Asche, Carl; Said, Quayyim; Joish, Vijay; Hall, Charles Oaxaca; Brixner, Diana

    2008-01-01

    The technology and sophistication of healthcare utilization databases have expanded over the last decade to include results of lab tests, vital signs, and other clinical information. This review provides an assessment of the methodological and analytical challenges of conducting chronic obstructive pulmonary disease (COPD) outcomes research in a national electronic medical records (EMR) dataset and its potential application towards the assessment of national health policy issues, as well as a description of the challenges or limitations. An EMR database and its application to measuring outcomes for COPD are described. The ability to measure adherence to the COPD evidence-based practice guidelines, generated by the NIH and HEDIS quality indicators, in this database was examined. Case studies, before and after their publication, were used to assess the adherence to guidelines and gauge the conformity to quality indicators. EMR was the only source of information for pulmonary function tests, but low frequency in ordering by primary care was an issue. The EMR data can be used to explore impact of variation in healthcare provision on clinical outcomes. The EMR database permits access to specific lab data and biometric information. The richness and depth of information on "real world" use of health services for large population-based analytical studies at relatively low cost render such databases an attractive resource for outcomes research. Various sources of information exist to perform outcomes research. It is important to understand the desired endpoints of such research and choose the appropriate database source.

  13. Carotid Ultrasound Imaging

    Science.gov (United States)

    ... prior to the exam. Bringing books, small toys, music or games can help to distract the child ... accredited facilities database . This website does not provide cost information. The costs for specific medical imaging tests, ...

  14. Diagnostic Medical Imaging in Pediatric Patients and Subsequent Cancer Risk.

    Science.gov (United States)

    Mulvihill, David J; Jhawar, Sachin; Kostis, John B; Goyal, Sharad

    2017-11-01

    The use of diagnostic medical imaging is becoming increasingly more commonplace in the pediatric setting. However, many medical imaging modalities expose pediatric patients to ionizing radiation, which has been shown to increase the risk of cancer development in later life. This review article provides a comprehensive overview of the available data regarding the risk of cancer development following exposure to ionizing radiation from diagnostic medical imaging. Attention is paid to modalities such as computed tomography scans and fluoroscopic procedures that can expose children to radiation doses orders of magnitude higher than standard diagnostic x-rays. Ongoing studies that seek to more precisely determine the relationship of diagnostic medical radiation in children and subsequent cancer development are discussed, as well as modern strategies to better quantify this risk. Finally, as cardiovascular imaging and intervention contribute substantially to medical radiation exposure, we discuss strategies to enhance radiation safety in these areas. Copyright © 2017 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

  15. Multispectral system for medical fluorescence imaging

    International Nuclear Information System (INIS)

    Andersson, P.S.; Montan, S.; Svanberg, S.

    1987-01-01

    The principles of a powerful multicolor imaging system for tissue fluorescence diagnostics are discussed. Four individually spectrally filtered images are formed on a matrix detector by means of a split-mirror arrangement. The four images are processed in a computer, pixel by pixel, by means of mathematical operations, leading to an optimized contrast image, which enhances a selected feature. The system is being developed primarily for medical fluorescence imaging, but has wide applications in fluorescence, reflectance, and transmission monitoring related to a wide range of industrial and environmental problems. The system operation is described for the case of linear imaging on a diode array detector. Laser-induced fluorescence is used for cancer tumor and arteriosclerotic plaque demarcation using the contrast enhancement capabilities of this imaging system. Further examples of applications include fluorescing minerals and flames

  16. Medical image computing for computer-supported diagnostics and therapy. Advances and perspectives.

    Science.gov (United States)

    Handels, H; Ehrhardt, J

    2009-01-01

    Medical image computing has become one of the most challenging fields in medical informatics. In image-based diagnostics of the future software assistance will become more and more important, and image analysis systems integrating advanced image computing methods are needed to extract quantitative image parameters to characterize the state and changes of image structures of interest (e.g. tumors, organs, vessels, bones etc.) in a reproducible and objective way. Furthermore, in the field of software-assisted and navigated surgery medical image computing methods play a key role and have opened up new perspectives for patient treatment. However, further developments are needed to increase the grade of automation, accuracy, reproducibility and robustness. Moreover, the systems developed have to be integrated into the clinical workflow. For the development of advanced image computing systems methods of different scientific fields have to be adapted and used in combination. The principal methodologies in medical image computing are the following: image segmentation, image registration, image analysis for quantification and computer assisted image interpretation, modeling and simulation as well as visualization and virtual reality. Especially, model-based image computing techniques open up new perspectives for prediction of organ changes and risk analysis of patients and will gain importance in diagnostic and therapy of the future. From a methodical point of view the authors identify the following future trends and perspectives in medical image computing: development of optimized application-specific systems and integration into the clinical workflow, enhanced computational models for image analysis and virtual reality training systems, integration of different image computing methods, further integration of multimodal image data and biosignals and advanced methods for 4D medical image computing. The development of image analysis systems for diagnostic support or

  17. [Research progress of multi-model medical image fusion and recognition].

    Science.gov (United States)

    Zhou, Tao; Lu, Huiling; Chen, Zhiqiang; Ma, Jingxian

    2013-10-01

    Medical image fusion and recognition has a wide range of applications, such as focal location, cancer staging and treatment effect assessment. Multi-model medical image fusion and recognition are analyzed and summarized in this paper. Firstly, the question of multi-model medical image fusion and recognition is discussed, and its advantage and key steps are discussed. Secondly, three fusion strategies are reviewed from the point of algorithm, and four fusion recognition structures are discussed. Thirdly, difficulties, challenges and possible future research direction are discussed.

  18. Synchrotrons and their applications in medical imaging and therapy

    International Nuclear Information System (INIS)

    Lewis, R.

    2004-01-01

    Full text: Australasia's first synchrotron is being built on the campus of Monash University near Melbourne. Is it of any relevance to the medical imaging and radiation therapy communities? The answer is an unequivocal yes. Synchrotrons overcome many of the problems with conventional X-ray sources and as a result make it possible to demonstrate extraordinary advances in both X-ray imaging and indeed in radio-therapy. Synchrotron imaging offers us a window into what is possible and the results are spectacular. Specific examples include lung images that reveal alveolar structure and computed tomography of single cells. For therapy treatments are being pioneered that seem to be effective on high grade gliomas. An overview of the status of medical applications using synchrotrons will be given and the proposed Australian medical imaging and therapy facilities will be described and some of the proposed research highlighted. Copyright (2004) Australasian College of Physical Scientists and Engineers in Medicine

  19. 76 FR 45402 - Advisory Committee; Medical Imaging Drugs Advisory Committee; Re-Establishment

    Science.gov (United States)

    2011-07-29

    .... FDA-2010-N-0002] Advisory Committee; Medical Imaging Drugs Advisory Committee; Re- Establishment... (FDA) is announcing the re- establishment of the Medical Imaging Drugs Advisory Committee in FDA's Center for Drug Evaluation and Research. This rule amends the current language for the Medical Imaging...

  20. High-performance method of morphological medical image processing

    Directory of Open Access Journals (Sweden)

    Ryabykh M. S.

    2016-07-01

    Full Text Available the article shows the implementation of grayscale morphology vHGW algorithm for selection borders in the medical image. Image processing is executed using OpenMP and NVIDIA CUDA technology for images with different resolution and different size of the structuring element.

  1. Digital fluoroscopy: a new development in medical imaging

    International Nuclear Information System (INIS)

    Maher, K.P.; Malone, J.F.; Dublin Inst. of Technology

    1986-01-01

    Medical fluoroscopy is briefly reviewed and video-image digitization is described. Image processing requirements and image processors available for digital fluoroscopy are discussed in detail. Specific reference is made to an application of digital fluoroscopy in the imaging of blood-vessels. This application involves an image substraction technique which is referred to as digital subtraction angiography (DSA). A number of DSA images of relevance to the discussion are included. (author)

  2. Database Description - JSNP | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available base Description General information of database Database name JSNP Alternative nam...n Science and Technology Agency Creator Affiliation: Contact address E-mail : Database...sapiens Taxonomy ID: 9606 Database description A database of about 197,000 polymorphisms in Japanese populat...1):605-610 External Links: Original website information Database maintenance site Institute of Medical Scien...er registration Not available About This Database Database Description Download License Update History of This Database

  3. Medical physics personnel for medical imaging: requirements, conditions of involvement and staffing levels-French recommendations.

    Science.gov (United States)

    Isambert, Aurélie; Le Du, Dominique; Valéro, Marc; Guilhem, Marie-Thérèse; Rousse, Carole; Dieudonné, Arnaud; Blanchard, Vincent; Pierrat, Noëlle; Salvat, Cécile

    2015-04-01

    The French regulations concerning the involvement of medical physicists in medical imaging procedures are relatively vague. In May 2013, the ASN and the SFPM issued recommendations regarding Medical Physics Personnel for Medical Imaging: Requirements, Conditions of Involvement and Staffing Levels. In these recommendations, the various areas of activity of medical physicists in radiology and nuclear medicine have been identified and described, and the time required to perform each task has been evaluated. Criteria for defining medical physics staffing levels are thus proposed. These criteria are defined according to the technical platform, the procedures and techniques practised on it, the number of patients treated and the number of persons in the medical and paramedical teams requiring periodic training. The result of this work is an aid available to each medical establishment to determine their own needs in terms of medical physics. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  4. A new method for the automatic retrieval of medical cases based on the RadLex ontology.

    Science.gov (United States)

    Spanier, A B; Cohen, D; Joskowicz, L

    2017-03-01

    The goal of medical case-based image retrieval (M-CBIR) is to assist radiologists in the clinical decision-making process by finding medical cases in large archives that most resemble a given case. Cases are described by radiology reports comprised of radiological images and textual information on the anatomy and pathology findings. The textual information, when available in standardized terminology, e.g., the RadLex ontology, and used in conjunction with the radiological images, provides a substantial advantage for M-CBIR systems. We present a new method for incorporating textual radiological findings from medical case reports in M-CBIR. The input is a database of medical cases, a query case, and the number of desired relevant cases. The output is an ordered list of the most relevant cases in the database. The method is based on a new case formulation, the Augmented RadLex Graph and an Anatomy-Pathology List. It uses a new case relatedness metric [Formula: see text] that prioritizes more specific medical terms in the RadLex tree over less specific ones and that incorporates the length of the query case. An experimental study on 8 CT queries from the 2015 VISCERAL 3D Case Retrieval Challenge database consisting of 1497 volumetric CT scans shows that our method has accuracy rates of 82 and 70% on the first 10 and 30 most relevant cases, respectively, thereby outperforming six other methods. The increasing amount of medical imaging data acquired in clinical practice constitutes a vast database of untapped diagnostically relevant information. This paper presents a new hybrid approach to retrieving the most relevant medical cases based on textual and image information.

  5. Medical image security using modified chaos-based cryptography approach

    Science.gov (United States)

    Talib Gatta, Methaq; Al-latief, Shahad Thamear Abd

    2018-05-01

    The progressive development in telecommunication and networking technologies have led to the increased popularity of telemedicine usage which involve storage and transfer of medical images and related information so security concern is emerged. This paper presents a method to provide the security to the medical images since its play a major role in people healthcare organizations. The main idea in this work based on the chaotic sequence in order to provide efficient encryption method that allows reconstructing the original image from the encrypted image with high quality and minimum distortion in its content and doesn’t effect in human treatment and diagnosing. Experimental results prove the efficiency of the proposed method using some of statistical measures and robust correlation between original image and decrypted image.

  6. Spatio-Temporal Encoding in Medical Ultrasound Imaging

    DEFF Research Database (Denmark)

    Gran, Fredrik

    2005-01-01

    In this dissertation two methods for spatio-temporal encoding in medical ultrasound imaging are investigated. The first technique is based on a frequency division approach. Here, the available spectrum of the transducer is divided into a set of narrow bands. A waveform is designed for each band...... the signal to noise ratio and simultaneously the penetration depth so that the medical doctor can image deeper lying structures. The method is tested both experimentally and in simulation and has also evaluated for the purpose of blood flow estimation. The work presented is based on four papers which...

  7. Population Pharmacokinetics of Tracers: A New Tool for Medical Imaging?

    Science.gov (United States)

    Gandia, Peggy; Jaudet, Cyril; Chatelut, Etienne; Concordet, Didier

    2017-02-01

    Positron emission tomography-computed tomography is a medical imaging method measuring the activity of a radiotracer chosen to accumulate in cancer cells. A recent trend of medical imaging analysis is to account for the radiotracer's pharmacokinetic properties at a voxel (three-dimensional-pixel) level to separate the different tissues. These analyses are closely linked to population pharmacokinetic-pharmacodynamic modelling. Kineticists possess the cultural background to improve medical imaging analysis. This article stresses the common points with population pharmacokinetics and highlights the methodological locks that need to be lifted.

  8. Design and Implementation of CNEOST Image Database Based on NoSQL System

    Science.gov (United States)

    Wang, Xin

    2014-04-01

    The China Near Earth Object Survey Telescope is the largest Schmidt telescope in China, and it has acquired more than 3 TB astronomical image data since it saw the first light in 2006. After the upgrade of the CCD camera in 2013, over 10 TB data will be obtained every year. The management of the massive images is not only an indispensable part of data processing pipeline but also the basis of data sharing. Based on the analysis of requirement, an image management system is designed and implemented by employing the non-relational database.

  9. PCANet-Based Structural Representation for Nonrigid Multimodal Medical Image Registration

    Directory of Open Access Journals (Sweden)

    Xingxing Zhu

    2018-05-01

    Full Text Available Nonrigid multimodal image registration remains a challenging task in medical image processing and analysis. The structural representation (SR-based registration methods have attracted much attention recently. However, the existing SR methods cannot provide satisfactory registration accuracy due to the utilization of hand-designed features for structural representation. To address this problem, the structural representation method based on the improved version of the simple deep learning network named PCANet is proposed for medical image registration. In the proposed method, PCANet is firstly trained on numerous medical images to learn convolution kernels for this network. Then, a pair of input medical images to be registered is processed by the learned PCANet. The features extracted by various layers in the PCANet are fused to produce multilevel features. The structural representation images are constructed for two input images based on nonlinear transformation of these multilevel features. The Euclidean distance between structural representation images is calculated and used as the similarity metrics. The objective function defined by the similarity metrics is optimized by L-BFGS method to obtain parameters of the free-form deformation (FFD model. Extensive experiments on simulated and real multimodal image datasets show that compared with the state-of-the-art registration methods, such as modality-independent neighborhood descriptor (MIND, normalized mutual information (NMI, Weber local descriptor (WLD, and the sum of squared differences on entropy images (ESSD, the proposed method provides better registration performance in terms of target registration error (TRE and subjective human vision.

  10. Integration of Medical Imaging Including Ultrasound into a New Clinical Anatomy Curriculum

    Science.gov (United States)

    Moscova, Michelle; Bryce, Deborah A.; Sindhusake, Doungkamol; Young, Noel

    2015-01-01

    In 2008 a new clinical anatomy curriculum with integrated medical imaging component was introduced into the University of Sydney Medical Program. Medical imaging used for teaching the new curriculum included normal radiography, MRI, CT scans, and ultrasound imaging. These techniques were incorporated into teaching over the first two years of the…

  11. Quantification of heterogeneity observed in medical images

    OpenAIRE

    Brooks, Frank J; Grigsby, Perry W

    2013-01-01

    Background There has been much recent interest in the quantification of visually evident heterogeneity within functional grayscale medical images, such as those obtained via magnetic resonance or positron emission tomography. In the case of images of cancerous tumors, variations in grayscale intensity imply variations in crucial tumor biology. Despite these considerable clinical implications, there is as yet no standardized method for measuring the heterogeneity observed via these imaging mod...

