WorldWideScience

Sample records for automated medical image

  1. Automated medical image segmentation techniques

    OpenAIRE

    Sharma Neeraj; Aggarwal Lalit

    2010-01-01

    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 ...

  2. Automative Multi Classifier Framework for Medical Image Analysis

    Directory of Open Access Journals (Sweden)

    R. Edbert Rajan

    2015-04-01

    Full Text Available Medical image processing is the technique used to create images of the human body for medical purposes. Nowadays, medical image processing plays a major role and a challenging solution for the critical stage in the medical line. Several researches have done in this area to enhance the techniques for medical image processing. However, due to some demerits met by some advanced technologies, there are still many aspects that need further development. Existing study evaluate the efficacy of the medical image analysis with the level-set shape along with fractal texture and intensity features to discriminate PF (Posterior Fossa tumor from other tissues in the brain image. To develop the medical image analysis and disease diagnosis, to devise an automotive subjective optimality model for segmentation of images based on different sets of selected features from the unsupervised learning model of extracted features. After segmentation, classification of images is done. The classification is processed by adapting the multiple classifier frameworks in the previous work based on the mutual information coefficient of the selected features underwent for image segmentation procedures. In this study, to enhance the classification strategy, we plan to implement enhanced multi classifier framework for the analysis of medical images and disease diagnosis. The performance parameter used for the analysis of the proposed enhanced multi classifier framework for medical image analysis is Multiple Class intensity, image quality, time consumption.

  3. Automated semantic indexing of imaging reports to support retrieval of medical images in the multimedia electronic medical record.

    Science.gov (United States)

    Lowe, H J; Antipov, I; Hersh, W; Smith, C A; Mailhot, M

    1999-12-01

    This paper describes preliminary work evaluating automated semantic indexing of radiology imaging reports to represent images stored in the Image Engine multimedia medical record system at the University of Pittsburgh Medical Center. The authors used the SAPHIRE indexing system to automatically identify important biomedical concepts within radiology reports and represent these concepts with terms from the 1998 edition of the U.S. National Library of Medicine's Unified Medical Language System (UMLS) Metathesaurus. This automated UMLS indexing was then compared with manual UMLS indexing of the same reports. Human indexing identified appropriate UMLS Metathesaurus descriptors for 81% of the important biomedical concepts contained in the report set. SAPHIRE automatically identified UMLS Metathesaurus descriptors for 64% of the important biomedical concepts contained in the report set. The overall conclusions of this pilot study were that the UMLS metathesaurus provided adequate coverage of the majority of the important concepts contained within the radiology report test set and that SAPHIRE could automatically identify and translate almost two thirds of these concepts into appropriate UMLS descriptors. Further work is required to improve both the recall and precision of this automated concept extraction process. PMID:10805018

  4. Automated semantic indexing of imaging reports to support retrieval of medical images in the multimedia electronic medical record.

    Science.gov (United States)

    Lowe, H J; Antipov, I; Hersh, W; Smith, C A; Mailhot, M

    1999-12-01

    This paper describes preliminary work evaluating automated semantic indexing of radiology imaging reports to represent images stored in the Image Engine multimedia medical record system at the University of Pittsburgh Medical Center. The authors used the SAPHIRE indexing system to automatically identify important biomedical concepts within radiology reports and represent these concepts with terms from the 1998 edition of the U.S. National Library of Medicine's Unified Medical Language System (UMLS) Metathesaurus. This automated UMLS indexing was then compared with manual UMLS indexing of the same reports. Human indexing identified appropriate UMLS Metathesaurus descriptors for 81% of the important biomedical concepts contained in the report set. SAPHIRE automatically identified UMLS Metathesaurus descriptors for 64% of the important biomedical concepts contained in the report set. The overall conclusions of this pilot study were that the UMLS metathesaurus provided adequate coverage of the majority of the important concepts contained within the radiology report test set and that SAPHIRE could automatically identify and translate almost two thirds of these concepts into appropriate UMLS descriptors. Further work is required to improve both the recall and precision of this automated concept extraction process.

  5. 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

  6. The Automated Medical Office

    OpenAIRE

    Petreman, Mel

    1990-01-01

    With shock and surprise many physicians learned in the 1980s that they must change the way they do business. Competition for patients, increasing government regulation, and the rapidly escalating risk of litigation forces physicians to seek modern remedies in office management. The author describes a medical clinic that strives to be paperless using electronic innovation to solve the problems of medical practice management. A computer software program to automate information management in a c...

  7. The automated medical office.

    Science.gov (United States)

    Petreman, M

    1990-08-01

    With shock and surprise many physicians learned in the 1980s that they must change the way they do business. Competition for patients, increasing government regulation, and the rapidly escalating risk of litigation forces physicians to seek modern remedies in office management. The author describes a medical clinic that strives to be paperless using electronic innovation to solve the problems of medical practice management. A computer software program to automate information management in a clinic shows that practical thinking linked to advanced technology can greatly improve office efficiency.

  8. [Value of automated medical indexing of an image database and a digital radiological library].

    Science.gov (United States)

    Duvauferrier, R; Le Beux, P; Pouliquen, B; Seka, L P; Morcet, N; Rolland, Y

    1997-06-01

    We indexed the contents of a radiology server on the web to facilitate access to research documents and to link reference texts to images contained in radiology databases. Indexation also allows case reports to be transformed with no supplementary work into formats compatible with computer-assisted training. Indexation was performed automatically by ADM-Index, the aim being to identify the medical concepts expressed within each medical text. Two types of texts were indexed: medical imaging reference books (Edicerf) and case reports with illustrations and captions (Iconocerf). These documents are now available on a web server with HTML format for Edicerf and on an Oracle database for Iconocerf. When the user consults a chapter of a book or a case report, the indexed terms are displayed in the heading; all reference texts and case reports containing the indexed terms can then be called up instantaneously. The user can express his search in natural language. Indexation follows the same process allowing instantaneous recall of all reference texts and case reports where the same concept appears in the diagnosis or clinical context. By using the context of the case reports as the search index, all case reports involving a common medical concept can be found. The context is interpreted as a question. When the user responds to this question, ADM-Index compares this response with the answer furnished by the reference texts and case reports. Correct or erroneous responses can thus be identified, converting the system into a computer-assisted training tool.

  9. Automated Medical Literature Retrieval

    Directory of Open Access Journals (Sweden)

    David Hawking

    2012-09-01

    Full Text Available Background The constantly growing publication rate of medical research articles puts increasing pressure on medical specialists who need to be aware of the recent developments in their field. The currently used literature retrieval systems allow researchers to find specific papers; however the search task is still repetitive and time-consuming. Aims In this paper we describe a system that retrieves medical publications by automatically generating queries based on data from an electronic patient record. This allows the doctor to focus on medical issues and provide an improved service to the patient, with higher confidence that it is underpinned by current research. Method Our research prototype automatically generates query terms based on the patient record and adds weight factors for each term. Currently the patient’s age is taken into account with a fuzzy logic derived weight, and terms describing blood-related anomalies are derived from recent blood test results. Conditionally selected homonyms are used for query expansion. The query retrieves matching records from a local index of PubMed publications and displays results in descending relevance for the given patient. Recent publications are clearly highlighted for instant recognition by the researcher. Results Nine medical specialists from the Royal Adelaide Hospital evaluated the system and submitted pre-trial and post-trial questionnaires. Throughout the study we received positive feedback as doctors felt the support provided by the prototype was useful, and which they would like to use in their daily routine. Conclusion By supporting the time-consuming task of query formulation and iterative modification as well as by presenting the search results in order of relevance for the specific patient, literature retrieval becomes part of the daily workflow of busy professionals.

  10. Medical imaging.

    OpenAIRE

    Kreel, L.

    1991-01-01

    There is now a wide choice of medical imaging to show both focal and diffuse pathologies in various organs. Conventional radiology with plain films, fluoroscopy and contrast medium have many advantages, being readily available with low-cost apparatus and a familiarity that almost leads to contempt. The use of plain films in chest disease and in trauma does not need emphasizing, yet there are still too many occasions when the answer obtainable from a plain radiograph has not been available. Th...

  11. A System For Automated Medical Photography

    Science.gov (United States)

    Tivattanasuk, Eva S.; Kaczoroski, Anthony J.; Rhodes, Michael L.

    1988-06-01

    A system is described that electronically controls the medical photography for a computed tomography (CT) scanner system. Multiple CT exams can be photographed with each image automatically adjusted to a specific gamma table presentation and positioned to any film location within a given film format. Our approach uses a library that can store 24 CT exam photography protocols. Library entries can be added, deleted, or edited. Mixed film formats, multiple image types, and automated annotation capabilities allow all CT exams to be filmed at our clinic cost-effectively and unattended. Using this automated approach to CT exam photography, one full-time equivalent CT technologist has been saved from the operational cost of our center. We outline the film protocol database, illustrate protocol options and by example, show the flexibility of this approach. Features of this system illustrate essential components of any such approach.

  12. 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....

  13. 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.......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....

  14. Medical linguistics: automated indexing into SNOMED.

    Science.gov (United States)

    Wingert, F

    1988-01-01

    This paper reviews the state of the art in processing medical language data. The area is divided into the topics: (1) morphologic analysis, (2) syntactic analysis, (3) semantic analysis, and (4) pragmatics. Additional attention is given to medical nomenclatures and classifications as the bases of (automated) indexing procedures which are required whenever medical information is formalized. These topics are completed by an evaluation of related data structures and methods used to organize language-based medical knowledge.

  15. 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 image...... fraction from 4D cardiac cine MRI, myocardial perfusion in bolus passage cardiac perfusion MRI, corpus callosum shape and area in mid-sagittal brain MRI, and finally, lung, heart, clavicle location and cardiothoracic ratio in anterior-posterior chest radiographs....

  16. Automated Orientation of Aerial Images

    DEFF Research Database (Denmark)

    Høhle, Joachim

    2002-01-01

    Methods for automated orientation of aerial images are presented. They are based on the use of templates, which are derived from existing databases, and area-based matching. The characteristics of available database information and the accuracy requirements for map compilation and orthoimage...... production are discussed on the example of Denmark. Details on the developed methods for interior and exterior orientation are described. Practical examples like the measurement of réseau images, updating of topographic databases and renewal of orthoimages are used to prove the feasibility of the developed...

  17. Medical Imaging: A Review

    Science.gov (United States)

    Ganguly, Debashis; Chakraborty, Srabonti; Balitanas, Maricel; Kim, Tai-Hoon

    The rapid progress of medical science and the invention of various medicines have benefited mankind and the whole civilization. Modern science also has been doing wonders in the surgical field. But, the proper and correct diagnosis of diseases is the primary necessity before the treatment. The more sophisticate the bio-instruments are, better diagnosis will be possible. The medical images plays an important role in clinical diagnosis and therapy of doctor and teaching and researching etc. Medical imaging is often thought of as a way to represent anatomical structures of the body with the help of X-ray computed tomography and magnetic resonance imaging. But often it is more useful for physiologic function rather than anatomy. With the growth of computer and image technology medical imaging has greatly influenced medical field. As the quality of medical imaging affects diagnosis the medical image processing has become a hotspot and the clinical applications wanting to store and retrieve images for future purpose needs some convenient process to store those images in details. This paper is a tutorial review of the medical image processing and repository techniques appeared in the literature.

  18. FUSION OF MEDICAL IMAGES

    Directory of Open Access Journals (Sweden)

    ALINE APARECIDA DE OLIVEIRA

    2013-08-01

    Full Text Available The use of image multiple modalities to achieve medical diagnosis has been commom practice lately. Nowadays the most used practice is medical image fusion, that is integrating information from several different methods within the same image. This paper aims at showing aplication and functionality of medical image fusion process such as Computed Tomography, Magnetic Resonance Imaging, Positron Emission Tomography and Doppler U.S. Image fusion process can be perfomed by pixel to pixel, region to region as well as based on decision taking. Free softwares can be found in the internet and images can be obtained either in separated or conneceted equipments. The choice of processes depends on several factors and the purpose of fusion as well as characteristics and conditions of each method should be taken into consideration. Currently equipment manufacturers are investing at improving the quality and detection capacity of images aiming at upgrading the fusion process which makes image interpretation more evident and trustworthy.

  19. [Medical image enhancement: Sharpening].

    Science.gov (United States)

    Kats, L; Vered, M

    2015-04-01

    Most digital imaging systems provide opportunities for image enhancement operations. These are applied to improve the original image and to make the image more appealing visually. One possible means of enhancing digital radiographic image is sharpening. The purpose of sharpening filters is to improve image quality by removing noise or edge enhancement. Sharpening filters may make the radiographic images subjectively more appealing. But during this process, important radiographic features may disappear while artifacts that simulate pathological process might be generated. Therefore, it is of utmost importance for dentists to be familiar with and aware of the use of image enhancement operations, provided by medical digital imaging programs. PMID:26255429

  20. 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...

  1. Medical Image Fusion

    Directory of Open Access Journals (Sweden)

    Mitra Rafizadeh

    2007-08-01

    Full Text Available Technological advances in medical imaging in the past two decades have enable radiologists to create images of the human body with unprecedented resolution. MRI, PET,... imaging devices can quickly acquire 3D images. Image fusion establishes an anatomical correlation between corresponding images derived from different examination. This fusion is applied either to combine images of different modalities (CT, MRI or single modality (PET-PET."nImage fusion is performed in two steps:"n1 Registration: spatial modification (eg. translation of model image relative to reference image in order to arrive at an ideal matching of both images. Registration methods are feature-based and intensity-based approaches."n2 Visualization: the goal of it is to depict the spatial relationship between the model image and refer-ence image. We can point out its clinical application in nuclear medicine (PET/CT.

  2. 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.

  3. Imaging and Analytics: The changing face of Medical Imaging

    Science.gov (United States)

    Foo, Thomas

    There have been significant technological advances in imaging capability over the past 40 years. Medical imaging capabilities have developed rapidly, along with technology development in computational processing speed and miniaturization. Moving to all-digital, the number of images that are acquired in a routine clinical examination has increased dramatically from under 50 images in the early days of CT and MRI to more than 500-1000 images today. The staggering number of images that are routinely acquired poses significant challenges for clinicians to interpret the data and to correctly identify the clinical problem. Although the time provided to render a clinical finding has not substantially changed, the amount of data available for interpretation has grown exponentially. In addition, the image quality (spatial resolution) and information content (physiologically-dependent image contrast) has also increased significantly with advances in medical imaging technology. On its current trajectory, medical imaging in the traditional sense is unsustainable. To assist in filtering and extracting the most relevant data elements from medical imaging, image analytics will have a much larger role. Automated image segmentation, generation of parametric image maps, and clinical decision support tools will be needed and developed apace to allow the clinician to manage, extract and utilize only the information that will help improve diagnostic accuracy and sensitivity. As medical imaging devices continue to improve in spatial resolution, functional and anatomical information content, image/data analytics will be more ubiquitous and integral to medical imaging capability.

  4. An automated imaging system for radiation biodosimetry.

    Science.gov (United States)

    Garty, Guy; Bigelow, Alan W; Repin, Mikhail; Turner, Helen C; Bian, Dakai; Balajee, Adayabalam S; Lyulko, Oleksandra V; Taveras, Maria; Yao, Y Lawrence; Brenner, David J

    2015-07-01

    We describe here an automated imaging system developed at the Center for High Throughput Minimally Invasive Radiation Biodosimetry. The imaging system is built around a fast, sensitive sCMOS camera and rapid switchable LED light source. It features complete automation of all the steps of the imaging process and contains built-in feedback loops to ensure proper operation. The imaging system is intended as a back end to the RABiT-a robotic platform for radiation biodosimetry. It is intended to automate image acquisition and analysis for four biodosimetry assays for which we have developed automated protocols: The Cytokinesis Blocked Micronucleus assay, the γ-H2AX assay, the Dicentric assay (using PNA or FISH probes) and the RABiT-BAND assay. PMID:25939519

  5. 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...... are shown. Both systems using linear and non-linear propagation of ultrasound are described. The blood velocity can also be non-invasively visualized using ultrasound and the basic signal processing for doing this is introduced. Examples for spectral velocity estimation, color flow maging and the new vector...

  6. Using grid technologies to face medical image analysis challenges

    OpenAIRE

    Montagnat, Johan; Breton, Vincent; Magnin, Isabelle

    2003-01-01

    International audience The availability of digital imagers inside hospitals and their ever growing inspection capabilities have established digital medical images as a key component of many pathologies diagnosis, follow-up and treatment. To face the growing image analysis requirements, automated medical image processing algorithms have been developed over the two past decades. In parallel, medical image databases have been set up in health centers. Some attempts have been made to cross dat...

  7. Automated image enhancement using power law transformations

    Indian Academy of Sciences (India)

    S P Vimal; P K Thiruvikraman

    2012-12-01

    We propose a scheme for automating power law transformations which are used for image enhancement. The scheme we propose does not require the user to choose the exponent in the power law transformation. This method works well for images having poor contrast, especially to those images in which the peaks corresponding to the background and the foreground are not widely separated.

  8. Automated image analysis techniques for cardiovascular magnetic resonance imaging

    NARCIS (Netherlands)

    Geest, Robertus Jacobus van der

    2011-01-01

    The introductory chapter provides an overview of various aspects related to quantitative analysis of cardiovascular MR (CMR) imaging studies. Subsequently, the thesis describes several automated methods for quantitative assessment of left ventricular function from CMR imaging studies. Several novel

  9. An automated vessel segmentation of retinal images using multiscale vesselness

    International Nuclear Information System (INIS)

    The ocular fundus image can provide information on pathological changes caused by local ocular diseases and early signs of certain systemic diseases, such as diabetes and hypertension. Automated analysis and interpretation of fundus images has become a necessary and important diagnostic procedure in ophthalmology. The extraction of blood vessels from retinal images is an important and challenging task in medical analysis and diagnosis. In this paper, we introduce an implementation of the anisotropic diffusion which allows reducing the noise and better preserving small structures like vessels in 2D images. A vessel detection filter, based on a multi-scale vesselness function, is then applied to enhance vascular structures.

  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. A cloud-based medical image repository

    Science.gov (United States)

    Maeder, Anthony J.; Planitz, Birgit M.; El Rifai, Diaa

    2012-02-01

    Many widely used digital medical image collections have been established but these are generally used as raw data sources without related image analysis toolsets. Providing associated functionality to allow specific types of operations to be performed on these images has proved beneficial in some cases (e.g. brain image registration and atlases). However, toolset development to provide generic image analysis functions on medical images has tended to be ad hoc, with Open Source options proliferating (e.g. ITK). Our Automated Medical Image Collection Annotation (AMICA) system is both an image repository, to which the research community can contribute image datasets, and a search/retrieval system that uses automated image annotation. AMICA was designed for the Windows Azure platform to leverage the flexibility and scalability of the cloud. It is intended that AMICA will expand beyond its initial pilot implementation (for brain CT, MR images) to accommodate a wide range of modalities and anatomical regions. This initiative aims to contribute to advances in clinical research by permitting a broader use and reuse of medical image data than is currently attainable. For example, cohort studies for cases with particular physiological or phenotypical profiles will be able to source and include enough cases to provide high statistical power, allowing more individualised risk factors to be assessed and thus allowing screening and staging processes to be optimised. Also, education, training and credentialing of clinicians in image interpretation, will be more effective because it will be possible to select instances of images with specific visual aspects, or correspond to types of cases where reading performance improvement is desirable.

  12. 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.

  13. Medical Image Analysis Facility

    Science.gov (United States)

    1978-01-01

    To improve the quality of photos sent to Earth by unmanned spacecraft. NASA's Jet Propulsion Laboratory (JPL) developed a computerized image enhancement process that brings out detail not visible in the basic photo. JPL is now applying this technology to biomedical research in its Medical lrnage Analysis Facility, which employs computer enhancement techniques to analyze x-ray films of internal organs, such as the heart and lung. A major objective is study of the effects of I stress on persons with heart disease. In animal tests, computerized image processing is being used to study coronary artery lesions and the degree to which they reduce arterial blood flow when stress is applied. The photos illustrate the enhancement process. The upper picture is an x-ray photo in which the artery (dotted line) is barely discernible; in the post-enhancement photo at right, the whole artery and the lesions along its wall are clearly visible. The Medical lrnage Analysis Facility offers a faster means of studying the effects of complex coronary lesions in humans, and the research now being conducted on animals is expected to have important application to diagnosis and treatment of human coronary disease. Other uses of the facility's image processing capability include analysis of muscle biopsy and pap smear specimens, and study of the microscopic structure of fibroprotein in the human lung. Working with JPL on experiments are NASA's Ames Research Center, the University of Southern California School of Medicine, and Rancho Los Amigos Hospital, Downey, California.

  14. Segmentation as a part of the intelligent medical image processing

    OpenAIRE

    Добріна, Ольга Олексіївна

    2012-01-01

    Segmentation is one of the key tools in medical image analysis that allows an accurate recognizing and delineating individual objects (e.g. organs) on the whole image quickly and effectively. In general, segmentation technics can be divided into two main groups: methods of explicitly specifying the desired feature and algorithms where the specification is implicit. Automated segmentation of medical images is a difficult task, because the images are often noisy and contain more than a single ...

  15. 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......, a good metric is required to measure distance or similarity between feature points so that the classification becomes feasible. Furthermore, in order to build a successful classifier, one needs to deeply understand how classifiers work. This thesis focuses on these three aspects of classification...... and explores these challenging areas. The first focus of the thesis is to properly combine different local feature experts and prior information to design an effective classifier. The preliminary classification results, provided by the experts, are fused in order to develop an automatic segmentation method...

  16. Automated Segmentation of Cardiac Magnetic Resonance Images

    DEFF Research Database (Denmark)

    Stegmann, Mikkel Bille; Nilsson, Jens Chr.; Grønning, Bjørn A.

    2001-01-01

    Magnetic resonance imaging (MRI) has been shown to be an accurate and precise technique to assess cardiac volumes and function in a non-invasive manner and is generally considered to be the current gold-standard for cardiac imaging [1]. Measurement of ventricular volumes, muscle mass and function...... is based on determination of the left-ventricular endocardial and epicardial borders. Since manual border detection is laborious, automated segmentation is highly desirable as a fast, objective and reproducible alternative. Automated segmentation will thus enhance comparability between and within cardiac...... studies and increase accuracy by allowing acquisition of thinner MRI-slices. This abstract demonstrates that statistical models of shape and appearance, namely the deformable models: Active Appearance Models, can successfully segment cardiac MRIs....

  17. Automated spectral imaging for clinical diagnostics

    Science.gov (United States)

    Breneman, John; Heffelfinger, David M.; Pettipiece, Ken; Tsai, Chris; Eden, Peter; Greene, Richard A.; Sorensen, Karen J.; Stubblebine, Will; Witney, Frank

    1998-04-01

    Bio-Rad Laboratories supplies imaging equipment for many applications in the life sciences. As part of our effort to offer more flexibility to the investigator, we are developing a microscope-based imaging spectrometer for the automated detection and analysis of either conventionally or fluorescently labeled samples. Immediate applications will include the use of fluorescence in situ hybridization (FISH) technology. The field of cytogenetics has benefited greatly from the increased sensitivity of FISH producing simplified analysis of complex chromosomal rearrangements. FISH methods for identification lends itself to automation more easily than the current cytogenetics industry standard of G- banding, however, the methods are complementary. Several technologies have been demonstrated successfully for analyzing the signals from labeled samples, including filter exchanging and interferometry. The detection system lends itself to other fluorescent applications including the display of labeled tissue sections, DNA chips, capillary electrophoresis or any other system using color as an event marker. Enhanced displays of conventionally stained specimens will also be possible.

  18. Medical alert bracelet (image)

    Science.gov (United States)

    People with diabetes should always wear a medical alert bracelet or necklace that emergency medical workers will be able to find. Medical identification products can help ensure proper treatment in an ...

  19. Prehospital digital photography and automated image transmission in an emergency medical service – an ancillary retrospective analysis of a prospective controlled trial

    Directory of Open Access Journals (Sweden)

    Bergrath Sebastian

    2013-01-01

    Full Text Available Abstract Background Still picture transmission was performed using a telemedicine system in an Emergency Medical Service (EMS during a prospective, controlled trial. In this ancillary, retrospective study the quality and content of the transmitted pictures and the possible influences of this application on prehospital time requirements were investigated. Methods A digital camera was used with a telemedicine system enabling encrypted audio and data transmission between an ambulance and a remotely located physician. By default, images were compressed (jpeg, 640 x 480 pixels. On occasion, this compression was deactivated (3648 x 2736 pixels. Two independent investigators assessed all transmitted pictures according to predefined criteria. In cases of different ratings, a third investigator had final decision competence. Patient characteristics and time intervals were extracted from the EMS protocol sheets and dispatch centre reports. Results Overall 314 pictures (mean 2.77 ± 2.42 pictures/mission were transmitted during 113 missions (group 1. Pictures were not taken for 151 missions (group 2. Regarding picture quality, the content of 240 (76.4% pictures was clearly identifiable; 45 (14.3% pictures were considered “limited quality” and 29 (9.2% pictures were deemed “not useful” due to not/hardly identifiable content. For pictures with file compression (n = 84 missions and without (n = 17 missions, the content was clearly identifiable in 74% and 97% of the pictures, respectively (p = 0.003. Medical reports (n = 98, 32.8%, medication lists (n = 49, 16.4% and 12-lead ECGs (n = 28, 9.4% were most frequently photographed. The patient characteristics of group 1 vs. 2 were as follows: median age – 72.5 vs. 56.5 years, p = 0.001; frequency of acute coronary syndrome – 24/113 vs. 15/151, p = 0.014. The NACA scores and gender distribution were comparable. Median on-scene times were longer with picture

  20. 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...... 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......-time data acquisition system. The system were implemented using the commercial available 2202 ProFocus BK Medical ultrasound scanner equipped with a research interface and a standard PC. The main feature of the system is the possibility to acquire several seconds of interleaved data, switching between...

  1. Generalized nonconvex optimization for medical image segmentation

    Science.gov (United States)

    Mitra, Sunanda; Joshi, Sujit

    2000-06-01

    Design of a generalized technique for medical image segmentation is a challenging task. Currently a number of approaches are being investigated for 2-D and 3-D medical image segmentation for diagnostic and research applications. The methodology used in this work is aimed at obtaining a generalized solution of non-convex optimization problems by including a structural constraint of mass or density and the concept of additivity properties of entropy to a recently developed statistical approach to clustering and classification. The original computationally intensive procedure is made more efficient both in processing time and accuracy by employing a new similarity parameter for generating the initial clusters that are updated by minimizing an energy function relating the image entropy and expected distortion. The application of the computationally intensive yet generalized solution to nonconvex optimization to a limited set of medical images has resulted in excellent segmentation when compared to other clustering based segmentation approaches. The addition of the parametric approach to determine the initial number of clusters allows significant reduction in processing time and better design of automated segmentation procedure. This research work generalizes a deterministic annealing i.e. a specific statistical approach to solve nonconvex optimization problems by developing a more efficient technique applicable to nonconvex optimization problems (getting trapped in local minima). However, the DA approach is extremely computationally intensive for applications such as image segmentation. The new integrated approach developed in this work allows this optimization technique to be used for medical image segmentation.

  2. Automated retinal image analysis for diabetic retinopathy in telemedicine.

    Science.gov (United States)

    Sim, Dawn A; Keane, Pearse A; Tufail, Adnan; Egan, Catherine A; Aiello, Lloyd Paul; Silva, Paolo S

    2015-03-01

    There will be an estimated 552 million persons with diabetes globally by the year 2030. Over half of these individuals will develop diabetic retinopathy, representing a nearly insurmountable burden for providing diabetes eye care. Telemedicine programmes have the capability to distribute quality eye care to virtually any location and address the lack of access to ophthalmic services. In most programmes, there is currently a heavy reliance on specially trained retinal image graders, a resource in short supply worldwide. These factors necessitate an image grading automation process to increase the speed of retinal image evaluation while maintaining accuracy and cost effectiveness. Several automatic retinal image analysis systems designed for use in telemedicine have recently become commercially available. Such systems have the potential to substantially improve the manner by which diabetes eye care is delivered by providing automated real-time evaluation to expedite diagnosis and referral if required. Furthermore, integration with electronic medical records may allow a more accurate prognostication for individual patients and may provide predictive modelling of medical risk factors based on broad population data. PMID:25697773

  3. Automated Image Retrieval of Chest CT Images Based on Local Grey Scale Invariant Features.

    Science.gov (United States)

    Arrais Porto, Marcelo; Cordeiro d'Ornellas, Marcos

    2015-01-01

    Textual-based tools are regularly employed to retrieve medical images for reading and interpretation using current retrieval Picture Archiving and Communication Systems (PACS) but pose some drawbacks. All-purpose content-based image retrieval (CBIR) systems are limited when dealing with medical images and do not fit well into PACS workflow and clinical practice. This paper presents an automated image retrieval approach for chest CT images based local grey scale invariant features from a local database. Performance was measured in terms of precision and recall, average retrieval precision (ARP), and average retrieval rate (ARR). Preliminary results have shown the effectiveness of the proposed approach. The prototype is also a useful tool for radiology research and education, providing valuable information to the medical and broader healthcare community. PMID:26262345

  4. Automated assessment of medical training evaluation text.

    Science.gov (United States)

    Zhang, Rui; Pakhomov, Serguei; Gladding, Sophia; Aylward, Michael; Borman-Shoap, Emily; Melton, Genevieve B

    2012-01-01

    Medical post-graduate residency training and medical student training increasingly utilize electronic systems to evaluate trainee performance based on defined training competencies with quantitative and qualitative data, the later of which typically consists of text comments. Medical education is concomitantly becoming a growing area of clinical research. While electronic systems have proliferated in number, little work has been done to help manage and analyze qualitative data from these evaluations. We explored the use of text-mining techniques to assist medical education researchers in sentiment analysis and topic analysis of residency evaluations with a sample of 812 evaluation statements. While comments were predominantly positive, sentiment analysis improved the ability to discriminate statements with 93% accuracy. Similar to other domains, Latent Dirichlet Analysis and Information Gain revealed groups of core subjects and appear to be useful for identifying topics from this data.

  5. Medical Imaging with Neural Networks

    International Nuclear Information System (INIS)

    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)

  6. Desktop supercomputers. Advance medical imaging.

    Science.gov (United States)

    Frisiello, R S

    1991-02-01

    Medical imaging tools that radiologists as well as a wide range of clinicians and healthcare professionals have come to depend upon are emerging into the next phase of functionality. The strides being made in supercomputing technologies--including reduction of size and price--are pushing medical imaging to a new level of accuracy and functionality.

  7. Distributed Object Medical Imaging Model

    CERN Document Server

    Noor, Ahmad Shukri Mohd

    2009-01-01

    Digital medical informatics and images are commonly used in hospitals today,. Because of the interrelatedness of the radiology department and other departments, especially the intensive care unit and emergency department, the transmission and sharing of medical images has become a critical issue. Our research group has developed a Java-based Distributed Object Medical Imaging Model(DOMIM) to facilitate the rapid development and deployment of medical imaging applications in a distributed environment that can be shared and used by related departments and mobile physiciansDOMIM is a unique suite of multimedia telemedicine applications developed for the use by medical related organizations. The applications support realtime patients' data, image files, audio and video diagnosis annotation exchanges. The DOMIM enables joint collaboration between radiologists and physicians while they are at distant geographical locations. The DOMIM environment consists of heterogeneous, autonomous, and legacy resources. The Common...

  8. MEDICAL IMAGE SEGMENTATION

    Directory of Open Access Journals (Sweden)

    Madhavi Latha

    2010-07-01

    Full Text Available Image segmentation is an essential but critical component in low level vision image analysis, pattern recognition, and in robotic systems. It is one of the most difficult and challenging tasks in image processing which determines the quality of the final result of the image analysis. Image segmentation is the process of dividing an image into different regions such that each region is homogeneous. Various image segmentation algorithms are discussed. Some examples in different image formats are presented and overall results discussed and compared considering different parameters.

  9. Despeckling of Medical Ultrasound Images

    OpenAIRE

    Michailovich, Oleg V.; Tannenbaum, Allen

    2006-01-01

    Speckle noise is an inherent property of medical ultrasound imaging, and it generally tends to reduce the image resolution and contrast, thereby reducing the diagnostic value of this imaging modality. As a result, speckle noise reduction is an important prerequisite, whenever ultrasound imaging is used for tissue characterization. Among the many methods that have been proposed to perform this task, there exists a class of approaches that use a multiplicative model of speckled image formation ...

  10. Automated landmark-guided deformable image registration

    Science.gov (United States)

    Kearney, Vasant; Chen, Susie; Gu, Xuejun; Chiu, Tsuicheng; Liu, Honghuan; Jiang, Lan; Wang, Jing; Yordy, John; Nedzi, Lucien; Mao, Weihua

    2015-01-01

    The purpose of this work is to develop an automated landmark-guided deformable image registration (LDIR) algorithm between the planning CT and daily cone-beam CT (CBCT) with low image quality. This method uses an automated landmark generation algorithm in conjunction with a local small volume gradient matching search engine to map corresponding landmarks between the CBCT and the planning CT. The landmarks act as stabilizing control points in the following Demons deformable image registration. LDIR is implemented on graphics processing units (GPUs) for parallel computation to achieve ultra fast calculation. The accuracy of the LDIR algorithm has been evaluated on a synthetic case in the presence of different noise levels and data of six head and neck cancer patients. The results indicate that LDIR performed better than rigid registration, Demons, and intensity corrected Demons for all similarity metrics used. In conclusion, LDIR achieves high accuracy in the presence of multimodality intensity mismatch and CBCT noise contamination, while simultaneously preserving high computational efficiency.

  11. Automated Quality Assurance of Medical Digital X-Ray Equipment

    International Nuclear Information System (INIS)

    Quality assurance of the x-ray equipment includes a set of various tests among which are installation and periodic exams performed by qualified engineers as well as daily routine tests carried out by the medical staff of the Radiology Department. As a rule, the decision concerning the applicability of the x-ray equipment for using in clinical studies is made on the basis of the routine tests results. The presented method is based on the detector's output signals, Signal-to-Noise Ratio and Modulation Transfer Function evaluation in automated way using the simple test-object's digital image registered with given geometry and x-ray exposure parameters settings. Rectangular 20 mm thick aluminum plate with fixed 1 mm thick well-finished steel edge (for general x-ray radiography/fluoroscopy systems) or 2 mm thick aluminum plate with fixed 1 mm thick aluminum well-finished edge (for digital x-ray mammography systems) can be used as a test equipment. Relevant to the decision concerning the x-ray device operation status are the parameters: deviations from the reference levels of the tube voltage and mAs as well as internal detector's noise variance and detector's gain deviations. Everyday testing procedure includes the following steps. On the first step the roentgenographer places the test-object at the center of the detector's surface, makes an exposure with specified parameters setting and geometry and after this, test results are displayed on the work station monitor or console screen in automatic way. In order to provide an automated regime of the presenting algorithm, the software must be integrated with the program module intended for the x-ray device control. The use of the presented method in clinical practice provides the reliable daily monitoring of the x-ray equipment operation status prior to its utilizing for patient diagnostic process. As a rule, it will take not more than 3-5 minutes for the roentgenographer to complete the routine

  12. Automated Quality Assurance Applied to Mammographic Imaging

    Directory of Open Access Journals (Sweden)

    Anne Davis

    2002-07-01

    Full Text Available Quality control in mammography is based upon subjective interpretation of the image quality of a test phantom. In order to suppress subjectivity due to the human observer, automated computer analysis of the Leeds TOR(MAM test phantom is investigated. Texture analysis via grey-level co-occurrence matrices is used to detect structures in the test object. Scoring of the substructures in the phantom is based on grey-level differences between regions and information from grey-level co-occurrence matrices. The results from scoring groups of particles within the phantom are presented.

  13. Medical imaging technology and applications

    CERN Document Server

    Iniewski, Krzysztof

    2014-01-01

    The book has two intentions. First, it assembles the latest research in the field of medical imaging technology in one place. Detailed descriptions of current state-of-the-art medical imaging systems (comprised of x-ray CT, MRI, ultrasound, and nuclear medicine) and data processing techniques are discussed. Information is provided that will give interested engineers and scientists a solid foundation from which to build with additional resources. Secondly, it exposes the reader to myriad applications that medical imaging technology has enabled.

  14. Medical image processing

    CERN Document Server

    Dougherty, Geoff

    2011-01-01

    This book is designed for end users in the field of digital imaging, who wish to update their skills and understanding with the latest techniques in image analysis. This book emphasizes the conceptual framework of image analysis and the effective use of image processing tools. It uses applications in a variety of fields to demonstrate and consolidate both specific and general concepts, and to build intuition, insight and understanding. Although the chapters are essentially self-contained they reference other chapters to form an integrated whole. Each chapter employs a pedagogical approach to e

  15. Automated radiopharmaceutical production systems for positron imaging

    International Nuclear Information System (INIS)

    This study provides information that will lead towards the widespread availability of systems for routine production of positron emitting isotopes and radiopharmaceuticals in a medical setting. The first part describes the collection, evaluation, and preparation in convenient form of the pertinent physical, engineering, and chemical data related to reaction yields and isotope production. The emphasis is on the production of the four short-lived isotopes C-11, N-13, O-15 and F-18. The second part is an assessment of radiation sources including cyclotrons, linear accelerators, and other more exotic devices. Various aspects of instrumentation including ease of installation, cost, and shielding are included. The third part of the study reviews the preparation of precursors and radiopharmaceuticals by automated chemical systems. 182 refs., 3 figs., 15 tabs

  16. 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.

  17. Java advanced medical image toolkit

    International Nuclear Information System (INIS)

    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

  18. Medical Image Fusion Using Discrete Wavelet Transform

    OpenAIRE

    Nayera Nahvi; Deep Mittal

    2014-01-01

    Medical image fusion is the process of registering and combining multiple images from single or multiple imaging modalities to improve the imaging quality and reduce randomness and redundancy in order to increase the clinical applicability of medical images for diagnosis and assessment of medical problems. Multimodal medical image fusion algorithms and devices have shown notable achievements in improving clinical accuracy of decisions based on medical images. The domain where ...

  19. Automated 3D renal segmentation based on image partitioning

    Science.gov (United States)

    Yeghiazaryan, Varduhi; Voiculescu, Irina D.

    2016-03-01

    Despite several decades of research into segmentation techniques, automated medical image segmentation is barely usable in a clinical context, and still at vast user time expense. This paper illustrates unsupervised organ segmentation through the use of a novel automated labelling approximation algorithm followed by a hypersurface front propagation method. The approximation stage relies on a pre-computed image partition forest obtained directly from CT scan data. We have implemented all procedures to operate directly on 3D volumes, rather than slice-by-slice, because our algorithms are dimensionality-independent. The results picture segmentations which identify kidneys, but can easily be extrapolated to other body parts. Quantitative analysis of our automated segmentation compared against hand-segmented gold standards indicates an average Dice similarity coefficient of 90%. Results were obtained over volumes of CT data with 9 kidneys, computing both volume-based similarity measures (such as the Dice and Jaccard coefficients, true positive volume fraction) and size-based measures (such as the relative volume difference). The analysis considered both healthy and diseased kidneys, although extreme pathological cases were excluded from the overall count. Such cases are difficult to segment both manually and automatically due to the large amplitude of Hounsfield unit distribution in the scan, and the wide spread of the tumorous tissue inside the abdomen. In the case of kidneys that have maintained their shape, the similarity range lies around the values obtained for inter-operator variability. Whilst the procedure is fully automated, our tools also provide a light level of manual editing.

  20. Automated vertebra identification in CT images

    Science.gov (United States)

    Ehm, Matthias; Klinder, Tobias; Kneser, Reinhard; Lorenz, Cristian

    2009-02-01

    In this paper, we describe and compare methods for automatically identifying individual vertebrae in arbitrary CT images. The identification is an essential precondition for a subsequent model-based segmentation, which is used in a wide field of orthopedic, neurological, and oncological applications, e.g., spinal biopsies or the insertion of pedicle screws. Since adjacent vertebrae show similar characteristics, an automated labeling of the spine column is a very challenging task, especially if no surrounding reference structures can be taken into account. Furthermore, vertebra identification is complicated due to the fact that many images are bounded to a very limited field of view and may contain only few vertebrae. We propose and evaluate two methods for automatically labeling the spine column by evaluating similarities between given models and vertebral objects. In one method, object boundary information is taken into account by applying a Generalized Hough Transform (GHT) for each vertebral object. In the other method, appearance models containing mean gray value information are registered to each vertebral object using cross and local correlation as similarity measures for the optimization function. The GHT is advantageous in terms of computational performance but cuts back concerning the identification rate. A correct labeling of the vertebral column has been successfully performed on 93% of the test set consisting of 63 disparate input images using rigid image registration with local correlation as similarity measure.

  1. Computerized Station For Semi-Automated Testing Image Intensifier Tubes

    OpenAIRE

    Chrzanowski Krzysztof

    2015-01-01

    Testing of image intensifier tubes is still done using mostly manual methods due to a series of both technical and legal problems with test automation. Computerized stations for semi-automated testing of IITs are considered as novelty and are under continuous improvements. This paper presents a novel test station that enables semi-automated measurement of image intensifier tubes. Wide test capabilities and advanced design solutions rise the developed test station significantly above the curre...

  2. Distributed Object Medical Imaging Model

    Directory of Open Access Journals (Sweden)

    Ahmad Shukri Mohd Noor

    2009-09-01

    Full Text Available Digital medical informatics and images are commonly used in hospitals today. Because of the interrelatedness of the radiology department and other departments, especially the intensive care unit and emergency department, the transmission and sharing of medical images has become a critical issue. Our research group has developed a Java-based Distributed Object Medical Imaging Model(DOMIM to facilitate the rapid development and deployment of medical imaging applications in a distributed environment that can be shared and used by related departments and mobile physiciansDOMIM is a unique suite of multimedia telemedicine applications developed for the use by medical related organizations. The applications support realtime patients' data, image files, audio and video diagnosis annotation exchanges. The DOMIM enables joint collaboration between radiologists and physicians while they are at distant geographical locations. The DOMIM environment consists of heterogeneous, autonomous, and legacy resources. The Common Object Request Broker Architecture (CORBA, Java Database Connectivity (JDBC, and Java language provide the capability to combine the DOMIM resources into an integrated, interoperable, and scalable system. The underneath technology, including IDL ORB, Event Service, IIOP JDBC/ODBC, legacy system wrapping and Java implementation are explored. This paper explores a distributed collaborative CORBA/JDBC based framework that will enhance medical information management requirements and development. It encompasses a new paradigm for the delivery of health services that requires process reengineering, cultural changes, as well as organizational changes.

  3. Automated object detection for astronomical images

    Science.gov (United States)

    Orellana, Sonny; Zhao, Lei; Boussalis, Helen; Liu, Charles; Rad, Khosrow; Dong, Jane

    2005-10-01

    Sponsored by the National Aeronautical Space Association (NASA), the Synergetic Education and Research in Enabling NASA-centered Academic Development of Engineers and Space Scientists (SERENADES) Laboratory was established at California State University, Los Angeles (CSULA). An important on-going research activity in this lab is to develop an easy-to-use image analysis software with the capability of automated object detection to facilitate astronomical research. This paper presented a fast object detection algorithm based on the characteristics of astronomical images. This algorithm consists of three steps. First, the foreground and background are separated using histogram-based approach. Second, connectivity analysis is conducted to extract individual object. The final step is post processing which refines the detection results. To improve the detection accuracy when some objects are blocked by clouds, top-hat transform is employed to split the sky into cloudy region and non-cloudy region. A multi-level thresholding algorithm is developed to select the optimal threshold for different regions. Experimental results show that our proposed approach can successfully detect the blocked objects by clouds.

  4. Physics instrumentation for medical imaging

    International Nuclear Information System (INIS)

    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

  5. Resolution enhancement in medical ultrasound imaging

    OpenAIRE

    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...

  6. Investigation of Bias in Continuous Medical Image Label Fusion

    OpenAIRE

    Fangxu Xing; Prince, Jerry L.; Landman, Bennett A.

    2016-01-01

    Image labeling is essential for analyzing morphometric features in medical imaging data. Labels can be obtained by either human interaction or automated segmentation algorithms, both of which suffer from errors. The Simultaneous Truth and Performance Level Estimation (STAPLE) algorithm for both discrete-valued and continuous-valued labels has been proposed to find the consensus fusion while simultaneously estimating rater performance. In this paper, we first show that the previously reported ...

  7. An automated digital imaging system for environmental monitoring applications

    Science.gov (United States)

    Bogle, Rian; Velasco, Miguel; Vogel, John

    2013-01-01

    Recent improvements in the affordability and availability of high-resolution digital cameras, data loggers, embedded computers, and radio/cellular modems have advanced the development of sophisticated automated systems for remote imaging. Researchers have successfully placed and operated automated digital cameras in remote locations and in extremes of temperature and humidity, ranging from the islands of the South Pacific to the Mojave Desert and the Grand Canyon. With the integration of environmental sensors, these automated systems are able to respond to local conditions and modify their imaging regimes as needed. In this report we describe in detail the design of one type of automated imaging system developed by our group. It is easily replicated, low-cost, highly robust, and is a stand-alone automated camera designed to be placed in remote locations, without wireless connectivity.

  8. Classification of Medical Brain Images

    Institute of Scientific and Technical Information of China (English)

    Pan Haiwei(潘海为); Li Jianzhong; Zhang Wei

    2003-01-01

    Since brain tumors endanger people's living quality and even their lives, the accuracy of classification becomes more important. Conventional classifying techniques are used to deal with those datasets with characters and numbers. It is difficult, however, to apply them to datasets that include brain images and medical history (alphanumeric data), especially to guarantee the accuracy. For these datasets, this paper combines the knowledge of medical field and improves the traditional decision tree. The new classification algorithm with the direction of the medical knowledge not only adds the interaction with the doctors, but also enhances the quality of classification. The algorithm has been used on real brain CT images and a precious rule has been gained from the experiments. This paper shows that the algorithm works well for real CT data.

  9. 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...

  10. Image analysis and platform development for automated phenotyping in cytomics

    NARCIS (Netherlands)

    Yan, Kuan

    2013-01-01

    This thesis is dedicated to the empirical study of image analysis in HT/HC screen study. Often a HT/HC screening produces extensive amounts that cannot be manually analyzed. Thus, an automated image analysis solution is prior to an objective understanding of the raw image data. Compared to general a

  11. Computerized Station For Semi-Automated Testing Image Intensifier Tubes

    Directory of Open Access Journals (Sweden)

    Chrzanowski Krzysztof

    2015-09-01

    Full Text Available Testing of image intensifier tubes is still done using mostly manual methods due to a series of both technical and legal problems with test automation. Computerized stations for semi-automated testing of IITs are considered as novelty and are under continuous improvements. This paper presents a novel test station that enables semi-automated measurement of image intensifier tubes. Wide test capabilities and advanced design solutions rise the developed test station significantly above the current level of night vision metrology.

  12. Fundamental mathematics and physics of medical imaging

    CERN Document Server

    Lancaster, Jack

    2016-01-01

    Authored by a leading educator, this book is ideal for medical imaging courses. Rather than focus on imaging modalities the book delves into the mechanisms of image formation and image quality common to all imaging systems: contrast mechanisms, noise, and spatial and temporal resolution. This is an extensively revised new edition of The Physics of Medical X-Ray Imaging by Bruce Hasegawa (Medical Physics Publishing, 1991). A wide range of modalities are covered including X-ray CT, MRI and SPECT.

  13. Medical Imaging of Hyperpolarized Gases

    Science.gov (United States)

    Miller, G. Wilson

    2009-08-01

    Since the introduction of hyperpolarized 3He and 129Xe as gaseous MRI contrast agents more than a decade ago, a rich variety of imaging techniques and medical applications have been developed. Magnetic resonance imaging of the inhaled gas depicts ventilated lung airspaces with unprecedented detail, and allows one to track airflow and pulmonary mechanics during respiration. Information about lung structure and function can also be obtained using the physical properties of the gas, including spin relaxation in the presence of oxygen, restricted diffusion inside the alveolar airspaces, and the NMR frequency shift of xenon dissolved in blood and tissue.

  14. Medical Imaging of Hyperpolarized Gases

    International Nuclear Information System (INIS)

    Since the introduction of hyperpolarized 3He and 129Xe as gaseous MRI contrast agents more than a decade ago, a rich variety of imaging techniques and medical applications have been developed. Magnetic resonance imaging of the inhaled gas depicts ventilated lung airspaces with unprecedented detail, and allows one to track airflow and pulmonary mechanics during respiration. Information about lung structure and function can also be obtained using the physical properties of the gas, including spin relaxation in the presence of oxygen, restricted diffusion inside the alveolar airspaces, and the NMR frequency shift of xenon dissolved in blood and tissue.

  15. Image segmentation for automated dental identification

    Science.gov (United States)

    Haj Said, Eyad; Nassar, Diaa Eldin M.; Ammar, Hany H.

    2006-02-01

    Dental features are one of few biometric identifiers that qualify for postmortem identification; therefore, creation of an Automated Dental Identification System (ADIS) with goals and objectives similar to the Automated Fingerprint Identification System (AFIS) has received increased attention. As a part of ADIS, teeth segmentation from dental radiographs films is an essential step in the identification process. In this paper, we introduce a fully automated approach for teeth segmentation with goal to extract at least one tooth from the dental radiograph film. We evaluate our approach based on theoretical and empirical basis, and we compare its performance with the performance of other approaches introduced in the literature. The results show that our approach exhibits the lowest failure rate and the highest optimality among all full automated approaches introduced in the literature.

  16. 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

  17. 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

  18. Radioisotopes and medical imaging in Sri Lanka

    International Nuclear Information System (INIS)

    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

  19. Towards Automated Annotation of Benthic Survey Images: Variability of Human Experts and Operational Modes of Automation.

    Science.gov (United States)

    Beijbom, Oscar; Edmunds, Peter J; Roelfsema, Chris; Smith, Jennifer; Kline, David I; Neal, Benjamin P; Dunlap, Matthew J; Moriarty, Vincent; Fan, Tung-Yung; Tan, Chih-Jui; Chan, Stephen; Treibitz, Tali; Gamst, Anthony; Mitchell, B Greg; Kriegman, David

    2015-01-01

    Global climate change and other anthropogenic stressors have heightened the need to rapidly characterize ecological changes in marine benthic communities across large scales. Digital photography enables rapid collection of survey images to meet this need, but the subsequent image annotation is typically a time consuming, manual task. We investigated the feasibility of using automated point-annotation to expedite cover estimation of the 17 dominant benthic categories from survey-images captured at four Pacific coral reefs. Inter- and intra- annotator variability among six human experts was quantified and compared to semi- and fully- automated annotation methods, which are made available at coralnet.ucsd.edu. Our results indicate high expert agreement for identification of coral genera, but lower agreement for algal functional groups, in particular between turf algae and crustose coralline algae. This indicates the need for unequivocal definitions of algal groups, careful training of multiple annotators, and enhanced imaging technology. Semi-automated annotation, where 50% of the annotation decisions were performed automatically, yielded cover estimate errors comparable to those of the human experts. Furthermore, fully-automated annotation yielded rapid, unbiased cover estimates but with increased variance. These results show that automated annotation can increase spatial coverage and decrease time and financial outlay for image-based reef surveys. PMID:26154157

  20. Towards Automated Annotation of Benthic Survey Images: Variability of Human Experts and Operational Modes of Automation.

    Directory of Open Access Journals (Sweden)

    Oscar Beijbom

    Full Text Available Global climate change and other anthropogenic stressors have heightened the need to rapidly characterize ecological changes in marine benthic communities across large scales. Digital photography enables rapid collection of survey images to meet this need, but the subsequent image annotation is typically a time consuming, manual task. We investigated the feasibility of using automated point-annotation to expedite cover estimation of the 17 dominant benthic categories from survey-images captured at four Pacific coral reefs. Inter- and intra- annotator variability among six human experts was quantified and compared to semi- and fully- automated annotation methods, which are made available at coralnet.ucsd.edu. Our results indicate high expert agreement for identification of coral genera, but lower agreement for algal functional groups, in particular between turf algae and crustose coralline algae. This indicates the need for unequivocal definitions of algal groups, careful training of multiple annotators, and enhanced imaging technology. Semi-automated annotation, where 50% of the annotation decisions were performed automatically, yielded cover estimate errors comparable to those of the human experts. Furthermore, fully-automated annotation yielded rapid, unbiased cover estimates but with increased variance. These results show that automated annotation can increase spatial coverage and decrease time and financial outlay for image-based reef surveys.

  1. Content-based retrieval based on binary vectors for 2-D medical images

    Institute of Scientific and Technical Information of China (English)

    龚鹏; 邹亚东; 洪海

    2003-01-01

    In medical research and clinical diagnosis, automated or computer-assisted classification and retrieval methods are highly desirable to offset the high cost of manual classification and manipulation by medical experts. To facilitate the decision-making in the health-care and the related areas, in this paper, a two-step content-based medical image retrieval algorithm is proposed. Firstly, in the preprocessing step, the image segmentation is performed to distinguish image objects, and on the basis of the ...

  2. Multiscale Medical Image Fusion in Wavelet Domain

    OpenAIRE

    Rajiv Singh; Ashish Khare

    2013-01-01

    Wavelet transforms have emerged as a powerful tool in image fusion. However, the study and analysis of medical image fusion is still a challenging area of research. Therefore, in this paper, we propose a multiscale fusion of multimodal medical images in wavelet domain. Fusion of medical images has been performed at multiple scales varying from minimum to maximum level using maximum selection rule which provides more flexibility and choice to select the relevant fused images. The experimental ...

  3. Survey on Denoising Techniques in Medical Images

    Directory of Open Access Journals (Sweden)

    Ravi Mohan

    2013-07-01

    Full Text Available Denoising of Medical Images is challenging problems for researchers noise is not only effect the quality of image but it Creates a major change in calculation of medical field. The Medical Images normally have a problem of high level components of noises. There are different techniques for producing medical images such as Magnetic Resonance Imaging(MRI, X-ray, Computed Tomography and Ultrasound, during this process noise is added that decreases the image quality and image analysis. Image denoising is an important task in image processing, use of wavelet transform improves the quality of an image and reduces noise level. Noise is an inherent property of medical imaging, and it generally tends to reduce the image resolution and contrast, thereby reducing the diagnostic value of this imaging modality there is an emergent attentiveness in using multi-resolution Wavelet filters in a variety of medical imaging applications. We Have review recent wavelet based denoising techniques for medical ultrasound, magnetic resonance images, and some tomography imaging techniques like Positron Emission tomography and Computer tomography imaging and discuss some of their potential applications in the clinical investigations of the brain. The paper deals with the use of wavelet transform for signal and image de-noising employing a selected method of thresholding of appropriate decomposition coefficients

  4. Towards Automated Annotation of Benthic Survey Images: Variability of Human Experts and Operational Modes of Automation

    OpenAIRE

    Oscar Beijbom; Edmunds, Peter J.; Chris Roelfsema; Jennifer Smith; Kline, David I.; Neal, Benjamin P.; Matthew J Dunlap; Vincent Moriarty; Tung-Yung Fan; Chih-Jui Tan; Stephen Chan; Tali Treibitz; Anthony Gamst; B. Greg Mitchell; David Kriegman

    2015-01-01

    Global climate change and other anthropogenic stressors have heightened the need to rapidly characterize ecological changes in marine benthic communities across large scales. Digital photography enables rapid collection of survey images to meet this need, but the subsequent image annotation is typically a time consuming, manual task. We investigated the feasibility of using automated point-annotation to expedite cover estimation of the 17 dominant benthic categories from survey-images capture...

  5. Cloud computing in medical imaging.

    Science.gov (United States)

    Kagadis, George C; Kloukinas, Christos; Moore, Kevin; Philbin, Jim; Papadimitroulas, Panagiotis; Alexakos, Christos; Nagy, Paul G; Visvikis, Dimitris; Hendee, William R

    2013-07-01

    Over the past century technology has played a decisive role in defining, driving, and reinventing procedures, devices, and pharmaceuticals in healthcare. Cloud computing has been introduced only recently but is already one of the major topics of discussion in research and clinical settings. The provision of extensive, easily accessible, and reconfigurable resources such as virtual systems, platforms, and applications with low service cost has caught the attention of many researchers and clinicians. Healthcare researchers are moving their efforts to the cloud, because they need adequate resources to process, store, exchange, and use large quantities of medical data. This Vision 20/20 paper addresses major questions related to the applicability of advanced cloud computing in medical imaging. The paper also considers security and ethical issues that accompany cloud computing.

  6. A machine learning approach to quantifying noise in medical images

    Science.gov (United States)

    Chowdhury, Aritra; Sevinsky, Christopher J.; Yener, Bülent; Aggour, Kareem S.; Gustafson, Steven M.

    2016-03-01

    As advances in medical imaging technology are resulting in significant growth of biomedical image data, new techniques are needed to automate the process of identifying images of low quality. Automation is needed because it is very time consuming for a domain expert such as a medical practitioner or a biologist to manually separate good images from bad ones. While there are plenty of de-noising algorithms in the literature, their focus is on designing filters which are necessary but not sufficient for determining how useful an image is to a domain expert. Thus a computational tool is needed to assign a score to each image based on its perceived quality. In this paper, we introduce a machine learning-based score and call it the Quality of Image (QoI) score. The QoI score is computed by combining the confidence values of two popular classification techniques—support vector machines (SVMs) and Naïve Bayes classifiers. We test our technique on clinical image data obtained from cancerous tissue samples. We used 747 tissue samples that are stained by four different markers (abbreviated as CK15, pck26, E_cad and Vimentin) leading to a total of 2,988 images. The results show that images can be classified as good (high QoI), bad (low QoI) or ugly (intermediate QoI) based on their QoI scores. Our automated labeling is in agreement with the domain experts with a bi-modal classification accuracy of 94%, on average. Furthermore, ugly images can be recovered and forwarded for further post-processing.

  7. Automated identification of animal species in camera trap images

    NARCIS (Netherlands)

    Yu, X.; Wang, J.; Kays, R.; Jansen, P.A.; Wang, T.; Huang, T.

    2013-01-01

    Image sensors are increasingly being used in biodiversity monitoring, with each study generating many thousands or millions of pictures. Efficiently identifying the species captured by each image is a critical challenge for the advancement of this field. Here, we present an automated species identif

  8. Automated diabetic retinopathy imaging in Indian eyes: A pilot study

    Directory of Open Access Journals (Sweden)

    Rupak Roy

    2014-01-01

    Full Text Available Aim: To evaluate the efficacy of an automated retinal image grading system in diabetic retinopathy (DR screening. Materials and Methods: Color fundus images of patients of a DR screening project were analyzed for the purpose of the study. For each eye two set of images were acquired, one centerd on the disk and the other centerd on the macula. All images were processed by automated DR screening software (Retmarker. The results were compared to ophthalmologist grading of the same set of photographs. Results: 5780 images of 1445 patients were analyzed. Patients were screened into two categories DR or no DR. Image quality was high, medium and low in 71 (4.91%, 1117 (77.30% and 257 (17.78% patients respectively. Specificity and sensitivity for detecting DR in the high, medium and low group were (0.59, 0.91; (0.11, 0.95 and (0.93, 0.14. Conclusion: Automated retinal image screening system for DR had a high sensitivity in high and medium quality images. Automated DR grading software′s hold promise in future screening programs.

  9. Despeckling of medical ultrasound images.

    Science.gov (United States)

    Michailovich, Oleg V; Tannenbaum, Allen

    2006-01-01

    Speckle noise is an inherent property of medical ultrasound imaging, and it generally tends to reduce the image resolution and contrast, thereby reducing the diagnostic value of this imaging modality. As a result, speckle noise reduction is an important prerequisite, whenever ultrasound imaging is used for tissue characterization. Among the many methods that have been proposed to perform this task, there exists a class of approaches that use a multiplicative model of speckled image formation and take advantage of the logarithmical transformation in order to convert multiplicative speckle noise into additive noise. The common assumption made in a dominant number of such studies is that the samples of the additive noise are mutually uncorrelated and obey a Gaussian distribution. The present study shows conceptually and experimentally that this assumption is oversimplified and unnatural. Moreover, it may lead to inadequate performance of the speckle reduction methods. The study introduces a simple preprocessing procedure, which modifies the acquired radio-frequency images (without affecting the anatomical information they contain), so that the noise in the log-transformation domain becomes very close in its behavior to a white Gaussian noise. As a result, the preprocessing allows filtering methods based on assuming the noise to be white and Gaussian, to perform in nearly optimal conditions. The study evaluates performances of three different, nonlinear filters--wavelet denoising, total variation filtering, and anisotropic diffusion--and demonstrates that, in all these cases, the proposed preprocessing significantly improves the quality of resultant images. Our numerical tests include a series of computer-simulated and in vivo experiments. PMID:16471433

  10. Medical Image Retrieval: A Multimodal Approach.

    Science.gov (United States)

    Cao, Yu; Steffey, Shawn; He, Jianbiao; Xiao, Degui; Tao, Cui; Chen, Ping; Müller, Henning

    2014-01-01

    Medical imaging is becoming a vital component of war on cancer. Tremendous amounts of medical image data are captured and recorded in a digital format during cancer care and cancer research. Facing such an unprecedented volume of image data with heterogeneous image modalities, it is necessary to develop effective and efficient content-based medical image retrieval systems for cancer clinical practice and research. While substantial progress has been made in different areas of content-based image retrieval (CBIR) research, direct applications of existing CBIR techniques to the medical images produced unsatisfactory results, because of the unique characteristics of medical images. In this paper, we develop a new multimodal medical image retrieval approach based on the recent advances in the statistical graphic model and deep learning. Specifically, we first investigate a new extended probabilistic Latent Semantic Analysis model to integrate the visual and textual information from medical images to bridge the semantic gap. We then develop a new deep Boltzmann machine-based multimodal learning model to learn the joint density model from multimodal information in order to derive the missing modality. Experimental results with large volume of real-world medical images have shown that our new approach is a promising solution for the next-generation medical imaging indexing and retrieval system. PMID:26309389

  11. Medical Image Retrieval: A Multimodal Approach.

    Science.gov (United States)

    Cao, Yu; Steffey, Shawn; He, Jianbiao; Xiao, Degui; Tao, Cui; Chen, Ping; Müller, Henning

    2014-01-01

    Medical imaging is becoming a vital component of war on cancer. Tremendous amounts of medical image data are captured and recorded in a digital format during cancer care and cancer research. Facing such an unprecedented volume of image data with heterogeneous image modalities, it is necessary to develop effective and efficient content-based medical image retrieval systems for cancer clinical practice and research. While substantial progress has been made in different areas of content-based image retrieval (CBIR) research, direct applications of existing CBIR techniques to the medical images produced unsatisfactory results, because of the unique characteristics of medical images. In this paper, we develop a new multimodal medical image retrieval approach based on the recent advances in the statistical graphic model and deep learning. Specifically, we first investigate a new extended probabilistic Latent Semantic Analysis model to integrate the visual and textual information from medical images to bridge the semantic gap. We then develop a new deep Boltzmann machine-based multimodal learning model to learn the joint density model from multimodal information in order to derive the missing modality. Experimental results with large volume of real-world medical images have shown that our new approach is a promising solution for the next-generation medical imaging indexing and retrieval system.

  12. Automation of Cassini Support Imaging Uplink Command Development

    Science.gov (United States)

    Ly-Hollins, Lisa; Breneman, Herbert H.; Brooks, Robert

    2010-01-01

    "Support imaging" is imagery requested by other Cassini science teams to aid in the interpretation of their data. The generation of the spacecraft command sequences for these images is performed by the Cassini Instrument Operations Team. The process initially established for doing this was very labor-intensive, tedious and prone to human error. Team management recognized this process as one that could easily benefit from automation. Team members were tasked to document the existing manual process, develop a plan and strategy to automate the process, implement the plan and strategy, test and validate the new automated process, and deliver the new software tools and documentation to Flight Operations for use during the Cassini extended mission. In addition to the goals of higher efficiency and lower risk in the processing of support imaging requests, an effort was made to maximize adaptability of the process to accommodate uplink procedure changes and the potential addition of new capabilities outside the scope of the initial effort.

  13. 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.

  14. 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. PMID:27577479

  15. Extended -Regular Sequence for Automated Analysis of Microarray Images

    Directory of Open Access Journals (Sweden)

    Jin Hee-Jeong

    2006-01-01

    Full Text Available Microarray study enables us to obtain hundreds of thousands of expressions of genes or genotypes at once, and it is an indispensable technology for genome research. The first step is the analysis of scanned microarray images. This is the most important procedure for obtaining biologically reliable data. Currently most microarray image processing systems require burdensome manual block/spot indexing work. Since the amount of experimental data is increasing very quickly, automated microarray image analysis software becomes important. In this paper, we propose two automated methods for analyzing microarray images. First, we propose the extended -regular sequence to index blocks and spots, which enables a novel automatic gridding procedure. Second, we provide a methodology, hierarchical metagrid alignment, to allow reliable and efficient batch processing for a set of microarray images. Experimental results show that the proposed methods are more reliable and convenient than the commercial tools.

  16. Fuzzy Emotional Semantic Analysis and Automated Annotation of Scene Images

    Directory of Open Access Journals (Sweden)

    Jianfang Cao

    2015-01-01

    Full Text Available With the advances in electronic and imaging techniques, the production of digital images has rapidly increased, and the extraction and automated annotation of emotional semantics implied by images have become issues that must be urgently addressed. To better simulate human subjectivity and ambiguity for understanding scene images, the current study proposes an emotional semantic annotation method for scene images based on fuzzy set theory. A fuzzy membership degree was calculated to describe the emotional degree of a scene image and was implemented using the Adaboost algorithm and a back-propagation (BP neural network. The automated annotation method was trained and tested using scene images from the SUN Database. The annotation results were then compared with those based on artificial annotation. Our method showed an annotation accuracy rate of 91.2% for basic emotional values and 82.4% after extended emotional values were added, which correspond to increases of 5.5% and 8.9%, respectively, compared with the results from using a single BP neural network algorithm. Furthermore, the retrieval accuracy rate based on our method reached approximately 89%. This study attempts to lay a solid foundation for the automated emotional semantic annotation of more types of images and therefore is of practical significance.

  17. The ImageCLEFmed Medical Image Retrieval Task Test Collection

    OpenAIRE

    Hersh, William; Müller, Henning; Kalpathy-Cramer, Jayashree

    2008-01-01

    A growing number of clinicians, educators, researchers, and others use digital images in their work and search for them via image retrieval systems. Yet, this area of information retrieval is much less understood and developed than searching for text-based content, such as biomedical literature and its derivations. The goal of the ImageCLEF medical image retrieval task (ImageCLEFmed) is to improve understanding and system capability in search for medical images. In this paper, we describe the...

  18. Automated image registration for FDOPA PET studies

    Science.gov (United States)

    Lin, Kang-Ping; Huang, Sung-Cheng; Yu, Dan-Chu; Melega, William; Barrio, Jorge R.; Phelps, Michael E.

    1996-12-01

    In this study, various image registration methods are investigated for their suitability for registration of L-6-[18F]-fluoro-DOPA (FDOPA) PET images. Five different optimization criteria including sum of absolute difference (SAD), mean square difference (MSD), cross-correlation coefficient (CC), standard deviation of pixel ratio (SDPR), and stochastic sign change (SSC) were implemented and Powell's algorithm was used to optimize the criteria. The optimization criteria were calculated either unidirectionally (i.e. only evaluating the criteria for comparing the resliced image 1 with the original image 2) or bidirectionally (i.e. averaging the criteria for comparing the resliced image 1 with the original image 2 and those for the sliced image 2 with the original image 1). Monkey FDOPA images taken at various known orientations were used to evaluate the accuracy of different methods. A set of human FDOPA dynamic images was used to investigate the ability of the methods for correcting subject movement. It was found that a large improvement in performance resulted when bidirectional rather than unidirectional criteria were used. Overall, the SAD, MSD and SDPR methods were found to be comparable in performance and were suitable for registering FDOPA images. The MSD method gave more adequate results for frame-to-frame image registration for correcting subject movement during a dynamic FDOPA study. The utility of the registration method is further demonstrated by registering FDOPA images in monkeys before and after amphetamine injection to reveal more clearly the changes in spatial distribution of FDOPA due to the drug intervention.

  19. 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.)

  20. Automated Localization of Optic Disc in Retinal Images

    Directory of Open Access Journals (Sweden)

    Deepali A.Godse

    2013-03-01

    Full Text Available An efficient detection of optic disc (OD in colour retinal images is a significant task in an automated retinal image analysis system. Most of the algorithms developed for OD detection are especially applicable to normal and healthy retinal images. It is a challenging task to detect OD in all types of retinal images, that is, normal, healthy images as well as abnormal, that is, images affected due to disease. This paper presents an automated system to locate an OD and its centre in all types of retinal images. The ensemble of steps based on different criteria produces more accurate results. The proposed algorithm gives excellent results and avoids false OD detection. The technique is developed and tested on standard databases provided for researchers on internet, Diaretdb0 (130 images, Diaretdb1 (89 images, Drive (40 images and local database (194 images. The local database images are collected from ophthalmic clinics. It is able to locate OD and its centre in 98.45% of all tested cases. The results achieved by different algorithms can be compared when algorithms are applied on same standard databases. This comparison is also discussed in this paper which shows that the proposed algorithm is more efficient.

  1. Automated image capture and defects detection by cavity inspection camera

    International Nuclear Information System (INIS)

    The defects as pit and scar make electric/magnetic field enhance and it cause field emission and quench in superconducting cavities. We used inspection camera to find these defects, but the current system which operated by human often mistake file naming and require long acquisition time. This study aims to solve these problems with introduction of cavity driving automation and defect inspection. We used rs232c of serial communication to drive of motor and camera for the automation of the inspection camera, and we used defect inspection software with defects reference images and pattern match software with the OpenCV lib. By the automation, we cut down the acquisition time from 8 hours to 2 hours, however defect inspection software is under preparation. The defect inspection software has a problem of complexity of image back ground. (author)

  2. Automated technological radiation installation for sterilization of medical goods

    Science.gov (United States)

    Auslender, V. L.; Bryazgin, A. A.; Voronin, L. A.; Polyakov, V. A.; Grodetskiy, V. P.; Izhboldin, I. K.; Mirsaetov, O. M.; Petrov, A. M.; Obidin, Yu. T.; Ponomaryov, V. N.

    1998-06-01

    Last years most of the developed countries are using radiation method based on electron accelerators for sterilization of medical goods as mostly safe and ecologically pure from all known methods. The report describes in details the automated installation for sterilization of single-use syringes working in the city of Izhevsk, Russia. The syringes are irradiated from two sides inside the packs containing 250 units each. The packs are automatically turned on the inclined part of the conveyor under influence of their own weight. The syringes are posed vertically along the beam fall. The ration of maximal absorbed dose to minimal is 1.4. The productive rate of installation is no less 100 000 syringes per hour. The installation is based on the linear pulse electron accelerator ILU-6. It is the single cavity machine with electron energy up to 2.5 MeV and average beam power up to 20 kW. The pulse nature of the current and automatic control system permit to vary the absorbed dose in great range. The electron energy, beam current, pulse repetition rate, beam position in the extracted window and transportation of the treated products are computer controlled.

  3. Automated morphometry of transgenic mouse brains in MR images

    NARCIS (Netherlands)

    Scheenstra, Alize Elske Hiltje

    2011-01-01

    Quantitative and local morphometry of mouse brain MRI is a relatively new field of research, where automated methods can be exploited to rapidly provide accurate and repeatable results. In this thesis we reviewed several existing methods and applications of quantitative morphometry to brain MR image

  4. Automated image analysis in the study of collagenous colitis

    DEFF Research Database (Denmark)

    Fiehn, Anne-Marie Kanstrup; Kristensson, Martin; Engel, Ulla;

    2016-01-01

    PURPOSE: The aim of this study was to develop an automated image analysis software to measure the thickness of the subepithelial collagenous band in colon biopsies with collagenous colitis (CC) and incomplete CC (CCi). The software measures the thickness of the collagenous band on microscopic...

  5. Watermarking patient data in encrypted medical images

    Indian Academy of Sciences (India)

    A Lavanya; V Natarajan

    2012-12-01

    In this paper, we propose a method for watermarking medical images for data integrity which consists of image encryption, data embedding and image-recovery phases. Data embedding can be completely recovered from the watermarked image after the watermark has been extracted. In the proposed method, we utilize standard stream cipher for image encryption and selecting non-region of interest tile to embed patient data. We show that the lower bound of the PSNR (peak-signal-to-noise-ratio) values for medical images is about 48 dB. Experimental results demonstrate that the proposed scheme can embed a large amount of data while keeping high visual quality of test images.

  6. PERFORMANCE EVALUATION OF CONTENT BASED IMAGE RETRIEVAL FOR MEDICAL IMAGES

    Directory of Open Access Journals (Sweden)

    SASI KUMAR. M

    2013-04-01

    Full Text Available Content-based image retrieval (CBIR technology benefits not only large image collections management, but also helps clinical care, biomedical research, and education. Digital images are found in X-Rays, MRI, CT which are used for diagnosing and planning treatment schedules. Thus, visual information management is challenging as the data quantity available is huge. Currently, available medical databases utilization is limited image retrieval issues. Archived digital medical images retrieval is always challenging and this is being researched more as images are of great importance in patient diagnosis, therapy, medical reference, and medical training. In this paper, an image matching scheme using Discrete Sine Transform for relevant feature extraction is presented. The efficiency of different algorithm for classifying the features to retrieve medical images is investigated.

  7. Pharmacy automation in Navy Medicine: a study of Naval Medical Center San Diego

    OpenAIRE

    Merkl, Abbie J.

    2015-01-01

    Approved for public release; distribution is unlimited In August 2012, Naval Medical Center San Diego implemented a state-of-the-art pharmacy automation system in an effort to reduce cost and improve efficiency. The objective of this study is to quantify the increase in efficiency after installation through a focus on observed post-automation prescription fill times during calendar year 2014 (CY2014) and a simulated pre-automation process. With a response of average daily prescription fill...

  8. SU-E-I-94: Automated Image Quality Assessment of Radiographic Systems Using An Anthropomorphic Phantom

    International Nuclear Information System (INIS)

    Purpose: In a large, academic medical center, consistent radiographic imaging performance is difficult to routinely monitor and maintain, especially for a fleet consisting of multiple vendors, models, software versions, and numerous imaging protocols. Thus, an automated image quality control methodology has been implemented using routine image quality assessment with a physical, stylized anthropomorphic chest phantom. Methods: The “Duke” Phantom (Digital Phantom 07-646, Supertech, Elkhart, IN) was imaged twice on each of 13 radiographic units from a variety of vendors at 13 primary care clinics. The first acquisition used the clinical PA chest protocol to acquire the post-processed “FOR PRESENTATION” image. The second image was acquired without an antiscatter grid followed by collection of the “FOR PROCESSING” image. Manual CNR measurements were made from the largest and thickest contrast-detail inserts in the lung, heart, and abdominal regions of the phantom in each image. An automated image registration algorithm was used to estimate the CNR of the same insert using similar ROIs. Automated measurements were then compared to the manual measurements. Results: Automatic and manual CNR measurements obtained from “FOR PRESENTATION” images had average percent differences of 0.42%±5.18%, −3.44%±4.85%, and 1.04%±3.15% in the lung, heart, and abdominal regions, respectively; measurements obtained from “FOR PROCESSING” images had average percent differences of -0.63%±6.66%, −0.97%±3.92%, and −0.53%±4.18%, respectively. The maximum absolute difference in CNR was 15.78%, 10.89%, and 8.73% in the respective regions. In addition to CNR assessment of the largest and thickest contrast-detail inserts, the automated method also provided CNR estimates for all 75 contrast-detail inserts in each phantom image. Conclusion: Automated analysis of a radiographic phantom has been shown to be a fast, robust, and objective means for assessing radiographic

  9. [Medical imaging: its medical economics and recent situation in Japan.].

    Science.gov (United States)

    Imai, Keiko

    2006-01-01

    Two fields of radiology, medical imaging and radiation therapy, are coded separately in medical fee system, and the health care statistics of 2003 shows that expenditure on the former was 5.2% of the whole medical cost and the latter 0.28%. Introduction of DPC, an abbreviation of Diagnostic Procedure Combination, was carried out in 2003, which was an essential reform of medical fee payment system that have been managed on fee-for-service base throughout, and 22% of beds for acute patients care are under the control of DPC payment in 2006. As medical imaging procedures are basically classified in inclusive payment in DPC system, their accurate statistics cannot be figured out because of the lack of description of individual procedures in DPC bills. Policy-making of medical economics will suffer a great loss from the deficiency of detailed data in published statistics. Important role in clinical diagnoses of CT and MR results an increase of fee paid for them up to more than half of total expenditure on medical imaging. So, dominant reduction of examination fee has been done for MR imaging, especially in 2002, to reduce the total cost of medical imaging. Follows could be featured as major topics of medical imaging in health insurance system, (a) fee is newly assigned for electronic handling of CT-and-MR images, and nuclear medicine, and (b) there is still a mismatch between actual payment and quality of medical facilities. As matters related to medical imaging, the followings should be stressed; (a) numbers of CT and MR units per population are dominantly high among OECD countries, but, those controlled by qualified radiologists are at the average level of those countries, (b) there is a big difference of MR examination quality among medical facilities, and (c) 76% of newly-installed high-end MR units are supplied by foreign industries. Hopefully, there will be an increase in the concern to medical fee payment system and health care cost because they possibly

  10. Automated image-based tracking and its application in ecology.

    Science.gov (United States)

    Dell, Anthony I; Bender, John A; Branson, Kristin; Couzin, Iain D; de Polavieja, Gonzalo G; Noldus, Lucas P J J; Pérez-Escudero, Alfonso; Perona, Pietro; Straw, Andrew D; Wikelski, Martin; Brose, Ulrich

    2014-07-01

    The behavior of individuals determines the strength and outcome of ecological interactions, which drive population, community, and ecosystem organization. Bio-logging, such as telemetry and animal-borne imaging, provides essential individual viewpoints, tracks, and life histories, but requires capture of individuals and is often impractical to scale. Recent developments in automated image-based tracking offers opportunities to remotely quantify and understand individual behavior at scales and resolutions not previously possible, providing an essential supplement to other tracking methodologies in ecology. Automated image-based tracking should continue to advance the field of ecology by enabling better understanding of the linkages between individual and higher-level ecological processes, via high-throughput quantitative analysis of complex ecological patterns and processes across scales, including analysis of environmental drivers.

  11. Automated vasculature extraction from placenta images

    Science.gov (United States)

    Almoussa, Nizar; Dutra, Brittany; Lampe, Bryce; Getreuer, Pascal; Wittman, Todd; Salafia, Carolyn; Vese, Luminita

    2011-03-01

    Recent research in perinatal pathology argues that analyzing properties of the placenta may reveal important information on how certain diseases progress. One important property is the structure of the placental blood vessels, which supply a fetus with all of its oxygen and nutrition. An essential step in the analysis of the vascular network pattern is the extraction of the blood vessels, which has only been done manually through a costly and time-consuming process. There is no existing method to automatically detect placental blood vessels; in addition, the large variation in the shape, color, and texture of the placenta makes it difficult to apply standard edge-detection algorithms. We describe a method to automatically detect and extract blood vessels from a given image by using image processing techniques and neural networks. We evaluate several local features for every pixel, in addition to a novel modification to an existing road detector. Pixels belonging to blood vessel regions have recognizable responses; hence, we use an artificial neural network to identify the pattern of blood vessels. A set of images where blood vessels are manually highlighted is used to train the network. We then apply the neural network to recognize blood vessels in new images. The network is effective in capturing the most prominent vascular structures of the placenta.

  12. Automated Pointing of Cardiac Imaging Catheters.

    Science.gov (United States)

    Loschak, Paul M; Brattain, Laura J; Howe, Robert D

    2013-12-31

    Intracardiac echocardiography (ICE) catheters enable high-quality ultrasound imaging within the heart, but their use in guiding procedures is limited due to the difficulty of manually pointing them at structures of interest. This paper presents the design and testing of a catheter steering model for robotic control of commercial ICE catheters. The four actuated degrees of freedom (4-DOF) are two catheter handle knobs to produce bi-directional bending in combination with rotation and translation of the handle. An extra degree of freedom in the system allows the imaging plane (dependent on orientation) to be directed at an object of interest. A closed form solution for forward and inverse kinematics enables control of the catheter tip position and the imaging plane orientation. The proposed algorithms were validated with a robotic test bed using electromagnetic sensor tracking of the catheter tip. The ability to automatically acquire imaging targets in the heart may improve the efficiency and effectiveness of intracardiac catheter interventions by allowing visualization of soft tissue structures that are not visible using standard fluoroscopic guidance. Although the system has been developed and tested for manipulating ICE catheters, the methods described here are applicable to any long thin tendon-driven tool (with single or bi-directional bending) requiring accurate tip position and orientation control.

  13. The accuracy of a designed software for automated localization of craniofacial landmarks on CBCT images

    International Nuclear Information System (INIS)

    Two-dimensional projection radiographs have been traditionally considered the modality of choice for cephalometric analysis. To overcome the shortcomings of two-dimensional images, three-dimensional computed tomography (CT) has been used to evaluate craniofacial structures. However, manual landmark detection depends on medical expertise, and the process is time-consuming. The present study was designed to produce software capable of automated localization of craniofacial landmarks on cone beam (CB) CT images based on image registration and to evaluate its accuracy. The software was designed using MATLAB programming language. The technique was a combination of feature-based (principal axes registration) and voxel similarity-based methods for image registration. A total of 8 CBCT images were selected as our reference images for creating a head atlas. Then, 20 CBCT images were randomly selected as the test images for evaluating the method. Three experts twice located 14 landmarks in all 28 CBCT images during two examinations set 6 weeks apart. The differences in the distances of coordinates of each landmark on each image between manual and automated detection methods were calculated and reported as mean errors. The combined intraclass correlation coefficient for intraobserver reliability was 0.89 and for interobserver reliability 0.87 (95% confidence interval, 0.82 to 0.93). The mean errors of all 14 landmarks were <4 mm. Additionally, 63.57% of landmarks had a mean error of <3 mm compared with manual detection (gold standard method). The accuracy of our approach for automated localization of craniofacial landmarks, which was based on combining feature-based and voxel similarity-based methods for image registration, was acceptable. Nevertheless we recommend repetition of this study using other techniques, such as intensity-based methods

  14. A cloud solution for medical image processing

    Directory of Open Access Journals (Sweden)

    Ali Mirarab,

    2014-07-01

    Full Text Available The rapid growth in the use of Electronic Health Records across the globe along with the rich mix of multimedia held within an EHR combined with the increasing level of detail due to advances in diagnostic medical imaging means increasing amounts of data can be stored for each patient. Also lack of image processing and analysis tools for handling the large image datasets has compromised researchers and practitioner‟s outcome. Migrating medical imaging applications and data to the Cloud can allow healthcare organizations to realize significant cost savings relating to hardware, software, buildings, power and staff, in addition to greater scalability, higher performance and resilience. This paper reviews medical image processing and its challenges, states cloud computing and cloud computing benefits due to medical image processing. Also, this paper introduces tools and methods for medical images processing using the cloud. Finally a method is provided for medical images processing based on Eucalyptus cloud infrastructure with image processing software “ImageJ” and using improved genetic algorithm for the allocation and distribution of resources. Based on conducted simulations and experimental results, the proposed method brings high scalability, simplicity, flexibility and fully customizability in addition to 40% cost reduction and twice increase in speed.