  12. An approach for access differentiation design in medical distributed applications built on databases.

    Science.gov (United States)

    Shoukourian, S K; Vasilyan, A M; Avagyan, A A; Shukurian, A K

    1999-01-01

    A formalized "top to bottom" design approach was described in [1] for distributed applications built on databases, which were considered as a medium between virtual and real user environments for a specific medical application. Merging different components within a unified distributed application posits new essential problems for software. Particularly protection tools, which are sufficient separately, become deficient during the integration due to specific additional links and relationships not considered formerly. E.g., it is impossible to protect a shared object in the virtual operating room using only DBMS protection tools, if the object is stored as a record in DB tables. The solution of the problem should be found only within the more general application framework. Appropriate tools are absent or unavailable. The present paper suggests a detailed outline of a design and testing toolset for access differentiation systems (ADS) in distributed medical applications which use databases. The appropriate formal model as well as tools for its mapping to a DMBS are suggested. Remote users connected via global networks are considered too.

  13. The Center for Integrated Molecular Brain Imaging (Cimbi) database

    DEFF Research Database (Denmark)

    Knudsen, Gitte M.; Jensen, Peter S.; Erritzoe, David

    2016-01-01

    We here describe a multimodality neuroimaging containing data from healthy volunteers and patients, acquired within the Lundbeck Foundation Center for Integrated Molecular Brain Imaging (Cimbi) in Copenhagen, Denmark. The data is of particular relevance for neurobiological research questions rela...... currently contains blood and in some instances saliva samples from about 500 healthy volunteers and 300 patients with e.g., major depression, dementia, substance abuse, obesity, and impulsive aggression. Data continue to be added to the Cimbi database and biobank....

  14. Anomaly detection for medical images based on a one-class classification

    Science.gov (United States)

    Wei, Qi; Ren, Yinhao; Hou, Rui; Shi, Bibo; Lo, Joseph Y.; Carin, Lawrence

    2018-02-01

    Detecting an anomaly such as a malignant tumor or a nodule from medical images including mammogram, CT or PET images is still an ongoing research problem drawing a lot of attention with applications in medical diagnosis. A conventional way to address this is to learn a discriminative model using training datasets of negative and positive samples. The learned model can be used to classify a testing sample into a positive or negative class. However, in medical applications, the high unbalance between negative and positive samples poses a difficulty for learning algorithms, as they will be biased towards the majority group, i.e., the negative one. To address this imbalanced data issue as well as leverage the huge amount of negative samples, i.e., normal medical images, we propose to learn an unsupervised model to characterize the negative class. To make the learned model more flexible and extendable for medical images of different scales, we have designed an autoencoder based on a deep neural network to characterize the negative patches decomposed from large medical images. A testing image is decomposed into patches and then fed into the learned autoencoder to reconstruct these patches themselves. The reconstruction error of one patch is used to classify this patch into a binary class, i.e., a positive or a negative one, leading to a one-class classifier. The positive patches highlight the suspicious areas containing anomalies in a large medical image. The proposed method has been tested on InBreast dataset and achieves an AUC of 0.84. The main contribution of our work can be summarized as follows. 1) The proposed one-class learning requires only data from one class, i.e., the negative data; 2) The patch-based learning makes the proposed method scalable to images of different sizes and helps avoid the large scale problem for medical images; 3) The training of the proposed deep convolutional neural network (DCNN) based auto-encoder is fast and stable.

  15. Medical applications: a database and characterization of apps in Apple iOS and Android platforms.

    Science.gov (United States)

    Seabrook, Heather J; Stromer, Julie N; Shevkenek, Cole; Bharwani, Aleem; de Grood, Jill; Ghali, William A

    2014-08-27

    Medical applications (apps) for smart phones and tablet computers are growing in number and are commonly used in healthcare. In this context, there is a need for a diverse community of app users, medical researchers, and app developers to better understand the app landscape. In mid-2012, we undertook an environmental scan and classification of the medical app landscape in the two dominant platforms by searching the medical category of the Apple iTunes and Google Play app download sites. We identified target audiences, functions, costs and content themes using app descriptions and captured these data in a database. We only included apps released or updated between October 1, 2011 and May 31, 2012, with a primary "medical" app store categorization, in English, that contained health or medical content. Our sample of Android apps was limited to the most popular apps in the medical category. Our final sample of Apple iOS (n = 4561) and Android (n = 293) apps illustrate a diverse medical app landscape. The proportion of Apple iOS apps for the public (35%) and for physicians (36%) is similar. Few Apple iOS apps specifically target nurses (3%). Within the Android apps, those targeting the public dominated in our sample (51%). The distribution of app functions is similar in both platforms with reference being the most common function. Most app functions and content themes vary considerably by target audience. Social media apps are more common for patients and the public, while conference apps target physicians. We characterized existing medical apps and illustrated their diversity in terms of target audience, main functions, cost and healthcare topic. The resulting app database is a resource for app users, app developers and health informatics researchers.

  16. A Novel Medical Image Watermarking in Three-dimensional Fourier Compressed Domain

    Directory of Open Access Journals (Sweden)

    Baoru Han

    2015-09-01

    Full Text Available Digital watermarking is a research hotspot in the field of image security, which is protected digital image copyright. In order to ensure medical image information security, a novel medical image digital watermarking algorithm in three-dimensional Fourier compressed domain is proposed. The novel medical image digital watermarking algorithm takes advantage of three-dimensional Fourier compressed domain characteristics, Legendre chaotic neural network encryption features and robust characteristics of differences hashing, which is a robust zero-watermarking algorithm. On one hand, the original watermarking image is encrypted in order to enhance security. It makes use of Legendre chaotic neural network implementation. On the other hand, the construction of zero-watermarking adopts differences hashing in three-dimensional Fourier compressed domain. The novel watermarking algorithm does not need to select a region of interest, can solve the problem of medical image content affected. The specific implementation of the algorithm and the experimental results are given in the paper. The simulation results testify that the novel algorithm possesses a desirable robustness to common attack and geometric attack.

  17. From spoken narratives to domain knowledge: mining linguistic data for medical image understanding.

    Science.gov (United States)

    Guo, Xuan; Yu, Qi; Alm, Cecilia Ovesdotter; Calvelli, Cara; Pelz, Jeff B; Shi, Pengcheng; Haake, Anne R

    2014-10-01

    Extracting useful visual clues from medical images allowing accurate diagnoses requires physicians' domain knowledge acquired through years of systematic study and clinical training. This is especially true in the dermatology domain, a medical specialty that requires physicians to have image inspection experience. Automating or at least aiding such efforts requires understanding physicians' reasoning processes and their use of domain knowledge. Mining physicians' references to medical concepts in narratives during image-based diagnosis of a disease is an interesting research topic that can help reveal experts' reasoning processes. It can also be a useful resource to assist with design of information technologies for image use and for image case-based medical education systems. We collected data for analyzing physicians' diagnostic reasoning processes by conducting an experiment that recorded their spoken descriptions during inspection of dermatology images. In this paper we focus on the benefit of physicians' spoken descriptions and provide a general workflow for mining medical domain knowledge based on linguistic data from these narratives. The challenge of a medical image case can influence the accuracy of the diagnosis as well as how physicians pursue the diagnostic process. Accordingly, we define two lexical metrics for physicians' narratives--lexical consensus score and top N relatedness score--and evaluate their usefulness by assessing the diagnostic challenge levels of corresponding medical images. We also report on clustering medical images based on anchor concepts obtained from physicians' medical term usage. These analyses are based on physicians' spoken narratives that have been preprocessed by incorporating the Unified Medical Language System for detecting medical concepts. The image rankings based on lexical consensus score and on top 1 relatedness score are well correlated with those based on challenge levels (Spearman correlation>0.5 and Kendall

  18. Intrasubject registration for change analysis in medical imaging

    NARCIS (Netherlands)

    Staring, M.

    2008-01-01

    Image matching is important for the comparison of medical images. Comparison is of clinical relevance for the analysis of differences due to changes in the health of a patient. For example, when a disease is imaged at two time points, then one wants to know if it is stable, has regressed, or

  19. An evaluation on CT image acquisition method for medical VR applications

    Science.gov (United States)

    Jang, Seong-wook; Ko, Junho; Yoo, Yon-sik; Kim, Yoonsang

    2017-02-01

    Recent medical virtual reality (VR) applications to minimize re-operations are being studied for improvements in surgical efficiency and reduction of operation error. The CT image acquisition method considering three-dimensional (3D) modeling for medical VR applications is important, because the realistic model is required for the actual human organ. However, the research for medical VR applications has focused on 3D modeling techniques and utilized 3D models. In addition, research on a CT image acquisition method considering 3D modeling has never been reported. The conventional CT image acquisition method involves scanning a limited area of the lesion for the diagnosis of doctors once or twice. However, the medical VR application is required to acquire the CT image considering patients' various postures and a wider area than the lesion. A wider area than the lesion is required because of the necessary process of comparing bilateral sides for dyskinesia diagnosis of the shoulder, pelvis, and leg. Moreover, patients' various postures are required due to the different effects on the musculoskeletal system. Therefore, in this paper, we perform a comparative experiment on the acquired CT images considering image area (unilateral/bilateral) and patients' postures (neutral/abducted). CT images are acquired from 10 patients for the experiments, and the acquired CT images are evaluated based on the length per pixel and the morphological deviation. Finally, by comparing the experiment results, we evaluate the CT image acquisition method for medical VR applications.

  20. A similarity-based data warehousing environment for medical images.

    Science.gov (United States)

    Teixeira, Jefferson William; Annibal, Luana Peixoto; Felipe, Joaquim Cezar; Ciferri, Ricardo Rodrigues; Ciferri, Cristina Dutra de Aguiar

    2015-11-01

    A core issue of the decision-making process in the medical field is to support the execution of analytical (OLAP) similarity queries over images in data warehousing environments. In this paper, we focus on this issue. We propose imageDWE, a non-conventional data warehousing environment that enables the storage of intrinsic features taken from medical images in a data warehouse and supports OLAP similarity queries over them. To comply with this goal, we introduce the concept of perceptual layer, which is an abstraction used to represent an image dataset according to a given feature descriptor in order to enable similarity search. Based on this concept, we propose the imageDW, an extended data warehouse with dimension tables specifically designed to support one or more perceptual layers. We also detail how to build an imageDW and how to load image data into it. Furthermore, we show how to process OLAP similarity queries composed of a conventional predicate and a similarity search predicate that encompasses the specification of one or more perceptual layers. Moreover, we introduce an index technique to improve the OLAP query processing over images. We carried out performance tests over a data warehouse environment that consolidated medical images from exams of several modalities. The results demonstrated the feasibility and efficiency of our proposed imageDWE to manage images and to process OLAP similarity queries. The results also demonstrated that the use of the proposed index technique guaranteed a great improvement in query processing. Copyright © 2015 Elsevier Ltd. All rights reserved.

  1. Shaping the future through innovations: From medical imaging to precision medicine.

    Science.gov (United States)

    Comaniciu, Dorin; Engel, Klaus; Georgescu, Bogdan; Mansi, Tommaso

    2016-10-01

    Medical images constitute a source of information essential for disease diagnosis, treatment and follow-up. In addition, due to its patient-specific nature, imaging information represents a critical component required for advancing precision medicine into clinical practice. This manuscript describes recently developed technologies for better handling of image information: photorealistic visualization of medical images with Cinematic Rendering, artificial agents for in-depth image understanding, support for minimally invasive procedures, and patient-specific computational models with enhanced predictive power. Throughout the manuscript we will analyze the capabilities of such technologies and extrapolate on their potential impact to advance the quality of medical care, while reducing its cost. Copyright © 2016 Elsevier B.V. All rights reserved.

  2. Unsupervised segmentation of medical image based on difference of mutual information

    Institute of Scientific and Technical Information of China (English)

    L(U) Qingwen; CHEN Wufan

    2006-01-01

    In the scope of medical image processing, segmentation is important and difficult. There are still two problems which trouble us in this field. One is how to determine the number of clusters in an image and the other is how to segment medical images containing lesions. A new segmentation method called DDC, based on difference of mutual information (dMI) and pixon, is proposed in this paper. Experiments demonstrate that dMI shows one kind of intrinsic relationship between the segmented image and the original one and so it can be used to well determine the number of clusters. Furthermore, multi-modality medical images with lesions can be automatically and successfully segmented by DDC method.

  3. Trends in the Use of Medical Imaging to Diagnose Appendicitis at an Academic Medical Center.

    Science.gov (United States)

    Repplinger, Michael D; Weber, Andrew C; Pickhardt, Perry J; Rajamanickam, Victoria P; Svenson, James E; Ehlenbach, William J; Westergaard, Ryan P; Reeder, Scott B; Jacobs, Elizabeth A

    2016-09-01

    To quantify the trends in imaging use for the diagnosis of appendicitis. A retrospective study covering a 22-year period was conducted at an academic medical center. Patients were identified by International Classification of Diseases-9 diagnosis code for appendicitis. Medical record data extraction of these patients included imaging test used (ultrasound, CT, or MRI), gender, age, and body mass index (BMI). The proportion of patients undergoing each scan was calculated by year. Regression analysis was performed to determine whether age, gender, or BMI affected imaging choice. The study included a total of 2,108 patients, including 967 (43.5%) females and 599 (27%) children (imaging used for the diagnosis of appendicitis decreased over time (P medical center, CT use increased more than 20-fold. However, no statistically significant trend was found for increased use of ultrasound or MRI. Copyright © 2016 American College of Radiology. Published by Elsevier Inc. All rights reserved.

  4. Medical image computing and computer-assisted intervention - MICCAI 2005. Proceedings; Pt. 1

    International Nuclear Information System (INIS)

    Duncan, J.S.; Gerig, G.

    2005-01-01

    The two-volume set LNCS 3749 and LNCS 3750 constitutes the refereed proceedings of the 8th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2005, held in Palm Springs, CA, USA, in October 2005. Based on rigorous peer reviews the program committee selected 237 carefully revised full papers from 632 submissions for presentation in two volumes. The first volume includes all the contributions related to image analysis and validation, vascular image segmentation, image registration, diffusion tensor image analysis, image segmentation and analysis, clinical applications - validation, imaging systems - visualization, computer assisted diagnosis, cellular and molecular image analysis, physically-based modeling, robotics and intervention, medical image computing for clinical applications, and biological imaging - simulation and modeling. The second volume collects the papers related to robotics, image-guided surgery and interventions, image registration, medical image computing, structural and functional brain analysis, model-based image analysis, image-guided intervention: simulation, modeling and display, and image segmentation and analysis. (orig.)

  5. Medical image computing and computer science intervention. MICCAI 2005. Pt. 2. Proceedings

    International Nuclear Information System (INIS)

    Duncan, J.S.; Yale Univ., New Haven, CT; Gerig, G.