  15. SAND: Automated VLBI imaging and analyzing pipeline

    Science.gov (United States)

    Zhang, Ming

    2016-05-01

    The Search And Non-Destroy (SAND) is a VLBI data reduction pipeline composed of a set of Python programs based on the AIPS interface provided by ObitTalk. It is designed for the massive data reduction of multi-epoch VLBI monitoring research. It can automatically investigate calibrated visibility data, search all the radio emissions above a given noise floor and do the model fitting either on the CLEANed image or directly on the uv data. It then digests the model-fitting results, intelligently identifies the multi-epoch jet component correspondence, and recognizes the linear or non-linear proper motion patterns. The outputs including CLEANed image catalogue with polarization maps, animation cube, proper motion fitting and core light curves. For uncalibrated data, a user can easily add inline modules to do the calibration and self-calibration in a batch for a specific array.

  16. The oncology medical image database (OMI-DB)

    Science.gov (United States)

    Halling-Brown, Mark D.; Looney, P. T.; Patel, M. N.; Warren, L. M.; Mackenzie, A.; Young, K. C.

    2014-03-01

    Many projects to evaluate or conduct research in medical imaging require the large-scale collection of images (both unprocessed and processed) and associated data. This demand has led us to design and implement a flexible oncology image repository, which prospectively collects images and data from multiple sites throughout the UK. This Oncology Medical Image Database (OMI-DB) has been created to support research involving medical imaging and contains unprocessed and processed medical images, associated annotations and data, and where applicable expert-determined ground truths describing features of interest. The process of collection, annotation and storage is almost fully automated and is extremely adaptable, allowing for quick and easy expansion to disparate imaging sites and situations. Initially the database was developed as part of a large research project in digital mammography (OPTIMAM). Hence the initial focus has been digital mammography; as a result, much of the work described will focus on this field. However, the OMI -DB has been designed to support multiple modalities and is extensible and expandable to store any associated data with full anonymisation. Currently, the majority of associated data is made up of radiological, clinical and pathological annotations extracted from the UK's National Breast Screening System (NBSS). In addition to the data, software and systems have been created to allow expert radiologists to annotate the images with interesting clinical features and provide descriptors of these features. The data from OMI-DB has been used in several observer studies and more are planned. To date we have collected 34,104 2D mammography images from 2,623 individuals.

  17. 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.

  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)

    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. Automated delineation of stroke lesions using brain CT images

    Directory of Open Access Journals (Sweden)

    Céline R. Gillebert

    2014-01-01

    Full Text Available Computed tomographic (CT images are widely used for the identification of abnormal brain tissue following infarct and hemorrhage in stroke. Manual lesion delineation is currently the standard approach, but is both time-consuming and operator-dependent. To address these issues, we present a method that can automatically delineate infarct and hemorrhage in stroke CT images. The key elements of this method are the accurate normalization of CT images from stroke patients into template space and the subsequent voxelwise comparison with a group of control CT images for defining areas with hypo- or hyper-intense signals. Our validation, using simulated and actual lesions, shows that our approach is effective in reconstructing lesions resulting from both infarct and hemorrhage and yields lesion maps spatially consistent with those produced manually by expert operators. A limitation is that, relative to manual delineation, there is reduced sensitivity of the automated method in regions close to the ventricles and the brain contours. However, the automated method presents a number of benefits in terms of offering significant time savings and the elimination of the inter-operator differences inherent to manual tracing approaches. These factors are relevant for the creation of large-scale lesion databases for neuropsychological research. The automated delineation of stroke lesions from CT scans may also enable longitudinal studies to quantify changes in damaged tissue in an objective and reproducible manner.

  1. Medical Image Retrieval: Past and Present

    OpenAIRE

    Hwang, Kyung Hoon; Lee, Haejun; Choi, Duckjoo

    2012-01-01

    With the widespread dissemination of picture archiving and communication systems (PACSs) in hospitals, the amount of imaging data is rapidly increasing. Effective image retrieval systems are required to manage these complex and large image databases. The authors reviewed the past development and the present state of medical image retrieval systems including text-based and content-based systems. In order to provide a more effective image retrieval service, the intelligent content-based retriev...

  2. Quantifying biodiversity using digital cameras and automated image analysis.

    Science.gov (United States)

    Roadknight, C. M.; Rose, R. J.; Barber, M. L.; Price, M. C.; Marshall, I. W.

    2009-04-01

    Monitoring the effects on biodiversity of extensive grazing in complex semi-natural habitats is labour intensive. There are also concerns about the standardization of semi-quantitative data collection. We have chosen to focus initially on automating the most time consuming aspect - the image analysis. The advent of cheaper and more sophisticated digital camera technology has lead to a sudden increase in the number of habitat monitoring images and information that is being collected. We report on the use of automated trail cameras (designed for the game hunting market) to continuously capture images of grazer activity in a variety of habitats at Moor House National Nature Reserve, which is situated in the North of England at an average altitude of over 600m. Rainfall is high, and in most areas the soil consists of deep peat (1m to 3m), populated by a mix of heather, mosses and sedges. The cameras have been continuously in operation over a 6 month period, daylight images are in full colour and night images (IR flash) are black and white. We have developed artificial intelligence based methods to assist in the analysis of the large number of images collected, generating alert states for new or unusual image conditions. This paper describes the data collection techniques, outlines the quantitative and qualitative data collected and proposes online and offline systems that can reduce the manpower overheads and increase focus on important subsets in the collected data. By converting digital image data into statistical composite data it can be handled in a similar way to other biodiversity statistics thus improving the scalability of monitoring experiments. Unsupervised feature detection methods and supervised neural methods were tested and offered solutions to simplifying the process. Accurate (85 to 95%) categorization of faunal content can be obtained, requiring human intervention for only those images containing rare animals or unusual (undecidable) conditions, and

  3. 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. PMID:9509399

  4. An Automated System for the Detection of Stratified Squamous Epithelial Cancer Cell Using Image Processing Techniques

    Directory of Open Access Journals (Sweden)

    Ram Krishna Kumar

    2013-06-01

    Full Text Available Early detection of cancer disease is a difficult problem and if it is not detected in starting phase the cancer can be fatal. Current medical procedures which are used to diagnose the cancer in body partsare time taking and more laboratory work is required for them. This work is an endeavor to possible recognition of cancer cells in the body part. The process consists of image taken of the affected area and digital image processing of the images to get a morphological pattern which differentiate normal cell to cancer cell. The technique is different than visual inspection and biopsy process. Image processing enables the visualization of cellular structure with substantial resolution. The aim of the work is to exploit differences in cellular organization between cancerous and normal tissue using image processing technique, thus allowing for automated, fast and accurate diagnosis.

  5. 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....

  6. Automated fetal spine detection in ultrasound images

    Science.gov (United States)

    Tolay, Paresh; Vajinepalli, Pallavi; Bhattacharya, Puranjoy; Firtion, Celine; Sisodia, Rajendra Singh

    2009-02-01

    A novel method is proposed for the automatic detection of fetal spine in ultrasound images along with its orientation in this paper. This problem presents a variety of challenges, including robustness to speckle noise, variations in the visible shape of the spine due to orientation of the ultrasound probe with respect to the fetus and the lack of a proper edge enclosing the entire spine on account of its composition out of distinct vertebra. The proposed method improves robustness and accuracy by making use of two independent techniques to estimate the spine, and then detects the exact location using a cross-correlation approach. Experimental results show that the proposed method is promising for fetal spine detection.

  7. Automated techniques for quality assurance of radiological image modalities

    Science.gov (United States)

    Goodenough, David J.; Atkins, Frank B.; Dyer, Stephen M.

    1991-05-01

    This paper will attempt to identify many of the important issues for quality assurance (QA) of radiological modalities. It is of course to be realized that QA can span many aspects of the diagnostic decision making process. These issues range from physical image performance levels to and through the diagnostic decision of the radiologist. We will use as a model for automated approaches a program we have developed to work with computed tomography (CT) images. In an attempt to unburden the user, and in an effort to facilitate the performance of QA, we have been studying automated approaches. The ultimate utility of the system is its ability to render in a safe and efficacious manner, decisions that are accurate, sensitive, specific and which are possible within the economic constraints of modern health care delivery.

  8. Automated Structure Detection in HRTEM Images: An Example with Graphene

    DEFF Research Database (Denmark)

    Kling, Jens; Vestergaard, Jacob Schack; Dahl, Anders Bjorholm;

    analysis. Single-layer graphene with its regular honeycomb lattice is a perfect model structure to apply automated structure detection. By utilizing Fourier analysis the initial perfect hexagonal structure can easily be recognized. The recorded hexagonal tessellation reflects the unperturbed structure...... challenging to interpret. In order to increase the signal-to-noise ratio of the images two routes can be pursued: 1) the exposure time can be increased; or 2) acquiring series of images and summarize them after alignment. Both methods have the disadvantage of summing images acquired over a certain period...... in the image. The centers of the C-hexagons are displayed as nodes. To segment the image into “pure” and “impure” regions, like areas with residual amorphous contamination or defects e.g. holes, a sliding window approach is used. The magnitude of the Fourier transformation within a window is compared...

  9. Image registration method for medical image sequences

    Science.gov (United States)

    Gee, Timothy F.; Goddard, James S.

    2013-03-26

    Image registration of low contrast image sequences is provided. In one aspect, a desired region of an image is automatically segmented and only the desired region is registered. Active contours and adaptive thresholding of intensity or edge information may be used to segment the desired regions. A transform function is defined to register the segmented region, and sub-pixel information may be determined using one or more interpolation methods.

  10. Medical image libraries: ICoS project

    Science.gov (United States)

    Honniball, John; Thomas, Peter

    1999-08-01

    FOr use of digital techniques for the production, manipulation and storage of images has resulted in the creation of digital image libraries. These libraries often store many thousands of images. While provision of storage media for such large amounts of data has been straightforward, provision of effective searching and retrieval tools has not. Medicine relies heavily on images as a diagnostic tool. The most obvious example is the x-ray, but many other image forms are in everyday use. Advances in technology are affecting the ways medical images are generated, stored and retrieved. The paper describes the work of the Image COding and Segmentation to Support Variable Rate Transmission Channels and Variable Resolution Platforms (ICoS) research project currently under way in Bristol, UK. ICoS is a project of the Mobile of England and Hewlett-Packard Research Laboratories Europe. Funding is provided by the Engineering and PHysical Sciences Research Council. The aim of the ICoS project is to demonstrate the practical application of computer networking to medical image libraries. Work at the University of the West of England concentrates on user interface and indexing issues. Metadata is used to organize the images, coded using the WWW Consortium standard Resource Description Framework. We are investigating the application of such standards to medical images, one outcome being to implement a metadata-based image library. This paper describes the ICoS project in detail and discuses both metadata system and user interfaces in the context of medical applications.

  11. AUTOMATED IMAGE MATCHING WITH CODED POINTS IN STEREOVISION MEASUREMENT

    Institute of Scientific and Technical Information of China (English)

    Dong Mingli; Zhou Xiaogang; Zhu Lianqing; Lü Naiguang; Sun Yunan

    2005-01-01

    A coding-based method to solve the image matching problems in stereovision measurement is presented. The solution is to add and append an identity ID to the retro-reflect point, so it can be identified efficiently under the complicated circumstances and has the characteristics of rotation, zooming, and deformation independence. Its design architecture and implementation process in details based on the theory of stereovision measurement are described. The method is effective on reducing processing data time, improving accuracy of image matching and automation of measuring system through experiments.

  12. 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.

  13. An automated system for whole microscopic image acquisition and analysis.

    Science.gov (United States)

    Bueno, Gloria; Déniz, Oscar; Fernández-Carrobles, María Del Milagro; Vállez, Noelia; Salido, Jesús

    2014-09-01

    The field of anatomic pathology has experienced major changes over the last decade. Virtual microscopy (VM) systems have allowed experts in pathology and other biomedical areas to work in a safer and more collaborative way. VMs are automated systems capable of digitizing microscopic samples that were traditionally examined one by one. The possibility of having digital copies reduces the risk of damaging original samples, and also makes it easier to distribute copies among other pathologists. This article describes the development of an automated high-resolution whole slide imaging (WSI) system tailored to the needs and problems encountered in digital imaging for pathology, from hardware control to the full digitization of samples. The system has been built with an additional digital monochromatic camera together with the color camera by default and LED transmitted illumination (RGB). Monochrome cameras are the preferred method of acquisition for fluorescence microscopy. The system is able to digitize correctly and form large high resolution microscope images for both brightfield and fluorescence. The quality of the digital images has been quantified using three metrics based on sharpness, contrast and focus. It has been proved on 150 tissue samples of brain autopsies, prostate biopsies and lung cytologies, at five magnifications: 2.5×, 10×, 20×, 40×, and 63×. The article is focused on the hardware set-up and the acquisition software, although results of the implemented image processing techniques included in the software and applied to the different tissue samples are also presented.

  14. ENVISION, from particle detectors to medical imaging

    CERN Multimedia

    2013-01-01

    Technologies developed for particle physics detectors are increasingly used in medical imaging tools like Positron Emission Tomography (PET). Produced by: CERN KT/Life Sciences and ENVISION Project Management: Manuela Cirilli 3D animation: Jeroen Huijben, Nymus3d

  15. Selective image encryption for Medical and Satellite Images

    OpenAIRE

    NaveenKumar S K; Panduranga H T

    2013-01-01

    Information security plays a very important role in fast growing information and communication technology. Few applications like medical image security and satellite image security needs to secure only selected portion of the image. This paper describes a concept of selective image encryption in two ways. First method divides the image in to sub blocks, then selected blocks are applied to encryption process. Second method automatically detects the positions of objects, and then selected objec...

  16. Leadership and power in medical imaging

    International Nuclear Information System (INIS)

    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

  17. Automated quantification technology for cerebrospinal fluid dynamics based on magnetic resonance image analysis

    International Nuclear Information System (INIS)

    Time-spatial labeling inversion pulse (Time-SLIP) technology, which is a non-contrast-enhanced magnetic resonance imaging (MRI) technology for the visualization of blood flow and cerebrospinal fluid (CSF) dynamics, is used for diagnosis of neurological diseases related to CSF including idiopathic normal-pressure hydrocephalus (iNPH), one of the causes of dementia. However, physicians must subjectively evaluate the velocity of CSF dynamics through observation of Time-SLIP images because no quantification technology exists that can express the values numerically. To address this issue, Toshiba, in cooperation with Toshiba Medical Systems Corporation and Toshiba Rinkan Hospital, has developed an automated quantification technology for CSF dynamics utilizing MR image analysis. We have confirmed the effectiveness of this technology through verification tests using a water phantom and quantification experiments using images of healthy volunteers. (author)

  18. Grid-enabling medical image analysis

    OpenAIRE

    Germain-Renaud, Cécile; Breton, Vincent; Clarysse, Patrick; Gaudeau, Yann; Glatard, Tristan; Jeannot, Emmanuel; Legre, Yannick; Loomis, Charles; Magnin, Isabelle; Montagnat, Johan; Moureaux, Jean-Marie; Osorio, Angel; Pennec, Xavier; Texier, Romain

    2005-01-01

    International audience Grids have emerged as a promising technology to handle the data and compute intensive requirements of many application areas. Digital medical image processing is a promising application area for grids. Given the volume of data, the sensitivity of medical information, and the joint complexity of medical datasets and computations expected in clinical practice, the challenge is to fill the gap between the grid middleware and the requirements of clinical applications. Th...

  19. Usefulness of automated biopsy guns in image-guided biopsy

    International Nuclear Information System (INIS)

    To evaluate the usefulness of automated biopsy guns in image-guided biopsy of lung, liver, pancreas and other organs. Using automated biopsy devices, 160 biopsies of variable anatomic sites were performed: Biopsies were performed under ultrasonographic(US) guidance in 95 and computed tomographic (CT) guidance in 65. We retrospectively analyzed histologic results and complications. Specimens were adequate for histopathologic diagnosis in 143 of the 160 patients(89.4%)-Diagnostic tissue was obtained in 130 (81.3%), suggestive tissue obtained in 13(8.1%), and non-diagnostic tissue was obtained in 14(8.7%). Inadequate tissue was obtained in only 3(1.9%). There was no statistically significant difference between US-guided and CT-guided percutaneous biopsy. There was no occurrence of significant complication. We have experienced mild complications in only 5 patients-2 hematuria and 2 hematochezia in transrectal prostatic biopsy, and 1 minimal pneumothorax in CT-guided percutaneous lung biopsy. All of them were resolved spontaneously. The image-guided biopsy using the automated biopsy gun was a simple, safe and accurate method of obtaining adequate specimen for the histopathologic diagnosis

  20. 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.

  1. I2Cnet medical image annotation service.

    Science.gov (United States)

    Chronaki, C E; Zabulis, X; Orphanoudakis, S C

    1997-01-01

    I2Cnet (Image Indexing by Content network) aims to provide services related to the content-based management of images in healthcare over the World-Wide Web. Each I2Cnet server maintains an autonomous repository of medical images and related information. The annotation service of I2Cnet allows specialists to interact with the contents of the repository, adding comments or illustrations to medical images of interest. I2Cnet annotations may be communicated to other users via e-mail or posted to I2Cnet for inclusion in its local repositories. This paper discusses the annotation service of I2Cnet and argues that such services pave the way towards the evolution of active digital medical image libraries.

  2. Selective image encryption for Medical and Satellite Images

    Directory of Open Access Journals (Sweden)

    NaveenKumar S K

    2013-02-01

    Full Text Available Information security plays a very important role in fast growing information and communication technology. Few applications like medical image security and satellite image security needs to secure only selected portion of the image. This paper describes a concept of selective image encryption in two ways. First method divides the image in to sub blocks, then selected blocks are applied to encryption process. Second method automatically detects the positions of objects, and then selected objects are applied to encryption process. Morphological techniques are used to detect the positions of the objects in given images. These two approaches are specifically developed to encrypt the portion of an image in medical images and satellite image.

  3. Physics for Medical Imaging Applications

    CERN Document Server

    Caner, Alesssandra; Rahal, Ghita

    2007-01-01

    The book introduces the fundamental aspects of digital imaging and covers four main themes: Ultrasound techniques and imaging applications; Magnetic resonance and MPJ in hospital; Digital imaging with X-rays; and Emission tomography (PET and SPECT). Each of these topics is developed by analysing the underlying physics principles and their implementation, quality and safety aspects, clinical performance and recent advancements in the field. Some issues specific to the individual techniques are also treated, e.g. choice of radioisotopes or contrast agents, optimisation of data acquisition and st

  4. Medical imaging principles and practices

    CERN Document Server

    Bronzino, Joseph D; Peterson, Donald R

    2013-01-01

    This book offers a selective review of key imaging modalities focusing on modalities with established clinical utilization. It provides a detailed overview of x-ray imaging and computed tomography, fundamental concepts in signal acquisition and processes, followed by an overview of functional MRI (fMRI) and chemical shift imaging. It also covers topics in Magnetic Resonance Microcopy, the physics of instrumentation and signal collection, and their application in clinical practice. The selection of topics provides readers with an appreciation of the depth and breadth of the field and the challenges ahead of the technical and clinical community of researchers and practitioners.

  5. 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 pointsets ar

  6. Multi-channel medical imaging system

    Science.gov (United States)

    Frangioni, John V.

    2016-05-03

    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 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 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.

  7. Multi-channel medical imaging system

    Energy Technology Data Exchange (ETDEWEB)

    Frangioni, John V.

    2016-05-03

    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 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 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.

  8. Automated image analysis for quantification of filamentous bacteria

    DEFF Research Database (Denmark)

    Fredborg, Marlene; Rosenvinge, Flemming Schønning; Spillum, Erik;

    2015-01-01

    Background Antibiotics of the β-lactam group are able to alter the shape of the bacterial cell wall, e.g. filamentation or a spheroplast formation. Early determination of antimicrobial susceptibility may be complicated by filamentation of bacteria as this can be falsely interpreted as growth...... in systems relying on colorimetry or turbidometry (such as Vitek-2, Phoenix, MicroScan WalkAway). The objective was to examine an automated image analysis algorithm for quantification of filamentous bacteria using the 3D digital microscopy imaging system, oCelloScope. Results Three E. coli strains displaying...... different resistant profiles and differences in filamentation kinetics were used to study a novel image analysis algorithm to quantify length of bacteria and bacterial filamentation. A total of 12 β-lactam antibiotics or β-lactam–β-lactamase inhibitor combinations were analyzed for their ability to induce...

  9. Automated localization of vertebra landmarks in MRI images

    Science.gov (United States)

    Pai, Akshay; Narasimhamurthy, Anand; Rao, V. S. Veeravasarapu; Vaidya, Vivek

    2011-03-01

    The identification of key landmark points in an MR spine image is an important step for tasks such as vertebra counting. In this paper, we propose a template matching based approach for automatic detection of two key landmark points, namely the second cervical vertebra (C2) and the sacrum from sagittal MR images. The approach is comprised of an approximate localization of vertebral column followed by matching with appropriate templates in order to detect/localize the landmarks. A straightforward extension of the work described here is an automated classification of spine section(s). It also serves as a useful building block for further automatic processing such as extraction of regions of interest for subsequent image processing and also in aiding the counting of vertebra.

  10. Automated blood vessel extraction using local features on retinal images

    Science.gov (United States)

    Hatanaka, Yuji; Samo, Kazuki; Tajima, Mikiya; Ogohara, Kazunori; Muramatsu, Chisako; Okumura, Susumu; Fujita, Hiroshi

    2016-03-01

    An automated blood vessel extraction using high-order local autocorrelation (HLAC) on retinal images is presented. Although many blood vessel extraction methods based on contrast have been proposed, a technique based on the relation of neighbor pixels has not been published. HLAC features are shift-invariant; therefore, we applied HLAC features to retinal images. However, HLAC features are weak to turned image, thus a method was improved by the addition of HLAC features to a polar transformed image. The blood vessels were classified using an artificial neural network (ANN) with HLAC features using 105 mask patterns as input. To improve performance, the second ANN (ANN2) was constructed by using the green component of the color retinal image and the four output values of ANN, Gabor filter, double-ring filter and black-top-hat transformation. The retinal images used in this study were obtained from the "Digital Retinal Images for Vessel Extraction" (DRIVE) database. The ANN using HLAC output apparent white values in the blood vessel regions and could also extract blood vessels with low contrast. The outputs were evaluated using the area under the curve (AUC) based on receiver operating characteristics (ROC) analysis. The AUC of ANN2 was 0.960 as a result of our study. The result can be used for the quantitative analysis of the blood vessels.

  11. A lossless encryption method for medical images using edge maps.

    Science.gov (United States)

    Zhou, Yicong; Panetta, Karen; Agaian, Sos

    2009-01-01

    Image encryption is an effective approach for providing security and privacy protection for medical images. This paper introduces a new lossless approach, called EdgeCrypt, to encrypt medical images using the information contained within an edge map. The algorithm can fully protect the selected objects/regions within medical images or the entire medical images. It can also encrypt other types of images such as grayscale images or color images. The algorithm can be used for privacy protection in the real-time medical applications such as wireless medical networking and mobile medical services. PMID:19965008

  12. A lossless encryption method for medical images using edge maps.

    Science.gov (United States)

    Zhou, Yicong; Panetta, Karen; Agaian, Sos

    2009-01-01

    Image encryption is an effective approach for providing security and privacy protection for medical images. This paper introduces a new lossless approach, called EdgeCrypt, to encrypt medical images using the information contained within an edge map. The algorithm can fully protect the selected objects/regions within medical images or the entire medical images. It can also encrypt other types of images such as grayscale images or color images. The algorithm can be used for privacy protection in the real-time medical applications such as wireless medical networking and mobile medical services.

  13. Photoacoustic Imaging: Opening New Frontiers in Medical Imaging

    Directory of Open Access Journals (Sweden)

    Keerthi S Valluru

    2011-01-01

    Full Text Available In today′s world, technology is advancing at an exponential rate and medical imaging is no exception. During the last hundred years, the field of medical imaging has seen a tremendous technological growth with the invention of imaging modalities including but not limited to X-ray, ultrasound, computed tomography, magnetic resonance imaging, positron emission tomography, and single-photon emission computed tomography. These tools have led to better diagnosis and improved patient care. However, each of these modalities has its advantages as well as disadvantages and none of them can reveal all the information a physician would like to have. In the last decade, a new diagnostic technology called photoacoustic imaging has evolved which is moving rapidly from the research phase to the clinical trial phase. This article outlines the basics of photoacoustic imaging and describes our hands-on experience in developing a comprehensive photoacoustic imaging system to detect tissue abnormalities.

  14. Human visual pattern recognition of medical images

    Science.gov (United States)

    Biederman, Irving

    1990-07-01

    The output of most medical imaging systems is a display for interpretation by human observers. This paper provides a general summary of recent work on shape recognition by humans. Two broad modes of visual image processing executed by different cortical loci can be distinguished: a) a mode for motor interaction which is sensitive to quantitative variation in image parameters and b) a mode for basic-level object recognition which is based on a small set of qualitative contrasts in viewpoint invariant properties of images edges. Many medical image classifications pose inherently difficult problems for the recognition system in that they are based on quantitative and surface patch variations--rather than qualitative--variations. But when recognition can be achieved quickly and accurately it is possible that a small viewpoint invariant contrast has been discovered and is being exploited by the interpreter.

  15. Radiation biology of medical imaging

    CERN Document Server

    Kelsey, Charles A; Sandoval, Daniel J; Chambers, Gregory D; Adolphi, Natalie L; Paffett, Kimberly S

    2014-01-01

    This book provides a thorough yet concise introduction to quantitative radiobiology and radiation physics, particularly the practical and medical application. Beginning with a discussion of the basic science of radiobiology, the book explains the fast processes that initiate damage in irradiated tissue and the kinetic patterns in which such damage is expressed at the cellular level. The final section is presented in a highly practical handbook style and offers application-based discussions in radiation oncology, fractionated radiotherapy, and protracted radiation among others. The text is also supplemented by a Web site.

  16. 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.

  17. An automated 3D reconstruction method of UAV images

    Science.gov (United States)

    Liu, Jun; Wang, He; Liu, Xiaoyang; Li, Feng; Sun, Guangtong; Song, Ping

    2015-10-01

    In this paper a novel fully automated 3D reconstruction approach based on low-altitude unmanned aerial vehicle system (UAVs) images will be presented, which does not require previous camera calibration or any other external prior knowledge. Dense 3D point clouds are generated by integrating orderly feature extraction, image matching, structure from motion (SfM) and multi-view stereo (MVS) algorithms, overcoming many of the cost, time limitations of rigorous photogrammetry techniques. An image topology analysis strategy is introduced to speed up large scene reconstruction by taking advantage of the flight-control data acquired by UAV. Image topology map can significantly reduce the running time of feature matching by limiting the combination of images. A high-resolution digital surface model of the study area is produced base on UAV point clouds by constructing the triangular irregular network. Experimental results show that the proposed approach is robust and feasible for automatic 3D reconstruction of low-altitude UAV images, and has great potential for the acquisition of spatial information at large scales mapping, especially suitable for rapid response and precise modelling in disaster emergency.

  18. Anisotropic Diffusion for Medical Image Enhancement

    Directory of Open Access Journals (Sweden)

    Nezamoddin N. Kachouie

    2010-10-01

    Full Text Available Advances in digital imaging techniques have made possible the acquisition of large volumes of Transrectal Ultrasound (TRUS prostate images so that there is considerable demand for automated segmentation. Prostate cancer diagnosis and treatment rely on segmentation of these Transrectal Ultrasound (TRUS prostate images, a challenging and difficult task due to weak prostate boundaries, speckle noise and the narrow range of gray levels, leading most image segmentation methods to perform poorly. The enhancement of ultrasound images is challenging, however prostate segmentation can be effectively improved in contrast enhanced images. Anisotropic diffusion has been used for image analysis based on selective smoothness or enhancement of local features such as region boundaries. In its formal form, anisotropic diffusion tends to encourage within-region smoothness and avoid diffusion across different regions. In this paper we extend the anisotropic diffusion to multiple directions such that segmentation methods can effectively be applied based on rich extracted features. A preliminary segmentation method based on extended diffusion is proposed. Finally an adaptive anisotropic diffusion is introduced based on image statistics.

  19. The impact of an automated dose-dispensing scheme on user compliance, medication understanding, and medication stockpiles

    DEFF Research Database (Denmark)

    Larsen, Anna Bira; Haugbølle, Lotte Stig

    2007-01-01

    BACKGROUND: It has been assumed that a new health technology, automated dose-dispensing (ADD), would result in benefits for medication users, including increased compliance, enhanced medication understanding, and improved safety. However, it was legislators and health professionals who pinpointed...... the more frequent type of behavior. After switching to ADD, most users experienced no change in understanding of their medications. ADD did not lead to automatic removal of old medications in users' homes; in fact for some users, ADD led to even larger medication stockpiles. Overall, reports from patients...... understanding, nor does it automatically eliminate stockpiles of old medication in users' homes. The gap between the perspectives of users and health professionals makes a compelling case for considering users' voices in the development and implementation of future health technologies....

  20. 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.

  1. Automated fine structure image analysis method for discrimination of diabetic retinopathy stage using conjunctival microvasculature images

    Science.gov (United States)

    Khansari, Maziyar M; O’Neill, William; Penn, Richard; Chau, Felix; Blair, Norman P; Shahidi, Mahnaz

    2016-01-01

    The conjunctiva is a densely vascularized mucus membrane covering the sclera of the eye with a unique advantage of accessibility for direct visualization and non-invasive imaging. The purpose of this study is to apply an automated quantitative method for discrimination of different stages of diabetic retinopathy (DR) using conjunctival microvasculature images. Fine structural analysis of conjunctival microvasculature images was performed by ordinary least square regression and Fisher linear discriminant analysis. Conjunctival images between groups of non-diabetic and diabetic subjects at different stages of DR were discriminated. The automated method’s discriminate rates were higher than those determined by human observers. The method allowed sensitive and rapid discrimination by assessment of conjunctival microvasculature images and can be potentially useful for DR screening and monitoring. PMID:27446692

  2. 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...

  3. 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...

  4. Granulometric profiling of aeolian dust deposits by automated image analysis

    Science.gov (United States)

    Varga, György; Újvári, Gábor; Kovács, János; Jakab, Gergely; Kiss, Klaudia; Szalai, Zoltán

    2016-04-01

    Determination of granulometric parameters is of growing interest in the Earth sciences. Particle size data of sedimentary deposits provide insights into the physicochemical environment of transport, accumulation and post-depositional alterations of sedimentary particles, and are important proxies applied in paleoclimatic reconstructions. It is especially true for aeolian dust deposits with a fairly narrow grain size range as a consequence of the extremely selective nature of wind sediment transport. Therefore, various aspects of aeolian sedimentation (wind strength, distance to source(s), possible secondary source regions and modes of sedimentation and transport) can be reconstructed only from precise grain size data. As terrestrial wind-blown deposits are among the most important archives of past environmental changes, proper explanation of the proxy data is a mandatory issue. Automated imaging provides a unique technique to gather direct information on granulometric characteristics of sedimentary particles. Granulometric data obtained from automatic image analysis of Malvern Morphologi G3-ID is a rarely applied new technique for particle size and shape analyses in sedimentary geology. Size and shape data of several hundred thousand (or even million) individual particles were automatically recorded in this study from 15 loess and paleosoil samples from the captured high-resolution images. Several size (e.g. circle-equivalent diameter, major axis, length, width, area) and shape parameters (e.g. elongation, circularity, convexity) were calculated by the instrument software. At the same time, the mean light intensity after transmission through each particle is automatically collected by the system as a proxy of optical properties of the material. Intensity values are dependent on chemical composition and/or thickness of the particles. The results of the automated imaging were compared to particle size data determined by three different laser diffraction instruments

  5. Automated angiogenesis quantification through advanced image processing techniques.

    Science.gov (United States)

    Doukas, Charlampos N; Maglogiannis, Ilias; Chatziioannou, Aristotle; Papapetropoulos, Andreas

    2006-01-01

    Angiogenesis, the formation of blood vessels in tumors, is an interactive process between tumor, endothelial and stromal cells in order to create a network for oxygen and nutrients supply, necessary for tumor growth. According to this, angiogenic activity is considered a suitable method for both tumor growth or inhibition detection. The angiogenic potential is usually estimated by counting the number of blood vessels in particular sections. One of the most popular assay tissues to study the angiogenesis phenomenon is the developing chick embryo and its chorioallantoic membrane (CAM), which is a highly vascular structure lining the inner surface of the egg shell. The aim of this study was to develop and validate an automated image analysis method that would give an unbiased quantification of the micro-vessel density and growth in angiogenic CAM images. The presented method has been validated by comparing automated results to manual counts over a series of digital chick embryo photos. The results indicate the high accuracy of the tool, which has been thus extensively used for tumor growth detection at different stages of embryonic development. PMID:17946107

  6. Automated Image Processing for the Analysis of DNA Repair Dynamics

    CERN Document Server

    Riess, Thorsten; Tomas, Martin; Ferrando-May, Elisa; Merhof, Dorit

    2011-01-01

    The efficient repair of cellular DNA is essential for the maintenance and inheritance of genomic information. In order to cope with the high frequency of spontaneous and induced DNA damage, a multitude of repair mechanisms have evolved. These are enabled by a wide range of protein factors specifically recognizing different types of lesions and finally restoring the normal DNA sequence. This work focuses on the repair factor XPC (xeroderma pigmentosum complementation group C), which identifies bulky DNA lesions and initiates their removal via the nucleotide excision repair pathway. The binding of XPC to damaged DNA can be visualized in living cells by following the accumulation of a fluorescent XPC fusion at lesions induced by laser microirradiation in a fluorescence microscope. In this work, an automated image processing pipeline is presented which allows to identify and quantify the accumulation reaction without any user interaction. The image processing pipeline comprises a preprocessing stage where the ima...

  7. Automated analysis of image mammogram for breast cancer diagnosis

    Science.gov (United States)

    Nurhasanah, Sampurno, Joko; Faryuni, Irfana Diah; Ivansyah, Okto

    2016-03-01

    Medical imaging help doctors in diagnosing and detecting diseases that attack the inside of the body without surgery. Mammogram image is a medical image of the inner breast imaging. Diagnosis of breast cancer needs to be done in detail and as soon as possible for determination of next medical treatment. The aim of this work is to increase the objectivity of clinical diagnostic by using fractal analysis. This study applies fractal method based on 2D Fourier analysis to determine the density of normal and abnormal and applying the segmentation technique based on K-Means clustering algorithm to image abnormal for determine the boundary of the organ and calculate the area of organ segmentation results. The results show fractal method based on 2D Fourier analysis can be used to distinguish between the normal and abnormal breast and segmentation techniques with K-Means Clustering algorithm is able to generate the boundaries of normal and abnormal tissue organs, so area of the abnormal tissue can be determined.

  8. Automated segmentation of three-dimensional MR brain images

    Science.gov (United States)

    Park, Jonggeun; Baek, Byungjun; Ahn, Choong-Il; Ku, Kyo Bum; Jeong, Dong Kyun; Lee, Chulhee

    2006-03-01

    Brain segmentation is a challenging problem due to the complexity of the brain. In this paper, we propose an automated brain segmentation method for 3D magnetic resonance (MR) brain images which are represented as a sequence of 2D brain images. The proposed method consists of three steps: pre-processing, removal of non-brain regions (e.g., the skull, meninges, other organs, etc), and spinal cord restoration. In pre-processing, we perform adaptive thresholding which takes into account variable intensities of MR brain images corresponding to various image acquisition conditions. In segmentation process, we iteratively apply 2D morphological operations and masking for the sequences of 2D sagittal, coronal, and axial planes in order to remove non-brain tissues. Next, final 3D brain regions are obtained by applying OR operation for segmentation results of three planes. Finally we reconstruct the spinal cord truncated during the previous processes. Experiments are performed with fifteen 3D MR brain image sets with 8-bit gray-scale. Experiment results show the proposed algorithm is fast, and provides robust and satisfactory results.

  9. An automated deformable image registration evaluation of confidence tool

    Science.gov (United States)

    Kirby, Neil; Chen, Josephine; Kim, Hojin; Morin, Olivier; Nie, Ke; Pouliot, Jean

    2016-04-01

    Deformable image registration (DIR) is a powerful tool for radiation oncology, but it can produce errors. Beyond this, DIR accuracy is not a fixed quantity and varies on a case-by-case basis. The purpose of this study is to explore the possibility of an automated program to create a patient- and voxel-specific evaluation of DIR accuracy. AUTODIRECT is a software tool that was developed to perform this evaluation for the application of a clinical DIR algorithm to a set of patient images. In brief, AUTODIRECT uses algorithms to generate deformations and applies them to these images (along with processing) to generate sets of test images, with known deformations that are similar to the actual ones and with realistic noise properties. The clinical DIR algorithm is applied to these test image sets (currently 4). From these tests, AUTODIRECT generates spatial and dose uncertainty estimates for each image voxel based on a Student’s t distribution. In this study, four commercially available DIR algorithms were used to deform a dose distribution associated with a virtual pelvic phantom image set, and AUTODIRECT was used to generate dose uncertainty estimates for each deformation. The virtual phantom image set has a known ground-truth deformation, so the true dose-warping errors of the DIR algorithms were also known. AUTODIRECT predicted error patterns that closely matched the actual error spatial distribution. On average AUTODIRECT overestimated the magnitude of the dose errors, but tuning the AUTODIRECT algorithms should improve agreement. This proof-of-principle test demonstrates the potential for the AUTODIRECT algorithm as an empirical method to predict DIR errors.

  10. Twofold processing for denoising ultrasound medical images

    OpenAIRE

    P.V.V.Kishore; Kumar, K. V. V.; kumar, D. Anil; M.V.D.Prasad; Goutham, E. N. D.; Rahul, R.; Krishna, C. B. S. Vamsi; Sandeep, Y.

    2015-01-01

    Ultrasound medical (US) imaging non-invasively pictures inside of a human body for disease diagnostics. Speckle noise attacks ultrasound images degrading their visual quality. A twofold processing algorithm is proposed in this work to reduce this multiplicative speckle noise. First fold used block based thresholding, both hard (BHT) and soft (BST), on pixels in wavelet domain with 8, 16, 32 and 64 non-overlapping block sizes. This first fold process is a better denoising method for reducing s...

  11. Image Sensors in Security and Medical Applications

    OpenAIRE

    Artyomov, Evgeny; Fish, Alexander; Yadid-Pecht, Orly

    2007-01-01

    This paper briefly reviews CMOS image sensor technology and its utilization in security and medical applications. The role and future trends of image sensors in each of the applications are discussed. To provide the reader deeper understanding of the technology aspects the paper concentrates on the selected applications such as surveillance, biometrics, capsule endoscopy and artificial retina. The reasons for concentrating on these applications are due to their importance in our d...

  12. 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.

  13. Scanning probe image wizard: A toolbox for automated scanning probe microscopy data analysis

    Science.gov (United States)

    Stirling, Julian; Woolley, Richard A. J.; Moriarty, Philip

    2013-11-01

    We describe SPIW (scanning probe image wizard), a new image processing toolbox for SPM (scanning probe microscope) images. SPIW can be used to automate many aspects of SPM data analysis, even for images with surface contamination and step edges present. Specialised routines are available for images with atomic or molecular resolution to improve image visualisation and generate statistical data on surface structure.

  14. Automated extraction of chemical structure information from digital raster images

    Directory of Open Access Journals (Sweden)

    Shedden Kerby A

    2009-02-01

    Full Text Available Abstract Background To search for chemical structures in research articles, diagrams or text representing molecules need to be translated to a standard chemical file format compatible with cheminformatic search engines. Nevertheless, chemical information contained in research articles is often referenced as analog diagrams of chemical structures embedded in digital raster images. To automate analog-to-digital conversion of chemical structure diagrams in scientific research articles, several software systems have been developed. But their algorithmic performance and utility in cheminformatic research have not been investigated. Results This paper aims to provide critical reviews for these systems and also report our recent development of ChemReader – a fully automated tool for extracting chemical structure diagrams in research articles and converting them into standard, searchable chemical file formats. Basic algorithms for recognizing lines and letters representing bonds and atoms in chemical structure diagrams can be independently run in sequence from a graphical user interface-and the algorithm parameters can be readily changed-to facilitate additional development specifically tailored to a chemical database annotation scheme. Compared with existing software programs such as OSRA, Kekule, and CLiDE, our results indicate that ChemReader outperforms other software systems on several sets of sample images from diverse sources in terms of the rate of correct outputs and the accuracy on extracting molecular substructure patterns. Conclusion The availability of ChemReader as a cheminformatic tool for extracting chemical structure information from digital raster images allows research and development groups to enrich their chemical structure databases by annotating the entries with published research articles. Based on its stable performance and high accuracy, ChemReader may be sufficiently accurate for annotating the chemical database with links

  15. Automated in situ brain imaging for mapping the Drosophila connectome.

    Science.gov (United States)

    Lin, Chi-Wen; Lin, Hsuan-Wen; Chiu, Mei-Tzu; Shih, Yung-Hsin; Wang, Ting-Yuan; Chang, Hsiu-Ming; Chiang, Ann-Shyn

    2015-01-01

    Mapping the connectome, a wiring diagram of the entire brain, requires large-scale imaging of numerous single neurons with diverse morphology. It is a formidable challenge to reassemble these neurons into a virtual brain and correlate their structural networks with neuronal activities, which are measured in different experiments to analyze the informational flow in the brain. Here, we report an in situ brain imaging technique called Fly Head Array Slice Tomography (FHAST), which permits the reconstruction of structural and functional data to generate an integrative connectome in Drosophila. Using FHAST, the head capsules of an array of flies can be opened with a single vibratome sectioning to expose the brains, replacing the painstaking and inconsistent brain dissection process. FHAST can reveal in situ brain neuroanatomy with minimal distortion to neuronal morphology and maintain intact neuronal connections to peripheral sensory organs. Most importantly, it enables the automated 3D imaging of 100 intact fly brains in each experiment. The established head model with in situ brain neuroanatomy allows functional data to be accurately registered and associated with 3D images of single neurons. These integrative data can then be shared, searched, visualized, and analyzed for understanding how brain-wide activities in different neurons within the same circuit function together to control complex behaviors.