    2005-01-01

    The two-volume set LNCS 3749 and LNCS 3750 constitutes the refereed proceedings of the 8th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2005, held in Palm Springs, CA, USA, in October 2005. Based on rigorous peer reviews the program committee selected 237 carefully revised full papers from 632 submissions for presentation in two volumes. The first volume includes all the contributions related to image analysis and validation, vascular image segmentation, image registration, diffusion tensor image analysis, image segmentation and analysis, clinical applications - validation, imaging systems - visualization, computer assisted diagnosis, cellular and molecular image analysis, physically-based modeling, robotics and intervention, medical image computing for clinical applications, and biological imaging - simulation and modeling. The second volume collects the papers related to robotics, image-guided surgery and interventions, image registration, medical image computing, structural and functional brain analysis, model-based image analysis, image-guided intervention: simulation, modeling and display, and image segmentation and analysis. (orig.)

  6. Medical image computing and computer-assisted intervention - MICCAI 2005. Proceedings; Pt. 1

    Energy Technology Data Exchange (ETDEWEB)

    Duncan, J.S. [Yale Univ., New Haven, CT (United States). Dept. of Biomedical Engineering and Diagnostic Radiology; Gerig, G. (eds.) [North Carolina Univ., Chapel Hill (United States). Dept. of Computer Science

    2005-07-01

    The two-volume set LNCS 3749 and LNCS 3750 constitutes the refereed proceedings of the 8th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2005, held in Palm Springs, CA, USA, in October 2005. Based on rigorous peer reviews the program committee selected 237 carefully revised full papers from 632 submissions for presentation in two volumes. The first volume includes all the contributions related to image analysis and validation, vascular image segmentation, image registration, diffusion tensor image analysis, image segmentation and analysis, clinical applications - validation, imaging systems - visualization, computer assisted diagnosis, cellular and molecular image analysis, physically-based modeling, robotics and intervention, medical image computing for clinical applications, and biological imaging - simulation and modeling. The second volume collects the papers related to robotics, image-guided surgery and interventions, image registration, medical image computing, structural and functional brain analysis, model-based image analysis, image-guided intervention: simulation, modeling and display, and image segmentation and analysis. (orig.)

  7. Medical image computing and computer science intervention. MICCAI 2005. Pt. 2. Proceedings

    Energy Technology Data Exchange (ETDEWEB)

    Duncan, J.S. [Yale Univ., New Haven, CT (United States). Dept. of Biomedical Engineering]|[Yale Univ., New Haven, CT (United States). Dept. of Diagnostic Radiology; Gerig, G. (eds.) [North Carolina Univ., Chapel Hill, NC (United States). Dept. of Computer Science

    2005-07-01

    The two-volume set LNCS 3749 and LNCS 3750 constitutes the refereed proceedings of the 8th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2005, held in Palm Springs, CA, USA, in October 2005. Based on rigorous peer reviews the program committee selected 237 carefully revised full papers from 632 submissions for presentation in two volumes. The first volume includes all the contributions related to image analysis and validation, vascular image segmentation, image registration, diffusion tensor image analysis, image segmentation and analysis, clinical applications - validation, imaging systems - visualization, computer assisted diagnosis, cellular and molecular image analysis, physically-based modeling, robotics and intervention, medical image computing for clinical applications, and biological imaging - simulation and modeling. The second volume collects the papers related to robotics, image-guided surgery and interventions, image registration, medical image computing, structural and functional brain analysis, model-based image analysis, image-guided intervention: simulation, modeling and display, and image segmentation and analysis. (orig.)

  8. Regional variation in Medicare payments for medical imaging: radiologists versus nonradiologists.

    Science.gov (United States)

    Rosman, David A; Nsiah, Eugene; Hughes, Danny R; Duszak, Richard

    2015-05-01

    The purpose of this article was to study regional variation in Medicare Physician Fee Schedule (MPFS) payments for medical imaging to radiologists compared with nonradiologists. Using a 5% random sample of all Medicare enrollees, which covered approximately 2.5 million Part B beneficiaries in 2011, total professional-only, technical-only, and global MPFS spending was calculated on a state-by-state and United States Census Bureau regional basis for all Medicare Berenson-Eggers Type of Service-defined medical imaging services. Payments to radiologists versus nonradiologists were identified and variation was analyzed. Nationally, mean MPFS medical imaging spending per Medicare beneficiary was $207.17 ($95.71 [46.2%] to radiologists vs $111.46 [53.8%] to nonradiologists). Of professional-only (typically interpretation) payments, 20.6% went to nonradiologists. Of technical-only (typically owned equipment) payments, 84.9% went to nonradiologists. Of global (both professional and technical) payments, 70.1% went to nonradiologists. The percentage of MPFS medical imaging spending on nonradiologists ranged from 32% (Minnesota) to 69.5% (South Carolina). The percentage of MPFS payments for medical imaging to nonradiologists exceeded those to radiologists in 58.8% of states. The relative percentage of MPFS payments to nonradiologists was highest in the South (58.5%) and lowest in the Northeast (48.0%). Nationally, 53.8% of MPFS payments for medical imaging services are made to nonradiologists, who claim a majority of MPFS payments in most states dominated by noninterpretive payments. This majority spending on nonradiologists may have implications in bundled and capitated payment models for radiology services. Medical imaging payment policy initiatives must consider the roles of all provider groups and associated regional variation.

  9. Teaching the physics of medical imaging: an active learning approach involving imaging of biological tissue

    DEFF Research Database (Denmark)

    Wilhjelm, Jens E.; Pihl, Michael Johannes; Lonsdale, Markus Nowak

    2008-01-01

    Introduction to medical imaging is an experimentally oriented course in the physics of medical imaging, where the students record, process and analyse 3D data of an unknown piece of formalin fixed animal tissue embedded in agar in order to estimate the tissue types present. Planar X-ray, CT, MRI......, ultrasound and SPECT/PET images are recorded, showing the tissue in very different ways. In order for the students to estimate the tissue type, they need to study the physical principles of the imaging modalities. The “true” answer is subsequently revealed by slicing the tissue....

  10. Imaging systems for medical diagnostics

    International Nuclear Information System (INIS)

    Krestel, E.

    1990-01-01

    This book provides physicians and clinical physicists with detailed information on today's imaging modalities and assists them in selecting the optimal system for each clinical application. Physicists, engineers and computer specialists engaged in research and development and sales departments will also find this book to be of considerable use. It may also be employed at universities, training centers and in technical seminars. The physiological and physical fundamentals are explained in part 1. The technical solutions contained in part 2 illustrate the numerous possibilities available in X-ray diagnostics, computed tomography, nuclear medical diagnostics, magnetic resonance imaging, sonography and biomagnetic diagnostics. (orig.)

  11. X-ray detectors in medical imaging

    International Nuclear Information System (INIS)

    Spahn, Martin

    2013-01-01

    Healthcare systems are subject to continuous adaptation, following trends such as the change of demographic structures, the rise of life-style related and chronic diseases, and the need for efficient and outcome-oriented procedures. This also influences the design of new imaging systems as well as their components. The applications of X-ray imaging in the medical field are manifold and have led to dedicated modalities supporting specific imaging requirements, for example in computed tomography (CT), radiography, angiography, surgery or mammography, delivering projection or volumetric imaging data. Depending on the clinical needs, some X-ray systems enable diagnostic imaging while others support interventional procedures. X-ray detector design requirements for the different medical applications can vary strongly with respect to size and shape, spatial resolution, frame rates and X-ray flux, among others. Today, integrating X-ray detectors are in common use. They are predominantly based on scintillators (e.g. CsI or Gd 2 O 2 S) and arrays of photodiodes made from crystalline silicon (Si) or amorphous silicon (a-Si) or they employ semiconductors (e.g. Se) with active a-Si readout matrices. Ongoing and future developments of X-ray detectors will include optimization of current state-of-the-art integrating detectors in terms of performance and cost, will enable the usage of large size CMOS-based detectors, and may facilitate photon counting techniques with the potential to further enhance performance characteristics and foster the prospect of new clinical applications

  12. Feature and Intensity Based Medical Image Registration Using Particle Swarm Optimization.

    Science.gov (United States)

    Abdel-Basset, Mohamed; Fakhry, Ahmed E; El-Henawy, Ibrahim; Qiu, Tie; Sangaiah, Arun Kumar

    2017-11-03

    Image registration is an important aspect in medical image analysis, and kinds use in a variety of medical applications. Examples include diagnosis, pre/post surgery guidance, comparing/merging/integrating images from multi-modal like Magnetic Resonance Imaging (MRI), and Computed Tomography (CT). Whether registering images across modalities for a single patient or registering across patients for a single modality, registration is an effective way to combine information from different images into a normalized frame for reference. Registered datasets can be used for providing information relating to the structure, function, and pathology of the organ or individual being imaged. In this paper a hybrid approach for medical images registration has been developed. It employs a modified Mutual Information (MI) as a similarity metric and Particle Swarm Optimization (PSO) method. Computation of mutual information is modified using a weighted linear combination of image intensity and image gradient vector flow (GVF) intensity. In this manner, statistical as well as spatial image information is included into the image registration process. Maximization of the modified mutual information is effected using the versatile Particle Swarm Optimization which is developed easily with adjusted less parameter. The developed approach has been tested and verified successfully on a number of medical image data sets that include images with missing parts, noise contamination, and/or of different modalities (CT, MRI). The registration results indicate the proposed model as accurate and effective, and show the posture contribution in inclusion of both statistical and spatial image data to the developed approach.

  13. Medical image archive node simulation and architecture

    Science.gov (United States)

    Chiang, Ted T.; Tang, Yau-Kuo

    1996-05-01

    It is a well known fact that managed care and new treatment technologies are revolutionizing the health care provider world. Community Health Information Network and Computer-based Patient Record projects are underway throughout the United States. More and more hospitals are installing digital, `filmless' radiology (and other imagery) systems. They generate a staggering amount of information around the clock. For example, a typical 500-bed hospital might accumulate more than 5 terabytes of image data in a period of 30 years for conventional x-ray images and digital images such as Magnetic Resonance Imaging and Computer Tomography images. With several hospitals contributing to the archive, the storage required will be in the hundreds of terabytes. Systems for reliable, secure, and inexpensive storage and retrieval of digital medical information do not exist today. In this paper, we present a Medical Image Archive and Distribution Service (MIADS) concept. MIADS is a system shared by individual and community hospitals, laboratories, and doctors' offices that need to store and retrieve medical images. Due to the large volume and complexity of the data, as well as the diversified user access requirement, implementation of the MIADS will be a complex procedure. One of the key challenges to implementing a MIADS is to select a cost-effective, scalable system architecture to meet the ingest/retrieval performance requirements. We have performed an in-depth system engineering study, and developed a sophisticated simulation model to address this key challenge. This paper describes the overall system architecture based on our system engineering study and simulation results. In particular, we will emphasize system scalability and upgradability issues. Furthermore, we will discuss our simulation results in detail. The simulations study the ingest/retrieval performance requirements based on different system configurations and architectures for variables such as workload, tape

  14. Development of an electronic medical report delivery system to 3G GSM mobile (cellular) phones for a medical imaging department.

    Science.gov (United States)

    Lim, Eugene Y; Lee, Chiang; Cai, Weidong; Feng, Dagan; Fulham, Michael

    2007-01-01

    Medical practice is characterized by a high degree of heterogeneity in collaborative and cooperative patient care. Fast and effective communication between medical practitioners can improve patient care. In medical imaging, the fast delivery of medical reports to referring medical practitioners is a major component of cooperative patient care. Recently, mobile phones have been actively deployed in telemedicine applications. The mobile phone is an ideal medium to achieve faster delivery of reports to the referring medical practitioners. In this study, we developed an electronic medical report delivery system from a medical imaging department to the mobile phones of the referring doctors. The system extracts a text summary of medical report and a screen capture of diagnostic medical image in JPEG format, which are transmitted to 3G GSM mobile phones.

  15. View interpolation for medical images on autostereoscopic displays

    NARCIS (Netherlands)

    Zinger, S.; Ruijters, D.; Do, Q.L.; With, de P.H.N.

    2012-01-01

    We present an approach for efficient rendering and transmitting views to a high-resolution autostereoscopic display for medical purposes. Displaying biomedical images on an autostereoscopic display poses different requirements than in a consumer case. For medical usage, it is essential that the

  16. General physicians: born or made? The use of a tracking database to answer medical workforce questions.

    Science.gov (United States)

    Poole, P; McHardy, K; Janssen, A

    2009-07-01

    The aim of the study was to use a tracking database to investigate the perceived influence of various factors on career choices of New Zealand medical graduates and to examine specifically whether experiences at medical school may have an effect on a decision to become a general physician. Questionnaires were distributed to medical students in the current University of Auckland programme at entry and exit points. The surveys have been completed by two entry cohorts and an exit one since 2006. The response rates were 70 and 88% in the entry and exit groups, respectively. More than 75% of exiting students reported an interest in pursuing a career in general internal medicine. In 42%, this is a 'strong interest' in general medicine compared with 23% in the entry cohort (P Auckland medical students. Only 11% of study respondents reported that student loan burden has a significant influence on career decisions. Quality experiences on attachments seem essential for undergraduates to promote interest in general medicine. There is potential for curriculum design and clinical experiences to be formulated to promote the 'making' of these doctors. Tracking databases will assist in answering some of these questions.

  17. SemVisM: semantic visualizer for medical image

    Science.gov (United States)

    Landaeta, Luis; La Cruz, Alexandra; Baranya, Alexander; Vidal, María.-Esther

    2015-01-01

    SemVisM is a toolbox that combines medical informatics and computer graphics tools for reducing the semantic gap between low-level features and high-level semantic concepts/terms in the images. This paper presents a novel strategy for visualizing medical data annotated semantically, combining rendering techniques, and segmentation algorithms. SemVisM comprises two main components: i) AMORE (A Modest vOlume REgister) to handle input data (RAW, DAT or DICOM) and to initially annotate the images using terms defined on medical ontologies (e.g., MesH, FMA or RadLex), and ii) VOLPROB (VOlume PRObability Builder) for generating the annotated volumetric data containing the classified voxels that belong to a particular tissue. SemVisM is built on top of the semantic visualizer ANISE.1

  18. Development of Standard Process for Private Information Protection of Medical Imaging Issuance

    International Nuclear Information System (INIS)

    Park, Bum Jin; Jeong, Jae Ho; Son, Gi Gyeong Son; Kang, Hee Doo; Yoo, Beong Gyu; Lee, Jong Seok

    2009-01-01

    The medical imaging issuance is changed from conventional film method to Digital Compact Disk solution because of development on IT technology. However other medical record department's are undergoing identification check through and through whereas medical imaging department cannot afford to do that. So, we examine present applicant's recognition of private intelligence safeguard, and medical imaging issuance condition by CD and DVD medium toward various medical facility and then perform comparative analysis associated with domestic and foreign law and recommendation, lastly suggest standard for medical imaging issuance and process relate with internal environment. First, we surveyed issuance process and required documents when situation of medical image issuance in the metropolitan medical facility by wire telephone between 2008.6.-12008.7.1. in accordance with the medical law Article 21clause 2, suggested standard through applicant's required documents occasionally - (1) in the event of oneself verifying identification, (2) in the event of family verifying applicant identification and family relations document (health insurance card, attested copy, and so on), (3) third person or representative verifying applicant identification and letter of attorney and certificate of one's seal impression. Second, also checked required documents of applicant in accordance with upper standard when situation of medical image issuance in Kyung-hee university medical center during 3 month 2008.5.-12008.7.31. Third, developed a work process by triangular position of issuance procedure for situation when verifying required documents and management of unpreparedness. Look all over the our manufactured output in the hospital - satisfy the all conditions 4 place(12%), possibly request everyone 4 place(12%), and apply in the clinic section 9 place(27%) that does not medical imaging issuance office, so we don't know about required documents condition. and look into whether meet or not

  19. Watermark Compression in Medical Image Watermarking Using Lempel-Ziv-Welch (LZW) Lossless Compression Technique.

    Science.gov (United States)

    Badshah, Gran; Liew, Siau-Chuin; Zain, Jasni Mohd; Ali, Mushtaq

    2016-04-01

    In teleradiology, image contents may be altered due to noisy communication channels and hacker manipulation. Medical image data is very sensitive and can not tolerate any illegal change. Illegally changed image-based analysis could result in wrong medical decision. Digital watermarking technique can be used to authenticate images and detect as well as recover illegal changes made to teleradiology images. Watermarking of medical images with heavy payload watermarks causes image perceptual degradation. The image perceptual degradation directly affects medical diagnosis. To maintain the image perceptual and diagnostic qualities standard during watermarking, the watermark should be lossless compressed. This paper focuses on watermarking of ultrasound medical images with Lempel-Ziv-Welch (LZW) lossless-compressed watermarks. The watermark lossless compression reduces watermark payload without data loss. In this research work, watermark is the combination of defined region of interest (ROI) and image watermarking secret key. The performance of the LZW compression technique was compared with other conventional compression methods based on compression ratio. LZW was found better and used for watermark lossless compression in ultrasound medical images watermarking. Tabulated results show the watermark bits reduction, image watermarking with effective tamper detection and lossless recovery.

  20. Open-source software platform for medical image segmentation applications

    Science.gov (United States)

    Namías, R.; D'Amato, J. P.; del Fresno, M.

    2017-11-01

    Segmenting 2D and 3D images is a crucial and challenging problem in medical image analysis. Although several image segmentation algorithms have been proposed for different applications, no universal method currently exists. Moreover, their use is usually limited when detection of complex and multiple adjacent objects of interest is needed. In addition, the continually increasing volumes of medical imaging scans require more efficient segmentation software design and highly usable applications. In this context, we present an extension of our previous segmentation framework which allows the combination of existing explicit deformable models in an efficient and transparent way, handling simultaneously different segmentation strategies and interacting with a graphic user interface (GUI). We present the object-oriented design and the general architecture which consist of two layers: the GUI at the top layer, and the processing core filters at the bottom layer. We apply the framework for segmenting different real-case medical image scenarios on public available datasets including bladder and prostate segmentation from 2D MRI, and heart segmentation in 3D CT. Our experiments on these concrete problems show that this framework facilitates complex and multi-object segmentation goals while providing a fast prototyping open-source segmentation tool.

  1. Plane Wave Medical Ultrasound Imaging Using Adaptive Beamforming

    DEFF Research Database (Denmark)

    Holfort, Iben Kraglund; Gran, Fredrik; Jensen, Jørgen Arendt

    2008-01-01

    In this paper, the adaptive, minimum variance (MV) beamformer is applied to medical ultrasound imaging. The Significant resolution and contrast gain provided by the adaptive, minimum variance (MV) beamformer, introduces the possibility of plane wave (PW) ultrasound imaging. Data is obtained using...

  2. From medical imaging data to 3D printed anatomical models.

    Directory of Open Access Journals (Sweden)

    Thore M Bücking

    Full Text Available Anatomical models are important training and teaching tools in the clinical environment and are routinely used in medical imaging research. Advances in segmentation algorithms and increased availability of three-dimensional (3D printers have made it possible to create cost-efficient patient-specific models without expert knowledge. We introduce a general workflow that can be used to convert volumetric medical imaging data (as generated by Computer Tomography (CT to 3D printed physical models. This process is broken up into three steps: image segmentation, mesh refinement and 3D printing. To lower the barrier to entry and provide the best options when aiming to 3D print an anatomical model from medical images, we provide an overview of relevant free and open-source image segmentation tools as well as 3D printing technologies. We demonstrate the utility of this streamlined workflow by creating models of ribs, liver, and lung using a Fused Deposition Modelling 3D printer.

  3. Current status on image processing in medical fields in Japan

    International Nuclear Information System (INIS)

    Atsumi, Kazuhiko

    1979-01-01

    Information on medical images are classified in the two patterns. 1) off-line images on films-x-ray films, cell image, chromosome image etc. 2) on-line images detected through sensors, RI image, ultrasonic image, thermogram etc. These images are divided into three characteristic, two dimensional three dimensional and dynamic images. The research on medical image processing have been reported in several meeting in Japan and many fields on images have been studied on RI, thermogram, x-ray film, x-ray-TV image, cancer cell, blood cell, bacteria, chromosome, ultrasonics, and vascular image. Processing on TI image useful and easy because of their digital displays. Software on smoothing, restoration (iterative approximation), fourier transformation, differentiation and subtration. Image on stomach and chest x-ray films have been processed automatically utilizing computer system. Computed Tomography apparatuses have been already developed in Japan and automated screening instruments on cancer cells and recently on blood cells classification have been also developed. Acoustical holography imaging and moire topography have been also studied in Japan. (author)

  4. Magnetic Resonance Imaging (MRI) -- Head

    Medline Plus

    Full Text Available ... radiation oncology provider in your community, you can search the ACR-accredited facilities database . This website does not provide cost information. The costs for specific medical imaging tests, treatments ...

  5. Children's (Pediatric) Abdominal Ultrasound Imaging

    Medline Plus

    Full Text Available ... radiation oncology provider in your community, you can search the ACR-accredited facilities database . This website does not provide cost information. The costs for specific medical imaging tests, treatments ...

  6. Children's (Pediatric) Magnetic Resonance Imaging

    Medline Plus

    Full Text Available ... radiation oncology provider in your community, you can search the ACR-accredited facilities database . This website does not provide cost information. The costs for specific medical imaging tests, treatments ...

  7. Robotic 3D scanner as an alternative to standard modalities of medical imaging.

    Science.gov (United States)

    Chromy, Adam; Zalud, Ludek

    2014-01-01

    There are special medical cases, where standard medical imaging modalities are able to offer sufficient results, but not in the optimal way. It means, that desired results are produced with unnecessarily high expenses, with redundant informations or with needless demands on patient. This paper deals with one special case, where information useful for examination is the body surface only, inner sight into the body is needless. New specialized medical imaging device is developed for this situation. In the Introduction section, analysis of presently used medical imaging modalities is presented, which declares, that no available imaging device is best fitting for mentioned purposes. In the next section, development of the new specialized medical imaging device is presented, and its principles and functions are described. Then, the parameters of new device are compared with present ones. It brings significant advantages comparing to present imaging systems.

  8. Multi-provider architecture for cloud outsourcing of medical imaging repositories.

    Science.gov (United States)

    Godinho, Tiago Marques; Bastião Silva, Luís A; Costa, Carlos; Oliveira, José Luís

    2014-01-01

    Over the last few years, the extended usage of medical imaging procedures has raised the medical community attention towards the optimization of their workflows. More recently, the federation of multiple institutions into a seamless distribution network has brought hope of increased quality healthcare services along with more efficient resource management. As a result, medical institutions are constantly looking for the best infrastructure to deploy their imaging archives. In this scenario, public cloud infrastructures arise as major candidates, as they offer elastic storage space, optimal data availability without great requirements of maintenance costs or IT personnel, in a pay-as-you-go model. However, standard methodologies still do not take full advantage of outsourced archives, namely because their integration with other in-house solutions is troublesome. This document proposes a multi-provider architecture for integration of outsourced archives with in-house PACS resources, taking advantage of foreign providers to store medical imaging studies, without disregarding security. It enables the retrieval of images from multiple archives simultaneously, improving performance, data availability and avoiding the vendor-locking problem. Moreover it enables load balancing and cache techniques.

  9. Image quality evaluation of medical color and monochrome displays using an imaging colorimeter

    Science.gov (United States)

    Roehrig, Hans; Gu, Xiliang; Fan, Jiahua

    2012-10-01

    The purpose of this presentation is to demonstrate the means which permit examining the accuracy of Image Quality with respect to MTF (Modulation Transfer Function) and NPS (Noise Power Spectrum) of Color Displays and Monochrome Displays. Indications were in the past that color displays could affect the clinical performance of color displays negatively compared to monochrome displays. Now colorimeters like the PM-1423 are available which have higher sensitivity and color accuracy than the traditional cameras like CCD cameras. Reference (1) was not based on measurements made with a colorimeter. This paper focuses on the measurements of physical characteristics of the spatial resolution and noise performance of color and monochrome medical displays which were made with a colorimeter and we will after this meeting submit the data to an ROC study so we have again a paper to present at a future SPIE Conference.Specifically, Modulation Transfer Function (MTF) and Noise Power Spectrum (NPS) were evaluated and compared at different digital driving levels (DDL) between the two medical displays. This paper focuses on the measurements of physical characteristics of the spatial resolution and noise performance of color and monochrome medical displays which were made with a colorimeter and we will after this meeting submit the data to an ROC study so we have again a paper to present at a future Annual SPIE Conference. Specifically, Modulation Transfer Function (MTF) and Noise Power Spectrum (NPS) were evaluated and compared at different digital driving levels (DDL) between the two medical displays. The Imaging Colorimeter. Measurement of color image quality needs were done with an imaging colorimeter as it is shown below. Imaging colorimetry is ideally suited to FPD measurement because imaging systems capture spatial data generating millions of data points in a single measurement operation. The imaging colorimeter which was used was the PM-1423 from Radiant Imaging. It uses

  10. 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.

  11. Medical Image Denoising Using Mixed Transforms

    Directory of Open Access Journals (Sweden)

    Jaleel Sadoon Jameel

    2018-02-01

    Full Text Available  In this paper,  a mixed transform method is proposed based on a combination of wavelet transform (WT and multiwavelet transform (MWT in order to denoise medical images. The proposed method consists of WT and MWT in cascade form to enhance the denoising performance of image processing. Practically, the first step is to add a noise to Magnetic Resonance Image (MRI or Computed Tomography (CT images for the sake of testing. The noisy image is processed by WT to achieve four sub-bands and each sub-band is treated individually using MWT before the soft/hard denoising stage. Simulation results show that a high peak signal to noise ratio (PSNR is improved significantly and the characteristic features are well preserved by employing mixed transform of WT and MWT due to their capability of separating noise signals from image signals. Moreover, the corresponding mean square error (MSE is decreased accordingly compared to other available methods.

  12. Real-Time Implementation of Medical Ultrasound Strain Imaging System

    International Nuclear Information System (INIS)

    Jeong, Mok Kun; Kwon, Sung Jae; Bae, Moo Ho

    2008-01-01

    Strain imaging in a medical ultrasound imaging system can differentiate the cancer or tumor in a lesion that is stiffer than the surrounding tissue. In this paper, a strain imaging technique using quasistatic compression is implemented that estimates the displacement between pre- and postcompression ultrasound echoes and obtains strain by differentiating it in the spatial direction. Displacements are computed from the phase difference of complex baseband signals obtained using their autocorrelation, and errors associated with converting the phase difference into time or distance are compensated for by taking into the center frequency variation. Also, to reduce the effect of operator's hand motion, the displacements of all scanlines are normalized with the result that satisfactory strain image quality has been obtained. These techniques have been incorporated into implementing a medical ultrasound strain imaging system that operates in real time.

  13. The masked educator-innovative simulation in an Australian undergraduate Medical Sonography and Medical Imaging program.

    Science.gov (United States)

    Reid-Searl, Kerry; Bowman, Anita; McAllister, Margaret; Cowling, Cynthia; Spuur, Kelly

    2014-12-01

    Clinical learning experiences for sonography and medical imaging students can sometimes involve the practice of technical procedures with less of a focus on developing communication skills with patients. Whilst patient-based simulation scenarios have been widely reported in other health education programmes, there is a paucity of research in sonography and medical imaging. The aim of this study was to explore the effectiveness of Mask-Ed™ (KRS Simulation) in the learning and teaching of clinical communication skills to undergraduate medical sonography and medical imaging students. Mask-Ed™ (KRS Simulation) is a simulation technique where the educator is hidden behind wearable realistic silicone body props including masks. Focus group interviews were conducted with 11 undergraduate medical sonography and medical imaging students at CQUniversity, Australia. The number of participants was limited to the size of the cohort of students enrolled in the course. Prior to these interviews participants were engaged in learning activities that featured the use of the Mask-Ed™ (KRS Simulation) method. Thematic analysis was employed to explore how the introduction of Mask-Ed™ (KRS Simulation) contributed to students' learning in relation to clinical communication skills. Key themes included: benefits of interacting with someone real rather than another student, learning made fun, awareness of empathy, therapeutic communication skills, engaged problem solving and purposeful reflection. Mask-Ed™ (KRS Simulation) combined with interactive sessions with an expert facilitator, contributed positively to students' learning in relation to clinical communication skills. Participants believed that interacting with someone real, as in the Mask-Ed characters was beneficial. In addition to the learning being described as fun, participants gained an awareness of empathy, therapeutic communication skills, engaged problem solving and purposeful reflection.

  14. SU-E-J-129: A Strategy to Consolidate the Image Database of a VERO Unit Into a Radiotherapy Management System

    International Nuclear Information System (INIS)

    Yan, Y; Medin, P; Yordy, J; Zhao, B; Jiang, S

    2014-01-01

    Purpose: To present a strategy to integrate the imaging database of a VERO unit with a treatment management system (TMS) to improve clinical workflow and consolidate image data to facilitate clinical quality control and documentation. Methods: A VERO unit is equipped with both kV and MV imaging capabilities for IGRT treatments. It has its own imaging database behind a firewall. It has been a challenge to transfer images on this unit to a TMS in a radiation therapy clinic so that registered images can be reviewed remotely with an approval or rejection record. In this study, a software system, iPump-VERO, was developed to connect VERO and a TMS in our clinic. The patient database folder on the VERO unit was mapped to a read-only folder on a file server outside VERO firewall. The application runs on a regular computer with the read access to the patient database folder. It finds the latest registered images and fuses them in one of six predefined patterns before sends them via DICOM connection to the TMS. The residual image registration errors will be overlaid on the fused image to facilitate image review. Results: The fused images of either registered kV planar images or CBCT images are fully DICOM compatible. A sentinel module is built to sense new registered images with negligible computing resources from the VERO ExacTrac imaging computer. It takes a few seconds to fuse registered images and send them to the TMS. The whole process is automated without any human intervention. Conclusion: Transferring images in DICOM connection is the easiest way to consolidate images of various sources in your TMS. Technically the attending does not have to go to the VERO treatment console to review image registration prior delivery. It is a useful tool for a busy clinic with a VERO unit

  15. 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.

  16. An analytical look at the effects of compression on medical images

    OpenAIRE

    Persons, Kenneth; Palisson, Patrice; Manduca, Armando; Erickson, Bradley J.; Savcenko, Vladimir

    1997-01-01

    This article will take an analytical look at how lossy Joint Photographic Experts Group (JPEG) and wavelet image compression techniques affect medical image content. It begins with a brief explanation of how the JPEG and wavelet algorithms work, and describes in general terms what effect they can have on image quality (removal of noise, blurring, and artifacts). It then focuses more specifically on medical image diagnostic content and explains why subtle pathologies, that may be difficult for...

  17. Three dimensional image presentation techniques in medical imaging

    International Nuclear Information System (INIS)

    Pizer, S.M.; Fuchs, H.