  16. 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...

  17. Gestalt descriptions embodiments and medical image interpretation

    DEFF Research Database (Denmark)

    Friis, Jan Kyrre Berg Olsen

    2016-01-01

    In this paper I will argue that medical specialists interpret and diagnose through technological mediations like X-ray and fMRI images, and by actualizing embodied skills tacitly they are determining the identity of objects in the perceptual field. The initial phase of human interpretation of vis...

  18. 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.

  19. Lesion Contrast Enhancement in Medical Ultrasound Imaging

    DEFF Research Database (Denmark)

    Stetson, Paul F.; Sommer, F.G.; Macovski, A.

    1997-01-01

    Methods for improving the contrast-to-noise ratio (CNR) of low-contrast lesions in medical ultrasound imaging are described. Differences in the frequency spectra and amplitude distributions of the lesion and its surroundings can be used to increase the CNR of the lesion relative to the background...

  20. Medical imaging with a microwave tomographic scanner.

    Science.gov (United States)

    Jofre, L; Hawley, M S; Broquetas, A; de los Reyes, E; Ferrando, M; Elias-Fusté, A R

    1990-03-01

    A microwave tomographic scanner for biomedical applications is presented. The scanner consists of a 64 element circular array with a useful diameter of 20 cm. Electronically scanning the transmitting and receiving antennas allows multiview measurements with no mechanical movement. Imaging parameters are appropriate for medical use: a spatial resolution of 7 mm and a contrast resolution of 1% for a measurement time of 3 s. Measurements on tissue-simulating phantoms and volunteers, together with numerical simulations, are presented to assess the system for absolute imaging of tissue distribution and for differential imaging of physiological, pathological, and induced changes in tissues. PMID:2329003

  1. Medical image registration using sparse coding of image patches.

    Science.gov (United States)

    Afzali, Maryam; Ghaffari, Aboozar; Fatemizadeh, Emad; Soltanian-Zadeh, Hamid

    2016-06-01

    Image registration is a basic task in medical image processing applications like group analysis and atlas construction. Similarity measure is a critical ingredient of image registration. Intensity distortion of medical images is not considered in most previous similarity measures. Therefore, in the presence of bias field distortions, they do not generate an acceptable registration. In this paper, we propose a sparse based similarity measure for mono-modal images that considers non-stationary intensity and spatially-varying distortions. The main idea behind this measure is that the aligned image is constructed by an analysis dictionary trained using the image patches. For this purpose, we use "Analysis K-SVD" to train the dictionary and find the sparse coefficients. We utilize image patches to construct the analysis dictionary and then we employ the proposed sparse similarity measure to find a non-rigid transformation using free form deformation (FFD). Experimental results show that the proposed approach is able to robustly register 2D and 3D images in both simulated and real cases. The proposed method outperforms other state-of-the-art similarity measures and decreases the transformation error compared to the previous methods. Even in the presence of bias field distortion, the proposed method aligns images without any preprocessing.

  2. Towards automated assistance for operating home medical devices.

    Science.gov (United States)

    Gao, Zan; Detyniecki, Marcin; Chen, Ming-Yu; Wu, Wen; Hauptmann, Alexander G; Wactlar, Howard D

    2010-01-01

    To detect errors when subjects operate a home medical device, we observe them with multiple cameras. We then perform action recognition with a robust approach to recognize action information based on explicitly encoding motion information. This algorithm detects interest points and encodes not only their local appearance but also explicitly models local motion. Our goal is to recognize individual human actions in the operations of a home medical device to see if the patient has correctly performed the required actions in the prescribed sequence. Using a specific infusion pump as a test case, requiring 22 operation steps from 6 action classes, our best classifier selects high likelihood action estimates from 4 available cameras, to obtain an average class recognition rate of 69%.

  3. 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...

  4. 21 CFR 892.2020 - Medical image communications device.

    Science.gov (United States)

    2010-04-01

    ... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Medical image communications device. 892.2020... (CONTINUED) MEDICAL DEVICES RADIOLOGY DEVICES Diagnostic Devices § 892.2020 Medical image communications device. (a) Identification. A medical image communications device provides electronic transfer of...

  5. 21 CFR 892.2010 - Medical image storage device.

    Science.gov (United States)

    2010-04-01

    ... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Medical image storage device. 892.2010 Section 892...) MEDICAL DEVICES RADIOLOGY DEVICES Diagnostic Devices § 892.2010 Medical image storage device. (a) Identification. A medical image storage device is a device that provides electronic storage and...

  6. Design patterns in medical imaging information systems

    Science.gov (United States)

    Hoo, Kent S., Jr.; Wong, Stephen T. C.; Laxer, Kenneth D.; Knowlton, Robert C.; Ching, Wan

    2000-05-01

    The purpose of this paper is to introduce a new and important conceptual framework of software design for the medical imaging community using design patterns. Use cases are created to summarize operational scenarios of clinicians using the system to complete certain tasks such as image segmentation. During design the Unified Modeling Language is used to translate the use cases into modeling diagrams that describe how the system functions. Next, design patterns are applied to build models that describe how software components interoperate to deliver that functionality. The software components are implemented using the Java language, CORBA architecture, and other web technologies. The biomedical image information system is used in epilepsy neurosurgical planning and diagnosis. This article proposes the use of proven software design models for solving medical imaging informatics design problems. Design patterns provide an excellent vehicle to leverage design solutions that have worked in the past to solve the problems we face in building user-friendly, reliable, and efficient information systems. This work introduces this new technology for building increasing complex medical image information systems. The rigorous application of software design techniques is essential in building information systems that are easy to use, rich in functionality, maintainable, reliable, and updatable.

  7. Estimating fractal dimension of medical images

    Science.gov (United States)

    Penn, Alan I.; Loew, Murray H.

    1996-04-01

    Box counting (BC) is widely used to estimate the fractal dimension (fd) of medical images on the basis of a finite set of pixel data. The fd is then used as a feature to discriminate between healthy and unhealthy conditions. We show that BC is ineffective when used on small data sets and give examples of published studies in which researchers have obtained contradictory and flawed results by using BC to estimate the fd of data-limited medical images. We present a new method for estimating fd of data-limited medical images. In the new method, fractal interpolation functions (FIFs) are used to generate self-affine models of the underlying image; each model, upon discretization, approximates the original data points. The fd of each FIF is analytically evaluated. The mean of the fds of the FIFs is the estimate of the fd of the original data. The standard deviation of the fds of the FIFs is a confidence measure of the estimate. The goodness-of-fit of the discretized models to the original data is a measure of self-affinity of the original data. In a test case, the new method generated a stable estimate of fd of a rib edge in a standard chest x-ray; box counting failed to generate a meaningful estimate of the same image.

  8. Medical diagnostic imaging systems: technology and applications

    International Nuclear Information System (INIS)

    This book attempts to assess the current status and future developments of the medical imaging industry. The first chapter contains brief descriptions, of the basic principles of various imaging modalities (radiologic, CT, nuclear, ultrasound, and thermography), and a chapter describing areas of clinical applications for each modality follows. Chapter 3 provides a profile of the industry, listing the various manufacturers of medical imaging products and their share of the market, based on 1976 to 1978 statistics. Chapter 4 describes briefly the current sources of research support (industry versus government agencies) but does not provide data either in absolute dollars or relative amounts. Chapters 5 to 14 cover a broad spectrum of advanced imaging systems by categories, including x-ray (5 and 6), CT (7 and 8), nuclear (9 and 10), ultrasound (11), thermography (12), NMR (13), and miscellaneous (14), and they may be considered the meat of the book because they provide the basis for predictions of future developments in the medical imaging industry

  9. Automated image analysis for space debris identification and astrometric measurements

    Science.gov (United States)

    Piattoni, Jacopo; Ceruti, Alessandro; Piergentili, Fabrizio

    2014-10-01

    The space debris is a challenging problem for the human activity in the space. Observation campaigns are conducted around the globe to detect and track uncontrolled space objects. One of the main problems in optical observation is obtaining useful information about the debris dynamical state by the images collected. For orbit determination, the most relevant information embedded in optical observation is the precise angular position, which can be evaluated by astrometry procedures, comparing the stars inside the image with star catalogs. This is typically a time consuming process, if done by a human operator, which makes this task impractical when dealing with large amounts of data, in the order of thousands images per night, generated by routinely conducted observations. An automated procedure is investigated in this paper that is capable to recognize the debris track inside a picture, calculate the celestial coordinates of the image's center and use these information to compute the debris angular position in the sky. This procedure has been implemented in a software code, that does not require human interaction and works without any supplemental information besides the image itself, detecting space objects and solving for their angular position without a priori information. The algorithm for object detection was developed inside the research team. For the star field computation, the software code astrometry.net was used and released under GPL v2 license. The complete procedure was validated by an extensive testing, using the images obtained in the observation campaign performed in a joint project between the Italian Space Agency (ASI) and the University of Bologna at the Broglio Space center, Kenya.

  10. Automated patient and medication payment method for clinical trials

    Directory of Open Access Journals (Sweden)

    Yawn BP

    2013-01-01

    Full Text Available Barbara P Yawn,1 Suzanne Madison,1 Susan Bertram,1 Wilson D Pace,2 Anne Fuhlbrigge,3 Elliot Israel,3 Dawn Littlefield,1 Margary Kurland,1 Michael E Wechsler41Olmsted Medical Center, Department of Research, Rochester, MN, 2UCDHSC, Department of Family Medicine, University of Colorado Health Science Centre, Aurora, CO, 3Brigham and Women's Hospital, Pulmonary and Critical Care Division, Boston, MA, 4National Jewish Medical Center, Division of Pulmonology, Denver, CO, USABackground: Published reports and studies related to patient compensation for clinical trials focus primarily on the ethical issues related to appropriate amounts to reimburse for patient's time and risk burden. Little has been published regarding the method of payment for patient participation. As clinical trials move into widely dispersed community practices and more complex designs, the method of payment also becomes more complex. Here we review the decision process and payment method selected for a primary care-based randomized clinical trial of asthma management in Black Americans.Methods: The method selected is a credit card system designed specifically for clinical trials that allows both fixed and variable real-time payments. We operationalized the study design by providing each patient with two cards, one for reimbursement for study visits and one for payment of medication costs directly to the pharmacies.Results: Of the 1015 patients enrolled, only two refused use of the ClinCard, requesting cash payments for visits and only rarely a weekend or fill-in pharmacist refused to use the card system for payment directly to the pharmacy. Overall, the system has been well accepted by patients and local study teams. The ClinCard administrative system facilitates the fiscal accounting and medication adherence record-keeping by the central teams. Monthly fees are modest, and all 12 study institutional review boards approved use of the system without concern for patient

  11. 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.

  12. Automated Recognition of 3D Features in GPIR Images

    Science.gov (United States)

    Park, Han; Stough, Timothy; Fijany, Amir

    2007-01-01

    A method of automated recognition of three-dimensional (3D) features in images generated by ground-penetrating imaging radar (GPIR) is undergoing development. GPIR 3D images can be analyzed to detect and identify such subsurface features as pipes and other utility conduits. Until now, much of the analysis of GPIR images has been performed manually by expert operators who must visually identify and track each feature. The present method is intended to satisfy a need for more efficient and accurate analysis by means of algorithms that can automatically identify and track subsurface features, with minimal supervision by human operators. In this method, data from multiple sources (for example, data on different features extracted by different algorithms) are fused together for identifying subsurface objects. The algorithms of this method can be classified in several different ways. In one classification, the algorithms fall into three classes: (1) image-processing algorithms, (2) feature- extraction algorithms, and (3) a multiaxis data-fusion/pattern-recognition algorithm that includes a combination of machine-learning, pattern-recognition, and object-linking algorithms. The image-processing class includes preprocessing algorithms for reducing noise and enhancing target features for pattern recognition. The feature-extraction algorithms operate on preprocessed data to extract such specific features in images as two-dimensional (2D) slices of a pipe. Then the multiaxis data-fusion/ pattern-recognition algorithm identifies, classifies, and reconstructs 3D objects from the extracted features. In this process, multiple 2D features extracted by use of different algorithms and representing views along different directions are used to identify and reconstruct 3D objects. In object linking, which is an essential part of this process, features identified in successive 2D slices and located within a threshold radius of identical features in adjacent slices are linked in a

  13. Medical Image Protection using steganography by crypto-image as cover Image

    Directory of Open Access Journals (Sweden)

    Vinay Pandey

    2012-09-01

    Full Text Available This paper presents securing the transmission of medical images. The presented algorithms will be applied to images. This work presents a new method that combines image cryptography, data hiding and Steganography technique for denoised and safe image transmission purpose. In This method we encrypt the original image with two shares mechanism encryption algorithm then embed the encrypted image with patient information by using lossless data embedding technique with data hiding method after that for more security. We apply steganography by encrypted image of any other medical image as cover image and embedded images as secrete image with the private key. In receiver side when the message is arrived then we apply the inverse methods in reverse order to get the original image and patient information and to remove noise we extract the image before the decryption of message. We have applied and showed the results of our method to medical images.

  14. Automated detection of open magnetic field regions in EUV images

    Science.gov (United States)

    Krista, Larisza Diana; Reinard, Alysha

    2016-05-01

    Open magnetic regions on the Sun are either long-lived (coronal holes) or transient (dimmings) in nature, but both appear as dark regions in EUV images. For this reason their detection can be done in a similar way. As coronal holes are often large and long-lived in comparison to dimmings, their detection is more straightforward. The Coronal Hole Automated Recognition and Monitoring (CHARM) algorithm detects coronal holes using EUV images and a magnetogram. The EUV images are used to identify dark regions, and the magnetogam allows us to determine if the dark region is unipolar – a characteristic of coronal holes. There is no temporal sensitivity in this process, since coronal hole lifetimes span days to months. Dimming regions, however, emerge and disappear within hours. Hence, the time and location of a dimming emergence need to be known to successfully identify them and distinguish them from regular coronal holes. Currently, the Coronal Dimming Tracker (CoDiT) algorithm is semi-automated – it requires the dimming emergence time and location as an input. With those inputs we can identify the dimming and track it through its lifetime. CoDIT has also been developed to allow the tracking of dimmings that split or merge – a typical feature of dimmings.The advantage of these particular algorithms is their ability to adapt to detecting different types of open field regions. For coronal hole detection, each full-disk solar image is processed individually to determine a threshold for the image, hence, we are not limited to a single pre-determined threshold. For dimming regions we also allow individual thresholds for each dimming, as they can differ substantially. This flexibility is necessary for a subjective analysis of the studied regions. These algorithms were developed with the goal to allow us better understand the processes that give rise to eruptive and non-eruptive open field regions. We aim to study how these regions evolve over time and what environmental

  15. Automating quality assurance of digital linear accelerators using a radioluminescent phosphor coated phantom and optical imaging

    Science.gov (United States)

    Jenkins, Cesare H.; Naczynski, Dominik J.; Yu, Shu-Jung S.; Yang, Yong; Xing, Lei

    2016-09-01

    Performing mechanical and geometric quality assurance (QA) tests for medical linear accelerators (LINAC) is a predominantly manual process that consumes significant time and resources. In order to alleviate this burden this study proposes a novel strategy to automate the process of performing these tests. The autonomous QA system consists of three parts: (1) a customized phantom coated with radioluminescent material; (2) an optical imaging system capable of visualizing the incidence of the radiation beam, light field or lasers on the phantom; and (3) software to process the captured signals. The radioluminescent phantom, which enables visualization of the radiation beam on the same surface as the light field and lasers, is placed on the couch and imaged while a predefined treatment plan is delivered from the LINAC. The captured images are then processed to self-calibrate the system and perform measurements for evaluating light field/radiation coincidence, jaw position indicators, cross-hair centering, treatment couch position indicators and localizing laser alignment. System accuracy is probed by intentionally introducing errors and by comparing with current clinical methods. The accuracy of self-calibration is evaluated by examining measurement repeatability under fixed and variable phantom setups. The integrated system was able to automatically collect, analyze and report the results for the mechanical alignment tests specified by TG-142. The average difference between introduced and measured errors was 0.13 mm. The system was shown to be consistent with current techniques. Measurement variability increased slightly from 0.1 mm to 0.2 mm when the phantom setup was varied, but no significant difference in the mean measurement value was detected. Total measurement time was less than 10 minutes for all tests as a result of automation. The system’s unique features of a phosphor-coated phantom and fully automated, operator independent self-calibration offer the

  16. Automating quality assurance of digital linear accelerators using a radioluminescent phosphor coated phantom and optical imaging.

    Science.gov (United States)

    Jenkins, Cesare H; Naczynski, Dominik J; Yu, Shu-Jung S; Yang, Yong; Xing, Lei

    2016-09-01

    Performing mechanical and geometric quality assurance (QA) tests for medical linear accelerators (LINAC) is a predominantly manual process that consumes significant time and resources. In order to alleviate this burden this study proposes a novel strategy to automate the process of performing these tests. The autonomous QA system consists of three parts: (1) a customized phantom coated with radioluminescent material; (2) an optical imaging system capable of visualizing the incidence of the radiation beam, light field or lasers on the phantom; and (3) software to process the captured signals. The radioluminescent phantom, which enables visualization of the radiation beam on the same surface as the light field and lasers, is placed on the couch and imaged while a predefined treatment plan is delivered from the LINAC. The captured images are then processed to self-calibrate the system and perform measurements for evaluating light field/radiation coincidence, jaw position indicators, cross-hair centering, treatment couch position indicators and localizing laser alignment. System accuracy is probed by intentionally introducing errors and by comparing with current clinical methods. The accuracy of self-calibration is evaluated by examining measurement repeatability under fixed and variable phantom setups. The integrated system was able to automatically collect, analyze and report the results for the mechanical alignment tests specified by TG-142. The average difference between introduced and measured errors was 0.13 mm. The system was shown to be consistent with current techniques. Measurement variability increased slightly from 0.1 mm to 0.2 mm when the phantom setup was varied, but no significant difference in the mean measurement value was detected. Total measurement time was less than 10 minutes for all tests as a result of automation. The system's unique features of a phosphor-coated phantom and fully automated, operator independent self-calibration offer the

  17. Massive Medical Images Retrieval System Based on Hadoop

    Directory of Open Access Journals (Sweden)

    Qing-An YAO

    2014-02-01

    Full Text Available In order to improve the efficiency of massive medical images retrieval, against the defects of the single-node medical image retrieval system, a massive medical images retrieval system based on Hadoop is put forward. Brushlet transform and Local binary patterns algorithm are introduced firstly to extract characteristics of the medical example image, and store the image feature library in the HDFS. Then using the Map to match the example image features with the features in the feature library, while the Reduce to receive the calculation results of each Map task and ranking the results according to the size of the similarity. At the end, find the optimal retrieval results of the medical images according to the ranking results. The experimental results show that compared with other medical image retrieval systems, the Hadoop based medical image retrieval system can reduce the time of image storage and retrieval, and improve the image retrieval speed.

  18. Automatic scale selection for medical image segmentation

    Science.gov (United States)

    Bayram, Ersin; Wyatt, Christopher L.; Ge, Yaorong

    2001-07-01

    The scale of interesting structures in medical images is space variant because of partial volume effects, spatial dependence of resolution in many imaging modalities, and differences in tissue properties. Existing segmentation methods either apply a single scale to the entire image or try fine-to-coarse/coarse-to-fine tracking of structures over multiple scales. While single scale approaches fail to fully recover the perceptually important structures, multi-scale methods have problems in providing reliable means to select proper scales and integrating information over multiple scales. A recent approach proposed by Elder and Zucker addresses the scale selection problem by computing a minimal reliable scale for each image pixel. The basic premise of this approach is that, while the scale of structures within an image vary spatially, the imaging system is fixed. Hence, sensor noise statistics can be calculated. Based on a model of edges to be detected, and operators to be used for detection, one can locally compute a unique minimal reliable scale at which the likelihood of error due to sensor noise is less than or equal to a predetermined threshold. In this paper, we improve the segmentation method based on the minimal reliable scale selection and evaluate its effectiveness with both simulated and actual medical data.

  19. Evaluation of a content-based retrieval system for blood cell images with automated methods.

    Science.gov (United States)

    Seng, Woo Chaw; Mirisaee, Seyed Hadi

    2011-08-01

    Content-based image retrieval techniques have been extensively studied for the past few years. With the growth of digital medical image databases, the demand for content-based analysis and retrieval tools has been increasing remarkably. Blood cell image is a key diagnostic tool for hematologists. An automated system that can retrieved relevant blood cell images correctly and efficiently would save the effort and time of hematologists. The purpose of this work is to develop such a content-based image retrieval system. Global color histogram and wavelet-based methods are used in the prototype. The system allows users to search by providing a query image and select one of four implemented methods. The obtained results demonstrate the proposed extended query refinement has the potential to capture a user's high level query and perception subjectivity by dynamically giving better query combinations. Color-based methods performed better than wavelet-based methods with regard to precision, recall rate and retrieval time. Shape and density of blood cells are suggested as measurements for future improvement. The system developed is useful for undergraduate education. PMID:20703533

  20. Extended query refinement for medical image retrieval.

    Science.gov (United States)

    Deserno, Thomas M; Güld, Mark O; Plodowski, Bartosz; Spitzer, Klaus; Wein, Berthold B; Schubert, Henning; Ney, Hermann; Seidl, Thomas

    2008-09-01

    The impact of image pattern recognition on accessing large databases of medical images has recently been explored, and content-based image retrieval (CBIR) in medical applications (IRMA) is researched. At the present, however, the impact of image retrieval on diagnosis is limited, and practical applications are scarce. One reason is the lack of suitable mechanisms for query refinement, in particular, the ability to (1) restore previous session states, (2) combine individual queries by Boolean operators, and (3) provide continuous-valued query refinement. This paper presents a powerful user interface for CBIR that provides all three mechanisms for extended query refinement. The various mechanisms of man-machine interaction during a retrieval session are grouped into four classes: (1) output modules, (2) parameter modules, (3) transaction modules, and (4) process modules, all of which are controlled by a detailed query logging. The query logging is linked to a relational database. Nested loops for interaction provide a maximum of flexibility within a minimum of complexity, as the entire data flow is still controlled within a single Web page. Our approach is implemented to support various modalities, orientations, and body regions using global features that model gray scale, texture, structure, and global shape characteristics. The resulting extended query refinement has a significant impact for medical CBIR applications. PMID:17497197

  1. Automated 3D ultrasound image segmentation to aid breast cancer image interpretation.

    Science.gov (United States)

    Gu, Peng; Lee, Won-Mean; Roubidoux, Marilyn A; Yuan, Jie; Wang, Xueding; Carson, Paul L

    2016-02-01

    Segmentation of an ultrasound image into functional tissues is of great importance to clinical diagnosis of breast cancer. However, many studies are found to segment only the mass of interest and not all major tissues. Differences and inconsistencies in ultrasound interpretation call for an automated segmentation method to make results operator-independent. Furthermore, manual segmentation of entire three-dimensional (3D) ultrasound volumes is time-consuming, resource-intensive, and clinically impractical. Here, we propose an automated algorithm to segment 3D ultrasound volumes into three major tissue types: cyst/mass, fatty tissue, and fibro-glandular tissue. To test its efficacy and consistency, the proposed automated method was employed on a database of 21 cases of whole breast ultrasound. Experimental results show that our proposed method not only distinguishes fat and non-fat tissues correctly, but performs well in classifying cyst/mass. Comparison of density assessment between the automated method and manual segmentation demonstrates good consistency with an accuracy of 85.7%. Quantitative comparison of corresponding tissue volumes, which uses overlap ratio, gives an average similarity of 74.54%, consistent with values seen in MRI brain segmentations. Thus, our proposed method exhibits great potential as an automated approach to segment 3D whole breast ultrasound volumes into functionally distinct tissues that may help to correct ultrasound speed of sound aberrations and assist in density based prognosis of breast cancer.

  2. Wavelet Transform based Medical Image Fusion With different fusion methods

    Directory of Open Access Journals (Sweden)

    Anjali Patil

    2015-03-01

    Full Text Available This paper proposes wavelet transform based image fusion algorithm, after studying the principles and characteristics of the discrete wavelet transform. Medical image fusion used to derive useful information from multimodality medical images. The idea is to improve the image content by fusing images like computer tomography (CT and magnetic resonance imaging (MRI images, so as to provide more information to the doctor and clinical treatment planning system. This paper based on the wavelet transformation to fused the medical images. The wavelet based fusion algorithms used on medical images CT and MRI, This involve the fusion with MIN , MAX, MEAN method. Also the result is obtained. With more available multimodality medical images in clinical applications, the idea of combining images from different modalities become very important and medical image fusion has emerged as a new promising research field

  3. Simplified labeling process for medical image segmentation.

    Science.gov (United States)

    Gao, Mingchen; Huang, Junzhou; Huang, Xiaolei; Zhang, Shaoting; Metaxas, Dimitris N

    2012-01-01

    Image segmentation plays a crucial role in many medical imaging applications by automatically locating the regions of interest. Typically supervised learning based segmentation methods require a large set of accurately labeled training data. However, thel labeling process is tedious, time consuming and sometimes not necessary. We propose a robust logistic regression algorithm to handle label outliers such that doctors do not need to waste time on precisely labeling images for training set. To validate its effectiveness and efficiency, we conduct carefully designed experiments on cervigram image segmentation while there exist label outliers. Experimental results show that the proposed robust logistic regression algorithms achieve superior performance compared to previous methods, which validates the benefits of the proposed algorithms. PMID:23286072

  4. New Trend of Medical Imaging Informatics

    Directory of Open Access Journals (Sweden)

    Jimmy Han

    2007-08-01

    Full Text Available This presentation offers an understanding of the rapidly changing medical market and devices, and provides ways for Medical Informatics Systems to keep up with this rapidly changing environment. The Infinitt Company of South Korea as one of the pioneers in the field of imaging informatics will present its three major solutions to meet these new trends. The Infinitt G3 will be presented as fully web-based RIS/PACS solution with advanced 3D capabilities all operating on a single platform, i.e. a solution for simultaneous fusion of RIS, PACS and 3D functions."nThe Infinitt Star PACS is presented as an on-demand PACS solution, which can operate in a web-based environment for easier image distribution, remote conferencing and Teleradiology practices. Infinitt Rapidia, which is a 3D imaging technology, that visualizes 3D images out of a large quantity of 2D images is presented as a tool to support diagnostic and surgery demands.

  5. A multiple-drawer medication layout problem in automated dispensing cabinets.

    Science.gov (United States)

    Pazour, Jennifer A; Meller, Russell D

    2012-12-01

    In this paper we investigate the problem of locating medications in automated dispensing cabinets (ADCs) to minimize human selection errors. We formulate the multiple-drawer medication layout problem and show that the problem can be formulated as a quadratic assignment problem. As a way to evaluate various medication layouts, we develop a similarity rating for medication pairs. To solve industry-sized problem instances, we develop a heuristic approach. We use hospital ADC transaction data to conduct a computational experiment to test the performance of our developed heuristics, to demonstrate how our approach can aid in ADC design trade-offs, and to illustrate the potential improvements that can be made when applying an analytical process to the multiple-drawer medication layout problem. Finally, we present conclusions and future research directions.

  6. HEP technologies to address medical imaging challenges

    CERN Document Server

    CERN. Geneva

    2016-01-01

    Developments in detector technologies aimed at solving challenges in present and future CERN experiments, particularly at the LHC, have triggered exceptional advances in the performance of medical imaging devices, allowing for a spectacular progress in in-vivo molecular imaging procedures, which are opening the way for tailored therapies of major diseases. This talk will briefly review the recent history of this prime example of technology transfer from HEP experiments to society, will describe the technical challenges being addressed by some ongoing projects, and will present a few new ideas for further developments and their foreseeable impact.

  7. Instrumentation of the ESRF medical imaging facility

    CERN Document Server

    Elleaume, H; Berkvens, P; Berruyer, G; Brochard, T; Dabin, Y; Domínguez, M C; Draperi, A; Fiedler, S; Goujon, G; Le Duc, G; Mattenet, M; Nemoz, C; Pérez, M; Renier, M; Schulze, C; Spanne, P; Suortti, P; Thomlinson, W; Estève, F; Bertrand, B; Le Bas, J F

    1999-01-01

    At the European Synchrotron Radiation Facility (ESRF) a beamport has been instrumented for medical research programs. Two facilities have been constructed for alternative operation. The first one is devoted to medical imaging and is focused on intravenous coronary angiography and computed tomography (CT). The second facility is dedicated to pre-clinical microbeam radiotherapy (MRT). This paper describes the instrumentation for the imaging facility. Two monochromators have been designed, both are based on bent silicon crystals in the Laue geometry. A versatile scanning device has been built for pre-alignment and scanning of the patient through the X-ray beam in radiography or CT modes. An intrinsic germanium detector is used together with large dynamic range electronics (16 bits) to acquire the data. The beamline is now at the end of its commissioning phase; intravenous coronary angiography is intended to start in 1999 with patients and the CT pre-clinical program is underway on small animals. The first in viv...

  8. Survey on Digital Watermarking on Medical Images

    Directory of Open Access Journals (Sweden)

    Kavitha K J

    2013-12-01

    Full Text Available The rapid growth in information and communication technologies has advances the medical data management systems immensely. In this regard, many different techniques and also the advanced equipment like Magnetic Resonance Imaging (MRI Scanner, Computer Tomography (CT scanner, Positron Emission of Tomography (PET, mammography, ultrasound, radiography etc. are used. Nowadays there is a rise of various diseases, for which several diagnoses are insufficient; therefore to achieve a correct diagnostic, there is need to exchange the data over Internet, but the main problem is while exchanging the data over Internet, we need to maintain their authenticity, integrity and confidentiality. Therefore, we need a system for effective storage, transmission, controlled manipulation and access of medical data keeping its authenticity, integrity and confidentiality. In this article, we discuss various water marking techniques used for effective storage, transmission, controlled manipulation and access of medical data keeping its authenticity, integrity and confidentiality.

  9. CERN crystals used in medical imaging

    CERN Multimedia

    Maximilien Brice

    2004-01-01

    This crystal is a type of material known as a scintillator. When a high energy charged particle or photon passes through a scintillator it glows. These materials are widely used in particle physics for particle detection, but their uses are being realized in further fields, such as Positron Emission Tomography (PET), an area of medical imaging that monitors the regions of energy use in the body.

  10. Machine learning for medical images analysis.

    Science.gov (United States)

    Criminisi, A

    2016-10-01

    This article discusses the application of machine learning for the analysis of medical images. Specifically: (i) We show how a special type of learning models can be thought of as automatically optimized, hierarchically-structured, rule-based algorithms, and (ii) We discuss how the issue of collecting large labelled datasets applies to both conventional algorithms as well as machine learning techniques. The size of the training database is a function of model complexity rather than a characteristic of machine learning methods.

  11. An Improved Medical Image Fusion Algorithm for Anatomical and Functional Medical Images

    Institute of Scientific and Technical Information of China (English)

    CHEN Mei-ling; TAO Ling; QIAN Zhi-yu

    2009-01-01

    In recent years,many medical image fusion methods had been exploited to derive useful information from multimodality medical image data,but,not an appropriate fusion algorithm for anatomical and functional medical images.In this paper,the traditional method of wavelet fusion is improved and a new fusion algorithm of anatomical and functional medical images,in which high-frequency and low-frequency coefficients are studied respectively.When choosing high-frequency coefficients,the global gradient of each sub-image is calculated to realize adaptive fusion,so that the fused image can reserve the functional information;while choosing the low coefficients is based on the analysis of the neighborbood region energy,so that the fused image can reserve the anatomical image's edge and texture feature.Experimental results and the quality evaluation parameters show that the improved fusion algorithm can enhance the edge and texture feature and retain the function information and anatomical information effectively.

  12. Automated torso organ segmentation from 3D CT images using conditional random field

    Science.gov (United States)

    Nimura, Yukitaka; Hayashi, Yuichiro; Kitasaka, Takayuki; Misawa, Kazunari; Mori, Kensaku

    2016-03-01

    This paper presents a segmentation method for torso organs using conditional random field (CRF) from medical images. A lot of methods have been proposed to enable automated extraction of organ regions from volumetric medical images. However, it is necessary to adjust empirical parameters of them to obtain precise organ regions. In this paper, we propose an organ segmentation method using structured output learning which is based on probabilistic graphical model. The proposed method utilizes CRF on three-dimensional grids as probabilistic graphical model and binary features which represent the relationship between voxel intensities and organ labels. Also we optimize the weight parameters of the CRF using stochastic gradient descent algorithm and estimate organ labels for a given image by maximum a posteriori (MAP) estimation. The experimental result revealed that the proposed method can extract organ regions automatically using structured output learning. The error of organ label estimation was 6.6%. The DICE coefficients of right lung, left lung, heart, liver, spleen, right kidney, and left kidney are 0.94, 0.92, 0.65, 0.67, 0.36, 0.38, and 0.37, respectively.

  13. 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.

  14. Automated movement correction for dynamic PET/CT images: Evaluation with phantom and patient data

    OpenAIRE

    Ye, H.; Wong, KP; Wardak, M; Dahlbom, M.; Kepe, V; Barrio, JR; Nelson, LD; Small, GW; Huang, SC

    2014-01-01

    Head movement during a dynamic brain PET/CT imaging results in mismatch between CT and dynamic PET images. It can cause artifacts in CT-based attenuation corrected PET images, thus affecting both the qualitative and quantitative aspects of the dynamic PET images and the derived parametric images. In this study, we developed an automated retrospective image-based movement correction (MC) procedure. The MC method first registered the CT image to each dynamic PET frames, then re-reconstructed th...

  15. Medical imaging and alternative health care organizations

    International Nuclear Information System (INIS)

    Imaging is not easy to measure in economic terms for France to day. The impact of innovation process is no more clear and especially the substitutions expected between different techniques. Nevertheless, these new techniques could provoque big changes in medical practices and health care organizations. They should probably increase the proportion of ambulatory patients in total examinations and encourage the development of extra-hospital health care. But, in France, alternative health care organizations (day hospital, home care, etc...) are under developed because of many non technical factors (behavioural managerial and institutional). Perhaps major potential change shall come from imaging networks. But can imaging development contribute to moderate health expanses growth rate. Economic evaluations of each new technique are difficult and ambiguous but necessary to maximize health care system efficiency

  16. Multilayer descriptors for medical image classification.

    Science.gov (United States)

    Lumini, Alessandra; Nanni, Loris; Brahnam, Sheryl

    2016-05-01

    In this paper, we propose a new method for improving the performance of 2D descriptors by building an n-layer image using different preprocessing approaches from which multilayer descriptors are extracted and used as feature vectors for training a Support Vector Machine. The different preprocessing approaches are used to build different n-layer images (n=3, n=5, etc.). We test both color and gray-level images, two well-known texture descriptors (Local Phase Quantization and Local Binary Pattern), and three of their variants suited for n-layer images (Volume Local Phase Quantization, Local Phase Quantization Three-Orthogonal-Planes, and Volume Local Binary Patterns). Our results show that multilayers and texture descriptors can be combined to outperform the standard single-layer approaches. Experiments on 10 datasets demonstrate the generalizability of the proposed descriptors. Most of these datasets are medical, but in each case the images are very different. Two datasets are completely unrelated to medicine and are included to demonstrate the discriminative power of the proposed descriptors across very different image recognition tasks. A MATLAB version of the complete system developed in this paper will be made available at https://www.dei.unipd.it/node/2357. PMID:26656952

  17. Wavelet Transform based Medical Image Fusion With different fusion methods

    OpenAIRE

    Anjali Patil; M N Tibdewal

    2015-01-01

    This paper proposes wavelet transform based image fusion algorithm, after studying the principles and characteristics of the discrete wavelet transform. Medical image fusion used to derive useful information from multimodality medical images. The idea is to improve the image content by fusing images like computer tomography (CT) and magnetic resonance imaging (MRI) images, so as to provide more information to the doctor and clinical treatment planning system. This paper based on t...

  18. A comparative study on medical image segmentation methods

    OpenAIRE

    Praylin Selva Blessy SELVARAJ ASSLEY; Helen Sulochana CHELLAKKON

    2014-01-01

    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 disa...

  19. Segmentation of Medical Image using Clustering and Watershed Algorithms

    OpenAIRE

    M. C.J. Christ; R. M. S. Parvathi

    2011-01-01

    Problem statement: Segmentation plays an important role in medical imaging. Segmentation of an image is the division or separation of the image into dissimilar regions of similar attribute. In this study we proposed a methodology that integrates clustering algorithm and marker controlled watershed segmentation algorithm for medical image segmentation. The use of the conservative watershed algorithm for medical image analysis is pervasive because of its advantages, such as always being able to...

  20. 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.)

  1. Automated Nanofiber Diameter Measurement in SEM Images Using a Robust Image Analysis Method

    Directory of Open Access Journals (Sweden)

    Ertan Öznergiz

    2014-01-01

    Full Text Available Due to the high surface area, porosity, and rigidity, applications of nanofibers and nanosurfaces have developed in recent years. Nanofibers and nanosurfaces are typically produced by electrospinning method. In the production process, determination of average fiber diameter is crucial for quality assessment. Average fiber diameter is determined by manually measuring the diameters of randomly selected fibers on scanning electron microscopy (SEM images. However, as the number of the images increases, manual fiber diameter determination becomes a tedious and time consuming task as well as being sensitive to human errors. Therefore, an automated fiber diameter measurement system is desired. In the literature, this task is achieved by using image analysis algorithms. Typically, these methods first isolate each fiber in the image and measure the diameter of each isolated fiber. Fiber isolation is an error-prone process. In this study, automated calculation of nanofiber diameter is achieved without fiber isolation using image processing and analysis algorithms. Performance of the proposed method was tested on real data. The effectiveness of the proposed method is shown by comparing automatically and manually measured nanofiber diameter values.

  2. Twofold processing for denoising ultrasound medical images.

    Science.gov (United States)

    Kishore, P V V; Kumar, K V V; Kumar, D Anil; Prasad, M V D; Goutham, E N D; Rahul, R; Krishna, C B S Vamsi; Sandeep, Y

    2015-01-01

    Ultrasound medical (US) imaging non-invasively pictures inside of a human body for disease diagnostics. Speckle noise attacks ultrasound images degrading their visual quality. A twofold processing algorithm is proposed in this work to reduce this multiplicative speckle noise. First fold used block based thresholding, both hard (BHT) and soft (BST), on pixels in wavelet domain with 8, 16, 32 and 64 non-overlapping block sizes. This first fold process is a better denoising method for reducing speckle and also inducing object of interest blurring. The second fold process initiates to restore object boundaries and texture with adaptive wavelet fusion. The degraded object restoration in block thresholded US image is carried through wavelet coefficient fusion of object in original US mage and block thresholded US image. Fusion rules and wavelet decomposition levels are made adaptive for each block using gradient histograms with normalized differential mean (NDF) to introduce highest level of contrast between the denoised pixels and the object pixels in the resultant image. Thus the proposed twofold methods are named as adaptive NDF block fusion with hard and soft thresholding (ANBF-HT and ANBF-ST). The results indicate visual quality improvement to an interesting level with the proposed twofold processing, where the first fold removes noise and second fold restores object properties. Peak signal to noise ratio (PSNR), normalized cross correlation coefficient (NCC), edge strength (ES), image quality Index (IQI) and structural similarity index (SSIM), measure the quantitative quality of the twofold processing technique. Validation of the proposed method is done by comparing with anisotropic diffusion (AD), total variational filtering (TVF) and empirical mode decomposition (EMD) for enhancement of US images. The US images are provided by AMMA hospital radiology labs at Vijayawada, India. PMID:26697285

  3. Vision 20/20: Perspectives on automated image segmentation for radiotherapy

    Energy Technology Data Exchange (ETDEWEB)

    Sharp, Gregory, E-mail: gcsharp@partners.org; Fritscher, Karl D.; Shusharina, Nadya [Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts 02114 (United States); Pekar, Vladimir [Philips Healthcare, Markham, Ontario 6LC 2S3 (Canada); Peroni, Marta [Center for Proton Therapy, Paul Scherrer Institut, 5232 Villigen-PSI (Switzerland); Veeraraghavan, Harini [Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York 10065 (United States); Yang, Jinzhong [Department of Radiation Physics, MD Anderson Cancer Center, Houston, Texas 77030 (United States)

    2014-05-15

    Due to rapid advances in radiation therapy (RT), especially image guidance and treatment adaptation, a fast and accurate segmentation of medical images is a very important part of the treatment. Manual delineation of target volumes and organs at risk is still the standard routine for most clinics, even though it is time consuming and prone to intra- and interobserver variations. Automated segmentation methods seek to reduce delineation workload and unify the organ boundary definition. In this paper, the authors review the current autosegmentation methods particularly relevant for applications in RT. The authors outline the methods’ strengths and limitations and propose strategies that could lead to wider acceptance of autosegmentation in routine clinical practice. The authors conclude that currently, autosegmentation technology in RT planning is an efficient tool for the clinicians to provide them with a good starting point for review and adjustment. Modern hardware platforms including GPUs allow most of the autosegmentation tasks to be done in a range of a few minutes. In the nearest future, improvements in CT-based autosegmentation tools will be achieved through standardization of imaging and contouring protocols. In the longer term, the authors expect a wider use of multimodality approaches and better understanding of correlation of imaging with biology and pathology.

  4. Automated Detection of Firearms and Knives in a CCTV Image.

    Science.gov (United States)

    Grega, Michał; Matiolański, Andrzej; Guzik, Piotr; Leszczuk, Mikołaj

    2016-01-01

    Closed circuit television systems (CCTV) are becoming more and more popular and are being deployed in many offices, housing estates and in most public spaces. Monitoring systems have been implemented in many European and American cities. This makes for an enormous load for the CCTV operators, as the number of camera views a single operator can monitor is limited by human factors. In this paper, we focus on the task of automated detection and recognition of dangerous situations for CCTV systems. We propose algorithms that are able to alert the human operator when a firearm or knife is visible in the image. We have focused on limiting the number of false alarms in order to allow for a real-life application of the system. The specificity and sensitivity of the knife detection are significantly better than others published recently. We have also managed to propose a version of a firearm detection algorithm that offers a near-zero rate of false alarms. We have shown that it is possible to create a system that is capable of an early warning in a dangerous situation, which may lead to faster and more effective response times and a reduction in the number of potential victims.

  5. Automated Detection of Firearms and Knives in a CCTV Image

    Directory of Open Access Journals (Sweden)

    Michał Grega

    2016-01-01

    Full Text Available Closed circuit television systems (CCTV are becoming more and more popular and are being deployed in many offices, housing estates and in most public spaces. Monitoring systems have been implemented in many European and American cities. This makes for an enormous load for the CCTV operators, as the number of camera views a single operator can monitor is limited by human factors. In this paper, we focus on the task of automated detection and recognition of dangerous situations for CCTV systems. We propose algorithms that are able to alert the human operator when a firearm or knife is visible in the image. We have focused on limiting the number of false alarms in order to allow for a real-life application of the system. The specificity and sensitivity of the knife detection are significantly better than others published recently. We have also managed to propose a version of a firearm detection algorithm that offers a near-zero rate of false alarms. We have shown that it is possible to create a system that is capable of an early warning in a dangerous situation, which may lead to faster and more effective response times and a reduction in the number of potential victims.

  6. X-ray detectors in medical imaging

    Energy Technology Data Exchange (ETDEWEB)

    Spahn, Martin, E-mail: martin.spahn@siemens.com [Siemens AG, Healthcare Sector, Imaging and Therapy Systems, 91301 Forchheim (Germany)

    2013-12-11

    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{sub 2}O{sub 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.

  7. [Tattoos and medical imaging: issues and myths].

    Science.gov (United States)

    Kluger, Nicolas

    2014-05-01

    Tattooing is characterized by the introduction in the dermis of exogenous pigments to obtain a permanent design. Whether it is a traditional tattoo applied on the skin or a cosmetic one (permanent make-up), its prevalence has boomed for the past 20 years. The increased prevalence of tattooed patients along with medical progresses, in the field of therapeutics or diagnostic means have lead to the discovery of "new" complications and unexpected issues. Medical imaging world has also been affected by the tattoo craze. It has been approximately 20 years when the first issues related to tattooing and permanent make-up aroused. However, cautions and questions as well as anecdotal severe case reports have sometimes led to an over-exaggerated response by some physicians such as the systematic avoidance of RMN imaging for tattooed individuals. This review is intended to summarize the risks but also the "myths" associated with tattoo in the daily practice of the radiologist for RMN, CT scan, mammography, Pet-scan and ultrasound imaging.

  8. Mining knowledge in medical image databases

    Science.gov (United States)

    Perner, Petra

    2000-04-01

    Availability of digital data within picture archiving and communication systems raises a possibility of health care and research enhancement associated with manipulation, processing and handling of data by computers. That is the basis for computer-assisted radiology development. Further development of computer-assisted radiology is associated with the use of new intelligent capabilities such as multimedia support and data mining in order to discover the relevant knowledge for diagnosis. In this paper, we present our work on data mining in medical picture archiving systems. We use decision tree induction in order to learn the knowledge for computer- assisted image analysis. We are applying our method to interpretation of x-ray images for lung cancer diagnosis. We are describing our methodology on how to perform data mining on picture archiving systems and our tool for data mining. Results are given. The method has shown very good results so that we are going on to apply it to other medical image diagnosis tasks such as lymph node diagnosis in MRI and investigation of breast MRI.

  9. Scalar-vector quantization of medical images.

    Science.gov (United States)

    Mohsenian, N; Shahri, H; Nasrabadi, N M

    1996-01-01

    A new coding scheme based on the scalar-vector quantizer (SVQ) is developed for compression of medical images. The SVQ is a fixed rate encoder and its rate-distortion performance is close to that of optimal entropy-constrained scalar quantizers (ECSQs) for memoryless sources. The use of a fixed-rate quantizer is expected to eliminate some of the complexity of using variable-length scalar quantizers. When transmission of images over noisy channels is considered, our coding scheme does not suffer from error propagation that is typical of coding schemes using variable-length codes. For a set of magnetic resonance (MR) images, coding results obtained from SVQ and ECSQ at low bit rates are indistinguishable. Furthermore, our encoded images are perceptually indistinguishable from the original when displayed on a monitor. This makes our SVQ-based coder an attractive compression scheme for picture archiving and communication systems (PACS). PACS are currently under study for use in an all-digital radiology environment in hospitals, where reliable transmission, storage, and high fidelity reconstruction of images are desired. PMID:18285124

  10. Medical Image Protection using steganography by crypto-image as cover Image

    OpenAIRE

    Vinay Pandey; Manish Shrivastava

    2012-01-01

    This paper presents securing the transmission of medical images. The presented algorithms will be applied to images. This work presents a new method that combines image cryptography, data hiding and Steganography technique for denoised and safe image transmission purpose. In This method we encrypt the original image with two shares mechanism encryption algorithm then embed the encrypted image with patient information by using lossless data embedding technique with data hiding method after tha...

  11. Medical image diagnosis of liver cancer using artificial intelligence

    International Nuclear Information System (INIS)

    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)

  12. 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...... is suggested. These investigations show that the MV beamformer provides a significantly reduced main-lobe width compared to the conventional delay and sum beamformer. The effects of near-field propagation and a comparison between a subband and a temporal implementation are considered. And an investigation...

  13. 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.

  14. Application of automated image analysis to coal petrography

    Science.gov (United States)

    Chao, E.C.T.; Minkin, J.A.; Thompson, C.L.

    1982-01-01

    The coal petrologist seeks to determine the petrographic characteristics of organic and inorganic coal constituents and their lateral and vertical variations within a single coal bed or different coal beds of a particular coal field. Definitive descriptions of coal characteristics and coal facies provide the basis for interpretation of depositional environments, diagenetic changes, and burial history and determination of the degree of coalification or metamorphism. Numerous coal core or columnar samples must be studied in detail in order to adequately describe and define coal microlithotypes, lithotypes, and lithologic facies and their variations. The large amount of petrographic information required can be obtained rapidly and quantitatively by use of an automated image-analysis system (AIAS). An AIAS can be used to generate quantitative megascopic and microscopic modal analyses for the lithologic units of an entire columnar section of a coal bed. In our scheme for megascopic analysis, distinctive bands 2 mm or more thick are first demarcated by visual inspection. These bands consist of either nearly pure microlithotypes or lithotypes such as vitrite/vitrain or fusite/fusain, or assemblages of microlithotypes. Megascopic analysis with the aid of the AIAS is next performed to determine volume percentages of vitrite, inertite, minerals, and microlithotype mixtures in bands 0.5 to 2 mm thick. The microlithotype mixtures are analyzed microscopically by use of the AIAS to determine their modal composition in terms of maceral and optically observable mineral components. Megascopic and microscopic data are combined to describe the coal unit quantitatively in terms of (V) for vitrite, (E) for liptite, (I) for inertite or fusite, (M) for mineral components other than iron sulfide, (S) for iron sulfide, and (VEIM) for the composition of the mixed phases (Xi) i = 1,2, etc. in terms of the maceral groups vitrinite V, exinite E, inertinite I, and optically observable mineral

  15. Medical imaging projects meet at CERN

    CERN Multimedia

    CERN Bulletin

    2013-01-01

    ENTERVISION, the Research Training Network in 3D Digital Imaging for Cancer Radiation Therapy, successfully passed its mid-term review held at CERN on 11 January. This multidisciplinary project aims at qualifying experts in medical imaging techniques for improved hadron therapy.   ENTERVISION provides training in physics, medicine, electronics, informatics, radiobiology and engineering, as well as a wide range of soft skills, to 16 researchers of different backgrounds and nationalities. The network is funded by the European Commission within the Marie Curie Initial Training Network, and relies on the EU-funded research project ENVISION to provide a training platform for the Marie Curie researchers. The two projects hold their annual meetings jointly, allowing the young researchers to meet senior scientists and to have a full picture of the latest developments in the field beyond their individual research project. ENVISION and ENTERVISION are both co-ordinated by CERN, and the Laboratory hosts t...

  16. MMSPix - A multimedia service (MMS) medical images weblog.

    Science.gov (United States)

    Fontelo, Paul; Liu, Fang; Muin, Michael; Ducut, Erick; Ackerman, Michael; Paalan-Vasquez, Franciene

    2007-01-01

    Smartphones with cameras have added a new dimension to augmenting medical image collections for education and teleconsultation. It allows healthcare personnel to instantly capture and send images through the multimedia messaging service (MMS) protocol. We developed a searchable archive, a mobile images Weblog of camera phone images for medical education. Registered users can view and comment on uploaded images. The archive is compartmentalized to allow sharing images with all viewers and by clinical specialty groups.

  17. CONTENT BASED MEDICAL IMAGE RETRIEVAL USING BINARY ASSOCIATION RULES

    OpenAIRE

    Akila; Uma Maheswari

    2013-01-01

    In this study, we propose a content-based medical image retrieval framework based on binary association rules to augment the results of medical image diagnosis, for supporting clinical decision making. Specifically, this work is employed on scanned Magnetic Resonance brain Images (MRI) and the proposed Content Based Image Retrieval (CBIR) process is for enhancing relevancy rate of retrieved images. The pertinent features of a query brain image are extracted by applying third order moment inva...

  18. Fast Model Adaptation for Automated Section Classification in Electronic Medical Records.

    Science.gov (United States)

    Ni, Jian; Delaney, Brian; Florian, Radu

    2015-01-01

    Medical information extraction is the automatic extraction of structured information from electronic medical records, where such information can be used for improving healthcare processes and medical decision making. In this paper, we study one important medical information extraction task called section classification. The objective of section classification is to automatically identify sections in a medical document and classify them into one of the pre-defined section types. Training section classification models typically requires large amounts of human labeled training data to achieve high accuracy. Annotating institution-specific data, however, can be both expensive and time-consuming; which poses a big hurdle for adapting a section classification model to new medical institutions. In this paper, we apply two advanced machine learning techniques, active learning and distant supervision, to reduce annotation cost and achieve fast model adaptation for automated section classification in electronic medical records. Our experiment results show that active learning reduces the annotation cost and time by more than 50%, and distant supervision can achieve good model accuracy using weakly labeled training data only. PMID:26262005

  19. Automated image analysis of atomic force microscopy images of rotavirus particles

    Energy Technology Data Exchange (ETDEWEB)

    Venkataraman, S. [Life Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831 (United States); Department of Electrical and Computer Engineering, University of Tennessee, Knoxville, TN 37996 (United States); Allison, D.P. [Life Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831 (United States); Department of Biochemistry, Cellular, and Molecular Biology, University of Tennessee, Knoxville, TN 37996 (United States); Molecular Imaging Inc. Tempe, AZ, 85282 (United States); Qi, H. [Department of Electrical and Computer Engineering, University of Tennessee, Knoxville, TN 37996 (United States); Morrell-Falvey, J.L. [Life Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831 (United States); Kallewaard, N.L. [Vanderbilt University Medical Center, Nashville, TN 37232-2905 (United States); Crowe, J.E. [Vanderbilt University Medical Center, Nashville, TN 37232-2905 (United States); Doktycz, M.J. [Life Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831 (United States)]. E-mail: doktyczmj@ornl.gov

    2006-06-15

    A variety of biological samples can be imaged by the atomic force microscope (AFM) under environments that range from vacuum to ambient to liquid. Generally imaging is pursued to evaluate structural features of the sample or perhaps identify some structural changes in the sample that are induced by the investigator. In many cases, AFM images of sample features and induced structural changes are interpreted in general qualitative terms such as markedly smaller or larger, rougher, highly irregular, or smooth. Various manual tools can be used to analyze images and extract more quantitative data, but this is usually a cumbersome process. To facilitate quantitative AFM imaging, automated image analysis routines are being developed. Viral particles imaged in water were used as a test case to develop an algorithm that automatically extracts average dimensional information from a large set of individual particles. The extracted information allows statistical analyses of the dimensional characteristics of the particles and facilitates interpretation related to the binding of the particles to the surface. This algorithm is being extended for analysis of other biological samples and physical objects that are imaged by AFM.

  20. EPR Hidden Medical Image Secret Sharing using DNA Cryptography

    OpenAIRE

    L.Jani Anbarasi; Dr.G.S.Anandha Mala

    2014-01-01

    Security of medical images is an important issue, since applications such as Tele diagnosis exchange information over insecure communication channels. In this paper, Shamir secret sharing algorithm combined with DNA cryptography is proposed. The method involves the dispersion of medical image and Electronic Patient Record (EPR) into shadow images, aiming at better security characteristics. The EPR is hidden into the medical image using DNA hiding techniques. Huffman encoding is used to compre...

  1. Medical Image Retrieval Based on Multi-Layer Resampling Template

    Institute of Scientific and Technical Information of China (English)

    WANG Xin-rui; YANG Yun-feng

    2014-01-01

    Medical image application in clinical diagnosis and treatment is becoming more and more widely, How to use a large number of images in the image management system and it is a very important issue how to assist doctors to analyze and diagnose. This paper studies the medical image retrieval based on multi-layer resampling template under the thought of the wavelet decomposition, the image retrieval method consists of two retrieval process which is coarse and fine retrieval. Coarse retrieval process is the medical image retrieval process based on the image contour features. Fine retrieval process is the medical image retrieval process based on multi-layer resampling template, a multi-layer sampling operator is employed to extract image resampling images each layer, then these resampling images are retrieved step by step to finish the process from coarse to fine retrieval.

  2. Investigation of Bias in Continuous Medical Image Label Fusion.

    Science.gov (United States)

    Xing, Fangxu; Prince, Jerry L; Landman, Bennett A

    2016-01-01

    Image labeling is essential for analyzing morphometric features in medical imaging data. Labels can be obtained by either human interaction or automated segmentation algorithms, both of which suffer from errors. The Simultaneous Truth and Performance Level Estimation (STAPLE) algorithm for both discrete-valued and continuous-valued labels has been proposed to find the consensus fusion while simultaneously estimating rater performance. In this paper, we first show that the previously reported continuous STAPLE in which bias and variance are used to represent rater performance yields a maximum likelihood solution in which bias is indeterminate. We then analyze the major cause of the deficiency and evaluate two classes of auxiliary bias estimation processes, one that estimates the bias as part of the algorithm initialization and the other that uses a maximum a posteriori criterion with a priori probabilities on the rater bias. We compare the efficacy of six methods, three variants from each class, in simulations and through empirical human rater experiments. We comment on their properties, identify deficient methods, and propose effective methods as solution. PMID:27258158

  3. Investigation of Bias in Continuous Medical Image Label Fusion.

    Directory of Open Access Journals (Sweden)

    Fangxu Xing

    Full Text Available Image labeling is essential for analyzing morphometric features in medical imaging data. Labels can be obtained by either human interaction or automated segmentation algorithms, both of which suffer from errors. The Simultaneous Truth and Performance Level Estimation (STAPLE algorithm for both discrete-valued and continuous-valued labels has been proposed to find the consensus fusion while simultaneously estimating rater performance. In this paper, we first show that the previously reported continuous STAPLE in which bias and variance are used to represent rater performance yields a maximum likelihood solution in which bias is indeterminate. We then analyze the major cause of the deficiency and evaluate two classes of auxiliary bias estimation processes, one that estimates the bias as part of the algorithm initialization and the other that uses a maximum a posteriori criterion with a priori probabilities on the rater bias. We compare the efficacy of six methods, three variants from each class, in simulations and through empirical human rater experiments. We comment on their properties, identify deficient methods, and propose effective methods as solution.

  4. Investigation of Bias in Continuous Medical Image Label Fusion.

    Science.gov (United States)

    Xing, Fangxu; Prince, Jerry L; Landman, Bennett A

    2016-01-01

    Image labeling is essential for analyzing morphometric features in medical imaging data. Labels can be obtained by either human interaction or automated segmentation algorithms, both of which suffer from errors. The Simultaneous Truth and Performance Level Estimation (STAPLE) algorithm for both discrete-valued and continuous-valued labels has been proposed to find the consensus fusion while simultaneously estimating rater performance. In this paper, we first show that the previously reported continuous STAPLE in which bias and variance are used to represent rater performance yields a maximum likelihood solution in which bias is indeterminate. We then analyze the major cause of the deficiency and evaluate two classes of auxiliary bias estimation processes, one that estimates the bias as part of the algorithm initialization and the other that uses a maximum a posteriori criterion with a priori probabilities on the rater bias. We compare the efficacy of six methods, three variants from each class, in simulations and through empirical human rater experiments. We comment on their properties, identify deficient methods, and propose effective methods as solution.

  5. Automated torso organ segmentation from 3D CT images using structured perceptron and dual decomposition

    Science.gov (United States)

    Nimura, Yukitaka; Hayashi, Yuichiro; Kitasaka, Takayuki; Mori, Kensaku

    2015-03-01

    This paper presents a method for torso organ segmentation from abdominal CT images using structured perceptron and dual decomposition. A lot of methods have been proposed to enable automated extraction of organ regions from volumetric medical images. However, it is necessary to adjust empirical parameters of them to obtain precise organ regions. This paper proposes an organ segmentation method using structured output learning. Our method utilizes a graphical model and binary features which represent the relationship between voxel intensities and organ labels. Also we optimize the weights of the graphical model by structured perceptron and estimate the best organ label for a given image by dynamic programming and dual decomposition. The experimental result revealed that the proposed method can extract organ regions automatically using structured output learning. The error of organ label estimation was 4.4%. The DICE coefficients of left lung, right lung, heart, liver, spleen, pancreas, left kidney, right kidney, and gallbladder were 0.91, 0.95, 0.77, 0.81, 0.74, 0.08, 0.83, 0.84, and 0.03, respectively.

  6. Use of automated image registration to generate mean brain SPECT image of Alzheimer's patients

    International Nuclear Information System (INIS)

    The purpose of this study was to compute and compare the group mean HMPAO brain SPECT images of patients with senile dementia of Alzheimer's type (SDAT) and age matched control subjects after transformation of the individual images to a standard size and shape. Ten patients with Alzheimer's disease (age 71.6±5.0 yr) and ten age matched normal subjects (age 71.0±6.1 yr) participated in this study. Tc-99m HMPAO brain SPECT and X-ray CT scans were acquired for each subject. SPECT images were normalized to an average activity of 100 counts/pixel. Individual brain images were transformed to a standard size and shape with the help of Automated Image Registration (AIR). Realigned brain SPECT images of both groups were used to generate mean and standard deviation images by arithmetic operations on voxel based numerical values. Mean images of both groups were compared by applying the unpaired t-test on a voxel by voxel basis to generate three dimensional T-maps. X-ray CT images of individual subjects were evaluated by means of a computer program for brain atrophy. A significant decrease in relative radioisotope (RI) uptake was present in the bilateral superior and inferior parietal lobules (p<0.05), bilateral inferior temporal gyri, and the bilateral superior and middle frontal gyri (p<0.001). The mean brain atrophy indices for patients and normal subjects were 0.853±0.042 and 0.933±0.017 respectively, the difference being statistically significant (p<0.001). The use of a brain image standardization procedure increases the accuracy of voxel based group comparisons. Thus, intersubject averaging enhances the capacity for detection of abnormalities in functional brain images by minimizing the influence of individual variation. (author)

  7. Imaging Automation and Volume Tomographic Visualization at Texas Neutron Imaging Facility

    International Nuclear Information System (INIS)

    A thermal neutron imaging facility for real-time neutron radiography and computed tomography has been developed at the University of Texas reactor. The facility produced good-quality radiographs and two-dimensional tomograms. Further developments have been recently accomplished. A computer software has been developed to automate and expedite the data acquisition and reconstruction processes. Volume tomographic visualization using Interactive Data Language (IDL) software has been demonstrated and will be further developed. Volume tomography provides the additional flexibility of producing slices of the object using software and thus avoids redoing the measurements

  8. Imaging automation and volume tomographic visualization at Texas Neutron Imaging Facility

    International Nuclear Information System (INIS)

    A thermal neutron imaging facility for real-time neutron radiography and computed tomography has been developed at the University of Texas reactor. The facility produced a good-quality radiographs and two-dimensional tomograms. Further developments have been recently accomplished. Further developments have been recently accomplished. A computer software has been developed to automate and expedite the data acquisition and reconstruction processes. Volume tomographic visualization using Interactive Data Language (IDL) software has been demonstrated and will be further developed. Volume tomography provides the additional flexibility of producing slices of the object using software and thus avoids redoing the measurements

  9. Multimodal Medical Image Fusion by Adaptive Manifold Filter

    OpenAIRE

    Peng Geng; Shuaiqi Liu; Shanna Zhuang

    2015-01-01

    Medical image fusion plays an important role in diagnosis and treatment of diseases such as image-guided radiotherapy and surgery. The modified local contrast information is proposed to fuse multimodal medical images. Firstly, the adaptive manifold filter is introduced into filtering source images as the low-frequency part in the modified local contrast. Secondly, the modified spatial frequency of the source images is adopted as the high-frequency part in the modified local contrast. Finally,...

  10. A New Medical Image Enhancement Based on Human Visual Characteristics

    Institute of Scientific and Technical Information of China (English)

    DONG Ai-bin; HE Jun

    2013-01-01

    Study of image enhancement shows that the quality of image heavily relies on human visual system. In this paper, we apply this fact effectively to design a new image enhancement method for medical images that improves the detail regions. First, the eye region of interest (ROI) is segmented; then the Un-sharp Masking (USM) is used to enhance the detail regions. Experiments show that the proposed method can effectively improve the accuracy of medical image enhancement and has a significant effect.

  11. Improving Diagnostic Viewing of Medical Images using Enhancement Algorithms

    Directory of Open Access Journals (Sweden)

    Hanan S.S. Ahmed

    2011-01-01

    Full Text Available Problem statement: Various images are low quality and difficultly to detect and extract information. Therefore, the image has to get under a process called image enhancement which contains an aggregation of techniques that look for improving the visual aspect of an image. Medical images are one of the fundamental images, because they are used in more sensitive field which is a medical field. The raw data obtained straight from devices of medical acquisition may afford a comparatively poor image quality representation and may destroy by several types of noises. Image Enhancement (IE and denoising algorithms for executing the requirements of digital medical image enhancement is introduced. The main goal of this study is to improve features and gain better characteristics of medical images for a right diagnosis. Approach: The proposed techniques start by the median filter for removing noise on images followed by unsharp mask filter which is believable the usual type of sharpening. Medical images were usually poor quality especially in contrast. For solving this problem, we proposed Contrast Limited Adaptive Histogram Equalization (CLAHE which is one of the techniques in a computer image processing domain. It was used to amend contrast in images. Results: For testing purposes, different sizes and various types of medical images were used and more than 60 images in different parts of the body. From the experts’ evaluation, they noted that the enhanced images improved up to 80% from the original images depends on medical images modalities. Conclusion: The proposed algorithms results were significant for increasing the visibleness of relatively details without distorting the images.

  12. Guideline report. Medical ultrasound imaging: progress and opportunities.

    Science.gov (United States)

    Burns, M

    1989-01-01

    Utilization of medical ultrasound has expanded rapidly during the past several years. In 1988, sales of ultrasound equipment will approach $600 million, which is higher than any other individual imaging modality, including the most capital intensive, such as magnetic resonance imaging (MRI), computed tomography (CT), and cath lab angiography. This growth would have been difficult to predict previously, since ultrasound appeared to be a relatively mature imaging modality not too long ago. There are several reasons for this growth. Technological developments have been quite rapid; ultrasound has become easier to use, image quality has improved dramatically, and diagnostic accuracy has been enhanced. There has been a proliferation of new equipment at all ends of the price spectrum, allowing the user a wide choice in instrument performance, multi-function capabilities, and automated features to increase patient throughput. The DRG environment and the prospect for more pre-admission tests have also been a stimulus. Hospital buying activity has expanded, and many more ultrasound exams are now being conducted on an outpatient basis. Sales to freestanding imaging centers and individual physicians have similarly increased. The hospital user is willing to pay a large premium for advanced technical performance and is prepared to retire or replace older technology in less than three years. This replacement cycle is much shorter than the four to five year period which existed prior to 1985. By comparison, some of the more traditional imaging areas, such as radiology, have replacement rates of eight to ten years. The reason for early replacement is obvious. Ultrasound exams in hospitals generate revenues at a rate that justifies the purchase of the most advanced equipment. It also improves the referral rate and positions the hospital as a high quality provider. Even with low utilization rates, an ultrasound instrument can normally pay for itself in less than one year of regular

  13. Twelve automated thresholding methods for segmentation of PET images: a phantom study

    Science.gov (United States)

    Prieto, Elena; Lecumberri, Pablo; Pagola, Miguel; Gómez, Marisol; Bilbao, Izaskun; Ecay, Margarita; Peñuelas, Iván; Martí-Climent, Josep M.

    2012-06-01

    Tumor volume delineation over positron emission tomography (PET) images is of great interest for proper diagnosis and therapy planning. However, standard segmentation techniques (manual or semi-automated) are operator dependent and time consuming while fully automated procedures are cumbersome or require complex mathematical development. The aim of this study was to segment PET images in a fully automated way by implementing a set of 12 automated thresholding algorithms, classical in the fields of optical character recognition, tissue engineering or non-destructive testing images in high-tech structures. Automated thresholding algorithms select a specific threshold for each image without any a priori spatial information of the segmented object or any special calibration of the tomograph, as opposed to usual thresholding methods for PET. Spherical 18F-filled objects of different volumes were acquired on clinical PET/CT and on a small animal PET scanner, with three different signal-to-background ratios. Images were segmented with 12 automatic thresholding algorithms and results were compared with the standard segmentation reference, a threshold at 42% of the maximum uptake. Ridler and Ramesh thresholding algorithms based on clustering and histogram-shape information, respectively, provided better results that the classical 42%-based threshold (p < 0.05). We have herein demonstrated that fully automated thresholding algorithms can provide better results than classical PET segmentation tools.

  14. Twelve automated thresholding methods for segmentation of PET images: a phantom study

    International Nuclear Information System (INIS)

    Tumor volume delineation over positron emission tomography (PET) images is of great interest for proper diagnosis and therapy planning. However, standard segmentation techniques (manual or semi-automated) are operator dependent and time consuming while fully automated procedures are cumbersome or require complex mathematical development. The aim of this study was to segment PET images in a fully automated way by implementing a set of 12 automated thresholding algorithms, classical in the fields of optical character recognition, tissue engineering or non-destructive testing images in high-tech structures. Automated thresholding algorithms select a specific threshold for each image without any a priori spatial information of the segmented object or any special calibration of the tomograph, as opposed to usual thresholding methods for PET. Spherical 18F-filled objects of different volumes were acquired on clinical PET/CT and on a small animal PET scanner, with three different signal-to-background ratios. Images were segmented with 12 automatic thresholding algorithms and results were compared with the standard segmentation reference, a threshold at 42% of the maximum uptake. Ridler and Ramesh thresholding algorithms based on clustering and histogram-shape information, respectively, provided better results that the classical 42%-based threshold (p < 0.05). We have herein demonstrated that fully automated thresholding algorithms can provide better results than classical PET segmentation tools. (paper)

  15. Automating and estimating glomerular filtration rate for dosing medications and staging chronic kidney disease

    Directory of Open Access Journals (Sweden)

    Trinkley KE

    2014-05-01

    Full Text Available Katy E Trinkley,1 S Michelle Nikels,2 Robert L Page II,1 Melanie S Joy11Skaggs School of Pharmacy and Pharmaceutical Sciences, 2School of Medicine, University of Colorado, Aurora, CO, USA Objective: The purpose of this paper is to serve as a review for primary care providers on the bedside methods for estimating glomerular filtration rate (GFR for dosing and chronic kidney disease (CKD staging and to discuss how automated health information technologies (HIT can enhance clinical documentation of staging and reduce medication errors in patients with CKD.Methods: A nonsystematic search of PubMed (through March 2013 was conducted to determine the optimal approach to estimate GFR for dosing and CKD staging and to identify examples of how automated HITs can improve health outcomes in patients with CKD. Papers known to the authors were included, as were scientific statements. Articles were chosen based on the judgment of the authors.Results: Drug-dosing decisions should be based on the method used in the published studies and package labeling that have been determined to be safe, which is most often the Cockcroft–Gault formula unadjusted for body weight. Although Modification of Diet in Renal Disease is more commonly used in practice for staging, the CKD–Epidemiology Collaboration (CKD–EPI equation is the most accurate formula for estimating the CKD staging, especially at higher GFR values. Automated HITs offer a solution to the complexity of determining which equation to use for a given clinical scenario. HITs can educate providers on which formula to use and how to apply the formula in a given clinical situation, ultimately improving appropriate medication and medical management in CKD patients.Conclusion: Appropriate estimation of GFR is key to optimal health outcomes. HITs assist clinicians in both choosing the most appropriate GFR estimation formula and in applying the results of the GFR estimation in practice. Key limitations of the

  16. An online interactive simulation system for medical imaging education.

    Science.gov (United States)

    Dikshit, Aditya; Wu, Dawei; Wu, Chunyan; Zhao, Weizhao

    2005-09-01

    This report presents a recently developed web-based medical imaging simulation system for teaching students or other trainees who plan to work in the medical imaging field. The increased importance of computer and information technology widely applied to different imaging techniques in clinics and medical research necessitates a comprehensive medical imaging education program. A complete tutorial of simulations introducing popular imaging modalities, such as X-ray, MRI, CT, ultrasound and PET, forms an essential component of such an education. Internet technologies provide a vehicle to carry medical imaging education online. There exist a number of internet-based medical imaging hyper-books or online documentations. However, there are few providing interactive computational simulations. We focus on delivering knowledge of the physical principles and engineering implementation of medical imaging techniques through an interactive website environment. The online medical imaging simulation system presented in this report outlines basic principles underlying different imaging techniques and image processing algorithms and offers trainees an interactive virtual laboratory. For education purposes, this system aims to provide general understanding of each imaging modality with comprehensive explanations, ample illustrations and copious references as its thrust, rather than complex physics or detailed math. This report specifically describes the development of the tutorial for commonly used medical imaging modalities. An internet-accessible interface is used to simulate various imaging algorithms with user-adjustable parameters. The tutorial is under the MATLAB Web Server environment. Macromedia Director MX is used to develop interactive animations integrating theory with graphic-oriented simulations. HTML and JavaScript are used to enable a user to explore these modules online in a web browser. Numerous multiple choice questions, links and references for advanced study are

  17. An online interactive simulation system for medical imaging education.

    Science.gov (United States)

    Dikshit, Aditya; Wu, Dawei; Wu, Chunyan; Zhao, Weizhao

    2005-09-01

    This report presents a recently developed web-based medical imaging simulation system for teaching students or other trainees who plan to work in the medical imaging field. The increased importance of computer and information technology widely applied to different imaging techniques in clinics and medical research necessitates a comprehensive medical imaging education program. A complete tutorial of simulations introducing popular imaging modalities, such as X-ray, MRI, CT, ultrasound and PET, forms an essential component of such an education. Internet technologies provide a vehicle to carry medical imaging education online. There exist a number of internet-based medical imaging hyper-books or online documentations. However, there are few providing interactive computational simulations. We focus on delivering knowledge of the physical principles and engineering implementation of medical imaging techniques through an interactive website environment. The online medical imaging simulation system presented in this report outlines basic principles underlying different imaging techniques and image processing algorithms and offers trainees an interactive virtual laboratory. For education purposes, this system aims to provide general understanding of each imaging modality with comprehensive explanations, ample illustrations and copious references as its thrust, rather than complex physics or detailed math. This report specifically describes the development of the tutorial for commonly used medical imaging modalities. An internet-accessible interface is used to simulate various imaging algorithms with user-adjustable parameters. The tutorial is under the MATLAB Web Server environment. Macromedia Director MX is used to develop interactive animations integrating theory with graphic-oriented simulations. HTML and JavaScript are used to enable a user to explore these modules online in a web browser. Numerous multiple choice questions, links and references for advanced study are

  18. Medical Image Analysis by Cognitive Information Systems - a Review.

    Science.gov (United States)

    Ogiela, Lidia; Takizawa, Makoto

    2016-10-01

    This publication presents a review of medical image analysis systems. The paradigms of cognitive information systems will be presented by examples of medical image analysis systems. The semantic processes present as it is applied to different types of medical images. Cognitive information systems were defined on the basis of methods for the semantic analysis and interpretation of information - medical images - applied to cognitive meaning of medical images contained in analyzed data sets. Semantic analysis was proposed to analyzed the meaning of data. Meaning is included in information, for example in medical images. Medical image analysis will be presented and discussed as they are applied to various types of medical images, presented selected human organs, with different pathologies. Those images were analyzed using different classes of cognitive information systems. Cognitive information systems dedicated to medical image analysis was also defined for the decision supporting tasks. This process is very important for example in diagnostic and therapy processes, in the selection of semantic aspects/features, from analyzed data sets. Those features allow to create a new way of analysis.

  19. Radiation Dose from Medical Imaging: A Primer for Emergency Physicians

    OpenAIRE

    Jones, Jesse G.A; Mills, Christopher N.; Mogensen, Monique A.; Lee, Christoph I.

    2012-01-01

    Introduction: Medical imaging now accounts for most of the US population’s exposure to ionizing radiation. A substantial proportion of this medical imaging is ordered in the emergency setting. We aim to provide a general overview of radiation dose from medical imaging with a focus on computed tomography, as well as a literature review of recent efforts to decrease unnecessary radiation exposure to patients in the emergency department setting. Methods: We conducted a literature revie...

  20. Survey of Despeckling Techniques for Medical Ultrasound Images

    Directory of Open Access Journals (Sweden)

    Jappreet Kaur

    2011-07-01

    Full Text Available Ultrasound imaging is the most commonly used imaging system in medical field. Main problem related to this imaging technique is introduction of speckle noise, thus making the image unclear. The success of ultrasonic examination depends on the image quality which is usually retarded due to speckle noise. There have been several techniques for effective suppression of speckle noise present in ultrasound images. This paper presents a review of some significant work carried out for despeckling of ultrasound images.

  1. SU-C-304-04: A Compact Modular Computational Platform for Automated On-Board Imager Quality Assurance

    International Nuclear Information System (INIS)

    quality assurance tests, such as 2D/3D image quality, making completely automated QA possible. Research Funding from Varian Medical Systems Inc. . Dr. Sasa Mutic receives compensation for providing patient safety training services from Varian Medical Systems, the sponsor of this study

  2. SU-C-304-04: A Compact Modular Computational Platform for Automated On-Board Imager Quality Assurance

    Energy Technology Data Exchange (ETDEWEB)

    Dolly, S [Washington University School of Medicine, Saint Louis, MO (United States); University of Missouri, Columbia, MO (United States); Cai, B; Chen, H; Anastasio, M; Sun, B; Yaddanapudi, S; Noel, C; Goddu, S; Mutic, S; Li, H [Washington University School of Medicine, Saint Louis, MO (United States); Tan, J [UTSouthwestern Medical Center, Dallas, TX (United States)

    2015-06-15

    quality assurance tests, such as 2D/3D image quality, making completely automated QA possible. Research Funding from Varian Medical Systems Inc. . Dr. Sasa Mutic receives compensation for providing patient safety training services from Varian Medical Systems, the sponsor of this study.

  3. Neuron Image Analyzer: Automated and Accurate Extraction of Neuronal Data from Low Quality Images.

    Science.gov (United States)

    Kim, Kwang-Min; Son, Kilho; Palmore, G Tayhas R

    2015-01-01

    Image analysis software is an essential tool used in neuroscience and neural engineering to evaluate changes in neuronal structure following extracellular stimuli. Both manual and automated methods in current use are severely inadequate at detecting and quantifying changes in neuronal morphology when the images analyzed have a low signal-to-noise ratio (SNR). This inadequacy derives from the fact that these methods often include data from non-neuronal structures or artifacts by simply tracing pixels with high intensity. In this paper, we describe Neuron Image Analyzer (NIA), a novel algorithm that overcomes these inadequacies by employing Laplacian of Gaussian filter and graphical models (i.e., Hidden Markov Model, Fully Connected Chain Model) to specifically extract relational pixel information corresponding to neuronal structures (i.e., soma, neurite). As such, NIA that is based on vector representation is less likely to detect false signals (i.e., non-neuronal structures) or generate artifact signals (i.e., deformation of original structures) than current image analysis algorithms that are based on raster representation. We demonstrate that NIA enables precise quantification of neuronal processes (e.g., length and orientation of neurites) in low quality images with a significant increase in the accuracy of detecting neuronal changes post-stimulation. PMID:26593337

  4. 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...

  5. 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...

  6. AMIsurvey, chimenea and other tools: Automated imaging for transient surveys with existing radio-observatories

    CERN Document Server

    Staley, Tim D

    2015-01-01

    In preparing the way for the Square Kilometre Array and its pathfinders, there is a pressing need to begin probing the transient sky in a fully robotic fashion using the current generation of radio telescopes. Effective exploitation of such surveys requires a largely automated data-reduction process. This paper introduces an end-to-end automated reduction pipeline, AMIsurvey, used for calibrating and imaging data from the Arcminute Microkelvin Imager Large Array. AMIsurvey makes use of several component libraries which have been packaged separately for open-source release. The most scientifically significant of these is chimenea, which implements a telescope agnostic algorithm for automated imaging of pre-calibrated multi-epoch radio-synthesis data, making use of CASA subroutines for the underlying image-synthesis operations. At a lower level, AMIsurvey relies upon two libraries, drive-ami and drive-casa, built to allow use of mature radio-astronomy software packages from within Python scripts. These packages...

  7. Medical Image Edge Detection Based on EMD Method

    Institute of Scientific and Technical Information of China (English)

    PENG Shichun; LIU Jian; YAN Guoping

    2006-01-01

    As a new image analysis technique, Empirical Mode Decomposition (EMD) has been drawn more attention in recent years. In this paper, we proposed a fast EMD method for the edge detection of medical images. We implemented the method in the following steps: a) Decompose the original medical image with the image pyramid technique; b) Implement the EMD at the low resolution level image; c) Map the Intrinsic Mode Functions (IMFs) into the original image; d) Use the edge detector in a coarse IMF at the beginning of the procedure; e) Trace the detected result to the finest IMF to obtain the final image edge. Experimental results demonstrated the effectiveness of the proposed method.

  8. Quantization of polyphenolic compounds in histological sections of grape berries by automated color image analysis

    Science.gov (United States)

    Clement, Alain; Vigouroux, Bertnand

    2003-04-01

    We present new results in applied color image analysis that put in evidence the significant influence of soil on localization and appearance of polyphenols in grapes. These results have been obtained with a new unsupervised classification algorithm founded on hierarchical analysis of color histograms. The process is automated thanks to a software platform we developed specifically for color image analysis and it's applications.

  9. Medical Images Fusion with Patch Based Structure Tensor.

    Science.gov (United States)

    Luo, Fen; Sun, Jiangfeng; Hou, Shouming

    2015-01-01

    Nowadays medical imaging has played an important role in clinical use, which provide important clues for medical diagnosis. In medical image fusion, the extraction of some fine details and description is critical. To solve this problem, a modified structure tensor by considering similarity between two patches is proposed. The patch based filter can suppress noise and add the robustness of the eigen-values of the structure tensor by allowing the use of more information of far away pixels. After defining the new structure tensor, we apply it into medical image fusion with a multi-resolution wavelet theory. The features are extracted and described by the eigen-values of two multi-modality source data. To test the performance of the proposed scheme, the CT and MR images are used as input source images for medical image fusion. The experimental results show that the proposed method can produce better results compared to some related approaches. PMID:26628927

  10. Knowledge Acquisition, Validation, and Maintenance in a Planning System for Automated Image Processing

    Science.gov (United States)

    Chien, Steve A.

    1996-01-01

    A key obstacle hampering fielding of AI planning applications is the considerable expense of developing, verifying, updating, and maintainting the planning knowledge base (KB). Planning systems must be able to compare favorably in terms of software lifecycle costs to other means of automation such as scripts or rule-based expert systems. This paper describes a planning application of automated imaging processing and our overall approach to knowledge acquisition for this application.