    1987-01-01

    Medical images can be presented three-dimensionally by techniques that either calculate the effect of reflections from surfaces predefined from slices or project a three-space of luminosities computed from voxel intensities onto the visual receptors. Sliced-based reflective displays are the most common type. Means of producing surface descriptions both via voxel sets and via slice contours are reviewed. Advantages of and means of transparent display to allow the appreciation of the 3D relationships among objects are set forth. Ways to produce additional depth cues by stereoscopy and the kinetic depth effect are discussed, and the importance of interactive modification of viewpoint, clipping plane, displayed objects, etc. are explained. A new device, UNC's Pixel-planes, for accomplishing this in real time are illustrated. Voxel intensity based display methods avoid the need for time-consuming predefinition of object surfaces and thus can allow exploration of 3D image data. Varifocal mirror hardware and fast computation of one or more projections based on object probabilities are two of the more important approaches. While 3D display provides important information about 3D relationships, it cannot provide the kind of appreciation of subtle grey-scale changes that 2D display can. Methods that can combine these two kinds of information by superimposing 2D grey-scale slices on or in the context of 3D displays are discussed. Applications of these techniques for both diagnosis and radiotherapy planning are used as illustrations and guides to the usefulness of these techniques with CT, MRI, and other 3D medical imaging modalities. 24 refs.; 5 figs

  18. 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...

  19. Multimedia medical data archive and retrieval server on the Internet

    Science.gov (United States)

    Komo, Darmadi; Levine, Betty A.; Freedman, Matthew T.; Mun, Seong K.; Tang, Y. K.; Chiang, Ted T.

    1997-05-01

    The Multimedia Medical Data Archive and Retrieval Server has been installed at the imaging science and information systems (ISIS) center in Georgetown University Medical Center to provide medical data archive and retrieval support for medical researchers. The medical data includes text, images, sound, and video. All medical data is keyword indexed using a database management system and placed temporarily in a staging area and then transferred to a StorageTek one terabyte tape library system with a robotic arm for permanent archive. There are two methods of interaction with the system. The first method is to use a web browser with HTML functions to perform insert, query, update, and retrieve operations. These generate dynamic SQL calls to the database and produce StorageTek API calls to the tape library. The HTML functions consist of a database, StorageTek interface, HTTP server, common gateway interface, and Java programs. The second method is to issue a DICOM store command, which is translated by the system's DICOM server to SQL calls and then produce StorageTek API calls to the tape library. The system performs as both an Internet and a DICOM server using standard protocols such as HTTP, HTML, Java, and DICOM. Users with proper authentication can log on to the server from anywhere on the Internet using a standard web browser resulting in a user-friendly, open environment, and platform independent solution for archiving multimedia medical data. It represents a complex integration of different components including a robotic tape storage system, database, user-interface, WWW protocols, and TCP/IP networking. The user will only deal with the WWW and DICOM server components of the system, the database and robotic tape library system are transparent and the user will not know that the medical data is stored on magnetic tapes. The server provides the researchers a cost-effective tool for archiving and retrieving medical data across a TCP/IP network environment. It will

  20. Plane-Wave Imaging Challenge in Medical Ultrasound

    DEFF Research Database (Denmark)

    Liebgott, Herve; Molares, Alfonso Rodriguez; Jensen, Jørgen Arendt

    2016-01-01

    for this effect, but comparing the different methods is difficult due to the lack of appropriate tools. PICMUS, the Plane-Wave Imaging Challenge in Medical Ultrasound aims to provide these tools. This paper describes the PICMUS challenge, its motivation, implementation, and metrics.......Plane-Wave imaging enables very high frame rates, up to several thousand frames per second. Unfortunately the lack of transmit focusing leads to reduced image quality, both in terms of resolution and contrast. Recently, numerous beamforming techniques have been proposed to compensate...

  1. Using photoshop filters to create anatomic line-art medical images.

    Science.gov (United States)

    Kirsch, Jacobo; Geller, Brian S

    2006-08-01

    There are multiple ways to obtain anatomic drawings suitable for publication or presentations. This article demonstrates how to use Photoshop to alter digital radiologic images to create line-art illustrations in a quick and easy way. We present two simple to use methods; however, not every image can adequately be transformed and personal preferences and specific changes need to be applied to each image to obtain the desired result. There are multiple ways to obtain anatomic drawings suitable for publication or to prepare presentations. Medical illustrators have always played a major role in the radiology and medical education process. Whether used to teach a complex surgical or radiologic procedure, to define typical or atypical patterns of the spread of disease, or to illustrate normal or aberrant anatomy, medical illustration significantly affects learning (). However, if you are not an accomplished illustrator, the alternatives can be expensive (contacting a professional medical illustrator or buying an already existing stock of digital images) or simply not necessarily applicable to what you are trying to communicate. The purpose of this article is to demonstrate how using Photoshop (Adobe Systems, San Jose, CA) to alter digital radiologic images we can create line-art illustrations in a quick, inexpensive, and easy way in preparation for electronic presentations and publication.

  2. Log-Gabor Energy Based Multimodal Medical Image Fusion in NSCT Domain

    Directory of Open Access Journals (Sweden)

    Yong Yang

    2014-01-01

    Full Text Available Multimodal medical image fusion is a powerful tool in clinical applications such as noninvasive diagnosis, image-guided radiotherapy, and treatment planning. In this paper, a novel nonsubsampled Contourlet transform (NSCT based method for multimodal medical image fusion is presented, which is approximately shift invariant and can effectively suppress the pseudo-Gibbs phenomena. The source medical images are initially transformed by NSCT followed by fusing low- and high-frequency components. The phase congruency that can provide a contrast and brightness-invariant representation is applied to fuse low-frequency coefficients, whereas the Log-Gabor energy that can efficiently determine the frequency coefficients from the clear and detail parts is employed to fuse the high-frequency coefficients. The proposed fusion method has been compared with the discrete wavelet transform (DWT, the fast discrete curvelet transform (FDCT, and the dual tree complex wavelet transform (DTCWT based image fusion methods and other NSCT-based methods. Visually and quantitatively experimental results indicate that the proposed fusion method can obtain more effective and accurate fusion results of multimodal medical images than other algorithms. Further, the applicability of the proposed method has been testified by carrying out a clinical example on a woman affected with recurrent tumor images.

  3. Image processing for medical diagnosis of human organs

    International Nuclear Information System (INIS)

    Tamura, Shin-ichi

    1989-01-01

    The report first describes expectations and needs for diagnostic imaging in the field of clinical medicine, radiation medicine in particular, viewed by the author as an image processing expert working at a medical institute. Then, medical image processing techniques are discussed in relation to advanced information processing techniques that are currently drawing much attention in the field of engineering. Finally, discussion is also made of practical applications of image processing techniques to diagnosis. In the field of clinical diagnosis, advanced equipment such as PACS (picture archiving and communication system) has come into wider use, and efforts have been made to shift from visual examination to more quantitative and objective diagnosis by means of such advanced systems. In clinical medicine, practical, robust systems are more useful than sophisticated ones. It is difficult, though important, to develop completely automatized diagnostic systems. The urgent, realistic goal, therefore, is to develop effective diagnosis support systems. In particular, operation support systems equipped with three-dimensional displays will be very useful. (N.K.)

  4. OSPACS: Ultrasound image management system

    Directory of Open Access Journals (Sweden)

    Bessant Conrad

    2008-06-01

    Full Text Available Abstract Background Ultrasound scanning uses the medical imaging format, DICOM, for electronically storing the images and data associated with a particular scan. Large health care facilities typically use a picture archiving and communication system (PACS for storing and retrieving such images. However, these systems are usually not suitable for managing large collections of anonymized ultrasound images gathered during a clinical screening trial. Results We have developed a system enabling the accurate archiving and management of ultrasound images gathered during a clinical screening trial. It is based upon a Windows application utilizing an open-source DICOM image viewer and a relational database. The system automates the bulk import of DICOM files from removable media by cross-validating the patient information against an external database, anonymizing the data as well as the image, and then storing the contents of the file as a field in a database record. These image records may then be retrieved from the database and presented in a tree-view control so that the user can select particular images for display in a DICOM viewer or export them to external media. Conclusion This system provides error-free automation of ultrasound image archiving and management, suitable for use in a clinical trial. An open-source project has been established to promote continued development of the system.

  5. Using digital watermarking to enhance security in wireless medical image transmission.

    Science.gov (United States)

    Giakoumaki, Aggeliki; Perakis, Konstantinos; Banitsas, Konstantinos; Giokas, Konstantinos; Tachakra, Sapal; Koutsouris, Dimitris

    2010-04-01

    During the last few years, wireless networks have been increasingly used both inside hospitals and in patients' homes to transmit medical information. In general, wireless networks suffer from decreased security. However, digital watermarking can be used to secure medical information. In this study, we focused on combining wireless transmission and digital watermarking technologies to better secure the transmission of medical images within and outside the hospital. We utilized an integrated system comprising the wireless network and the digital watermarking module to conduct a series of tests. The test results were evaluated by medical consultants. They concluded that the images suffered no visible quality degradation and maintained their diagnostic integrity. The proposed integrated system presented reasonable stability, and its performance was comparable to that of a fixed network. This system can enhance security during the transmission of medical images through a wireless channel.

  6. An efficient similarity measure technique for medical image registration

    Indian Academy of Sciences (India)

    In this paper, an efficient similarity measure technique is proposed for medical image registration. The proposed approach is based on the Gerschgorin circles theorem. In this approach, image registration is carried out by considering Gerschgorin bounds of a covariance matrix of two compared images with normalized ...

  7. Lossy image compression for digital medical imaging systems

    Science.gov (United States)

    Wilhelm, Paul S.; Haynor, David R.; Kim, Yongmin; Nelson, Alan C.; Riskin, Eve A.

    1990-07-01

    Image compression at rates of 10:1 or greater could make PACS much more responsive and economically attractive. This paper describes a protocol for subjective and objective evaluation of the fidelity of compressed/decompressed images to the originals and presents the results ofits application to four representative and promising compression methods. The methods examined are predictive pruned tree-structured vector quantization, fractal compression, the discrete cosine transform with equal weighting of block bit allocation, and the discrete cosine transform with human visual system weighting of block bit allocation. Vector quantization is theoretically capable of producing the best compressed images, but has proven to be difficult to effectively implement. It has the advantage that it can reconstruct images quickly through a simple lookup table. Disadvantages are that codebook training is required, the method is computationally intensive, and achieving the optimum performance would require prohibitively long vector dimensions. Fractal compression is a relatively new compression technique, but has produced satisfactory results while being computationally simple. It is fast at both image compression and image reconstruction. Discrete cosine iransform techniques reproduce images well, but have traditionally been hampered by the need for intensive computing to compress and decompress images. A protocol was developed for side-by-side observer comparison of reconstructed images with originals. Three 1024 X 1024 CR (Computed Radiography) images and two 512 X 512 X-ray CT images were viewed at six bit rates (0.2, 0.4, 0.6, 0.9, 1.2, and 1.5 bpp for CR, and 1.0, 1.3, 1.6, 1.9, 2.2, 2.5 bpp for X-ray CT) by nine radiologists at the University of Washington Medical Center. The CR images were viewed on a Pixar II Megascan (2560 X 2048) monitor and the CT images on a Sony (1280 X 1024) monitor. The radiologists' subjective evaluations of image fidelity were compared to

  8. Advantages of semiconductor CZT for medical imaging

    Science.gov (United States)

    Wagenaar, Douglas J.; Parnham, Kevin; Sundal, Bjorn; Maehlum, Gunnar; Chowdhury, Samir; Meier, Dirk; Vandehei, Thor; Szawlowski, Marek; Patt, Bradley E.

    2007-09-01

    Cadmium zinc telluride (CdZnTe, or CZT) is a room-temperature semiconductor radiation detector that has been developed in recent years for a variety of applications. CZT has been investigated for many potential uses in medical imaging, especially in the field of single photon emission computed tomography (SPECT). CZT can also be used in positron emission tomography (PET) as well as photon-counting and integration-mode x-ray radiography and computed tomography (CT). The principal advantages of CZT are 1) direct conversion of x-ray or gamma-ray energy into electron-hole pairs; 2) energy resolution; 3) high spatial resolution and hence high space-bandwidth product; 4) room temperature operation, stable performance, high density, and small volume; 5) depth-of-interaction (DOI) available through signal processing. These advantages will be described in detail with examples from our own CZT systems. The ability to operate at room temperature, combined with DOI and very small pixels, make the use of multiple, stationary CZT "mini-gamma cameras" a realistic alternative to today's large Anger-type cameras that require motion to obtain tomographic sampling. The compatibility of CZT with Magnetic Resonance Imaging (MRI)-fields is demonstrated for a new type of multi-modality medical imaging, namely SPECT/MRI. For pre-clinical (i.e., laboratory animal) imaging, the advantages of CZT lie in spatial and energy resolution, small volume, automated quality control, and the potential for DOI for parallax removal in pinhole imaging. For clinical imaging, the imaging of radiographically dense breasts with CZT enables scatter rejection and hence improved contrast. Examples of clinical breast images with a dual-head CZT system are shown.

  9. 78 FR 734 - Medical Imaging Drugs Advisory Committee; Notice of Meeting

    Science.gov (United States)

    2013-01-04

    ...] Medical Imaging Drugs Advisory Committee; Notice of Meeting AGENCY: Food and Drug Administration, HHS... and Drug Administration (FDA). The meeting will be open to the public. Name of Committee: Medical Imaging Drugs Advisory Committee. General Function of the Committee: To provide advice and recommendations...

  10. Creating New Medical Ontologies for Image Annotation A Case Study

    CERN Document Server

    Stanescu, Liana; Brezovan, Marius; Mihai, Cristian Gabriel

    2012-01-01

    Creating New Medical Ontologies for Image Annotation focuses on the problem of the medical images automatic annotation process, which is solved in an original manner by the authors. All the steps of this process are described in detail with algorithms, experiments and results. The original algorithms proposed by authors are compared with other efficient similar algorithms. In addition, the authors treat the problem of creating ontologies in an automatic way, starting from Medical Subject Headings (MESH). They have presented some efficient and relevant annotation models and also the basics of the annotation model used by the proposed system: Cross Media Relevance Models. Based on a text query the system will retrieve the images that contain objects described by the keywords.

  11. Deep Learning- and Transfer Learning-Based Super Resolution Reconstruction from Single Medical Image

    Directory of Open Access Journals (Sweden)

    YiNan Zhang

    2017-01-01

    Full Text Available Medical images play an important role in medical diagnosis and research. In this paper, a transfer learning- and deep learning-based super resolution reconstruction method is introduced. The proposed method contains one bicubic interpolation template layer and two convolutional layers. The bicubic interpolation template layer is prefixed by mathematics deduction, and two convolutional layers learn from training samples. For saving training medical images, a SIFT feature-based transfer learning method is proposed. Not only can medical images be used to train the proposed method, but also other types of images can be added into training dataset selectively. In empirical experiments, results of eight distinctive medical images show improvement of image quality and time reduction. Further, the proposed method also produces slightly sharper edges than other deep learning approaches in less time and it is projected that the hybrid architecture of prefixed template layer and unfixed hidden layers has potentials in other applications.