  11. Biomedical Image Processing with Morphology and Segmentation Methods for Medical Image Analysis

    Directory of Open Access Journals (Sweden)

    Joyjit Patra

    2013-07-01

    Full Text Available Modern three-dimensional (3-D medical imaging offers the potential and promise for major advances in science and medicine as higher fidelity images are produced.It has developed into one of the most important fields within scientific imaging due to the rapid and continuing progress in computerized medical image visualization and advances in analysis methods and computer-aided diagnosis[1],and is now,for example,a vital part of the early detection,diagnosis, and treatment of cancer.The challenge is to effectively process and analyze the images in order to effectively extract, quantify,and interpret this information to gain understanding and insight into the structure and function of the organs being imaged.The general goal is to understand the information and put it to practical use.A multitude of diagnostic medical imaging systems are used to probe the human body.They comprise both microscopic (viz. cellular level and macroscopic (viz.organ and systems level modalities.Interpretation of the resulting images requires sophisticated image processing methods that enhance visual interpretation and image analysis methods that provide automated or semiautomated tissue detection,measurement, and characterization [2–4].In general,multiple transformations will be needed in order to extract the data of interest from an image,and a hierarchy in the processing steps will be evident, e.g., enhancement will precede restoration,which will precede analysis,feature extraction,and classification[5].Often,these are performed sequentially, but more sophisticated tasks will require feedback of parameters to preceding steps so that the processing includes a number of iterative loops.Segmentation is one of the key tools in medical image analysis.The objective of segmentation is to provide reliable, fast, and effective organ delineation.While traditionally, particularly in computer vision, segmentation is seen as an early vision tool used for subsequent recognition

  12. Survey of Despeckling Techniques for Medical Ultrasound Images

    OpenAIRE

    Jappreet Kaur; Jasdeep Kaur; Manpreet Kaur

    2011-01-01

    Ultrasound imaging is the most commonly used imaging system in medical field. Main problem related to this imaging technique is introduction of speckle noise, thus making the image unclear. The success of ultrasonic examination depends on the image quality which is usually retarded due to speckle noise. There have been several techniques for effective suppression of speckle noise present in ultrasound images. This paper presents a review of some significant work carried out for despeckling ...

  13. 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.

  14. Automated Photogrammetric Image Matching with Sift Algorithm and Delaunay Triangulation

    DEFF Research Database (Denmark)

    Karagiannis, Georgios; Antón Castro, Francesc/François; Mioc, Darka

    2016-01-01

    An algorithm for image matching of multi-sensor and multi-temporal satellite images is developed. The method is based on the SIFT feature detector proposed by Lowe in (Lowe, 1999). First, SIFT feature points are detected independently in two images (reference and sensed image). The features detec...... of each feature set for each image are computed. The isomorphism of the Delaunay triangulations is determined to guarantee the quality of the image matching. The algorithm is implemented in Matlab and tested on World-View 2, SPOT6 and TerraSAR-X image patches....

  15. Automated Micro-Object Detection for Mobile Diagnostics Using Lens-Free Imaging Technology

    Directory of Open Access Journals (Sweden)

    Mohendra Roy

    2016-05-01

    Full Text Available Lens-free imaging technology has been extensively used recently for microparticle and biological cell analysis because of its high throughput, low cost, and simple and compact arrangement. However, this technology still lacks a dedicated and automated detection system. In this paper, we describe a custom-developed automated micro-object detection method for a lens-free imaging system. In our previous work (Roy et al., we developed a lens-free imaging system using low-cost components. This system was used to generate and capture the diffraction patterns of micro-objects and a global threshold was used to locate the diffraction patterns. In this work we used the same setup to develop an improved automated detection and analysis algorithm based on adaptive threshold and clustering of signals. For this purpose images from the lens-free system were then used to understand the features and characteristics of the diffraction patterns of several types of samples. On the basis of this information, we custom-developed an automated algorithm for the lens-free imaging system. Next, all the lens-free images were processed using this custom-developed automated algorithm. The performance of this approach was evaluated by comparing the counting results with standard optical microscope results. We evaluated the counting results for polystyrene microbeads, red blood cells, and HepG2, HeLa, and MCF7 cells. The comparison shows good agreement between the systems, with a correlation coefficient of 0.91 and linearity slope of 0.877. We also evaluated the automated size profiles of the microparticle samples. This Wi-Fi-enabled lens-free imaging system, along with the dedicated software, possesses great potential for telemedicine applications in resource-limited settings.

  16. Automated Micro-Object Detection for Mobile Diagnostics Using Lens-Free Imaging Technology.

    Science.gov (United States)

    Roy, Mohendra; Seo, Dongmin; Oh, Sangwoo; Chae, Yeonghun; Nam, Myung-Hyun; Seo, Sungkyu

    2016-01-01

    Lens-free imaging technology has been extensively used recently for microparticle and biological cell analysis because of its high throughput, low cost, and simple and compact arrangement. However, this technology still lacks a dedicated and automated detection system. In this paper, we describe a custom-developed automated micro-object detection method for a lens-free imaging system. In our previous work (Roy et al.), we developed a lens-free imaging system using low-cost components. This system was used to generate and capture the diffraction patterns of micro-objects and a global threshold was used to locate the diffraction patterns. In this work we used the same setup to develop an improved automated detection and analysis algorithm based on adaptive threshold and clustering of signals. For this purpose images from the lens-free system were then used to understand the features and characteristics of the diffraction patterns of several types of samples. On the basis of this information, we custom-developed an automated algorithm for the lens-free imaging system. Next, all the lens-free images were processed using this custom-developed automated algorithm. The performance of this approach was evaluated by comparing the counting results with standard optical microscope results. We evaluated the counting results for polystyrene microbeads, red blood cells, and HepG2, HeLa, and MCF7 cells. The comparison shows good agreement between the systems, with a correlation coefficient of 0.91 and linearity slope of 0.877. We also evaluated the automated size profiles of the microparticle samples. This Wi-Fi-enabled lens-free imaging system, along with the dedicated software, possesses great potential for telemedicine applications in resource-limited settings. PMID:27164146

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

    Directory of Open Access Journals (Sweden)

    G. G. Stromov

    2014-01-01

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

  18. Improved Strategies for Parallel Medical Image Processing Applications

    Institute of Scientific and Technical Information of China (English)

    WANG Kun; WANG Xiao-ying; LI San-li; CHEN Ying

    2008-01-01

    In order to meet the demands of high efficient and real-time computer assisted diagnosis as well as screening in medical area, to improve the efficacy of parallel medical image processing is of great importance. This article proposes improved strategies for parallel medical image processing applications,which is categorized into two genera. For each genus individual strategy is devised, including the theoretic algorithm for minimizing the exertion time. Experiment using mammograms not only justifies the validity of the theoretic analysis, with reasonable difference between the theoretic and measured value, but also shows that when adopting the improved strategies, efficacy of medical image parallel processing is improved greatly.

  19. A novel automated image analysis method for accurate adipocyte quantification

    OpenAIRE

    Osman, Osman S.; Selway, Joanne L; Kępczyńska, Małgorzata A; Stocker, Claire J.; O’Dowd, Jacqueline F; Cawthorne, Michael A.; Arch, Jonathan RS; Jassim, Sabah; Langlands, Kenneth

    2013-01-01

    Increased adipocyte size and number are associated with many of the adverse effects observed in metabolic disease states. While methods to quantify such changes in the adipocyte are of scientific and clinical interest, manual methods to determine adipocyte size are both laborious and intractable to large scale investigations. Moreover, existing computational methods are not fully automated. We, therefore, developed a novel automatic method to provide accurate measurements of the cross-section...

  20. Medical image of the week: sarcoidosis

    Directory of Open Access Journals (Sweden)

    Hansra A

    2016-02-01

    Full Text Available No abstract available. Article truncated after 150 words. We present a 58-year-old African American man with a complicated medical history including long-standing sarcoidosis that has caused him chronic, unrelenting pain for two decades. He initially underwent placement of an intrathecal morphine pump, but recently began complaining of increasing pain. Consequently, he was seen at our hospital for interrogation of his pain pump by the interventional radiologist, and was incidentally noted to have bilateral calcified hilar lymphadenopathy on fluoroscopic imaging. A dedicated chest x-ray confirmed the abnormality, which was consistent with his known diagnosis of sarcoidosis. Sarcoidosis is a complex disease process characterized by noncaseous granulomas that can affect various organ systems, with pulmonary involvement in up to 90% of cases (1. Though sarcoidosis is a diagnosis of exclusion, clinicians should recognize that bilateral hilar lymphadenopathy is highly concerning for the underlying noncaseating granulomatous disease (2. The most common pattern of lymphadenopathy is well-defined, bilateral, symmetric hilar and right ...

  1. Data Hiding Scheme on Medical Image using Graph Coloring

    Science.gov (United States)

    Astuti, Widi; Adiwijaya; Novia Wisety, Untari

    2015-06-01

    The utilization of digital medical images is now widely spread[4]. The medical images is supposed to get protection since it has probability to pass through unsecure network. Several watermarking techniques have been developed so that the digital medical images can be guaranteed in terms of its originality. In watermarking, the medical images becomes a protected object. Nevertheless, the medical images can actually be a medium of hiding secret data such as patient medical record. The data hiding is done by inserting data into image - usually called steganography in images. Because the medical images can influence the diagnose change, steganography will only be applied to non-interest region. Vector Quantization (VQ) is one of lossydata compression technique which is sufficiently prominent and frequently used. Generally, the VQ based steganography scheme still has limitation in terms of the data capacity which can be inserted. This research is aimed to make a Vector Quantization-based steganography scheme and graph coloring. The test result shows that the scheme can insert 28768 byte data which equals to 10077 characters for images area of 3696 pixels.

  2. Medical Images Fusion with Patch Based Structure Tensor

    OpenAIRE

    Luo, Fen; Sun, Jiangfeng; Hou, Shouming

    2015-01-01

    Nowadays medical imaging has played an important role in clinical use, which provide important clues for medical diagnosis. In medical image fusion, the extraction of some fine details and description is critical. To solve this problem, a modified structure tensor by considering similarity between two patches is proposed. The patch based filter can suppress noise and add the robustness of the eigen-values of the structure tensor by allowing the use of more information of far away pixels. Afte...

  3. 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.

  4. Performance Improvement of Multi Image Fusion in Wavelet Domain for Medical Images

    OpenAIRE

    Basant Dhakad; Vivek Shrivastava

    2013-01-01

    Today, image fusion as one kind of information integrated technology has played an important role in many fields. Most of previous image fusion methods aim at obtaining as many as information from the different images. But in this paper the fusion criterion is to minimize different error between the fused image and the input images. This paper presents the use of image fusion of medical images. Multi-sensor image fusion is the process of combining information from two or more imag...

  5. Improving Automated Annotation of Benthic Survey Images Using Wide-band Fluorescence

    Science.gov (United States)

    Beijbom, Oscar; Treibitz, Tali; Kline, David I.; Eyal, Gal; Khen, Adi; Neal, Benjamin; Loya, Yossi; Mitchell, B. Greg; Kriegman, David

    2016-03-01

    Large-scale imaging techniques are used increasingly for ecological surveys. However, manual analysis can be prohibitively expensive, creating a bottleneck between collected images and desired data-products. This bottleneck is particularly severe for benthic surveys, where millions of images are obtained each year. Recent automated annotation methods may provide a solution, but reflectance images do not always contain sufficient information for adequate classification accuracy. In this work, the FluorIS, a low-cost modified consumer camera, was used to capture wide-band wide-field-of-view fluorescence images during a field deployment in Eilat, Israel. The fluorescence images were registered with standard reflectance images, and an automated annotation method based on convolutional neural networks was developed. Our results demonstrate a 22% reduction of classification error-rate when using both images types compared to only using reflectance images. The improvements were large, in particular, for coral reef genera Platygyra, Acropora and Millepora, where classification recall improved by 38%, 33%, and 41%, respectively. We conclude that convolutional neural networks can be used to combine reflectance and fluorescence imagery in order to significantly improve automated annotation accuracy and reduce the manual annotation bottleneck.

  6. Automated retinal image quality assessment on the UK Biobank dataset for epidemiological studies.

    Science.gov (United States)

    Welikala, R A; Fraz, M M; Foster, P J; Whincup, P H; Rudnicka, A R; Owen, C G; Strachan, D P; Barman, S A

    2016-04-01

    Morphological changes in the retinal vascular network are associated with future risk of many systemic and vascular diseases. However, uncertainty over the presence and nature of some of these associations exists. Analysis of data from large population based studies will help to resolve these uncertainties. The QUARTZ (QUantitative Analysis of Retinal vessel Topology and siZe) retinal image analysis system allows automated processing of large numbers of retinal images. However, an image quality assessment module is needed to achieve full automation. In this paper, we propose such an algorithm, which uses the segmented vessel map to determine the suitability of retinal images for use in the creation of vessel morphometric data suitable for epidemiological studies. This includes an effective 3-dimensional feature set and support vector machine classification. A random subset of 800 retinal images from UK Biobank (a large prospective study of 500,000 middle aged adults; where 68,151 underwent retinal imaging) was used to examine the performance of the image quality algorithm. The algorithm achieved a sensitivity of 95.33% and a specificity of 91.13% for the detection of inadequate images. The strong performance of this image quality algorithm will make rapid automated analysis of vascular morphometry feasible on the entire UK Biobank dataset (and other large retinal datasets), with minimal operator involvement, and at low cost. PMID:26894596

  7. Automated Video Analysis of Non-verbal Communication in a Medical Setting.

    Science.gov (United States)

    Hart, Yuval; Czerniak, Efrat; Karnieli-Miller, Orit; Mayo, Avraham E; Ziv, Amitai; Biegon, Anat; Citron, Atay; Alon, Uri

    2016-01-01

    Non-verbal communication plays a significant role in establishing good rapport between physicians and patients and may influence aspects of patient health outcomes. It is therefore important to analyze non-verbal communication in medical settings. Current approaches to measure non-verbal interactions in medicine employ coding by human raters. Such tools are labor intensive and hence limit the scale of possible studies. Here, we present an automated video analysis tool for non-verbal interactions in a medical setting. We test the tool using videos of subjects that interact with an actor portraying a doctor. The actor interviews the subjects performing one of two scripted scenarios of interviewing the subjects: in one scenario the actor showed minimal engagement with the subject. The second scenario included active listening by the doctor and attentiveness to the subject. We analyze the cross correlation in total kinetic energy of the two people in the dyad, and also characterize the frequency spectrum of their motion. We find large differences in interpersonal motion synchrony and entrainment between the two performance scenarios. The active listening scenario shows more synchrony and more symmetric followership than the other scenario. Moreover, the active listening scenario shows more high-frequency motion termed jitter that has been recently suggested to be a marker of followership. The present approach may be useful for analyzing physician-patient interactions in terms of synchrony and dominance in a range of medical settings. PMID:27602002

  8. Microscopic images dataset for automation of RBCs counting.

    Science.gov (United States)

    Abbas, Sherif

    2015-12-01

    A method for Red Blood Corpuscles (RBCs) counting has been developed using RBCs light microscopic images and Matlab algorithm. The Dataset consists of Red Blood Corpuscles (RBCs) images and there RBCs segmented images. A detailed description using flow chart is given in order to show how to produce RBCs mask. The RBCs mask was used to count the number of RBCs in the blood smear image.

  9. Automated analysis of protein subcellular location in time series images

    OpenAIRE

    Hu, Yanhua; Osuna-Highley, Elvira; Hua, Juchang; Nowicki, Theodore Scott; Stolz, Robert; McKayle, Camille; Murphy, Robert F.

    2010-01-01

    Motivation: Image analysis, machine learning and statistical modeling have become well established for the automatic recognition and comparison of the subcellular locations of proteins in microscope images. By using a comprehensive set of features describing static images, major subcellular patterns can be distinguished with near perfect accuracy. We now extend this work to time series images, which contain both spatial and temporal information. The goal is to use temporal features to improve...

  10. Automated quadrilateral mesh generation for digital image structures

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    With the development of advanced imaging technology, digital images are widely used. This paper proposes an automatic quadrilateral mesh generation algorithm for multi-colour imaged structures. It takes an original arbitrary digital image as an input for automatic quadrilateral mesh generation, this includes removing the noise, extracting and smoothing the boundary geometries between different colours, and automatic all-quad mesh generation with the above boundaries as constraints. An application example is...

  11. Evaluation of an improved technique for automated center lumen line definition in cardiovascular image data

    International Nuclear Information System (INIS)

    The aim of the study was to evaluate a new method for automated definition of a center lumen line in vessels in cardiovascular image data. This method, called VAMPIRE, is based on improved detection of vessel-like structures. A multiobserver evaluation study was conducted involving 40 tracings in clinical CTA data of carotid arteries to compare VAMPIRE with an established technique. This comparison showed that VAMPIRE yields considerably more successful tracings and improved handling of stenosis, calcifications, multiple vessels, and nearby bone structures. We conclude that VAMPIRE is highly suitable for automated definition of center lumen lines in vessels in cardiovascular image data. (orig.)

  12. Evaluation of an improved technique for automated center lumen line definition in cardiovascular image data

    Energy Technology Data Exchange (ETDEWEB)

    Gratama van Andel, Hugo A.F. [Erasmus MC-University Medical Center Rotterdam, Department of Medical Informatics, Rotterdam (Netherlands); Erasmus MC-University Medical Center Rotterdam, Department of Radiology, Rotterdam (Netherlands); Academic Medical Centre-University of Amsterdam, Department of Medical Physics, Amsterdam (Netherlands); Meijering, Erik; Vrooman, Henri A.; Stokking, Rik [Erasmus MC-University Medical Center Rotterdam, Department of Medical Informatics, Rotterdam (Netherlands); Erasmus MC-University Medical Center Rotterdam, Department of Radiology, Rotterdam (Netherlands); Lugt, Aad van der; Monye, Cecile de [Erasmus MC-University Medical Center Rotterdam, Department of Radiology, Rotterdam (Netherlands)

    2006-02-01

    The aim of the study was to evaluate a new method for automated definition of a center lumen line in vessels in cardiovascular image data. This method, called VAMPIRE, is based on improved detection of vessel-like structures. A multiobserver evaluation study was conducted involving 40 tracings in clinical CTA data of carotid arteries to compare VAMPIRE with an established technique. This comparison showed that VAMPIRE yields considerably more successful tracings and improved handling of stenosis, calcifications, multiple vessels, and nearby bone structures. We conclude that VAMPIRE is highly suitable for automated definition of center lumen lines in vessels in cardiovascular image data. (orig.)

  13. Study on the Medical Image Distributed Dynamic Processing Method

    Institute of Scientific and Technical Information of China (English)

    张全海; 施鹏飞

    2003-01-01

    To meet the challenge of implementing rapidly advanced, time-consuming medical image processing algorithms,it is necessary to develop a medical image processing technology to process a 2D or 3D medical image dynamically on the web. But in a premier system, only static image processing can be provided with the limitation of web technology. The development of Java and CORBA (common object request broker architecture) overcomes the shortcoming of the web static application and makes the dynamic processing of medical images on the web available. To develop an open solution of distributed computing, we integrate the Java, and web with the CORBA and present a web-based medical image dynamic processing methed, which adopts Java technology as the language to program application and components of the web and utilies the CORBA architecture to cope with heterogeneous property of a complex distributed system. The method also provides a platform-independent, transparent processing architecture to implement the advanced image routines and enable users to access large dataset and resources according to the requirements of medical applications. The experiment in this paper shows that the medical image dynamic processing method implemented on the web by using Java and the CORBA is feasible.

  14. A New Method of CT MedicalImages Contrast Enhancement

    Institute of Scientific and Technical Information of China (English)

    SUNFeng-rong; LIUWei; WANGChang-yu; MEILiang-mo

    2004-01-01

    A new method of contrast enhancement is proposed in the paper using multiscale edge representation of images, and is applied to the field of CT medical image processing. Comparing to the traditional Window technique, our method is adaptive and meets the demand of radiology clinics more better. The clinical experiment results show the practicality and the potential applied value of our methodin the field of CT medical images contrast enhancement.

  15. A backscattered x-ray imager for medical applications

    Science.gov (United States)

    Morris, Eric Jude L.; Dibianca, Frank A.; Shukla, Hemant; Gulabani, Daya

    2005-04-01

    Conventional X-ray radiographic systems rely on transmitted photons for the production of images. Backscatter imaging makes use of the more abundant scattered photons for image formation. Specifically, incoherently (Compton) scattered X-ray photons are detected and used for image formation in this modality of medical imaging. However, additional information is obtained when the transmitted X-ray photons are also detected and used. Transmission radiography produces a two-dimensional image of a three dimensional system, therefore image information from a shallower object is often contaminated by image information from underlying objects. Backscattered x-ray imaging largely overcomes this deficiency by imaging depth selectively, which reduces corruption of shallow imaging information by information from deeper objects lying under it. Backscattered x-ray imaging may be particularly useful for examining anatomical structures at shallow depths beneath the skin. Some typical applications for such imaging might be breast imaging, middle ear imaging, imaging of skin melanomas, etc. Previous investigations, by way of theoretical calculations and computational simulations into the feasibility of this kind of imaging have uncovered high-contrast and SNR parameters. Simulations indicate that this method can be used for imaging relatively high-density objects at depths of up to approximately five centimeters below the surface. This paper presents both theoretical and experimental SNR results on this new medical imaging modality.

  16. Improved automated synthesis and preliminary animal PET/CT imaging of 11C-acetate

    International Nuclear Information System (INIS)

    To study a simple and rapid automated synthetic technology of 11C-acetate (11C- AC), automated synthesis of 11C-AC was performed by carboxylation of MeMgBr/tetrahydrofuran (THF) on a polyethylene loop with 11C-CO2, followed by hydrolysis and purification on solid-phase extraction cartridges using a 11C-Choline/Methionine synthesizer made in China. A high and reproducible radiochemical yield of above 40% (decay corrected) was obtained within the whole synthesis time about 8 min from 11C-CO2. The radiochemical purity of 11C-AC was over 95%. The novel, simple and rapid on-column hydrolysis-purification procedure should adaptable to the fully automated synthesis of 11C-AC at several commercial synthesis module. 11C-AC injection produced by the automated procedure is safe and effective, and can be used for PET imaging of animals and humans. (authors)

  17. A review of automated image understanding within 3D baggage computed tomography security screening.

    Science.gov (United States)

    Mouton, Andre; Breckon, Toby P

    2015-01-01

    Baggage inspection is the principal safeguard against the transportation of prohibited and potentially dangerous materials at airport security checkpoints. Although traditionally performed by 2D X-ray based scanning, increasingly stringent security regulations have led to a growing demand for more advanced imaging technologies. The role of X-ray Computed Tomography is thus rapidly expanding beyond the traditional materials-based detection of explosives. The development of computer vision and image processing techniques for the automated understanding of 3D baggage-CT imagery is however, complicated by poor image resolutions, image clutter and high levels of noise and artefacts. We discuss the recent and most pertinent advancements and identify topics for future research within the challenging domain of automated image understanding for baggage security screening CT.

  18. A hidden Markov Model for image fusion and their joint segmentation in medical image computing

    OpenAIRE

    Feron, Olivier; Mohammad-Djafari, Ali

    2004-01-01

    In this work we propose a Bayesian framework for fully automated image fusion and their joint segmentation. More specifically, we consider the case where we have observed images of the same object through different image processes or through different spectral bands. The objective of this work is then to propose a coherent approach to combine these data sets and obtain a segmented image which can be considered as the fusion result of these observations. The proposed approach is based on a Hid...

  19. Automated quantification of budding Saccharomyces cerevisiae using a novel image cytometry method.

    Science.gov (United States)

    Laverty, Daniel J; Kury, Alexandria L; Kuksin, Dmitry; Pirani, Alnoor; Flanagan, Kevin; Chan, Leo Li-Ying

    2013-06-01

    The measurements of concentration, viability, and budding percentages of Saccharomyces cerevisiae are performed on a routine basis in the brewing and biofuel industries. Generation of these parameters is of great importance in a manufacturing setting, where they can aid in the estimation of product quality, quantity, and fermentation time of the manufacturing process. Specifically, budding percentages can be used to estimate the reproduction rate of yeast populations, which directly correlates with metabolism of polysaccharides and bioethanol production, and can be monitored to maximize production of bioethanol during fermentation. The traditional method involves manual counting using a hemacytometer, but this is time-consuming and prone to human error. In this study, we developed a novel automated method for the quantification of yeast budding percentages using Cellometer image cytometry. The automated method utilizes a dual-fluorescent nucleic acid dye to specifically stain live cells for imaging analysis of unique morphological characteristics of budding yeast. In addition, cell cycle analysis is performed as an alternative method for budding analysis. We were able to show comparable yeast budding percentages between manual and automated counting, as well as cell cycle analysis. The automated image cytometry method is used to analyze and characterize corn mash samples directly from fermenters during standard fermentation. Since concentration, viability, and budding percentages can be obtained simultaneously, the automated method can be integrated into the fermentation quality assurance protocol, which may improve the quality and efficiency of beer and bioethanol production processes.

  20. Automated detection of a prostate Ni-Ti stent in electronic portal images

    DEFF Research Database (Denmark)

    Carl, Jesper; Nielsen, Henning; Nielsen, Jane;

    2006-01-01

    of a thermo-expandable Ni-Ti stent. The current study proposes a new detection algorithm for automated detection of the Ni-Ti stent in electronic portal images. The algorithm is based on the Ni-Ti stent having a cylindrical shape with a fixed diameter, which was used as the basis for an automated detection...... algorithm. The automated method uses enhancement of lines combined with a grayscale morphology operation that looks for enhanced pixels separated with a distance similar to the diameter of the stent. The images in this study are all from prostate cancer patients treated with radiotherapy in a previous study....... Images of a stent inserted in a humanoid phantom demonstrated a localization accuracy of 0.4-0.7  mm which equals the pixel size in the image. The automated detection of the stent was compared to manual detection in 71 pairs of orthogonal images taken in nine patients. The algorithm was successful in 67...

  1. A feasibility assessment of automated FISH image and signal analysis to assist cervical cancer detection

    Science.gov (United States)

    Wang, Xingwei; Li, Yuhua; Liu, Hong; Li, Shibo; Zhang, Roy R.; Zheng, Bin

    2012-02-01

    Fluorescence in situ hybridization (FISH) technology provides a promising molecular imaging tool to detect cervical cancer. Since manual FISH analysis is difficult, time-consuming, and inconsistent, the automated FISH image scanning systems have been developed. Due to limited focal depth of scanned microscopic image, a FISH-probed specimen needs to be scanned in multiple layers that generate huge image data. To improve diagnostic efficiency of using automated FISH image analysis, we developed a computer-aided detection (CAD) scheme. In this experiment, four pap-smear specimen slides were scanned by a dual-detector fluorescence image scanning system that acquired two spectrum images simultaneously, which represent images of interphase cells and FISH-probed chromosome X. During image scanning, once detecting a cell signal, system captured nine image slides by automatically adjusting optical focus. Based on the sharpness index and maximum intensity measurement, cells and FISH signals distributed in 3-D space were projected into a 2-D con-focal image. CAD scheme was applied to each con-focal image to detect analyzable interphase cells using an adaptive multiple-threshold algorithm and detect FISH-probed signals using a top-hat transform. The ratio of abnormal cells was calculated to detect positive cases. In four scanned specimen slides, CAD generated 1676 con-focal images that depicted analyzable cells. FISH-probed signals were independently detected by our CAD algorithm and an observer. The Kappa coefficients for agreement between CAD and observer ranged from 0.69 to 1.0 in detecting/counting FISH signal spots. The study demonstrated the feasibility of applying automated FISH image and signal analysis to assist cyto-geneticists in detecting cervical cancers.

  2. Comparison of semi-automated image analysis and manual methods for tissue quantification in pancreatic carcinoma

    Energy Technology Data Exchange (ETDEWEB)

    Sims, A.J. [Regional Medical Physics Department, Freeman Hospital, Newcastle upon Tyne (United Kingdom)]. E-mail: a.j.sims@newcastle.ac.uk; Murray, A. [Regional Medical Physics Department, Freeman Hospital, Newcastle upon Tyne (United Kingdom); Bennett, M.K. [Department of Histopathology, Newcastle upon Tyne Hospitals NHS Trust, Newcastle upon Tyne (United Kingdom)

    2002-04-21

    Objective measurements of tissue area during histological examination of carcinoma can yield valuable prognostic information. However, such measurements are not made routinely because the current manual approach is time consuming and subject to large statistical sampling error. In this paper, a semi-automated image analysis method for measuring tissue area in histological samples is applied to the measurement of stromal tissue, cell cytoplasm and lumen in samples of pancreatic carcinoma and compared with the standard manual point counting method. Histological samples from 26 cases of pancreatic carcinoma were stained using the sirius red, light-green method. Images from each sample were captured using two magnifications. Image segmentation based on colour cluster analysis was used to subdivide each image into representative colours which were classified manually into one of three tissue components. Area measurements made using this technique were compared to corresponding manual measurements and used to establish the comparative accuracy of the semi-automated image analysis technique, with a quality assurance study to measure the repeatability of the new technique. For both magnifications and for each tissue component, the quality assurance study showed that the semi-automated image analysis algorithm had better repeatability than its manual equivalent. No significant bias was detected between the measurement techniques for any of the comparisons made using the 26 cases of pancreatic carcinoma. The ratio of manual to semi-automatic repeatability errors varied from 2.0 to 3.6. Point counting would need to be increased to be between 400 and 1400 points to achieve the same repeatability as for the semi-automated technique. The results demonstrate that semi-automated image analysis is suitable for measuring tissue fractions in histological samples prepared with coloured stains and is a practical alternative to manual point counting. (author)

  3. Comparison of semi-automated image analysis and manual methods for tissue quantification in pancreatic carcinoma

    International Nuclear Information System (INIS)

    Objective measurements of tissue area during histological examination of carcinoma can yield valuable prognostic information. However, such measurements are not made routinely because the current manual approach is time consuming and subject to large statistical sampling error. In this paper, a semi-automated image analysis method for measuring tissue area in histological samples is applied to the measurement of stromal tissue, cell cytoplasm and lumen in samples of pancreatic carcinoma and compared with the standard manual point counting method. Histological samples from 26 cases of pancreatic carcinoma were stained using the sirius red, light-green method. Images from each sample were captured using two magnifications. Image segmentation based on colour cluster analysis was used to subdivide each image into representative colours which were classified manually into one of three tissue components. Area measurements made using this technique were compared to corresponding manual measurements and used to establish the comparative accuracy of the semi-automated image analysis technique, with a quality assurance study to measure the repeatability of the new technique. For both magnifications and for each tissue component, the quality assurance study showed that the semi-automated image analysis algorithm had better repeatability than its manual equivalent. No significant bias was detected between the measurement techniques for any of the comparisons made using the 26 cases of pancreatic carcinoma. The ratio of manual to semi-automatic repeatability errors varied from 2.0 to 3.6. Point counting would need to be increased to be between 400 and 1400 points to achieve the same repeatability as for the semi-automated technique. The results demonstrate that semi-automated image analysis is suitable for measuring tissue fractions in histological samples prepared with coloured stains and is a practical alternative to manual point counting. (author)

  4. 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...

  5. Client-side Medical Image Colorization in a Collaborative Environment.

    Science.gov (United States)

    Virag, Ioan; Stoicu-Tivadar, Lăcrămioara; Crişan-Vida, Mihaela

    2015-01-01

    The paper presents an application related to collaborative medicine using a browser based medical visualization system with focus on the medical image colorization process and the underlying open source web development technologies involved. Browser based systems allow physicians to share medical data with their remotely located counterparts or medical students, assisting them during patient diagnosis, treatment monitoring, surgery planning or for educational purposes. This approach brings forth the advantage of ubiquity. The system can be accessed from a any device, in order to process the images, assuring the independence towards having a specific proprietary operating system. The current work starts with processing of DICOM (Digital Imaging and Communications in Medicine) files and ends with the rendering of the resulting bitmap images on a HTML5 (fifth revision of the HyperText Markup Language) canvas element. The application improves the image visualization emphasizing different tissue densities. PMID:25991287

  6. The Automated Alert System for the Hospital Infection Control and the Safety of Medical Staff Based on EMR Data.

    Science.gov (United States)

    Jo, Eunmi

    2016-01-01

    This report is about planning, developing, and implementing the automated alert system for the Hospital infection control and the safety of medical staffs about information on patients exposed to infection based on EMR Data in a tertiary hospital in Korea. PMID:27332375

  7. A New Approach To Embed Medical Information Into Medical Images

    Directory of Open Access Journals (Sweden)

    Esra Ayça Güzeldereli

    2013-08-01

    Full Text Available In recent years, under the light of developments in the field of computer, there has been an increasing demand for data processing in the health sector. Many different methods are being used to connect the personal information or diagnosis with the patient. These methods can differ from each other according to imaging techniques. In this thesis, this kind of data hiding/embedding techniques are mostly prefered in order to provide a privacy for patients. Also, useful to use compression techniques with data compressing for preserving the originality of the image which is damaged by large size of personal information saved in memory.

  8. Real Time Medical Image Consultation System Through Internet

    Directory of Open Access Journals (Sweden)

    D. Durga Prasad

    2010-01-01

    Full Text Available Teleconsultation among doctors using a telemedicine system typically involves dealing with and sharing medical images of the patients. This paper describes a software tool written in Java which enables the participating doctors to view medical images such as blood slides, X-Ray, USG, ECG etc. online and even allows them to mark and/or zoom specific areas. It is a multi-party secure image communication system tool that can be used by doctors and medical consultants over the Internet.

  9. Infrared thermal imaging for automated detection of diabetic foot complications

    NARCIS (Netherlands)

    Netten, van Jaap J.; Baal, van Jeff G.; Liu, Chanjuan; Heijden, van der Ferdi; Bus, Sicco A.

    2013-01-01

    Background: Although thermal imaging can be a valuable technology in the prevention and management of diabetic foot disease, it is not yet widely used in clinical practice. Technological advancement in infrared imaging increases its application range. The aim was to explore the first steps in the ap

  10. Automated Selection of Uniform Regions for CT Image Quality Detection

    CERN Document Server

    Naeemi, Maitham D; Roychodhury, Sohini

    2016-01-01

    CT images are widely used in pathology detection and follow-up treatment procedures. Accurate identification of pathological features requires diagnostic quality CT images with minimal noise and artifact variation. In this work, a novel Fourier-transform based metric for image quality (IQ) estimation is presented that correlates to additive CT image noise. In the proposed method, two windowed CT image subset regions are analyzed together to identify the extent of variation in the corresponding Fourier-domain spectrum. The two square windows are chosen such that their center pixels coincide and one window is a subset of the other. The Fourier-domain spectral difference between these two sub-sampled windows is then used to isolate spatial regions-of-interest (ROI) with low signal variation (ROI-LV) and high signal variation (ROI-HV), respectively. Finally, the spatial variance ($var$), standard deviation ($std$), coefficient of variance ($cov$) and the fraction of abdominal ROI pixels in ROI-LV ($\

  11. Automated and unbiased image analyses as tools in phenotypic classification of small-spored Alternaria species

    DEFF Research Database (Denmark)

    Andersen, Birgitte; Hansen, Michael Edberg; Smedsgaard, Jørn

    2005-01-01

    often has been broadly applied to various morphologically and chemically distinct groups of isolates from different hosts. The purpose of this study was to develop and evaluate automated and unbiased image analysis systems that will analyze different phenotypic characters and facilitate testing...

  12. Automated medical resident rotation and shift scheduling to ensure quality resident education and patient care.

    Science.gov (United States)

    Smalley, Hannah K; Keskinocak, Pinar

    2016-03-01

    At academic teaching hospitals around the country, the majority of clinical care is provided by resident physicians. During their training, medical residents often rotate through various hospitals and/or medical services to maximize their education. Depending on the size of the training program, manually constructing such a rotation schedule can be cumbersome and time consuming. Further, rules governing allowable duty hours for residents have grown more restrictive in recent years (ACGME 2011), making day-to-day shift scheduling of residents more difficult (Connors et al., J Thorac Cardiovasc Surg 137:710-713, 2009; McCoy et al., May Clin Proc 86(3):192, 2011; Willis et al., J Surg Edu 66(4):216-221, 2009). These rules limit lengths of duty periods, allowable duty hours in a week, and rest periods, to name a few. In this paper, we present two integer programming models (IPs) with the goals of (1) creating feasible assignments of residents to rotations over a one-year period, and (2) constructing night and weekend call-shift schedules for the individual rotations. These models capture various duty-hour rules and constraints, provide the ability to test multiple what-if scenarios, and largely automate the process of schedule generation, solving these scheduling problems more effectively and efficiently compared to manual methods. Applying our models on data from a surgical residency program, we highlight the infeasibilities created by increased duty-hour restrictions placed on residents in conjunction with current scheduling paradigms. PMID:25171938

  13. [A medical image semantic modeling based on hierarchical Bayesian networks].

    Science.gov (United States)

    Lin, Chunyi; Ma, Lihong; Yin, Junxun; Chen, Jianyu

    2009-04-01

    A semantic modeling approach for medical image semantic retrieval based on hierarchical Bayesian networks was proposed, in allusion to characters of medical images. It used GMM (Gaussian mixture models) to map low-level image features into object semantics with probabilities, then it captured high-level semantics through fusing these object semantics using a Bayesian network, so that it built a multi-layer medical image semantic model, aiming to enable automatic image annotation and semantic retrieval by using various keywords at different semantic levels. As for the validity of this method, we have built a multi-level semantic model from a small set of astrocytoma MRI (magnetic resonance imaging) samples, in order to extract semantics of astrocytoma in malignant degree. Experiment results show that this is a superior approach.

  14. Automated registration of multispectral MR vessel wall images of the carotid artery

    Energy Technology Data Exchange (ETDEWEB)

    Klooster, R. van ' t; Staring, M.; Reiber, J. H. C.; Lelieveldt, B. P. F.; Geest, R. J. van der, E-mail: rvdgeest@lumc.nl [Department of Radiology, Division of Image Processing, Leiden University Medical Center, 2300 RC Leiden (Netherlands); Klein, S. [Department of Radiology and Department of Medical Informatics, Biomedical Imaging Group Rotterdam, Erasmus MC, Rotterdam 3015 GE (Netherlands); Kwee, R. M.; Kooi, M. E. [Department of Radiology, Cardiovascular Research Institute Maastricht, Maastricht University Medical Center, Maastricht 6202 AZ (Netherlands)

    2013-12-15

    Purpose: Atherosclerosis is the primary cause of heart disease and stroke. The detailed assessment of atherosclerosis of the carotid artery requires high resolution imaging of the vessel wall using multiple MR sequences with different contrast weightings. These images allow manual or automated classification of plaque components inside the vessel wall. Automated classification requires all sequences to be in alignment, which is hampered by patient motion. In clinical practice, correction of this motion is performed manually. Previous studies applied automated image registration to correct for motion using only nondeformable transformation models and did not perform a detailed quantitative validation. The purpose of this study is to develop an automated accurate 3D registration method, and to extensively validate this method on a large set of patient data. In addition, the authors quantified patient motion during scanning to investigate the need for correction. Methods: MR imaging studies (1.5T, dedicated carotid surface coil, Philips) from 55 TIA/stroke patients with ipsilateral <70% carotid artery stenosis were randomly selected from a larger cohort. Five MR pulse sequences were acquired around the carotid bifurcation, each containing nine transverse slices: T1-weighted turbo field echo, time of flight, T2-weighted turbo spin-echo, and pre- and postcontrast T1-weighted turbo spin-echo images (T1W TSE). The images were manually segmented by delineating the lumen contour in each vessel wall sequence and were manually aligned by applying throughplane and inplane translations to the images. To find the optimal automatic image registration method, different masks, choice of the fixed image, different types of the mutual information image similarity metric, and transformation models including 3D deformable transformation models, were evaluated. Evaluation of the automatic registration results was performed by comparing the lumen segmentations of the fixed image and

  15. Wavelet Thresholding Techniques in Despeckling of Medical Ultrasound Images

    OpenAIRE

    R. Vanithamani; G. Umamaheswari

    2014-01-01

    This paper presents a review of wavelet thresholding techniques for despeckling of medical ultrasound images. An ultrasound image is first transformed into wavelet domain and then the wavelet coefficients are processed by different wavelet thresholding techniques. The denoised image is obtained by taking the inverse wavelet transform of the modified wavelet coefficients. The performance of the techniques reviewed in this paper is evaluated using the image quality assessment parameters such...

  16. Backpropagation Neural Network Implementation for Medical Image Compression

    Directory of Open Access Journals (Sweden)

    Kamil Dimililer

    2013-01-01

    Full Text Available Medical images require compression, before transmission or storage, due to constrained bandwidth and storage capacity. An ideal image compression system must yield high-quality compressed image with high compression ratio. In this paper, Haar wavelet transform and discrete cosine transform are considered and a neural network is trained to relate the X-ray image contents to their ideal compression method and their optimum compression ratio.

  17. Barcode Annotations for Medical Image Retrieval: A Preliminary Investigation

    OpenAIRE

    Tizhoosh, Hamid R.

    2015-01-01

    This paper proposes to generate and to use barcodes to annotate medical images and/or their regions of interest such as organs, tumors and tissue types. A multitude of efficient feature-based image retrieval methods already exist that can assign a query image to a certain image class. Visual annotations may help to increase the retrieval accuracy if combined with existing feature-based classification paradigms. Whereas with annotations we usually mean textual descriptions, in this paper barco...

  18. An image-processing program for automated counting

    Science.gov (United States)

    Cunningham, D.J.; Anderson, W.H.; Anthony, R.M.

    1996-01-01

    An image-processing program developed by the National Institute of Health, IMAGE, was modified in a cooperative project between remote sensing specialists at the Ohio State University Center for Mapping and scientists at the Alaska Science Center to facilitate estimating numbers of black brant (Branta bernicla nigricans) in flocks at Izembek National Wildlife Refuge. The modified program, DUCK HUNT, runs on Apple computers. Modifications provide users with a pull down menu that optimizes image quality; identifies objects of interest (e.g., brant) by spectral, morphometric, and spatial parameters defined interactively by users; counts and labels objects of interest; and produces summary tables. Images from digitized photography, videography, and high- resolution digital photography have been used with this program to count various species of waterfowl.