  12. The virtual microscopy database-sharing digital microscope images for research and education.

    Science.gov (United States)

    Lee, Lisa M J; Goldman, Haviva M; Hortsch, Michael

    2018-02-14

    Over the last 20 years, virtual microscopy has become the predominant modus of teaching the structural organization of cells, tissues, and organs, replacing the use of optical microscopes and glass slides in a traditional histology or pathology laboratory setting. Although virtual microscopy image files can easily be duplicated, creating them requires not only quality histological glass slides but also an expensive whole slide microscopic scanner and massive data storage devices. These resources are not available to all educators and researchers, especially at new institutions in developing countries. This leaves many schools without access to virtual microscopy resources. The Virtual Microscopy Database (VMD) is a new resource established to address this problem. It is a virtual image file-sharing website that allows researchers and educators easy access to a large repository of virtual histology and pathology image files. With the support from the American Association of Anatomists (Bethesda, MD) and MBF Bioscience Inc. (Williston, VT), registration and use of the VMD are currently free of charge. However, the VMD site is restricted to faculty and staff of research and educational institutions. Virtual Microscopy Database users can upload their own collection of virtual slide files, as well as view and download image files for their own non-profit educational and research purposes that have been deposited by other VMD clients. Anat Sci Educ. © 2018 American Association of Anatomists. © 2018 American Association of Anatomists.

  13. GenderMedDB: an interactive database of sex and gender-specific medical literature.

    Science.gov (United States)

    Oertelt-Prigione, Sabine; Gohlke, Björn-Oliver; Dunkel, Mathias; Preissner, Robert; Regitz-Zagrosek, Vera

    2014-01-01

    Searches for sex and gender-specific publications are complicated by the absence of a specific algorithm within search engines and by the lack of adequate archives to collect the retrieved results. We previously addressed this issue by initiating the first systematic archive of medical literature containing sex and/or gender-specific analyses. This initial collection has now been greatly enlarged and re-organized as a free user-friendly database with multiple functions: GenderMedDB (http://gendermeddb.charite.de). GenderMedDB retrieves the included publications from the PubMed database. Manuscripts containing sex and/or gender-specific analysis are continuously screened and the relevant findings organized systematically into disciplines and diseases. Publications are furthermore classified by research type, subject and participant numbers. More than 11,000 abstracts are currently included in the database, after screening more than 40,000 publications. The main functions of the database include searches by publication data or content analysis based on pre-defined classifications. In addition, registrants are enabled to upload relevant publications, access descriptive publication statistics and interact in an open user forum. Overall, GenderMedDB offers the advantages of a discipline-specific search engine as well as the functions of a participative tool for the gender medicine community.

  14. The library without walls: images, medical dictionaries, atlases, medical encyclopedias free on web.

    Science.gov (United States)

    Giglia, E

    2008-09-01

    The aim of this article was to present the ''reference room'' of the Internet, a real library without walls. The reader will find medical encyclopedias, dictionaries, atlases, e-books, images, and will also learn something useful about the use and reuse of images in a text and in a web site, according to the copyright law.

  15. Establishing advanced practice for medical imaging in New Zealand

    International Nuclear Information System (INIS)

    Yielder, Jill; Young, Adrienne; Park, Shelley; Coleman, Karen

    2014-01-01

    Introduction: This article presents the outcome and recommendations following the second stage of a role development project conducted on behalf of the New Zealand Institute of Medical Radiation Technology (NZIMRT). The study sought to support the development of profiles and criteria that may be used to formulate Advanced Scopes of Practice for the profession. It commenced in 2011, following on from initial research that occurred between 2005 and 2008 investigating role development and a possible career structure for medical radiation technologists (MRTs) in New Zealand (NZ). Methods: The study sought to support the development of profiles and criteria that could be used to develop Advanced Scopes of Practice for the profession through inviting 12 specialist medical imaging groups in NZ to participate in a survey. Results: Findings showed strong agreement on potential profiles and on generic criteria within them; however, there was less agreement on specific skills criteria within specialist areas. Conclusions: The authors recommend that one Advanced Scope of Practice be developed for Medical Imaging, with the establishment of generic and specialist criteria. Systems for approval of the overall criteria package for any individual Advanced Practitioner (AP) profile, audit and continuing professional development requirements need to be established by the Medical Radiation Technologists Board (MRTB) to meet the local needs of clinical departments. It is further recommended that the NZIMRT and MRTB promote and support the need for an AP pathway for medical imaging in NZ

  16. Establishing advanced practice for medical imaging in New Zealand

    Energy Technology Data Exchange (ETDEWEB)

    Yielder, Jill, E-mail: j.yielder@auckland.ac.nz [University of Auckland, Auckland (New Zealand); Young, Adrienne; Park, Shelley; Coleman, Karen [University of Otago, Wellington (New Zealand); University of Auckland, Auckland (New Zealand)

    2014-02-15

    Introduction: This article presents the outcome and recommendations following the second stage of a role development project conducted on behalf of the New Zealand Institute of Medical Radiation Technology (NZIMRT). The study sought to support the development of profiles and criteria that may be used to formulate Advanced Scopes of Practice for the profession. It commenced in 2011, following on from initial research that occurred between 2005 and 2008 investigating role development and a possible career structure for medical radiation technologists (MRTs) in New Zealand (NZ). Methods: The study sought to support the development of profiles and criteria that could be used to develop Advanced Scopes of Practice for the profession through inviting 12 specialist medical imaging groups in NZ to participate in a survey. Results: Findings showed strong agreement on potential profiles and on generic criteria within them; however, there was less agreement on specific skills criteria within specialist areas. Conclusions: The authors recommend that one Advanced Scope of Practice be developed for Medical Imaging, with the establishment of generic and specialist criteria. Systems for approval of the overall criteria package for any individual Advanced Practitioner (AP) profile, audit and continuing professional development requirements need to be established by the Medical Radiation Technologists Board (MRTB) to meet the local needs of clinical departments. It is further recommended that the NZIMRT and MRTB promote and support the need for an AP pathway for medical imaging in NZ.

  17. Medical Imaging Field of Magnetic Resonance Imaging: Identification of Specialties within the Field

    Science.gov (United States)

    Grey, Michael L.

    2009-01-01

    This study was conducted to determine if specialty areas are emerging in the magnetic resonance imaging (MRI) profession due to advancements made in the medical sciences, imaging technology, and clinical applications used in MRI that would require new developments in education/training programs and national registry examinations. In this…

  18. Top 100 Cited articles on Radiation Exposure in Medical Imaging: A Bibliometric Analysis.

    Science.gov (United States)

    Kinnin, Jason; Hanna, Tarek N; Jutras, Marc; Hasan, Babar; Bhatia, Rick; Khosa, Faisal

    2018-03-20

    Bibliometric analyses by highest number of citations can help researchers and funding agencies in determining the most influential articles in a field. The main objective of this analysis was to identify the top 100 cited articles addressing radiation exposure from medical imaging and assess their characteristics. Relevant articles were extracted from the Scopus database after a systematic search by researchers using an iteratively defined Boolean search string. Subsequently, exclusion criteria were applied. A list of top 100 articles was prepared, and articles were ranked according to the citations they had received. No time restriction was applied. Descriptive statistics of the data were compiled. The top-cited articles were published from 1970-2013, with the most articles published in 2009 and 2010 (12 articles in each year). The citations ranged from 107-1888 with a median of 272. Manuscripts from our top-cited list originated from 20 different countries, with contributions made by 158 authors and 160 organizations. Eighty-eight percent of studies evaluated patient-related radiation exposure, 7% health care workers, and 5% both or were not specified. Thirty-two percent of studies examined adult populations, 14% pediatric, and 54% included both populations or did not specify. Seventy-two percent of studies were dedicated to Computed Tomography, 8% to radiography/fluoroscopy, 9% to interventional procedures, 4% to nuclear medicine, and 7% to a combination of 2 or more modalities. The top 100 cited articles in medical imaging related to radiation exposure are diverse, originating from many countries with numerous contributing authors. The most common topics covered involve CT and adult patients. The recent peak in the most-highly cited articles (2010) suggests that increased attention has been devoted to this field in recent years. Based on these results, it would appear that research on radiation exposure in medical imaging is poised to continue expanding

  19. Small average differences in attenuation corrected images between men and women in myocardial perfusion scintigraphy: a novel normal stress database

    International Nuclear Information System (INIS)

    Trägårdh, Elin; Sjöstrand, Karl; Jakobsson, David; Edenbrandt, Lars

    2011-01-01

    The American Society of Nuclear Cardiology and the Society of Nuclear Medicine state that incorporation of attenuation-corrected (AC) images in myocardial perfusion scintigraphy (MPS) will improve image quality, interpretive certainty, and diagnostic accuracy. However, commonly used software packages for MPS usually include normal stress databases for non-attenuation corrected (NC) images but not for attenuation-corrected (AC) images. The aim of the study was to develop and compare different normal stress databases for MPS in relation to NC vs. AC images, male vs. female gender, and presence vs. absence of obesity. The principal hypothesis was that differences in mean count values between men and women would be smaller with AC than NC images, thereby allowing for construction and use of gender-independent AC stress database. Normal stress perfusion databases were developed with data from 126 male and 205 female patients with normal MPS. The following comparisons were performed for all patients and separately for normal weight vs. obese patients: men vs. women for AC; men vs. women for NC; AC vs. NC for men; and AC vs. NC for women. When comparing AC for men vs. women, only minor differences in mean count values were observed, and there were no differences for normal weight vs. obese patients. For all other analyses major differences were found, particularly for the inferior wall. The results support the hypothesis that it is possible to use not only gender independent but also weight independent AC stress databases

  20. Method for Surface Scanning in Medical Imaging and Related Apparatus

    DEFF Research Database (Denmark)

    2015-01-01

    A method and apparatus for surface scanning in medical imaging is provided. The surface scanning apparatus comprises an image source, a first optical fiber bundle comprising first optical fibers having proximal ends and distal ends, and a first optical coupler for coupling an image from the image...

  1. Medical Imaging in Differentiating the Diabetic Charcot Foot from Osteomyelitis.

    Science.gov (United States)

    Short, Daniel J; Zgonis, Thomas

    2017-01-01

    Diabetic Charcot neuroarthropathy (DCN) poses a great challenge to diagnose in the early stages and when plain radiographs do not depict any initial signs of osseous fragmentation or dislocation in a setting of a high clinical index of suspicion. Medical imaging, including magnetic resonance imaging, computed tomography, and advanced bone scintigraphy, has its own unique clinical indications when treating the DCN with or without concomitant osteomyelitis. This article reviews different clinical case scenarios for choosing the most accurate medical imaging in differentiating DCN from osteomyelitis. Copyright © 2016 Elsevier Inc. All rights reserved.

  2. Fast fluid registration of medical images

    DEFF Research Database (Denmark)

    Bro-Nielsen, Morten; Gramkow, Claus

    1996-01-01

    This paper offers a new fast algorithm for non-rigid viscous fluid registration of medical images that is at least an order of magnitude faster than the previous method by (Christensen et al., 1994). The core algorithm in the fluid registration method is based on a linear elastic deformation...

  3. Meditate don't medicate: How medical imaging evidence supports the role of meditation in the treatment of depression

    International Nuclear Information System (INIS)

    Annells, S.; Kho, K.; Bridge, P.

    2016-01-01

    Introduction: Depression is a debilitating psychiatric disorder that affects a large proportion of the population. The current treatment for depression involves anti-depressant medication which is associated with side effects and a heightened risk of relapse. Methods: A systematic literature review was performed to determine the value of medical imaging studies in measuring the impact of meditation on depression. Results: Medical imaging studies have successfully demonstrated that meditation may counteract or prevent the physiological cause of depression by decreasing amygdala activity and increasing grey matter volume and activity of the hippocampus, prefrontal cortex and other brain regions associated with attention and emotional self-regulation. Recent advances in functional imaging have enabled visualisation of neural plasticity within the brain. This has shown that for meditators, practice-induced alterations could be due to micro-anatomical processes that may represent an increased functional capacity within the brain regions activated. These changes within brain physiology in association with the skills gained during meditation such as self-regulation, mental processing of negative information and relaxation techniques could potentially lead to a permanent cure for depression and thus prevent relapse. Conclusions: The results of this review suggest that medical imaging has a valuable role to play in evidencing the physiological changes within the brain caused by meditation that counteract those that cause depression. These studies indicate that meditation is a viable alternative to medication for clinical treatment of patients with depression. More rigorous longitudinal imaging studies are proposed to enhance understanding of the neural pathways and mechanisms of meditation. - Highlights: • Medical imaging demonstrates physiological changes that counteract those that cause depression. • Meditation is an alternative to medication for clinical treatment of

  4. Diagnostic imaging over the last 50 years: research and development in medical imaging science and technology

    International Nuclear Information System (INIS)

    Doi, Kunio

    2006-01-01

    Over the last 50 years, diagnostic imaging has grown from a state of infancy to a high level of maturity. Many new imaging modalities have been developed. However, modern medical imaging includes not only image production but also image processing, computer-aided diagnosis (CAD), image recording and storage, and image transmission, most of which are included in a picture archiving and communication system (PACS). The content of this paper includes a short review of research and development in medical imaging science and technology, which covers (a) diagnostic imaging in the 1950s, (b) the importance of image quality and diagnostic performance, (c) MTF, Wiener spectrum, NEQ and DQE, (d) ROC analysis, (e) analogue imaging systems, (f) digital imaging systems, (g) image processing, (h) computer-aided diagnosis, (i) PACS, (j) 3D imaging and (k) future directions. Although some of the modalities are already very sophisticated, further improvements will be made in image quality for MRI, ultrasound and molecular imaging. The infrastructure of PACS is likely to be improved further in terms of its reliability, speed and capacity. However, CAD is currently still in its infancy, and is likely to be a subject of research for a long time. (review)

  5. Medical Image Fusion Algorithm Based on Nonlinear Approximation of Contourlet Transform and Regional Features

    Directory of Open Access Journals (Sweden)

    Hui Huang

    2017-01-01

    Full Text Available According to the pros and cons of contourlet transform and multimodality medical imaging, here we propose a novel image fusion algorithm that combines nonlinear approximation of contourlet transform with image regional features. The most important coefficient bands of the contourlet sparse matrix are retained by nonlinear approximation. Low-frequency and high-frequency regional features are also elaborated to fuse medical images. The results strongly suggested that the proposed algorithm could improve the visual effects of medical image fusion and image quality, image denoising, and enhancement.

  6. License - Trypanosomes Database | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available switchLanguage; BLAST Search Image Search Home About Archive Update History Data List Contact us Trypanoso... Attribution-Share Alike 2.1 Japan . If you use data from this database, please be sure attribute this database as follows: Trypanoso...nse Update History of This Database Site Policy | Contact Us License - Trypanosomes Database | LSDB Archive ...

  7. Characteristics of pediatric chemotherapy medication errors in a national error reporting database.

    Science.gov (United States)

    Rinke, Michael L; Shore, Andrew D; Morlock, Laura; Hicks, Rodney W; Miller, Marlene R

    2007-07-01

    Little is known regarding chemotherapy medication errors in pediatrics despite studies suggesting high rates of overall pediatric medication errors. In this study, the authors examined patterns in pediatric chemotherapy errors. The authors queried the United States Pharmacopeia MEDMARX database, a national, voluntary, Internet-accessible error reporting system, for all error reports from 1999 through 2004 that involved chemotherapy medications and patients aged error reports, 85% reached the patient, and 15.6% required additional patient monitoring or therapeutic intervention. Forty-eight percent of errors originated in the administering phase of medication delivery, and 30% originated in the drug-dispensing phase. Of the 387 medications cited, 39.5% were antimetabolites, 14.0% were alkylating agents, 9.3% were anthracyclines, and 9.3% were topoisomerase inhibitors. The most commonly involved chemotherapeutic agents were methotrexate (15.3%), cytarabine (12.1%), and etoposide (8.3%). The most common error types were improper dose/quantity (22.9% of 327 cited error types), wrong time (22.6%), omission error (14.1%), and wrong administration technique/wrong route (12.2%). The most common error causes were performance deficit (41.3% of 547 cited error causes), equipment and medication delivery devices (12.4%), communication (8.8%), knowledge deficit (6.8%), and written order errors (5.5%). Four of the 5 most serious errors occurred at community hospitals. Pediatric chemotherapy errors often reached the patient, potentially were harmful, and differed in quality between outpatient and inpatient areas. This study indicated which chemotherapeutic agents most often were involved in errors and that administering errors were common. Investigation is needed regarding targeted medication administration safeguards for these high-risk medications. Copyright (c) 2007 American Cancer Society.