  19. ASTRiDE: Automated Streak Detection for Astronomical Images

    Science.gov (United States)

    Kim, Dae-Won

    2016-05-01

    ASTRiDE detects streaks in astronomical images using a "border" of each object (i.e. "boundary-tracing" or "contour-tracing") and their morphological parameters. Fast moving objects such as meteors, satellites, near-Earth objects (NEOs), or even cosmic rays can leave streak-like traces in the images; ASTRiDE can detect not only long streaks but also relatively short or curved streaks.

  20. Automated Drusen Segmentation and Quantification in SD-OCT Images

    OpenAIRE

    Chen, Qiang; Leng, Theodore; Zheng, Luoluo; Kutzscher, Lauren; Ma, Jeffrey; de Sisternes, Luis; Rubin, Daniel L.

    2013-01-01

    Spectral domain optical coherence tomography (SD-OCT) is a useful tool for the visualization of drusen, a retinal abnormality seen in patients with age-related macular degeneration (AMD); however, objective assessment of drusen is thwarted by the lack of a method to robustly quantify these lesions on serial OCT images. Here, we describe an automatic drusen segmentation method for SD-OCT retinal images, which leverages a priori knowledge of normal retinal morphology and anatomical features. Th...

  1. EPR Hidden Medical Image Secret Sharing using DNA Cryptography

    Directory of Open Access Journals (Sweden)

    L.Jani Anbarasi

    2014-07-01

    Full Text Available Security of medical images is an important issue, since applications such as Tele diagnosis exchange information over insecure communication channels. In this paper, Shamir secret sharing algorithm combined with DNA cryptography is proposed. The method involves the dispersion of medical image and Electronic Patient Record (EPR into shadow images, aiming at better security characteristics. The EPR is hidden into the medical image using DNA hiding techniques. Huffman encoding is used to compress the DNA encoded secret image, which is then securely shared into shadow images using Shamir secret sharing. Then, the shadows are embedded into a host image using steganographic technique with modular operation. During reconstruction, at least t shadows are pooled to reconstruct the compressed secret image, which is again decoded using Huffman decoding to reveal the DNA encoded secret image. The medical image and EPR are separated using the reverse technique of DNA hiding. The simulation results and the security analysis prove that this method can hide longer EPR strings along with better confidentiality and authenticity. Better PSNR is achieved and the correlation co-efficient shows that this also has the ability of resisting various attacks.

  2. An automated image analysis system to measure and count organisms in laboratory microcosms.

    Science.gov (United States)

    Mallard, François; Le Bourlot, Vincent; Tully, Thomas

    2013-01-01

    1. Because of recent technological improvements in the way computer and digital camera perform, the potential use of imaging for contributing to the study of communities, populations or individuals in laboratory microcosms has risen enormously. However its limited use is due to difficulties in the automation of image analysis. 2. We present an accurate and flexible method of image analysis for detecting, counting and measuring moving particles on a fixed but heterogeneous substrate. This method has been specifically designed to follow individuals, or entire populations, in experimental laboratory microcosms. It can be used in other applications. 3. The method consists in comparing multiple pictures of the same experimental microcosm in order to generate an image of the fixed background. This background is then used to extract, measure and count the moving organisms, leaving out the fixed background and the motionless or dead individuals. 4. We provide different examples (springtails, ants, nematodes, daphnia) to show that this non intrusive method is efficient at detecting organisms under a wide variety of conditions even on faintly contrasted and heterogeneous substrates. 5. The repeatability and reliability of this method has been assessed using experimental populations of the Collembola Folsomia candida. 6. We present an ImageJ plugin to automate the analysis of digital pictures of laboratory microcosms. The plugin automates the successive steps of the analysis and recursively analyses multiple sets of images, rapidly producing measurements from a large number of replicated microcosms. PMID:23734199

  3. An automated image analysis system to measure and count organisms in laboratory microcosms.

    Directory of Open Access Journals (Sweden)

    François Mallard

    Full Text Available 1. Because of recent technological improvements in the way computer and digital camera perform, the potential use of imaging for contributing to the study of communities, populations or individuals in laboratory microcosms has risen enormously. However its limited use is due to difficulties in the automation of image analysis. 2. We present an accurate and flexible method of image analysis for detecting, counting and measuring moving particles on a fixed but heterogeneous substrate. This method has been specifically designed to follow individuals, or entire populations, in experimental laboratory microcosms. It can be used in other applications. 3. The method consists in comparing multiple pictures of the same experimental microcosm in order to generate an image of the fixed background. This background is then used to extract, measure and count the moving organisms, leaving out the fixed background and the motionless or dead individuals. 4. We provide different examples (springtails, ants, nematodes, daphnia to show that this non intrusive method is efficient at detecting organisms under a wide variety of conditions even on faintly contrasted and heterogeneous substrates. 5. The repeatability and reliability of this method has been assessed using experimental populations of the Collembola Folsomia candida. 6. We present an ImageJ plugin to automate the analysis of digital pictures of laboratory microcosms. The plugin automates the successive steps of the analysis and recursively analyses multiple sets of images, rapidly producing measurements from a large number of replicated microcosms.

  4. Medical Image Compression using Wavelet Decomposition for Prediction Method

    CERN Document Server

    Ramesh, S M

    2010-01-01

    In this paper offers a simple and lossless compression method for compression of medical images. Method is based on wavelet decomposition of the medical images followed by the correlation analysis of coefficients. The correlation analyses are the basis of prediction equation for each sub band. Predictor variable selection is performed through coefficient graphic method to avoid multicollinearity problem and to achieve high prediction accuracy and compression rate. The method is applied on MRI and CT images. Results show that the proposed approach gives a high compression rate for MRI and CT images comparing with state of the art methods.

  5. MEDICAL IMAGE SEGMENTATION BASED ON A MODIFIED LEVEL SET ALGORITHM

    Institute of Scientific and Technical Information of China (English)

    Yang Yong; Lin Pan; Zheng Chongxun; Gu Jianwen

    2005-01-01

    Objective To present a novel modified level set algorithm for medical image segmentation. Methods The algorithm is developed by substituting the speed function of level set algorithm with the region and gradient information of the image instead of the conventional gradient information. This new algorithm has been tested by a series of different modality medical images. Results We present various examples and also evaluate and compare the performance of our method with the classical level set method on weak boundaries and noisy images. Conclusion Experimental results show the proposed algorithm is effective and robust.

  6. Tele-medical imaging conference system based on the Web.

    Science.gov (United States)

    Choi, Heung-Kook; Park, Se-Myung; Kang, Jae-Hyo; Kim, Sang-Kyoon; Choi, Hang-Mook

    2002-06-01

    In this paper, a medical imaging conference system is presented, which is carried out in the Web environment using the distributed object technique, CORBA. Independent of platforms and different developing languages, the CORBA-based medical imaging conference system is very powerful for system development, extension and maintenance. With this Web client/server, one could easily execute a medical imaging conference using Applets on the Web. The Java language, which is object-oriented and independent of platforms, has the advantage of free usage wherever the Web browser is. By using the proposed system, we envisage being able to open a tele-conference using medical images, e.g. CT, MRI, X-ray etc., easily and effectively among remote hospitals.

  7. Four challenges in medical image analysis from an industrial perspective.

    Science.gov (United States)

    Weese, Jürgen; Lorenz, Cristian

    2016-10-01

    Today's medical imaging systems produce a huge amount of images containing a wealth of information. However, the information is hidden in the data and image analysis algorithms are needed to extract it, to make it readily available for medical decisions and to enable an efficient work flow. Advances in medical image analysis over the past 20 years mean there are now many algorithms and ideas available that allow to address medical image analysis tasks in commercial solutions with sufficient performance in terms of accuracy, reliability and speed. At the same time new challenges have arisen. Firstly, there is a need for more generic image analysis technologies that can be efficiently adapted for a specific clinical task. Secondly, efficient approaches for ground truth generation are needed to match the increasing demands regarding validation and machine learning. Thirdly, algorithms for analyzing heterogeneous image data are needed. Finally, anatomical and organ models play a crucial role in many applications, and algorithms to construct patient-specific models from medical images with a minimum of user interaction are needed. These challenges are complementary to the on-going need for more accurate, more reliable and faster algorithms, and dedicated algorithmic solutions for specific applications.

  8. Visualisation of multi-dimensional medical images with application to brain electrical impedance tomography

    OpenAIRE

    Zhang, Yan

    2007-01-01

    Medical imaging plays an important role in modem medicine. With the increasing complexity and information presented by medical images, visualisation is vital for medical research and clinical applications to interpret the information presented in these images. The aim of this research is to investigate improvements to medical image visualisation, particularly for multi-dimensional medical image datasets. A recently developed medical imaging technique known as Electrical Impedance Tomograp...

  9. Medical Images Watermarking Algorithm Based on Improved DCT

    OpenAIRE

    Yv-fan SHANG; Yi-ning KANG

    2013-01-01

    Targeting at the incessant securities problems of digital information management system in modern medical system, this paper presents the robust watermarking algorithm for medical images based on Arnold transformation and DCT. The algorithm first deploys the scrambling technology to encrypt the watermark information and then combines it with the visual feature vector of the image to generate a binary logic series through the hash function. The sequence as taken as keys and stored in the third...

  10. Optimal Embedding for Shape Indexing in Medical Image Databases

    OpenAIRE

    Qian, Xiaoning; Tagare, Hemant D.; Fulbright, Robert K.; Long, Rodney; Antani, Sameer

    2010-01-01

    This paper addresses the problem of indexing shapes in medical image databases. Shapes of organs are often indicative of disease, making shape similarity queries important in medical image databases. Mathematically, shapes with landmarks belong to shape spaces which are curved manifolds with a well defined metric. The challenge in shape indexing is to index data in such curved spaces. One natural indexing scheme is to use metric trees, but metric trees are prone to inefficiency. This paper pr...

  11. Accuracy Validation for Medical Image Registration Algorithms: a Review

    Institute of Scientific and Technical Information of China (English)

    Zhe Liu; Xiang Deng; Guang-zhi Wang

    2012-01-01

    Accuracy validation is essential to clinical application of medical image registration techniques.Registration validation remains a challenging problem in practice mainly due to lack of 'ground truth'.In this paper,an overview of current validation methods for medical image registration is presented with detailed discussion of their benefits and drawbacks.Special focus is on non-rigid registration validation.Promising solution is also discussed.

  12. Signal and image processing in medical applications

    CERN Document Server

    Kumar, Amit; Rahim, B Abdul; Kumar, D Sravan

    2016-01-01

    This book highlights recent findings on and analyses conducted on signals and images in the area of medicine. The experimental investigations involve a variety of signals and images and their methodologies range from very basic to sophisticated methods. The book explains how signal and image processing methods can be used to detect and forecast abnormalities in an easy-to-follow manner, offering a valuable resource for researchers, engineers, physicians and bioinformatics researchers alike.

  13. Multimodal medical image fusion using Butterworth high pass filter and Cross bilateral filter

    OpenAIRE

    Lalotra Bharti; Vig Renu; Budhiraja Sumit

    2016-01-01

    Multimodal Medical Image fusion is a prominent area of interest. Medical image fusion is the process of combining images from different modalities. It improves imaging quality and reduces the redundant information. The main aim of Medical Image fusion is in having better quality of fused image for the diagnostic purposes. Image fusion improves capability and reliability of images. In medical background, sharpness of fused image is the basic criteria of quality. In this paper, quality of fused...

  14. Automated Contour Detection for Intravascular Ultrasound Image Sequences Based on Fast Active Contour Algorithm

    Institute of Scientific and Technical Information of China (English)

    DONG Hai-yan; WANG Hui-nan

    2006-01-01

    Intravascular ultrasound can provide high-resolution real-time crosssectional images about lumen, plaque and tissue. Traditionally, the luminal border and medial-adventitial border are traced manually. This process is extremely timeconsuming and the subjective difference would be large. In this paper, a new automated contour detection method is introduced based on fast active contour model.Experimental results found that lumen and vessel area measurements after automated detection showed good agreement with manual tracings with high correlation coefficients (0.94 and 0.95, respectively) and small system difference ( -0.32 and 0.56, respectively). So it can be a reliable and accurate diagnostic tool.

  15. An Automated Platform for High-Resolution Tissue Imaging Using Nanospray Desorption Electrospray Ionization Mass Spectrometry

    Energy Technology Data Exchange (ETDEWEB)

    Lanekoff, Ingela T.; Heath, Brandi S.; Liyu, Andrey V.; Thomas, Mathew; Carson, James P.; Laskin, Julia

    2012-10-02

    An automated platform has been developed for acquisition and visualization of mass spectrometry imaging (MSI) data using nanospray desorption electrospray ionization (nano-DESI). The new system enables robust operation of the nano-DESI imaging source over many hours. This is achieved by controlling the distance between the sample and the probe by mounting the sample holder onto an automated XYZ stage and defining the tilt of the sample plane. This approach is useful for imaging of relatively flat samples such as thin tissue sections. Custom software called MSI QuickView was developed for visualization of large data sets generated in imaging experiments. MSI QuickView enables fast visualization of the imaging data during data acquisition and detailed processing after the entire image is acquired. The performance of the system is demonstrated by imaging rat brain tissue sections. High resolution mass analysis combined with MS/MS experiments enabled identification of lipids and metabolites in the tissue section. In addition, high dynamic range and sensitivity of the technique allowed us to generate ion images of low-abundance isobaric lipids. High-spatial resolution image acquired over a small region of the tissue section revealed the spatial distribution of an abundant brain metabolite, creatine, in the white and gray matter that is consistent with the literature data obtained using magnetic resonance spectroscopy.

  16. Image cytometer method for automated assessment of human spermatozoa concentration

    DEFF Research Database (Denmark)

    Egeberg, D L; Kjaerulff, S; Hansen, C;

    2013-01-01

    In the basic clinical work-up of infertile couples, a semen analysis is mandatory and the sperm concentration is one of the most essential variables to be determined. Sperm concentration is usually assessed by manual counting using a haemocytometer and is hence labour intensive and may be subjected...... to investigator bias. Here we show that image cytometry can be used to accurately measure the sperm concentration of human semen samples with great ease and reproducibility. The impact of several factors (pipetting, mixing, round cell content, sperm concentration), which can influence the read-out as well....... Moreover, by evaluation of repeated measurements it appeared that image cytometry produced more consistent and accurate measurements than manual counting of human spermatozoa concentration. In conclusion, image cytometry provides an appealing substitute of manual counting by providing reliable, robust...

  17. Automated Classification of Glaucoma Images by Wavelet Energy Features

    Directory of Open Access Journals (Sweden)

    N.Annu

    2013-04-01

    Full Text Available Glaucoma is the second leading cause of blindness worldwide. As glaucoma progresses, more optic nerve tissue is lost and the optic cup grows which leads to vision loss. This paper compiles a systemthat could be used by non-experts to filtrate cases of patients not affected by the disease. This work proposes glaucomatous image classification using texture features within images and efficient glaucoma classification based on Probabilistic Neural Network (PNN. Energy distribution over wavelet sub bands is applied to compute these texture features. Wavelet features were obtained from the daubechies (db3, symlets (sym3, and biorthogonal (bio3.3, bio3.5, and bio3.7 wavelet filters. It uses a technique to extract energy signatures obtained using 2-D discrete wavelet transform and the energy obtained from the detailed coefficients can be used to distinguish between normal and glaucomatous images. We observedan accuracy of around 95%, this demonstrates the effectiveness of these methods.

  18. A survey of medical image registration - under review.

    Science.gov (United States)

    Viergever, Max A; Maintz, J B Antoine; Klein, Stefan; Murphy, Keelin; Staring, Marius; Pluim, Josien P W

    2016-10-01

    A retrospective view on the past two decades of the field of medical image registration is presented, guided by the article "A survey of medical image registration" (Maintz and Viergever, 1998). It shows that the classification of the field introduced in that article is still usable, although some modifications to do justice to advances in the field would be due. The main changes over the last twenty years are the shift from extrinsic to intrinsic registration, the primacy of intensity-based registration, the breakthrough of nonlinear registration, the progress of inter-subject registration, and the availability of generic image registration software packages. Two problems that were called urgent already 20 years ago, are even more urgent nowadays: Validation of registration methods, and translation of results of image registration research to clinical practice. It may be concluded that the field of medical image registration has evolved, but still is in need of further development in various aspects.

  19. Automated detection of meteors in observed image sequence

    Science.gov (United States)

    Šimberová, Stanislava; Suk, Tomáš

    2015-12-01

    We propose a new detection technique based on statistical characteristics of images in the video sequence. These characteristics displayed in time enable to catch any bright track during the whole sequence. We applied our method to the image datacubes that are created from camera pictures of the night sky. Meteor flying through the Earth's atmosphere leaves a light trail lasting a few seconds on the sky background. We developed a special technique to recognize this event automatically in the complete observed video sequence. For further analysis leading to the precise recognition of object we suggest to apply Fourier and Hough transformations.

  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.

  1. 3D thermal medical image visualization tool: Integration between MRI and thermographic images.

    Science.gov (United States)

    Abreu de Souza, Mauren; Chagas Paz, André Augusto; Sanches, Ionildo Jóse; Nohama, Percy; Gamba, Humberto Remigio

    2014-01-01

    Three-dimensional medical image reconstruction using different images modalities require registration techniques that are, in general, based on the stacking of 2D MRI/CT images slices. In this way, the integration of two different imaging modalities: anatomical (MRI/CT) and physiological information (infrared image), to generate a 3D thermal model, is a new methodology still under development. This paper presents a 3D THERMO interface that provides flexibility for the 3D visualization: it incorporates the DICOM parameters; different color scale palettes at the final 3D model; 3D visualization at different planes of sections; and a filtering option that provides better image visualization. To summarize, the 3D thermographc medical image visualization provides a realistic and precise medical tool. The merging of two different imaging modalities allows better quality and more fidelity, especially for medical applications in which the temperature changes are clinically significant.

  2. Hybrid LWT-SVD Watermarking Optimized Using Metaheuristic Algorithms along with Encryption for Medical Image Security

    OpenAIRE

    Venugopal Reddy .CH; Siddaiah.P

    2015-01-01

    Medical image security provides challenges and opportunities, watermarking and encryption of medical images provides the necessary control over the flow of medical information. In this paper a dual security approach is employed .A medical image is considered as watermark and is watermarked inside a natural image. This approach is to wean way the potential attacker by disguising the medical image as a natural image. To further enhance the security the watermarked image is encrypted using encry...

  3. Medical Image Fusion: A survey of the state of the art

    OpenAIRE

    James, A. P.; Dasarathy, B. V.

    2013-01-01

    Medical image fusion is the process of registering and combining multiple images from single or multiple imaging modalities to improve the imaging quality and reduce randomness and redundancy in order to increase the clinical applicability of medical images for diagnosis and assessment of medical problems. Multi-modal medical image fusion algorithms and devices have shown notable achievements in improving clinical accuracy of decisions based on medical images. This review article provides a f...

  4. APES Beamforming Applied to Medical Ultrasound Imaging

    DEFF Research Database (Denmark)

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

    2009-01-01

    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...

  5. Automated cell colony counting and analysis using the circular Hough image transform algorithm (CHiTA)

    Energy Technology Data Exchange (ETDEWEB)

    Bewes, J M; Suchowerska, N; McKenzie, D R [School of Physics, University of Sydney, Sydney, NSW (Australia)], E-mail: jbewes@physics.usyd.edu.au

    2008-11-07

    We present an automated cell colony counting method that is flexible, robust and capable of providing more in-depth clonogenic analysis than existing manual and automated approaches. The full form of the Hough transform without approximation has been implemented, for the first time. Improvements in computing speed have facilitated this approach. Colony identification was achieved by pre-processing the raw images of the colonies in situ in the flask, including images of the flask edges, by erosion, dilation and Gaussian smoothing processes. Colony edges were then identified by intensity gradient field discrimination. Our technique eliminates the need for specialized hardware for image capture and enables the use of a standard desktop scanner for distortion-free image acquisition. Additional parameters evaluated included regional colony counts, average colony area, nearest neighbour distances and radial distribution. This spatial and qualitative information extends the utility of the clonogenic assay, allowing analysis of spatially-variant cytotoxic effects. To test the automated system, two flask types and three cell lines with different morphology, cell size and plating density were examined. A novel Monte Carlo method of simulating cell colony images, as well as manual counting, were used to quantify algorithm accuracy. The method was able to identify colonies with unusual morphology, to successfully resolve merged colonies and to correctly count colonies adjacent to flask edges.

  6. Automated cell colony counting and analysis using the circular Hough image transform algorithm (CHiTA)

    Science.gov (United States)

    Bewes, J. M.; Suchowerska, N.; McKenzie, D. R.

    2008-11-01

    We present an automated cell colony counting method that is flexible, robust and capable of providing more in-depth clonogenic analysis than existing manual and automated approaches. The full form of the Hough transform without approximation has been implemented, for the first time. Improvements in computing speed have facilitated this approach. Colony identification was achieved by pre-processing the raw images of the colonies in situ in the flask, including images of the flask edges, by erosion, dilation and Gaussian smoothing processes. Colony edges were then identified by intensity gradient field discrimination. Our technique eliminates the need for specialized hardware for image capture and enables the use of a standard desktop scanner for distortion-free image acquisition. Additional parameters evaluated included regional colony counts, average colony area, nearest neighbour distances and radial distribution. This spatial and qualitative information extends the utility of the clonogenic assay, allowing analysis of spatially-variant cytotoxic effects. To test the automated system, two flask types and three cell lines with different morphology, cell size and plating density were examined. A novel Monte Carlo method of simulating cell colony images, as well as manual counting, were used to quantify algorithm accuracy. The method was able to identify colonies with unusual morphology, to successfully resolve merged colonies and to correctly count colonies adjacent to flask edges.

  7. Automation of the method gamma of comparison dosimetry images

    International Nuclear Information System (INIS)

    The objective of this work was the development of JJGAMMA application analysis software, which enables this task systematically, minimizing intervention specialist and therefore the variability due to the observer. Both benefits, allow comparison of images is done in practice with the required frequency and objectivity. (Author)

  8. Automated identification of retained surgical items in radiological images

    Science.gov (United States)

    Agam, Gady; Gan, Lin; Moric, Mario; Gluncic, Vicko

    2015-03-01

    Retained surgical items (RSIs) in patients is a major operating room (OR) patient safety concern. An RSI is any surgical tool, sponge, needle or other item inadvertently left in a patients body during the course of surgery. If left undetected, RSIs may lead to serious negative health consequences such as sepsis, internal bleeding, and even death. To help physicians efficiently and effectively detect RSIs, we are developing computer-aided detection (CADe) software for X-ray (XR) image analysis, utilizing large amounts of currently available image data to produce a clinically effective RSI detection system. Physician analysis of XRs for the purpose of RSI detection is a relatively lengthy process that may take up to 45 minutes to complete. It is also error prone due to the relatively low acuity of the human eye for RSIs in XR images. The system we are developing is based on computer vision and machine learning algorithms. We address the problem of low incidence by proposing synthesis algorithms. The CADe software we are developing may be integrated into a picture archiving and communication system (PACS), be implemented as a stand-alone software application, or be integrated into portable XR machine software through application programming interfaces. Preliminary experimental results on actual XR images demonstrate the effectiveness of the proposed approach.

  9. Computer-assisted tree taxonomy by automated image recognition

    NARCIS (Netherlands)

    Pauwels, E.J.; Zeeuw, P.M.de; Ranguelova, E.B.

    2009-01-01

    We present an algorithm that performs image-based queries within the domain of tree taxonomy. As such, it serves as an example relevant to many other potential applications within the field of biodiversity and photo-identification. Unsupervised matching results are produced through a chain of comput

  10. Automated Hierarchical Time Gain Compensation for In Vivo Ultrasound Imaging

    DEFF Research Database (Denmark)

    Moshavegh, Ramin; Hemmsen, Martin Christian; Martins, Bo;

    2015-01-01

    Time gain compensation (TGC) is essential to ensure the optimal image quality of the clinical ultrasound scans. When large fluid collections are present within the scan plane, the attenuation distribution is changed drastically and TGC compensation becomes challenging. This paper presents...

  11. Automated Coronal Loop Identification Using Digital Image Processing Techniques

    Science.gov (United States)

    Lee, Jong K.; Gary, G. Allen; Newman, Timothy S.

    2003-01-01

    The results of a master thesis project on a study of computer algorithms for automatic identification of optical-thin, 3-dimensional solar coronal loop centers from extreme ultraviolet and X-ray 2-dimensional images will be presented. These center splines are proxies of associated magnetic field lines. The project is pattern recognition problems in which there are no unique shapes or edges and in which photon and detector noise heavily influence the images. The study explores extraction techniques using: (1) linear feature recognition of local patterns (related to the inertia-tensor concept), (2) parametric space via the Hough transform, and (3) topological adaptive contours (snakes) that constrains curvature and continuity as possible candidates for digital loop detection schemes. We have developed synthesized images for the coronal loops to test the various loop identification algorithms. Since the topology of these solar features is dominated by the magnetic field structure, a first-order magnetic field approximation using multiple dipoles provides a priori information in the identification process. Results from both synthesized and solar images will be presented.

  12. AUTOMATED VIDEO IMAGE MORPHOMETRY OF THE CORNEAL ENDOTHELIUM

    NARCIS (Netherlands)

    SIERTSEMA, JV; LANDESZ, M; VANDENBROM, H; VANRIJ, G

    1993-01-01

    The central corneal endothelium of 13 eyes in 13 subjects was visualized with a non-contact specular microscope. This report describes the computer-assisted morphometric analysis of enhanced digitized images, using a direct input by means of a frame grabber. The output consisted of mean cell area, c

  13. Medical image of the week: prozac eyes

    Directory of Open Access Journals (Sweden)

    Shetty S

    2015-12-01

    Full Text Available A 59-year-old man with a past medical history significant for hypertension, obesity and depression underwent an overnight polysomnogram for high clinical suspicion for obstructive sleep apnea. His current medications include doxepin, fluoxetine, bupropion, ambien and amlodipine. A snapshot during NREM sleep is shown (Figure 1. Fluoxetine (Prozac® is a potent selective serotonin reuptake inhibitor (SSRI.“Omnipause” neurons in the brainstem inhibit saccadic eye movements. NREM eye movements result from the potentiation of serotonergic neurons that inhibit these neurons (1. These eye movements occur during all stages of NREM sleep. These atypical eye movements have been reported to be present with a lower incidence with use of other antidepressants, benzodiazepines and neuroleptics and they tend to persist even after discontinuation of the medication (2. The clinical significance of these eye movements is unknown.

  14. Automated Detection of Contaminated Radar Image Pixels in Mountain Areas

    Institute of Scientific and Technical Information of China (English)

    LIU Liping; Qin XU; Pengfei ZHANG; Shun LIU

    2008-01-01

    In mountain areas,radar observations are often contaminated(1)by echoes from high-speed moving vehicles and(2)by point-wise ground clutter under either normal propagation(NP)or anomalous propa-gation(AP)conditions.Level II data are collected from KMTX(Salt Lake City,Utah)radar to analyze these two types of contamination in the mountain area around the Great Salt Lake.Human experts provide the"ground truth"for possible contamination of either type on each individual pixel.Common features are then extracted for contaminated pixels of each type.For example,pixels contaminated by echoes from high-speed moving vehicles are characterized by large radial velocity and spectrum width.Echoes from a moving train tend to have larger velocity and reflectivity but smaller spectrum width than those from moving vehicles on highways.These contaminated pixels are only seen in areas of large terrain gradient(in the radial direction along the radar beam).The same is true for the second type of contamination-point-wise ground clutters.Six quality control(QC)parameters are selected to quantify the extracted features.Histograms are computed for each QC parameter and grouped for contaminated pixels of each type and also for non-contaminated pixels.Based on the computed histograms,a fuzzy logical algorithm is developed for automated detection of contaminated pixels.The algorithm is tested with KMTX radar data under different(clear and rainy)weather conditions.

  15. Medical Image Authentication Using DPT Watermarking: A Preliminary Attempt

    Science.gov (United States)

    Wong, M. L. Dennis; Goh, Antionette W.-T.; Chua, Hong Siang

    Secure authentication of digital medical image content provides great value to the e-Health community and medical insurance industries. Fragile Watermarking has been proposed to provide the mechanism to authenticate digital medical image securely. Transform Domain based Watermarking are typically slower than spatial domain watermarking owing to the overhead in calculation of coefficients. In this paper, we propose a new Discrete Pascal Transform based watermarking technique. Preliminary experiment result shows authentication capability. Possible improvements on the proposed scheme are also presented before conclusions.

  16. Automated marker tracking using noisy X-ray images degraded by the treatment beam

    Energy Technology Data Exchange (ETDEWEB)

    Wisotzky, E. [Fraunhofer Institute for Production Systems and Design Technology (IPK), Berlin (Germany); German Cancer Research Center (DKFZ), Heidelberg (Germany); Fast, M.F.; Nill, S. [The Royal Marsden NHS Foundation Trust, London (United Kingdom). Joint Dept. of Physics; Oelfke, U. [The Royal Marsden NHS Foundation Trust, London (United Kingdom). Joint Dept. of Physics; German Cancer Research Center (DKFZ), Heidelberg (Germany)

    2015-09-01

    This study demonstrates the feasibility of automated marker tracking for the real-time detection of intrafractional target motion using noisy kilovoltage (kV) X-ray images degraded by the megavoltage (MV) treatment beam. The authors previously introduced the in-line imaging geometry, in which the flat-panel detector (FPD) is mounted directly underneath the treatment head of the linear accelerator. They found that the 121 kVp image quality was severely compromised by the 6 MV beam passing through the FPD at the same time. Specific MV-induced artefacts present a considerable challenge for automated marker detection algorithms. For this study, the authors developed a new imaging geometry by re-positioning the FPD and the X-ray tube. This improved the contrast-to-noise-ratio between 40% and 72% at the 1.2 mAs/image exposure setting. The increase in image quality clearly facilitates the quick and stable detection of motion with the aid of a template matching algorithm. The setup was tested with an anthropomorphic lung phantom (including an artificial lung tumour). In the tumour one or three Calypso {sup registered} beacons were embedded to achieve better contrast during MV radiation. For a single beacon, image acquisition and automated marker detection typically took around 76±6 ms. The success rate was found to be highly dependent on imaging dose and gantry angle. To eliminate possible false detections, the authors implemented a training phase prior to treatment beam irradiation and also introduced speed limits for motion between subsequent images.

  17. Automated and Accurate Detection of Soma Location and Surface Morphology in Large-Scale 3D Neuron Images

    OpenAIRE

    Cheng Yan; Anan Li; Bin Zhang,; Wenxiang Ding; Qingming Luo; Hui Gong

    2013-01-01

    Automated and accurate localization and morphometry of somas in 3D neuron images is essential for quantitative studies of neural networks in the brain. However, previous methods are limited in obtaining the location and surface morphology of somas with variable size and uneven staining in large-scale 3D neuron images. In this work, we proposed a method for automated soma locating in large-scale 3D neuron images that contain relatively sparse soma distributions. This method involves three step...

  18. Implementation of Synthetic Aperture Imaging in Medical Ultrasound

    DEFF Research Database (Denmark)

    Jensen, Jørgen Arendt; Kortbek, Jacob; Nikolov, Svetoslav;

    2010-01-01

    The main advantage of medical ultrasound imaging is its real time capability, which makes it possible to visualize dynamic structures in the human body. Real time synthetic aperture imaging puts very high demands on the hardware, which currently cannot be met. A method for reducing the number of...

  19. The Application of Partial Differential Equations in Medical Image Processing

    Directory of Open Access Journals (Sweden)

    Mohammad Madadpour Inallou

    2013-10-01

    Full Text Available Mathematical models are the foundation of biomedical computing. Partial Differential Equations (PDEs in Medical Imaging is concerned with acquiring images of the body for research, diagnosis and treatment. Biomedical Image Processing and its influence has undergoing a revolution in the past decade. Image processing has become an important component in contemporary science and technology and has been an interdisciplinary research field attracting expertise from applied mathematics, biology, computer sciences, engineering, statistics, microscopy, radiologic sciences, physics, medicine and etc. Medical imaging equipment is taking on an increasingly critical role in healthcare as the industry strives to lower patient costs and achieve earlier disease prediction using noninvasive means. The subsections of medical imaging are categorized to two: Conventional (X-Ray and Ultrasound and Computed (CT, MRI, fMRI, SPECT, PET and etc. This paper is organized as fallow: First section describes some kind of image processing. Second section is about techniques and requirements, and in the next sections the proceeding of Analyzing, Smoothing, Segmentation, De-noising and Registration in Medical Image Processing Equipment by PDEs Framework will be regarded

  20. A scanned beam THz imaging system for medical applications

    Science.gov (United States)

    Taylor, Zachary D.; Li, Wenzao; Suen, Jon; Tewari, Priyamvada; Bennett, David; Bajwa, Neha; Brown, Elliott; Culjat, Martin; Grundfest, Warren; Singh, Rahul

    2011-10-01

    THz medical imaging has been a topic of increased interest recently due largely to improvements in source and detector technology and the identification of suitable applications. One aspect of THz medical imaging research not often adequately addressed is pixel acquisition rate and phenomenology. The majority of active THz imaging systems use translation stages to raster scan a sample beneath a fixed THz beam. While these techniques have produced high resolution images of characterization targets and animal models they do not scale well to human imaging where clinicians are unwilling to place patients on large translation stages. This paper presents a scanned beam THz imaging system that can acquire a 1 cm2 area with 1 mm2 pixels and a per-pixel SNR of 40 dB in less than 5 seconds. The system translates a focused THz beam across a stationary target using a spinning polygonal mirror and HDPE objective lens. The illumination is centered at 525 GHz with ~ 125 GHz of response normalized bandwidth and the component layout is designed to optically co-locate the stationary source and detector ensuring normal incidence across a 50 mm × 50 mm field of view at standoff of 190 mm. Component characterization and images of a test target are presented. These results are some of the first ever reported for a short standoff, high resolution, scanned beam THz imaging system and represent an important step forward for practical integration of THz medical imaging where fast image acquisition times and stationary targets (patients) are requisite.

  1. Multi-scale visual words for hierarchical medical image categorisation

    Science.gov (United States)

    Markonis, Dimitrios; Seco de Herrera, Alba G.; Eggel, Ivan; Müller, Henning

    2012-02-01

    The biomedical literature published regularly has increased strongly in past years and keeping updated even in narrow domains is difficult. Images represent essential information of their articles and can help to quicker browse through large volumes of articles in connection with keyword search. Content-based image retrieval is helping the retrieval of visual content. To facilitate retrieval of visual information, image categorisation can be an important first step. To represent scientific articles visually, medical images need to be separated from general images such as flowcharts or graphs to facilitate browsing, as graphs contain little information. Medical modality classification is a second step to focus search. The techniques described in this article first classify images into broad categories. In a second step the images are further classified into the exact medical modalities. The system combines the Scale-Invariant Feature Transform (SIFT) and density-based clustering (DENCLUE). Visual words are first created globally to differentiate broad categories and then within each category a new visual vocabulary is created for modality classification. The results show the difficulties to differentiate between some modalities by visual means alone. On the other hand the improvement of the accuracy of the two-step approach shows the usefulness of the method. The system is currently being integrated into the Goldminer image search engine of the ARRS (American Roentgen Ray Society) as a web service, allowing concentrating image search onto clinically relevant images automatically.

  2. Automated segmentation of pigmented skin lesions in multispectral imaging

    International Nuclear Information System (INIS)

    The aim of this study was to develop an algorithm for the automatic segmentation of multispectral images of pigmented skin lesions. The study involved 1700 patients with 1856 cutaneous pigmented lesions, which were analysed in vivo by a novel spectrophotometric system, before excision. The system is able to acquire a set of 15 different multispectral images at equally spaced wavelengths between 483 and 951 nm. An original segmentation algorithm was developed and applied to the whole set of lesions and was able to automatically contour them all. The obtained lesion boundaries were shown to two expert clinicians, who, independently, rejected 54 of them. The 97.1% contour accuracy indicates that the developed algorithm could be a helpful and effective instrument for the automatic segmentation of skin pigmented lesions. (note)

  3. Medical Image Fusion: A survey of the state of the art

    CERN Document Server

    James, A P

    2014-01-01

    Medical image fusion is the process of registering and combining multiple images from single or multiple imaging modalities to improve the imaging quality and reduce randomness and redundancy in order to increase the clinical applicability of medical images for diagnosis and assessment of medical problems. Multi-modal medical image fusion algorithms and devices have shown notable achievements in improving clinical accuracy of decisions based on medical images. This review article provides a factual listing of methods and summarizes the broad scientific challenges faced in the field of medical image fusion. We characterize the medical image fusion research based on (1) the widely used image fusion methods, (2) imaging modalities, and (3) imaging of organs that are under study. This review concludes that even though there exists several open ended technological and scientific challenges, the fusion of medical images has proved to be useful for advancing the clinical reliability of using medical imaging for medi...

  4. Automated interpretation of PET/CT images in patients with lung cancer

    DEFF Research Database (Denmark)

    Gutte, Henrik; Jakobsson, David; Olofsson, Fredrik;

    2007-01-01

    cancer. METHODS: A total of 87 patients who underwent PET/CT examinations due to suspected lung cancer comprised the training group. The test group consisted of PET/CT images from 49 patients suspected with lung cancer. The consensus interpretations by two experienced physicians were used as the 'gold...... for localization of lesions in the PET images in the feature extraction process. Eight features from each examination were used as inputs to artificial neural networks trained to classify the images. Thereafter, the performance of the network was evaluated in the test set. RESULTS: The performance of the automated...

  5. Extending and applying active appearance models for automated, high precision segmentation in different image modalities

    DEFF Research Database (Denmark)

    Stegmann, Mikkel Bille; Fisker, Rune; Ersbøll, Bjarne Kjær

    2001-01-01

    , an initialization scheme is designed thus making the usage of AAMs fully automated. Using these extensions it is demonstrated that AAMs can segment bone structures in radiographs, pork chops in perspective images and the left ventricle in cardiovascular magnetic resonance images in a robust, fast and accurate...... object class description, which can be employed to rapidly search images for new object instances. The proposed extensions concern enhanced shape representation, handling of homogeneous and heterogeneous textures, refinement optimization using Simulated Annealing and robust statistics. Finally...

  6. Principal Components Analysis In Medical Imaging

    Science.gov (United States)

    Weaver, J. B.; Huddleston, A. L.

    1986-06-01

    Principal components analysis, PCA, is basically a data reduction technique. PCA has been used in several problems in diagnostic radiology: processing radioisotope brain scans (Ref.1), automatic alignment of radionuclide images (Ref. 2), processing MRI images (Ref. 3,4), analyzing first-pass cardiac studies (Ref. 5) correcting for attenuation in bone mineral measurements (Ref. 6) and in dual energy x-ray imaging (Ref. 6,7). This paper will progress as follows; a brief introduction to the mathematics of PCA will be followed by two brief examples of how PCA has been used in the literature. Finally my own experience with PCA in dual-energy x-ray imaging will be given.

  7. Speckle Noise Reduction in Medical Ultrasound Images

    Directory of Open Access Journals (Sweden)

    Faouzi Benzarti

    2012-03-01

    Full Text Available Ultrasound imaging is an incontestable vital tool for diagnosis, it provides in non-invasive manner the internal structure of the body to detect eventually diseases or abnormalities tissues. Unfortunately, the presence of speckle noise in these images affects edges and fine details which limit the contrast resolution and make diagnostic more difficult. In this paper, we propose a denoising approach which combines logarithmic transformation and a non linear diffusion tensor. Since speckle noise is multiplicative and nonwhite process, the logarithmic transformation is a reasonable choice to convert signal-dependent or pure multiplicative noise to an additive one. The key idea from using diffusion tensor is to adapt the flow diffusion towards the local orientation by applying anisotropic diffusion along the coherent structure direction of interesting features in the image. To illustrate the effective performance of our algorithm, we present some experimental results on synthetically and real echographic images.

  8. Automatic Medical Image Classification and Abnormality Detection Using KNearest Neighbour

    Directory of Open Access Journals (Sweden)

    Dr. R. J. Ramteke , Khachane Monali Y.

    2012-12-01

    Full Text Available This research work presents a method for automatic classification of medical images in two classes Normal and Abnormal based on image features and automatic abnormality detection. Our proposed system consists of four phases Preprocessing, Feature extraction, Classification, and Post processing. Statistical texture feature set is derived from normal and abnormal images. We used the KNN classifier for classifying image. The KNN classifier performance compared with kernel based SVM classifier (Linear and RBF. The confusion matrix computed and result shows that KNN obtain 80% classification rate which is more than SVM classification rate. So we choose KNN algorithm for classification of images. If image classified as abnormal then post processing step applied on the image and abnormal region is highlighted on the image. The system has been tested on the number of real CT scan brain images.

  9. Automated 3D ultrasound image segmentation for assistant diagnosis of breast cancer

    Science.gov (United States)

    Wang, Yuxin; Gu, Peng; Lee, Won-Mean; Roubidoux, Marilyn A.; Du, Sidan; Yuan, Jie; Wang, Xueding; Carson, Paul L.

    2016-04-01

    Segmentation of an ultrasound image into functional tissues is of great importance to clinical diagnosis of breast cancer. However, many studies are found to segment only the mass of interest and not all major tissues. Differences and inconsistencies in ultrasound interpretation call for an automated segmentation method to make results operator-independent. Furthermore, manual segmentation of entire three-dimensional (3D) ultrasound volumes is time-consuming, resource-intensive, and clinically impractical. Here, we propose an automated algorithm to segment 3D ultrasound volumes into three major tissue types: cyst/mass, fatty tissue, and fibro-glandular tissue. To test its efficacy and consistency, the proposed automated method was employed on a database of 21 cases of whole breast ultrasound. Experimental results show that our proposed method not only distinguishes fat and non-fat tissues correctly, but performs well in classifying cyst/mass. Comparison of density assessment between the automated method and manual segmentation demonstrates good consistency with an accuracy of 85.7%. Quantitative comparison of corresponding tissue volumes, which uses overlap ratio, gives an average similarity of 74.54%, consistent with values seen in MRI brain segmentations. Thus, our proposed method exhibits great potential as an automated approach to segment 3D whole breast ultrasound volumes into functionally distinct tissues that may help to correct ultrasound speed of sound aberrations and assist in density based prognosis of breast cancer.