  8. Image Quality Characteristics of Handheld Display Devices for Medical Imaging

    Science.gov (United States)

    Yamazaki, Asumi; Liu, Peter; Cheng, Wei-Chung; Badano, Aldo

    2013-01-01

    Handheld devices such as mobile phones and tablet computers have become widespread with thousands of available software applications. Recently, handhelds are being proposed as part of medical imaging solutions, especially in emergency medicine, where immediate consultation is required. However, handheld devices differ significantly from medical workstation displays in terms of display characteristics. Moreover, the characteristics vary significantly among device types. We investigate the image quality characteristics of various handheld devices with respect to luminance response, spatial resolution, spatial noise, and reflectance. We show that the luminance characteristics of the handheld displays are different from those of workstation displays complying with grayscale standard target response suggesting that luminance calibration might be needed. Our results also demonstrate that the spatial characteristics of handhelds can surpass those of medical workstation displays particularly for recent generation devices. While a 5 mega-pixel monochrome workstation display has horizontal and vertical modulation transfer factors of 0.52 and 0.47 at the Nyquist frequency, the handheld displays released after 2011 can have values higher than 0.63 at the respective Nyquist frequencies. The noise power spectra for workstation displays are higher than 1.2×10−5 mm2 at 1 mm−1, while handheld displays have values lower than 3.7×10−6 mm2. Reflectance measurements on some of the handheld displays are consistent with measurements for workstation displays with, in some cases, low specular and diffuse reflectance coefficients. The variability of the characterization results among devices due to the different technological features indicates that image quality varies greatly among handheld display devices. PMID:24236113

  9. A survey on deep learning in medical image analysis.

    Science.gov (United States)

    Litjens, Geert; Kooi, Thijs; Bejnordi, Babak Ehteshami; Setio, Arnaud Arindra Adiyoso; Ciompi, Francesco; Ghafoorian, Mohsen; van der Laak, Jeroen A W M; van Ginneken, Bram; Sánchez, Clara I

    2017-12-01

    Deep learning algorithms, in particular convolutional networks, have rapidly become a methodology of choice for analyzing medical images. This paper reviews the major deep learning concepts pertinent to medical image analysis and summarizes over 300 contributions to the field, most of which appeared in the last year. We survey the use of deep learning for image classification, object detection, segmentation, registration, and other tasks. Concise overviews are provided of studies per application area: neuro, retinal, pulmonary, digital pathology, breast, cardiac, abdominal, musculoskeletal. We end with a summary of the current state-of-the-art, a critical discussion of open challenges and directions for future research. Copyright © 2017 Elsevier B.V. All rights reserved.

  10. Secure public cloud platform for medical images sharing.

    Science.gov (United States)

    Pan, Wei; Coatrieux, Gouenou; Bouslimi, Dalel; Prigent, Nicolas

    2015-01-01

    Cloud computing promises medical imaging services offering large storage and computing capabilities for limited costs. In this data outsourcing framework, one of the greatest issues to deal with is data security. To do so, we propose to secure a public cloud platform devoted to medical image sharing by defining and deploying a security policy so as to control various security mechanisms. This policy stands on a risk assessment we conducted so as to identify security objectives with a special interest for digital content protection. These objectives are addressed by means of different security mechanisms like access and usage control policy, partial-encryption and watermarking.

  11. Magnetic Resonance Imaging (MRI) -- Head

    Medline Plus

    Full Text Available ... scanner. top of page How does the procedure work? Unlike conventional x-ray examinations and computed tomography ( ... medical imaging or radiation oncology provider in your community, you can search the ACR-accredited facilities database . ...

  12. Children's (Pediatric) Magnetic Resonance Imaging

    Medline Plus

    Full Text Available ... scanner. top of page How does the procedure work? Unlike conventional x-ray examinations and computed tomography ( ... medical imaging or radiation oncology provider in your community, you can search the ACR-accredited facilities database . ...

  13. Children's (Pediatric) Abdominal Ultrasound Imaging

    Medline Plus

    Full Text Available ... Send us your feedback Did you find the information you were looking for? Yes No Please type ... facilities database . This website does not provide cost information. The costs for specific medical imaging tests, treatments ...

  14. Magnetic Resonance Imaging (MRI) -- Head

    Medline Plus

    Full Text Available ... tissue and fluid, known as edema . MRI typically costs more and may take more time to perform ... accredited facilities database . This website does not provide cost information. The costs for specific medical imaging tests, ...

  15. Children's (Pediatric) Magnetic Resonance Imaging

    Medline Plus

    Full Text Available ... the heart, such as electrocardiography (ECG). MRI typically costs more and may take more time to perform ... accredited facilities database . This website does not provide cost information. The costs for specific medical imaging tests, ...

  16. TECHNOLOGIES OF BRAIN IMAGES PROCESSING

    Directory of Open Access Journals (Sweden)

    O.M. Klyuchko

    2017-12-01

    Full Text Available The purpose of present research was to analyze modern methods of processing biological images implemented before storage in databases for biotechnological purposes. The databases further were incorporated into web-based digital systems. Examples of such information systems were described in the work for two levels of biological material organization; databases for storing data of histological analysis and of whole brain were described. Methods of neuroimaging processing for electronic brain atlas were considered. It was shown that certain pathological features can be revealed in histological image processing. Several medical diagnostic techniques (for certain brain pathologies, etc. as well as a few biotechnological methods are based on such effects. Algorithms of image processing were suggested. Electronic brain atlas was conveniently for professionals in different fields described in details. Approaches of brain atlas elaboration, “composite” scheme for large deformations as well as several methods of mathematic images processing were described as well.

  17. Dual-tree complex wavelet for medical image watermarking

    International Nuclear Information System (INIS)

    Mavudila, K.R.; Ndaye, B.M.; Masmoudi, L.; Hassanain, N.; Cherkaoui, M.

    2010-01-01

    In order to transmit medical data between hospitals, we insert the information for each patient in the image and its diagnosis, the watermarking consist to insert a message in the image and try to find it with the maximum possible fidelity. This paper presents a blind watermarking scheme in wavelet transform domain dual tree (DTT), who increasing the robustness and preserves the image quality. This system is transparent to the user and allows image integrity control. In addition, it provides information on the location of potential alterations and an evaluation of image modifications which is of major importance in a medico-legal framework. An example using head magnetic resonance and mammography imaging illustrates the overall method. Wavelet techniques can be successfully applied in various image processing methods, namely in image de noising, segmentation, classification, watermarking and others. In this paper we discussed the application of dual tree complex wavelet transform (D T-CWT), which has significant advantages over classic discrete wavelet transform (DWT), for certain image processing problems. The D T-CWT is a form of discreet wavelet transform which generates complex coefficients by using a dual tree of wavelet filters to obtain their real and imaginary parts. The main part of the paper is devoted to profit the exceptional quality for D T-CWT, compared to classical DWT, for a blind medical image watermarking, our schemes are using for the performance bivariate shrinkage with local variance estimation and are robust of attacks and favourably preserves the visual quality. Experimental results show that embedded watermarks using CWT give good image quality and are robust in comparison with the classical DWT.

  18. Comparison of Indian Council for Medical Research and Lunar Databases for Categorization of Male Bone Mineral Density.

    Science.gov (United States)

    Singh, Surya K; Patel, Vivek H; Gupta, Balram

    2017-06-19

    The mainstay of diagnosis of osteoporosis is dual-energy X-ray absorptiometry (DXA) scan measuring areal bone mineral density (BMD) (g/cm 2 ). The aim of the present study was to compare the Indian Council of Medical Research database (ICMRD) and the Lunar ethnic reference database of DXA scans in the diagnosis of osteoporosis in male patients. In this retrospective study, all male patients who underwent a DXA scan were included. The areal BMD (g/cm 2 ) was measured at either the lumbar spine (L1-L4) or the total hip using the Lunar DXA machine (software version 8.50) manufactured by GE Medical Systems (Shanghai, China). The Indian Council of Medical Research published a reference data for BMD in the Indian population derived from the population-based study conducted in healthy Indian individuals, which was used to analyze the BMD result by Lunar DXA scan. The 2 results were compared for various values using statistical software SPSS for Windows (version 16; SPSS Inc., Chicago, IL). A total 238 male patients with a mean age of 57.2 yr (standard deviation ±15.9) were included. Overall, 26.4% (66/250) and 2.8% (7/250) of the subjects were classified in the osteoporosis group according to the Lunar database and the ICMRD, respectively. Out of the 250 sites of the DXA scan, 28.8% (19/66) and 60.0% (40/66) of the cases classified as osteoporosis by the Lunar database were reclassified as normal and osteopenia by ICMRD, respectively. In conclusion, the Indian Council of Medical Research data underestimated the degree of osteoporosis in male subjects that might result in deferring of treatment. In view of the discrepancy, the decision on the treatment of osteoporosis should be based on the multiple fracture risk factors and less reliably on the BMD T-score. Copyright © 2017 The International Society for Clinical Densitometry. Published by Elsevier Inc. All rights reserved.

  19. An atlas of the (near) future: cognitive computing applications for medical imaging (Conference Presentation)

    Science.gov (United States)

    LeGrand, Anne

    2017-02-01

    The role of medical imaging in global health systems is literally fundamental. Like labs, medical images are used at one point or another in almost every high cost, high value episode of care. CT scans, mammograms, and x-rays, for example, "atlas" the body and help chart a course forward for a patient's care team. Imaging precision has improved as a result of technological advancements and breakthroughs in related medical research. Those advancements also bring with them exponential growth in medical imaging data. As IBM trains Watson to "see" medical images, Ms. Le Grand will discuss recent advances made by Watson Health and explore the potential value of "augmented intelligence" to assist healthcare providers like radiologists and cardiologists, as well as the patients they serve.

  20. Anniversary Paper: Image processing and manipulation through the pages of Medical Physics

    International Nuclear Information System (INIS)

    Armato, Samuel G. III; Ginneken, Bram van

    2008-01-01

    The language of radiology has gradually evolved from ''the film'' (the foundation of radiology since Wilhelm Roentgen's 1895 discovery of x-rays) to ''the image,'' an electronic manifestation of a radiologic examination that exists within the bits and bytes of a computer. Rather than simply storing and displaying radiologic images in a static manner, the computational power of the computer may be used to enhance a radiologist's ability to visually extract information from the image through image processing and image manipulation algorithms. Image processing tools provide a broad spectrum of opportunities for image enhancement. Gray-level manipulations such as histogram equalization, spatial alterations such as geometric distortion correction, preprocessing operations such as edge enhancement, and enhanced radiography techniques such as temporal subtraction provide powerful methods to improve the diagnostic quality of an image or to enhance structures of interest within an image. Furthermore, these image processing algorithms provide the building blocks of more advanced computer vision methods. The prominent role of medical physicists and the AAPM in the advancement of medical image processing methods, and in the establishment of the ''image'' as the fundamental entity in radiology and radiation oncology, has been captured in 35 volumes of Medical Physics.

  1. Ordering of diagnostic information in encoded medical images. Accuracy progression

    Science.gov (United States)

    Przelaskowski, A.; Jóźwiak, R.; Krzyżewski, T.; Wróblewska, A.

    2008-03-01

    A concept of diagnostic accuracy progression for embedded coding of medical images was presented. Implementation of JPEG2000 encoder with a modified PCRD optimization algorithm was realized and initially verified as a tool for accurate medical image streaming. Mean square error as a distortion measure was replaced by other numerical measures to revise quality progression according to diagnostic importance of successively encoded image information. A faster increment of image diagnostic importance during reconstruction of initial packets of code stream was reached. Modified Jasper code was initially tested on a set of mammograms containing clusters of microcalcifications and malignant masses, and other radiograms. Teleradiologic applications were considered as the first area of interests.

  2. 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.

  3. High-performance floating-point image computing workstation for medical applications

    Science.gov (United States)

    Mills, Karl S.; Wong, Gilman K.; Kim, Yongmin

    1990-07-01

    The medical imaging field relies increasingly on imaging and graphics techniques in diverse applications with needs similar to (or more stringent than) those of the military, industrial and scientific communities. However, most image processing and graphics systems available for use in medical imaging today are either expensive, specialized, or in most cases both. High performance imaging and graphics workstations which can provide real-time results for a number of applications, while maintaining affordability and flexibility, can facilitate the application of digital image computing techniques in many different areas. This paper describes the hardware and software architecture of a medium-cost floating-point image processing and display subsystem for the NeXT computer, and its applications as a medical imaging workstation. Medical imaging applications of the workstation include use in a Picture Archiving and Communications System (PACS), in multimodal image processing and 3-D graphics workstation for a broad range of imaging modalities, and as an electronic alternator utilizing its multiple monitor display capability and large and fast frame buffer. The subsystem provides a 2048 x 2048 x 32-bit frame buffer (16 Mbytes of image storage) and supports both 8-bit gray scale and 32-bit true color images. When used to display 8-bit gray scale images, up to four different 256-color palettes may be used for each of four 2K x 2K x 8-bit image frames. Three of these image frames can be used simultaneously to provide pixel selectable region of interest display. A 1280 x 1024 pixel screen with 1: 1 aspect ratio can be windowed into the frame buffer for display of any portion of the processed image or images. In addition, the system provides hardware support for integer zoom and an 82-color cursor. This subsystem is implemented on an add-in board occupying a single slot in the NeXT computer. Up to three boards may be added to the NeXT for multiple display capability (e

  4. Physics-based deformable organisms for medical image analysis

    Science.gov (United States)

    Hamarneh, Ghassan; McIntosh, Chris

    2005-04-01

    Previously, "Deformable organisms" were introduced as a novel paradigm for medical image analysis that uses artificial life modelling concepts. Deformable organisms were designed to complement the classical bottom-up deformable models methodologies (geometrical and physical layers), with top-down intelligent deformation control mechanisms (behavioral and cognitive layers). However, a true physical layer was absent and in order to complete medical image segmentation tasks, deformable organisms relied on pure geometry-based shape deformations guided by sensory data, prior structural knowledge, and expert-generated schedules of behaviors. In this paper we introduce the use of physics-based shape deformations within the deformable organisms framework yielding additional robustness by allowing intuitive real-time user guidance and interaction when necessary. We present the results of applying our physics-based deformable organisms, with an underlying dynamic spring-mass mesh model, to segmenting and labelling the corpus callosum in 2D midsagittal magnetic resonance images.

  5. A framework for interactive visualization of digital medical images.

    Science.gov (United States)

    Koehring, Andrew; Foo, Jung Leng; Miyano, Go; Lobe, Thom; Winer, Eliot

    2008-10-01

    The visualization of medical images obtained from scanning techniques such as computed tomography and magnetic resonance imaging is a well-researched field. However, advanced tools and methods to manipulate these data for surgical planning and other tasks have not seen widespread use among medical professionals. Radiologists have begun using more advanced visualization packages on desktop computer systems, but most physicians continue to work with basic two-dimensional grayscale images or not work directly with the data at all. In addition, new display technologies that are in use in other fields have yet to be fully applied in medicine. It is our estimation that usability is the key aspect in keeping this new technology from being more widely used by the medical community at large. Therefore, we have a software and hardware framework that not only make use of advanced visualization techniques, but also feature powerful, yet simple-to-use, interfaces. A virtual reality system was created to display volume-rendered medical models in three dimensions. It was designed to run in many configurations, from a large cluster of machines powering a multiwalled display down to a single desktop computer. An augmented reality system was also created for, literally, hands-on interaction when viewing models of medical data. Last, a desktop application was designed to provide a simple visualization tool, which can be run on nearly any computer at a user's disposal. This research is directed toward improving the capabilities of medical professionals in the tasks of preoperative planning, surgical training, diagnostic assistance, and patient education.

  6. Pseudo-color processing in nuclear medical image

    International Nuclear Information System (INIS)

    Wang Zhiqian; Jin Yongjie

    1992-01-01

    The application of pseudo-color technology in nuclear medical image processing is discussed. It includes selection of the number of pseudo-colors, method of realizing pseudo-color transformation, function of pseudo-color transformation and operation on the function

  7. Prototype Web-based continuing medical education using FlashPix images.

    Science.gov (United States)

    Landman, A; Yagi, Y; Gilbertson, J; Dawson, R; Marchevsky, A; Becich, M J

    2000-01-01

    Continuing Medical Education (CME) is a requirement among practicing physicians to promote continuous enhancement of clinical knowledge to reflect new developments in medical care. Previous research has harnessed the Web to disseminate complete pathology CME case studies including history, images, diagnoses, and discussions to the medical community. Users submit real-time diagnoses and receive instantaneous feedback, eliminating the need for hard copies of case material and case evaluation forms. This project extends the Web-based CME paradigm with the incorporation of multi-resolution FlashPix images and an intuitive, interactive user interface. The FlashPix file format combines a high-resolution version of an image with a hierarchy of several lower resolution copies, providing real-time magnification via a single image file. The Web interface was designed specifically to simulate microscopic analysis, using the latest Javascript, Java and Common Gateway Interface tools. As the project progresses to the evaluation stage, it is hoped that this active learning format will provide a practical and efficacious environment for continuing medical education with additional application potential in classroom demonstrations, proficiency testing, and telepathology. Using Microsoft Internet Explorer 4.0 and above, the working prototype Web-based CME environment is accessible at http://telepathology.upmc.edu/WebInterface/NewInterface/welcome.html.

  8. A Hybrid Technique for Medical Image Segmentation

    Directory of Open Access Journals (Sweden)

    Alamgir Nyma

    2012-01-01

    Full Text Available Medical image segmentation is an essential and challenging aspect in computer-aided diagnosis and also in pattern recognition research. This paper proposes a hybrid method for magnetic resonance (MR image segmentation. We first remove impulsive noise inherent in MR images by utilizing a vector median filter. Subsequently, Otsu thresholding is used as an initial coarse segmentation method that finds the homogeneous regions of the input image. Finally, an enhanced suppressed fuzzy c-means is used to partition brain MR images into multiple segments, which employs an optimal suppression factor for the perfect clustering in the given data set. To evaluate the robustness of the proposed approach in noisy environment, we add different types of noise and different amount of noise to T1-weighted brain MR images. Experimental results show that the proposed algorithm outperforms other FCM based algorithms in terms of segmentation accuracy for both noise-free and noise-inserted MR images.

  9. Multi-Modality Medical Image Fusion Based on Wavelet Analysis and Quality Evaluation

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    Multi-modality medical image fusion has more and more important applications in medical image analysisand understanding. In this paper, we develop and apply a multi-resolution method based on wavelet pyramid to fusemedical images from different modalities such as PET-MRI and CT-MRI. In particular, we evaluate the different fusionresults when applying different selection rules and obtain optimum combination of fusion parameters.

  10. What We Do and Do Not Know about Teaching Medical Image Interpretation

    NARCIS (Netherlands)

    Kok, E M; Van Geel, Koos; van Merrienboer, Jeroen J. G.; Robben, S G F

    2017-01-01

    Educators in medical image interpretation have difficulty finding scientific evidence as to how they should design their instruction. We review and comment on 81 papers that investigated instructional design in medical image interpretation. We distinguish between studies that evaluated complete

  11. Application of an internet web-site of medical images in tele-radiology

    International Nuclear Information System (INIS)

    Wang Weizhong; Wang Hua; Xie Jingxia; Wang Songzhang; Li Xiangdong; Qian Min; Cao Huixia

    2000-01-01

    Objective: To build and Internet web-site of medical images for tele-education and tele-consultation. Methods: Collecting medical images of cases that fulfilled diagnostic standards for teaching and were pathologically proved. The images were digitized using digital camera and scanner. Frontpage 98, Homesite 2.5 and text editors were used for programming. Results: The web site encompasses many useful cases and was update every week. With smart and friendly interface, easy used navigation, the site runs reliably in TCP/IP environment. The site's URL is http://imager.163.net. At present, the site has received about 100 visits per week. Conclusion: The well-designed and programmed internet web site of medical images would be easily acceptable and is going to play an important role in tele-education and tele-consultation

  12. Development of imaging biomarkers and generation of big data.

    Science.gov (United States)

    Alberich-Bayarri, Ángel; Hernández-Navarro, Rafael; Ruiz-Martínez, Enrique; García-Castro, Fabio; García-Juan, David; Martí-Bonmatí, Luis

    2017-06-01

    Several image processing algorithms have emerged to cover unmet clinical needs but their application to radiological routine with a clear clinical impact is still not straightforward. Moving from local to big infrastructures, such as Medical Imaging Biobanks (millions of studies), or even more, Federations of Medical Imaging Biobanks (in some cases totaling to hundreds of millions of studies) require the integration of automated pipelines for fast analysis of pooled data to extract clinically relevant conclusions, not uniquely linked to medical imaging, but in combination to other information such as genetic profiling. A general strategy for the development of imaging biomarkers and their integration in the cloud for the quantitative management and exploitation in large databases is herein presented. The proposed platform has been successfully launched and is being validated nowadays among the early adopters' community of radiologists, clinicians, and medical imaging researchers.

  13. Cloud-Based NoSQL Open Database of Pulmonary Nodules for Computer-Aided Lung Cancer Diagnosis and Reproducible Research.

    Science.gov (United States)

    Ferreira Junior, José Raniery; Oliveira, Marcelo Costa; de Azevedo-Marques, Paulo Mazzoncini

    2016-12-01

    Lung cancer is the leading cause of cancer-related deaths in the world, and its main manifestation is pulmonary nodules. Detection and classification of pulmonary nodules are challenging tasks that must be done by qualified specialists, but image interpretation errors make those tasks difficult. In order to aid radiologists on those hard tasks, it is important to integrate the computer-based tools with the lesion detection, pathology diagnosis, and image interpretation processes. However, computer-aided diagnosis research faces the problem of not having enough shared medical reference data for the development, testing, and evaluation of computational methods for diagnosis. In order to minimize this problem, this paper presents a public nonrelational document-oriented cloud-based database of pulmonary nodules characterized by 3D texture attributes, identified by experienced radiologists and classified in nine different subjective characteristics by the same specialists. Our goal with the development of this database is to improve computer-aided lung cancer diagnosis and pulmonary nodule detection and classification research through the deployment of this database in a cloud Database as a Service framework. Pulmonary nodule data was provided by the Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI), image descriptors were acquired by a volumetric texture analysis, and database schema was developed using a document-oriented Not only Structured Query Language (NoSQL) approach. The proposed database is now with 379 exams, 838 nodules, and 8237 images, 4029 of them are CT scans and 4208 manually segmented nodules, and it is allocated in a MongoDB instance on a cloud infrastructure.

  14. Seventh Medical Image Computing and Computer Assisted Intervention Conference (MICCAI 2012)

    CERN Document Server

    Miller, Karol; Nielsen, Poul; Computational Biomechanics for Medicine : Models, Algorithms and Implementation

    2013-01-01

    One of the greatest challenges for mechanical engineers is to extend the success of computational mechanics to fields outside traditional engineering, in particular to biology, biomedical sciences, and medicine. This book is an opportunity for computational biomechanics specialists to present and exchange opinions on the opportunities of applying their techniques to computer-integrated medicine. Computational Biomechanics for Medicine: Models, Algorithms and Implementation collects the papers from the Seventh Computational Biomechanics for Medicine Workshop held in Nice in conjunction with the Medical Image Computing and Computer Assisted Intervention conference. The topics covered include: medical image analysis, image-guided surgery, surgical simulation, surgical intervention planning, disease prognosis and diagnostics, injury mechanism analysis, implant and prostheses design, and medical robotics.

  15. A Total Information Management System For All Medical Images

    Science.gov (United States)

    Ouimette, Donald; Nudelman, Sol; Ramsby, Gale; Spackman, Thomas

    1985-09-01

    A PACS has been designed for the University of Connecticut Health Center to serve all departments acquiring images for diagnosis, surgery and therapy. It incorporates a multiple community communications architecture to provide complete information management for medical images, medical data and departmental administrative matter. The system is modular and expandable. It permits an initial installation for radiology and subsequent expansion to include other departments at the Health Center, beginning with internal medicine, surgery, ophthalmology and dentistry. The design permits sufficient expansion to offer the potential for accepting the additional burden of a hospital information system. Primary parameters that led to this system design were based on the anticipation that departments in time could achieve generating 60 to 90% of their images suited to insertion in a PACS, that a high network throughput for large block image transfers would be essen-tial and that total system reliability was fundamental to success.

  16. Beat-Frequency/Microsphere Medical Ultrasonic Imaging

    Science.gov (United States)

    Yost, William T.; Cantrell, John H.; Pretlow, Robert A., III

    1995-01-01

    Medical ultrasonic imaging system designed to provide quantitative data on various flows of blood in chambers, blood vessels, muscles, and tissues of heart. Sensitive enough to yield readings on flows of blood in heart even when microspheres used as ultrasonic contrast agents injected far from heart and diluted by circulation of blood elsewhere in body.

  17. WE-H-202-04: Advanced Medical Image Registration Techniques

    International Nuclear Information System (INIS)

    Christensen, G.

    2016-01-01

    Deformable image registration has now been commercially available for several years, with solid performance in a number of sites and for several applications including contour and dose mapping. However, more complex applications have arisen, such as assessing response to radiation therapy over time, registering images pre- and post-surgery, and auto-segmentation from atlases. These applications require innovative registration algorithms to achieve accurate alignment. The goal of this session is to highlight emerging registration technology and these new applications. The state of the art in image registration will be presented from an engineering perspective. Translational clinical applications will also be discussed to tie these new registration approaches together with imaging and radiation therapy applications in specific diseases such as cervical and lung cancers. Learning Objectives: To understand developing techniques and algorithms in deformable image registration that are likely to translate into clinical tools in the near future. To understand emerging imaging and radiation therapy clinical applications that require such new registration algorithms. Research supported in part by the National Institutes of Health under award numbers P01CA059827, R01CA166119, and R01CA166703. Disclosures: Phillips Medical systems (Hugo), Roger Koch (Christensen) support, Varian Medical Systems (Brock), licensing agreements from Raysearch (Brock) and Varian (Hugo).; K. Brock, Licensing Agreement - RaySearch Laboratories. Research Funding - Varian Medical Systems; G. Hugo, Research grant from National Institutes of Health, award number R01CA166119.; G. Christensen, Research support from NIH grants CA166119 and CA166703 and a gift from Roger Koch. There are no conflicts of interest.

  18. WE-H-202-04: Advanced Medical Image Registration Techniques

    Energy Technology Data Exchange (ETDEWEB)

    Christensen, G. [University of Iowa (United States)

    2016-06-15

    Deformable image registration has now been commercially available for several years, with solid performance in a number of sites and for several applications including contour and dose mapping. However, more complex applications have arisen, such as assessing response to radiation therapy over time, registering images pre- and post-surgery, and auto-segmentation from atlases. These applications require innovative registration algorithms to achieve accurate alignment. The goal of this session is to highlight emerging registration technology and these new applications. The state of the art in image registration will be presented from an engineering perspective. Translational clinical applications will also be discussed to tie these new registration approaches together with imaging and radiation therapy applications in specific diseases such as cervical and lung cancers. Learning Objectives: To understand developing techniques and algorithms in deformable image registration that are likely to translate into clinical tools in the near future. To understand emerging imaging and radiation therapy clinical applications that require such new registration algorithms. Research supported in part by the National Institutes of Health under award numbers P01CA059827, R01CA166119, and R01CA166703. Disclosures: Phillips Medical systems (Hugo), Roger Koch (Christensen) support, Varian Medical Systems (Brock), licensing agreements from Raysearch (Brock) and Varian (Hugo).; K. Brock, Licensing Agreement - RaySearch Laboratories. Research Funding - Varian Medical Systems; G. Hugo, Research grant from National Institutes of Health, award number R01CA166119.; G. Christensen, Research support from NIH grants CA166119 and CA166703 and a gift from Roger Koch. There are no conflicts of interest.

  19. A service protocol for post-processing of medical images on the mobile device

    Science.gov (United States)

    He, Longjun; Ming, Xing; Xu, Lang; Liu, Qian

    2014-03-01

    With computing capability and display size growing, the mobile device has been used as a tool to help clinicians view patient information and medical images anywhere and anytime. It is uneasy and time-consuming for transferring medical images with large data size from picture archiving and communication system to mobile client, since the wireless network is unstable and limited by bandwidth. Besides, limited by computing capability, memory and power endurance, it is hard to provide a satisfactory quality of experience for radiologists to handle some complex post-processing of medical images on the mobile device, such as real-time direct interactive three-dimensional visualization. In this work, remote rendering technology is employed to implement the post-processing of medical images instead of local rendering, and a service protocol is developed to standardize the communication between the render server and mobile client. In order to make mobile devices with different platforms be able to access post-processing of medical images, the Extensible Markup Language is taken to describe this protocol, which contains four main parts: user authentication, medical image query/ retrieval, 2D post-processing (e.g. window leveling, pixel values obtained) and 3D post-processing (e.g. maximum intensity projection, multi-planar reconstruction, curved planar reformation and direct volume rendering). And then an instance is implemented to verify the protocol. This instance can support the mobile device access post-processing of medical image services on the render server via a client application or on the web page.

  20. Novel gaseous detectors for medical imaging

    International Nuclear Information System (INIS)

    Danielsson, M.; Fonte, P.; Francke, T.; Iacobaeus, C.; Ostling, J.; Peskov, V.

    2004-01-01

    We have developed and successfully tested prototypes of two new types of gaseous detectors for medical imaging purposes. The first one is called the Electronic Portal Imaging Device (EPID). It is oriented on monitoring and the precise alignment of the therapeutic cancer treatment beam (pulsed gamma radiation) with respect to the patient's tumor position. The latest will be determined from an X-ray image of the patient obtained in the time intervals between the gamma pulses. The detector is based on a 'sandwich' of hole-type gaseous detectors (GEM and glass microcapillary plates) with metallic gamma and X-ray converters coated with CsI layers. The second detector is an X-ray image scanner oriented on mammography and other radiographic applications. It is based on specially developed by us high rate RPCs that are able to operate at rates of 10 5 Hz/mm 2 with a position resolution better than 50 μm at 1 atm. The quality of the images obtained with the latest version of this device were in most cases more superior than those obtained from commercially available detectors