  10. Remote Minimally Invasive Surgery – Haptic Feedback and Selective Automation in Medical Robotics

    Directory of Open Access Journals (Sweden)

    Christoph Staub

    2011-01-01

    Full Text Available The automation of recurrent tasks and force feedback are complex problems in medical robotics. We present a novel approach that extends human-machine skill-transfer by a scaffolding framework. It assumes a consolidated working environment for both, the trainee and the trainer. The trainer provides hints and cues in a basic structure which is already understood by the learner. In this work, the scaffolding is constituted by abstract patterns, which facilitate the structuring and segmentation of information during “Learning by Demonstration” (LbD. With this concept, the concrete example of knot-tying for suturing is exemplified and evaluated. During the evaluation, most problems and failures arose due to intrinsic system imprecisions of the medical robot system. These inaccuracies were then improved by the visual guidance of the surgical instruments. While the benefits of force feedback in telesurgery has already been demonstrated and measured forces are also used during task learning, the transmission of signals between the operator console and the robot system over long-distances or across-network remote connections is still a challenge due to time-delay. Especially during incision processes with a scalpel into tissue, a delayed force feedback yields to an unpredictable force perception at the operator-side and can harm the tissue which the robot is interacting with. We propose a XFEM-based incision force prediction algorithm that simulates the incision contact-forces in real-time and compensates the delayed force sensor readings. A realistic 4-arm system for minimally invasive robotic heart surgery is used as a platform for the research.

  11. Patients radiation protection in medical imaging. Conference proceedings

    International Nuclear Information System (INIS)

    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)

  12. Automation of disbond detection in aircraft fuselage through thermal image processing

    Science.gov (United States)

    Prabhu, D. R.; Winfree, W. P.

    1992-01-01

    A procedure for interpreting thermal images obtained during the nondestructive evaluation of aircraft bonded joints is presented. The procedure operates on time-derivative thermal images and resulted in a disbond image with disbonds highlighted. The size of the 'black clusters' in the output disbond image is a quantitative measure of disbond size. The procedure is illustrated using simulation data as well as data obtained through experimental testing of fabricated samples and aircraft panels. Good results are obtained, and, except in pathological cases, 'false calls' in the cases studied appeared only as noise in the output disbond image which was easily filtered out. The thermal detection technique coupled with an automated image interpretation capability will be a very fast and effective method for inspecting bonded joints in an aircraft structure.

  13. Compact storage of medical images with patient information.

    Science.gov (United States)

    Acharya, R; Anand, D; Bhat, S; Niranjan, U C

    2001-12-01

    Digital watermarking is a technique of hiding specific identification data for copyright authentication. This technique is adapted here for interleaving patient information with medical images to reduce storage and transmission overheads. The text data are encrypted before interleaving with images to ensure greater security. The graphical signals are compressed and subsequently interleaved with the image. Differential pulse-code-modulation and adaptive-delta-modulation techniques are employed for data compression, and encryption and results are tabulated for a specific example.

  14. Active index for content-based medical image retrieval.

    Science.gov (United States)

    Chang, S K

    1996-01-01

    This paper introduces the active index for content-based medical image retrieval. The dynamic nature of the active index is its most important characteristic. With an active index, we can effectively and efficiently handle smart images that respond to accessing, probing and other actions. The main applications of the active index are to prefetch image and multimedia data, and to facilitate similarity retrieval. The experimental active index system is described. PMID:8954230

  15. Advanced techniques in medical image segmentation of the liver

    OpenAIRE

    López Mir, Fernando

    2016-01-01

    [EN] Image segmentation is, along with multimodal and monomodal registration, the operation with the greatest applicability in medical image processing. There are many operations and filters, as much as applications and cases, where the segmentation of an organic tissue is the first step. The case of liver segmentation in radiological images is, after the brain, that on which the highest number of scientific publications can be found. This is due, on the one hand, to the need to continue inno...

  16. Active index for content-based medical image retrieval.

    Science.gov (United States)

    Chang, S K

    1996-01-01

    This paper introduces the active index for content-based medical image retrieval. The dynamic nature of the active index is its most important characteristic. With an active index, we can effectively and efficiently handle smart images that respond to accessing, probing and other actions. The main applications of the active index are to prefetch image and multimedia data, and to facilitate similarity retrieval. The experimental active index system is described.

  17. Medical Images Watermarking Algorithm Based on Improved DCT

    Directory of Open Access Journals (Sweden)

    Yv-fan SHANG

    2013-12-01

    Full Text Available Targeting at the incessant securities problems of digital information management system in modern medical system, this paper presents the robust watermarking algorithm for medical images based on Arnold transformation and DCT. The algorithm first deploys the scrambling technology to encrypt the watermark information and then combines it with the visual feature vector of the image to generate a binary logic series through the hash function. The sequence as taken as keys and stored in the third party to obtain ownership of the original image. Having no need for artificial selection of a region of interest, no capacity constraint, no participation of the original medical image, such kind of watermark extracting solves security and speed problems in the watermark embedding and extracting. The simulation results also show that the algorithm is simple in operation and excellent in robustness and invisibility. In a word, it is more practical compared with other algorithms

  18. Medical image of the week: polysomnogram artifact

    Directory of Open Access Journals (Sweden)

    Bartell J

    2015-02-01

    Full Text Available A 54 year-old man with a past medical history of attention deficit hyperactivity disorder (ADHD, low back pain, and paroxysmal supraventricular tachycardia presented to the sleep laboratory for evaluation of sleep disordered breathing. Pertinent medications include fluoxetine, ambien, and clonazepam. His Epworth sleepiness score was 18. He had a total sleep time of 12 min. On the night of his sleep study, the patient was restless and repeatedly changed positions in bed. Figures 1 and 2 show the artifact determined to be lead displacement of O1M2 after the patient shifted in bed, inadvertently removing one of his scalp electrodes. The sine waves are 60 Hz in frequency. Once the problem was identified, the lead was quickly replaced to its proper position.

  19. Extended Field Laser Confocal Microscopy (EFLCM: Combining automated Gigapixel image capture with in silico virtual microscopy

    Directory of Open Access Journals (Sweden)

    Strandh Christer

    2008-07-01

    Full Text Available Abstract Background Confocal laser scanning microscopy has revolutionized cell biology. However, the technique has major limitations in speed and sensitivity due to the fact that a single laser beam scans the sample, allowing only a few microseconds signal collection for each pixel. This limitation has been overcome by the introduction of parallel beam illumination techniques in combination with cold CCD camera based image capture. Methods Using the combination of microlens enhanced Nipkow spinning disc confocal illumination together with fully automated image capture and large scale in silico image processing we have developed a system allowing the acquisition, presentation and analysis of maximum resolution confocal panorama images of several Gigapixel size. We call the method Extended Field Laser Confocal Microscopy (EFLCM. Results We show using the EFLCM technique that it is possible to create a continuous confocal multi-colour mosaic from thousands of individually captured images. EFLCM can digitize and analyze histological slides, sections of entire rodent organ and full size embryos. It can also record hundreds of thousands cultured cells at multiple wavelength in single event or time-lapse fashion on fixed slides, in live cell imaging chambers or microtiter plates. Conclusion The observer independent image capture of EFLCM allows quantitative measurements of fluorescence intensities and morphological parameters on a large number of cells. EFLCM therefore bridges the gap between the mainly illustrative fluorescence microscopy and purely quantitative flow cytometry. EFLCM can also be used as high content analysis (HCA instrument for automated screening processes.

  20. Unsupervised detection of abnormalities in medical images using salient features

    Science.gov (United States)

    Alpert, Sharon; Kisilev, Pavel

    2014-03-01

    In this paper we propose a new method for abnormality detection in medical images which is based on the notion of medical saliency. The proposed method is general and is suitable for a variety of tasks related to detection of: 1) lesions and microcalcifications (MCC) in mammographic images, 2) stenoses in angiographic images, 3) lesions found in magnetic resonance (MRI) images of brain. The main idea of our approach is that abnormalities manifest as rare events, that is, as salient areas compared to normal tissues. We define the notion of medical saliency by combining local patch information from the lightness channel with geometric shape local descriptors. We demonstrate the efficacy of the proposed method by applying it to various modalities, and to various abnormality detection problems. Promising results are demonstrated for detection of MCC and of masses in mammographic images, detection of stenoses in angiography images, and detection of lesions in brain MRI. We also demonstrate how the proposed automatic abnormality detection method can be combined with a system that performs supervised classification of mammogram images into benign or malignant/premalignant MCC's. We use a well known DDSM mammogram database for the experiment on MCC classification, and obtain 80% accuracy in classifying images containing premalignant MCC versus benign ones. In contrast to supervised detection methods, the proposed approach does not rely on ground truth markings, and, as such, is very attractive and applicable for big corpus image data processing.

  1. Denoising of Medical Images Using Total Variational Method

    Directory of Open Access Journals (Sweden)

    V N Prudhvi Raj

    2012-05-01

    Full Text Available Feature extraction and object recognition from images acquired by various imaging modalities are playingthe key role in diagnosing the various diseases. These operations will become difficult if the images arecorrupted with noise. So the need for developing the efficient algorithms for noise removal became animportant research area today. Developing Image denoising algorithms is a difficult operation because finedetails in a medical image embedding diagnostic information should not be destroyed during noiseremoval. In this paper the total variational method which had success in computational fluid dynamics isadopted to denoise the medical images. We are using split Bregman method from optimisation theory tofind the solution to this non-linear convex optimisation problem. The present approach will outperform indenoising the medical images while compared with the traditional spatial domain filtering methods. Theperformance metrics we used to measure the quality of the denoised images is PSNR (Peak signal to noiseratio.The results showed that these methods are removing the noise effectively while preserving the edgeinformation in the images.

  2. Workstation scheme and implementation for a medical imaging information system

    Institute of Scientific and Technical Information of China (English)

    陶勇浩; 缪竞陶

    2003-01-01

    Objective To discuss the scheme and implementation of workstation configuration for medical imaging information systems suitable to the practical situation in China. Methods The workstations were logically divided into picture archiving and communication system (PACS) workstations and radiology information system (RIS) workstations. The former applied to three kinds of diagnostic practice: the small matrix images, large matrix images and high resolution grayscale display applications. The latter consisted many different models defined by the usage and function processes.Results A dual-screen configuration for image interpretation workstations integrated the image-viewing and reporting procedures physically. Small matrix images as CT or MR were operated on 17 inch (1 inch=2.54 cm) color monitors, while conventional X-ray interpretation was performed on 21 inch color monitors or portrait format grayscale 2 k by 2.5 k monitors. All other RIS workstations not involved in imaging process were set up with a common PC configuration. Conclusion Workstation schemes for medical imaging information systems should satisfy the basic requirements of medical imaging and investment budget.

  3. Medical image of the week: renal infarction

    OpenAIRE

    August J; Huang JJ

    2015-01-01

    No abstract available. Article truncated at 150 words. A 79-year-old woman with past medical history of persistent atrial fibrillation not on anticoagulation, coronary artery disease, hypertension, diabetes, and hyperlipidemia presented with right flank pain accompanied by nausea and vomiting for two days. Laboratory studies showed leukocytosis with creatinine of 1.2. Urinalysis was negative for signs of infection and red blood cells. However, despite being on analgesic, she continued to have...

  4. Medical image of the week: panloubular emphysema

    OpenAIRE

    Mathur A; Carr T

    2015-01-01

    No abstract available. Article truncated after 150 words. A 60 year old female, non-smoker with a past medical history of chronic rhinosinusitis with nasal polyps presented with an eight year history of productive cough and dyspnea. Previous treatment with inhaled corticosteroids, courses of systemic corticosteroids and antibiotics provided modest improvement in her symptoms. Pulmonary function testing revealed a severe obstructive ventilatory defect without significant bronchodilator respons...

  5. Medical image of the week: aspergilloma

    Directory of Open Access Journals (Sweden)

    Hsu W

    2014-05-01

    Full Text Available No abstract available. Article truncated after 150 words. A 69-year-old woman, a current smoker, with very severe chronic obstructive pulmonary disease and prior atypical mycobacterium, was found unresponsive by her family and intubated in the field by emergency medical services for respiratory distress. Her CT thorax showed severe emphysematous disease, apical bullous disease, and a large left upper lobe cavitation with debris (Figure 1. She was treated with broad-spectrum antibiotics and anti-fungal medications. Hemoptysis was never seen. Sputum cultures over a span of two weeks repeatedly showed Aspergillus fumigatus and outside medical records confirmed the patient had a known history of stable aspergilloma not requiring therapy. Aspergillomas usually arises in cavitary areas of the lung damaged by previous infections. The fungus ball is a combination of colonization by Aspergillus hyphae and cellular debris. Individuals with aspergillomas are usually asymptomatic or have mild symptoms (chronic cough and do not require treatment unless it begins to invade into the cavity ...

  6. Automated detection of diabetic retinopathy in retinal images

    Directory of Open Access Journals (Sweden)

    Carmen Valverde

    2016-01-01

    Full Text Available Diabetic retinopathy (DR is a disease with an increasing prevalence and the main cause of blindness among working-age population. The risk of severe vision loss can be significantly reduced by timely diagnosis and treatment. Systematic screening for DR has been identified as a cost-effective way to save health services resources. Automatic retinal image analysis is emerging as an important screening tool for early DR detection, which can reduce the workload associated to manual grading as well as save diagnosis costs and time. Many research efforts in the last years have been devoted to developing automatic tools to help in the detection and evaluation of DR lesions. However, there is a large variability in the databases and evaluation criteria used in the literature, which hampers a direct comparison of the different studies. This work is aimed at summarizing the results of the available algorithms for the detection and classification of DR pathology. A detailed literature search was conducted using PubMed. Selected relevant studies in the last 10 years were scrutinized and included in the review. Furthermore, we will try to give an overview of the available commercial software for automatic retinal image analysis.

  7. Automated Peripheral Neuropathy Assessment Using Optical Imaging and Foot Anthropometry.

    Science.gov (United States)

    Siddiqui, Hafeez-U R; Spruce, Michelle; Alty, Stephen R; Dudley, Sandra

    2015-08-01

    A large proportion of individuals who live with type-2 diabetes suffer from plantar sensory neuropathy. Regular testing and assessment for the condition is required to avoid ulceration or other damage to patient's feet. Currently accepted practice involves a trained clinician testing a patient's feet manually with a hand-held nylon monofilament probe. The procedure is time consuming, labor intensive, requires special training, is prone to error, and repeatability is difficult. With the vast increase in type-2 diabetes, the number of plantar sensory neuropathy sufferers has already grown to such an extent as to make a traditional manual test problematic. This paper presents the first investigation of a novel approach to automatically identify the pressure points on a given patient's foot for the examination of sensory neuropathy via optical image processing incorporating plantar anthropometry. The method automatically selects suitable test points on the plantar surface that correspond to those repeatedly chosen by a trained podiatrist. The proposed system automatically identifies the specific pressure points at different locations, namely the toe (hallux), metatarsal heads and heel (Calcaneum) areas. The approach is generic and has shown 100% reliability on the available database used. The database consists of Chinese, Asian, African, and Caucasian foot images. PMID:26186748

  8. Quantification of Structure from Medical Images

    DEFF Research Database (Denmark)

    Qazi, Arish Asif

    , segmented from MR images of the knee. The cartilage tissue is considered to be a key determinant in the onset of Osteoarthritis (OA), a degenerative joint disease, with no known cure. The primary obstacle has been the dependence on radiography as the ‘gold standard’ for detecting the manifestation...... based on diffusion tensor imaging, a technique widely used for analysis of the white matter of the central nervous system in the living human brain. An inherent drawback of the traditional diffusion tensor model is its limited ability to provide detailed information about multi-directional fiber...

  9. SVM for density estimation and application to medical image segmentation

    Institute of Scientific and Technical Information of China (English)

    ZHANG Zhao; ZHANG Su; ZHANG Chen-xi; CHEN Ya-zhu

    2006-01-01

    A method of medical image segmentation based on support vector machine (SVM) for density estimation is presented. We used this estimator to construct a prior model of the image intensity and curvature profile of the structure from training images. When segmenting a novel image similar to the training images, the technique of narrow level set method is used. The higher dimensional surface evolution metric is defined by the prior model instead of by energy minimization function. This method offers several advantages. First, SVM for density estimation is consistent and its solution is sparse. Second, compared to the traditional level set methods, this method incorporates shape information on the object to be segmented into the segmentation process.Segmentation results are demonstrated on synthetic images, MR images and ultrasonic images.

  10. Registering multiple medical images using the shared chain mutual information

    Institute of Scientific and Technical Information of China (English)

    Jing Jin; Qiang Wang; Yi Shen

    2007-01-01

    @@ A new approach to the simultaneous registration of multiple medical images is proposed using shared chain mutual information (SCMI) as the matching measure. The presented method applies SCMI to measure the shared information between the multiple images. Registration is achieved by adjusting the relative position of the floating image until the SCMI between all the images is maximized. Using this measure, we registered three and four simulated magnetic resonance imaging (MRI) images using downhill simplex optimization to search for the optimal transformation parameters. Accuracy and validity of the proposed method for multiple-image registration are testified by comparing the results with that of twoimage registration. Furthermore, the performance of the proposed method is validated by registering the real ultrasonic image sequence.

  11. Automated Image-Based Procedures for Adaptive Radiotherapy

    DEFF Research Database (Denmark)

    Bjerre, Troels

    Fractionated radiotherapy for cancer treatment is a field of constant innovation. Developments in dose delivery techniques have made it possible to precisely direct ionizing radiation at complicated targets. In order to further increase tumour control probability (TCP) and decrease normal...... to encourage bone rigidity and local tissue volume change only in the gross tumour volume and the lungs. This is highly relevant in adaptive radiotherapy when modelling significant tumour volume changes. - It is described how cone beam CT reconstruction can be modelled as a deformation of a planning CT scan...... be employed for contour propagation in adaptive radiotherapy. - MRI-radiotherapy devices have the potential to offer near real-time intrafraction imaging without any additional ionising radiation. It is detailed how the use of multiple, orthogonal slices can form the basis for reliable 3D soft tissue tracking....

  12. MEDICAL IMAGE SEGMENTATION FOR ANATOMICAL KNOWLEDGE EXTRACTION

    Directory of Open Access Journals (Sweden)

    Ms Maya Eapen

    2014-01-01

    Full Text Available Computed Tomography-Angiography (CTA images of the abdomen, followed by precise segmentation and subsequent computation of shape based features of liver play an important role in hepatic surgery, patient/donor diagnosis during liver transplantation and at various treatment stages. Nevertheless, the issues like intensity similarity and Partial Volume Effect (PVE between the neighboring organs; left the task of liver segmentation critical. The accurate segmentation of liver helps the surgeons to perfectly classify the patients based on their liver anatomy which in turn helps them in the treatment decision phase. In this study, we propose an effective Advanced Region Growing (ARG algorithm for segmentation of liver from CTA images. The performance of the proposed technique was tested with several CTA images acquired across a wide range of patients. The proposed ARG algorithm identifies the liver regions on the images based on the statistical features (intensity distribution and orientation value. The proposed technique addressed the aforementioned issues and been evaluated both quantitatively and qualitatively. For quantitative analysis proposed method was compared with manual segmentation (gold standard. The method was also compared with standard region growing.

  13. Automated grading of renal cell carcinoma using whole slide imaging

    Directory of Open Access Journals (Sweden)

    Fang-Cheng Yeh

    2014-01-01

    Full Text Available Introduction: Recent technology developments have demonstrated the benefit of using whole slide imaging (WSI in computer-aided diagnosis. In this paper, we explore the feasibility of using automatic WSI analysis to assist grading of clear cell renal cell carcinoma (RCC, which is a manual task traditionally performed by pathologists. Materials and Methods: Automatic WSI analysis was applied to 39 hematoxylin and eosin-stained digitized slides of clear cell RCC with varying grades. Kernel regression was used to estimate the spatial distribution of nuclear size across the entire slides. The analysis results were correlated with Fuhrman nuclear grades determined by pathologists. Results: The spatial distribution of nuclear size provided a panoramic view of the tissue sections. The distribution images facilitated locating regions of interest, such as high-grade regions and areas with necrosis. The statistical analysis showed that the maximum nuclear size was significantly different (P < 0.001 between low-grade (Grades I and II and high-grade tumors (Grades III and IV. The receiver operating characteristics analysis showed that the maximum nuclear size distinguished high-grade and low-grade tumors with a false positive rate of 0.2 and a true positive rate of 1.0. The area under the curve is 0.97. Conclusion: The automatic WSI analysis allows pathologists to see the spatial distribution of nuclei size inside the tumors. The maximum nuclear size can also be used to differentiate low-grade and high-grade clear cell RCC with good sensitivity and specificity. These data suggest that automatic WSI analysis may facilitate pathologic grading of renal tumors and reduce variability encountered with manual grading.

  14. Automated parasite faecal egg counting using fluorescence labelling, smartphone image capture and computational image analysis.

    Science.gov (United States)

    Slusarewicz, Paul; Pagano, Stefanie; Mills, Christopher; Popa, Gabriel; Chow, K Martin; Mendenhall, Michael; Rodgers, David W; Nielsen, Martin K

    2016-07-01

    Intestinal parasites are a concern in veterinary medicine worldwide and for human health in the developing world. Infections are identified by microscopic visualisation of parasite eggs in faeces, which is time-consuming, requires technical expertise and is impractical for use on-site. For these reasons, recommendations for parasite surveillance are not widely adopted and parasite control is based on administration of rote prophylactic treatments with anthelmintic drugs. This approach is known to promote anthelmintic resistance, so there is a pronounced need for a convenient egg counting assay to promote good clinical practice. Using a fluorescent chitin-binding protein, we show that this structural carbohydrate is present and accessible in shells of ova of strongyle, ascarid, trichurid and coccidian parasites. Furthermore, we show that a cellular smartphone can be used as an inexpensive device to image fluorescent eggs and, by harnessing the computational power of the phone, to perform image analysis to count the eggs. Strongyle egg counts generated by the smartphone system had a significant linear correlation with manual McMaster counts (R(2)=0.98), but with a significantly lower coefficient of variation (P=0.0177). Furthermore, the system was capable of differentiating equine strongyle and ascarid eggs similar to the McMaster method, but with significantly lower coefficients of variation (Psmartphones as relatively sophisticated, inexpensive and portable medical diagnostic devices. PMID:27025771

  15. Watermarking techniques used in medical images: a survey.

    Science.gov (United States)

    Mousavi, Seyed Mojtaba; Naghsh, Alireza; Abu-Bakar, S A R

    2014-12-01

    The ever-growing numbers of medical digital images and the need to share them among specialists and hospitals for better and more accurate diagnosis require that patients' privacy be protected. As a result of this, there is a need for medical image watermarking (MIW). However, MIW needs to be performed with special care for two reasons. Firstly, the watermarking procedure cannot compromise the quality of the image. Secondly, confidential patient information embedded within the image should be flawlessly retrievable without risk of error after image decompressing. Despite extensive research undertaken in this area, there is still no method available to fulfill all the requirements of MIW. This paper aims to provide a useful survey on watermarking and offer a clear perspective for interested researchers by analyzing the strengths and weaknesses of different existing methods.

  16. Medical image of the week: refractory dyspnea

    Directory of Open Access Journals (Sweden)

    Malo J

    2012-12-01

    Full Text Available A 61 year old man with an extensive smoking history and emphysema was referred for evaluation of dyspnea refractory to standard therapy. He was diagnosed with a pulmonary embolism 5 months prior to presentation and has been on warfarin since that time. Review of the patient’s CT scan performed prior to the visit demonstrated dilated main; right; and left pulmonary arteries (Figure 1. Also visualized was an eccentrically located thrombus with areas of calcification and central recanalization. Echocardiography confirmed the presence of elevated pulmonary pressures consistent with a diagnosis of chronic thromboembolic pulmonary hypertension (CTEPH. Medical therapy and a referral for pulmonary artery endarterectomy are being considered.

  17. Hybrid segmentation framework for 3D medical image analysis

    Science.gov (United States)

    Chen, Ting; Metaxas, Dimitri N.

    2003-05-01

    Medical image segmentation is the process that defines the region of interest in the image volume. Classical segmentation methods such as region-based methods and boundary-based methods cannot make full use of the information provided by the image. In this paper we proposed a general hybrid framework for 3D medical image segmentation purposes. In our approach we combine the Gibbs Prior model, and the deformable model. First, Gibbs Prior models are applied onto each slice in a 3D medical image volume and the segmentation results are combined to a 3D binary masks of the object. Then we create a deformable mesh based on this 3D binary mask. The deformable model will be lead to the edge features in the volume with the help of image derived external forces. The deformable model segmentation result can be used to update the parameters for Gibbs Prior models. These methods will then work recursively to reach a global segmentation solution. The hybrid segmentation framework has been applied to images with the objective of lung, heart, colon, jaw, tumor, and brain. The experimental data includes MRI (T1, T2, PD), CT, X-ray, Ultra-Sound images. High quality results are achieved with relatively efficient time cost. We also did validation work using expert manual segmentation as the ground truth. The result shows that the hybrid segmentation may have further clinical use.

  18. Automated Formosat Image Processing System for Rapid Response to International Disasters

    Science.gov (United States)

    Cheng, M. C.; Chou, S. C.; Chen, Y. C.; Chen, B.; Liu, C.; Yu, S. J.

    2016-06-01

    FORMOSAT-2, Taiwan's first remote sensing satellite, was successfully launched in May of 2004 into the Sun-synchronous orbit at 891 kilometers of altitude. With the daily revisit feature, the 2-m panchromatic, 8-m multi-spectral resolution images captured have been used for researches and operations in various societal benefit areas. This paper details the orchestration of various tasks conducted in different institutions in Taiwan in the efforts responding to international disasters. The institutes involved including its space agency-National Space Organization (NSPO), Center for Satellite Remote Sensing Research of National Central University, GIS Center of Feng-Chia University, and the National Center for High-performance Computing. Since each institution has its own mandate, the coordinated tasks ranged from receiving emergency observation requests, scheduling and tasking of satellite operation, downlink to ground stations, images processing including data injection, ortho-rectification, to delivery of image products. With the lessons learned from working with international partners, the FORMOSAT Image Processing System has been extensively automated and streamlined with a goal to shorten the time between request and delivery in an efficient manner. The integrated team has developed an Application Interface to its system platform that provides functions of search in archive catalogue, request of data services, mission planning, inquiry of services status, and image download. This automated system enables timely image acquisition and substantially increases the value of data product. Example outcome of these efforts in recent response to support Sentinel Asia in Nepal Earthquake is demonstrated herein.

  19. OpenComet: An automated tool for comet assay image analysis

    Directory of Open Access Journals (Sweden)

    Benjamin M. Gyori

    2014-01-01

    Full Text Available Reactive species such as free radicals are constantly generated in vivo and DNA is the most important target of oxidative stress. Oxidative DNA damage is used as a predictive biomarker to monitor the risk of development of many diseases. The comet assay is widely used for measuring oxidative DNA damage at a single cell level. The analysis of comet assay output images, however, poses considerable challenges. Commercial software is costly and restrictive, while free software generally requires laborious manual tagging of cells. This paper presents OpenComet, an open-source software tool providing automated analysis of comet assay images. It uses a novel and robust method for finding comets based on geometric shape attributes and segmenting the comet heads through image intensity profile analysis. Due to automation, OpenComet is more accurate, less prone to human bias, and faster than manual analysis. A live analysis functionality also allows users to analyze images captured directly from a microscope. We have validated OpenComet on both alkaline and neutral comet assay images as well as sample images from existing software packages. Our results show that OpenComet achieves high accuracy with significantly reduced analysis time.

  20. Development of a methodology for automated assessment of the quality of digitized images in mammography

    International Nuclear Information System (INIS)

    The process of evaluating the quality of radiographic images in general, and mammography in particular, can be much more accurate, practical and fast with the help of computer analysis tools. The purpose of this study is to develop a computational methodology to automate the process of assessing the quality of mammography images through techniques of digital imaging processing (PDI), using an existing image processing environment (ImageJ). With the application of PDI techniques was possible to extract geometric and radiometric characteristics of the images evaluated. The evaluated parameters include spatial resolution, high-contrast detail, low contrast threshold, linear detail of low contrast, tumor masses, contrast ratio and background optical density. The results obtained by this method were compared with the results presented in the visual evaluations performed by the Health Surveillance of Minas Gerais. Through this comparison was possible to demonstrate that the automated methodology is presented as a promising alternative for the reduction or elimination of existing subjectivity in the visual assessment methodology currently in use. (author)

  1. Medical Image Dynamic Collaborative Processing on the Distributed Environment

    Institute of Scientific and Technical Information of China (English)

    2003-01-01

    A new trend in the development of medical image processing systems is to enhance the sharing of medical resources and the collaborative processing of medical specialists. This paper presents an architecture of medical image dynamic collaborative processing on the distributed environment by combining the JAVA, CORBA (Common Object Request and Broker Architecture) and the MAS (Multi-Agents System) collaborative mechanism. The architecture allows medical specialists or applications to share records and communicate with each other on the web by overcoming the shortcut of traditional approach using Common Gateway Interface (CGI) and client/server architecture, and can support the remote heterogeneous systems collaboration. The new approach improves the collaborative processing of medical data and applications and is able to enhance the interoperation among heterogeneous system. Research on the system will help the collaboration and cooperation among medical application systems distributed on the web, thus supply high quality medical service such as diagnosis and therapy to practicing specialists regardless of their actual geographic location.

  2. Resource estimation in high performance medical image computing.

    Science.gov (United States)

    Banalagay, Rueben; Covington, Kelsie Jade; Wilkes, D M; Landman, Bennett A

    2014-10-01

    Medical imaging analysis processes often involve the concatenation of many steps (e.g., multi-stage scripts) to integrate and realize advancements from image acquisition, image processing, and computational analysis. With the dramatic increase in data size for medical imaging studies (e.g., improved resolution, higher throughput acquisition, shared databases), interesting study designs are becoming intractable or impractical on individual workstations and servers. Modern pipeline environments provide control structures to distribute computational load in high performance computing (HPC) environments. However, high performance computing environments are often shared resources, and scheduling computation across these resources necessitates higher level modeling of resource utilization. Submission of 'jobs' requires an estimate of the CPU runtime and memory usage. The resource requirements for medical image processing algorithms are difficult to predict since the requirements can vary greatly between different machines, different execution instances, and different data inputs. Poor resource estimates can lead to wasted resources in high performance environments due to incomplete executions and extended queue wait times. Hence, resource estimation is becoming a major hurdle for medical image processing algorithms to efficiently leverage high performance computing environments. Herein, we present our implementation of a resource estimation system to overcome these difficulties and ultimately provide users with the ability to more efficiently utilize high performance computing resources.

  3. Medical Image Fusion Based on Rolling Guidance Filter and Spiking Cortical Model

    OpenAIRE

    Liu Shuaiqi; Zhao Jie; Shi Mingzhu

    2015-01-01

    Medical image fusion plays an important role in diagnosis and treatment of diseases such as image-guided radiotherapy and surgery. Although numerous medical image fusion methods have been proposed, most of these approaches are sensitive to the noise and usually lead to fusion image distortion, and image information loss. Furthermore, they lack universality when dealing with different kinds of medical images. In this paper, we propose a new medical image fusion to overcome the aforementioned i...

  4. Medical image of the week: necrotizing pancreatitis

    Directory of Open Access Journals (Sweden)

    Desai H

    2015-08-01

    Full Text Available No abstract available. Article truncated after 150 words. A 60-year-old man with a past medical history significant for coronary artery disease status post percutaneous coronary intervention was admitted to Banner University Medical Center for acute pancreatitis complicated by a pericardial effusion requiring pericardiocentesis. The following day, the patient developed severe shortness of breath requiring increasing amounts of supplemental oxygen. The patient was emergently transferred to ICU for noninvasive bilevel positive airway pressure ventilation, but he subsequently required intubation. Throughout his worsening condition, he denied any abdominal pain, only relaying ongoing substernal chest pain. His troponins, however, remained negative and echocardiography failed to show any reaccumulation of the pericardial effusion. CT scan of the chest failed to show any pulmonary embolism. But, CT abdomen displayed acute pancreatitis complicated by peripancreatic gas consistent with necrotizing pancreatitis (Figure 1. Emergent laparotomy was completed. There were no signs of stomach or duodenal perforation. Purulent fluid was removed from the lesser sac and ...

  5. Medical image of the week: sleep bruxism

    Directory of Open Access Journals (Sweden)

    Bartell J

    2015-03-01

    Full Text Available No abstract available. Article truncated at 150 words. A 42 year-old man with a past medical history of insomnia, post-traumatic stress disorder, depression and both migraine and tension headaches was referred for an overnight sleep study. He had presented to the sleep clinic with symptoms of obstructive sleep apnea. Medications included sumatriptan, amitryptiline, sertraline, and trazodone. His sleep study showed: sleep efficiency of 58.2%, apnea-hypopnea index of 33 events per hour, and arousal index of 14.5/hr. Periodic limb movement index was 29.2/hr. The time spent in the sleep stages included N1 (3.6%, N2 (72.5%, N3 (12.9%, and REM (10.9%. Figure 1 is representative of the several brief waveforms seen on his EEG and chin EMG. Sleep bruxism (SB is a type of sleep-related movement disorder that is characterized by involuntary masticatory muscle contraction resulting in grinding and clenching of the teeth and typically associated with arousals from sleep (1,2. The American academy of sleep medicine (AASM criteria for ...

  6. RootGraph: a graphic optimization tool for automated image analysis of plant roots.

    Science.gov (United States)

    Cai, Jinhai; Zeng, Zhanghui; Connor, Jason N; Huang, Chun Yuan; Melino, Vanessa; Kumar, Pankaj; Miklavcic, Stanley J

    2015-11-01

    This paper outlines a numerical scheme for accurate, detailed, and high-throughput image analysis of plant roots. In contrast to existing root image analysis tools that focus on root system-average traits, a novel, fully automated and robust approach for the detailed characterization of root traits, based on a graph optimization process is presented. The scheme, firstly, distinguishes primary roots from lateral roots and, secondly, quantifies a broad spectrum of root traits for each identified primary and lateral root. Thirdly, it associates lateral roots and their properties with the specific primary root from which the laterals emerge. The performance of this approach was evaluated through comparisons with other automated and semi-automated software solutions as well as against results based on manual measurements. The comparisons and subsequent application of the algorithm to an array of experimental data demonstrate that this method outperforms existing methods in terms of accuracy, robustness, and the ability to process root images under high-throughput conditions.

  7. Development of Raman microspectroscopy for automated detection and imaging of basal cell carcinoma

    Science.gov (United States)

    Larraona-Puy, Marta; Ghita, Adrian; Zoladek, Alina; Perkins, William; Varma, Sandeep; Leach, Iain H.; Koloydenko, Alexey A.; Williams, Hywel; Notingher, Ioan

    2009-09-01

    We investigate the potential of Raman microspectroscopy (RMS) for automated evaluation of excised skin tissue during Mohs micrographic surgery (MMS). The main aim is to develop an automated method for imaging and diagnosis of basal cell carcinoma (BCC) regions. Selected Raman bands responsible for the largest spectral differences between BCC and normal skin regions and linear discriminant analysis (LDA) are used to build a multivariate supervised classification model. The model is based on 329 Raman spectra measured on skin tissue obtained from 20 patients. BCC is discriminated from healthy tissue with 90+/-9% sensitivity and 85+/-9% specificity in a 70% to 30% split cross-validation algorithm. This multivariate model is then applied on tissue sections from new patients to image tumor regions. The RMS images show excellent correlation with the gold standard of histopathology sections, BCC being detected in all positive sections. We demonstrate the potential of RMS as an automated objective method for tumor evaluation during MMS. The replacement of current histopathology during MMS by a ``generalization'' of the proposed technique may improve the feasibility and efficacy of MMS, leading to a wider use according to clinical need.

  8. Medical image of the week: tracheal perforation

    Directory of Open Access Journals (Sweden)

    Parsa N

    2014-12-01

    Full Text Available A 45 year old Caucasian man with a history of HIV/AIDS was admitted for septic shock secondary to right lower lobe community acquired pneumonia. The patient’s respiratory status continued to decline requiring emergency intubation in a non-ICU setting. Four laryngoscope intubation attempts were made including an inadvertent esophageal intubation. Subsequent CT imaging revealed a tracheal defect (Figure 1, red arrow with communication to the mediastinum and air around the trachea consistent with pneumomediastinum (Figure 2, orange arrow and figure 3, yellow arrow. Pneumopericardium (figure 4, blue arrow was also evident post-intubation. The patient’s hemodynamic status remained stable. Two days following respiratory intubation subsequent chest imaging revealed resolution of the pneumomediastinum and pneumopericardium and patient continued to do well without hemodynamic compromise or presence of subcutaneous emphysema. Post-intubation tracheal perforation is a rare complication of traumatic intubation and may be managed with surgical intervention or conservative treatment (1.

  9. Automated construction of arterial and venous trees in retinal images.

    Science.gov (United States)

    Hu, Qiao; Abràmoff, Michael D; Garvin, Mona K

    2015-10-01

    While many approaches exist to segment retinal vessels in fundus photographs, only a limited number focus on the construction and disambiguation of arterial and venous trees. Previous approaches are local and/or greedy in nature, making them susceptible to errors or limiting their applicability to large vessels. We propose a more global framework to generate arteriovenous trees in retinal images, given a vessel segmentation. In particular, our approach consists of three stages. The first stage is to generate an overconnected vessel network, named the vessel potential connectivity map (VPCM), consisting of vessel segments and the potential connectivity between them. The second stage is to disambiguate the VPCM into multiple anatomical trees, using a graph-based metaheuristic algorithm. The third stage is to classify these trees into arterial or venous (A/V) trees. We evaluated our approach with a ground truth built based on a public database, showing a pixel-wise classification accuracy of 88.15% using a manual vessel segmentation as input, and 86.11% using an automatic vessel segmentation as input. PMID:26636114

  10. Medical image of the week: Leriche syndrome

    OpenAIRE

    Berlinberg A; Elaini T; Hypes C

    2016-01-01

    No abstract available. Article truncated at 150 words. A 68-year-old man with GOLD stage 4 COPD was admitted to the Intensive Care Unit for worsening hypoxic and hypercarbic respiratory failure. The patient was treated with steroids for COPD exacerbation, and required continuous BIPAP. On hospital day 2 concern arose for possible pulmonary embolism given worsening oxygenation despite BIPAP, and a thoracic CT angiogram was performed. On imaging, an incidental finding was discovered that the pa...

  11. Medical image of the week: sarcoidosis

    OpenAIRE

    Knox KS

    2013-01-01

    A 42 year old African-American man from Indianapolis presented with cough and skin lesions. ACE level was elevated at 86 μg/L. Spirometry was normal except for a diffusing capacity 52% of predicted. Imaging was suggestive of sarcoidosis versus granulomatous infection. Bronchoscopy with bronchoalveolar lavage cytospin revealed a lymphocytic alveolitis (27% lymphocytes) with a CD4:CD8 ratio of 6.2:1 by flow cytometry. Biopsy showed classic noncaseating granulomas and no organisms supportin...

  12. Medical image of the week: Boerhaave syndrome

    Directory of Open Access Journals (Sweden)

    Parsa N

    2016-06-01

    Full Text Available No abstract available. Article truncated at 150 words. A 41-year-old woman with a history of gastroesophageal reflux disease (GERD, asthma and iron deficiency anemia presented with complaints of right sided chest pain, nausea and emesis for several days prior to hospital presentation. She had also been experiencing progressive dysphagia to solids for a month preceding admission. CT chest imaging revealed mega-esophagus (Figure 1A with rupture into the right lung parenchyma and resultant abscess formation (Figure 1B and 1C. A subsequent echocardiogram also confirmed mitral valve endocarditis. An image-guided chest tube was placed in the abscess for drainage. Endoscopy was attempted but visualization was difficult due to the presence of retained food. Given her low albumin and poor nutritional state, a jejunostomy tube was placed. Follow up CT imaging with contrast through a nasogastric tube confirmed extravasation of esophageal contrast into the right lung parenchyma (Figure 1D. Blood and sputum cultures grew Candida glabrata. She was initially started on ...

  13. Recent advances in radiology and medical imaging

    Energy Technology Data Exchange (ETDEWEB)

    Steiner, R.E.; Sherwood, T.

    1986-01-01

    The first chapter, on the radiology of arthritis, is an overview. The second and seventh chapters are on the chest the former, on adult respiratory distress syndrome, is a brief summary, and the latter, on digital radiography of the chest with the prototype slit-scanning technique. The third chapter reviews computed tomography of the lumbar spine. The following two chapters are on MR imaging, one on the central nervous system (covering demyelinating diseases, cardiovascular disease, infections, and tumors), with excellent illustrations; and one on MR imaging of the body. The illustrations are good. The following chapter is on extracardiac digital subtraction angiography (DSA), with an interesting table comparing and contrasting conventional angiography with both intraveneous and intraarterial DSA. The eighth chapter on pediatric imaging fits a world of experience. Chapter 9 is an update on contrast media, while the next chapter is on barium infusion examination of the small intestine. The final three chapters are concerned with the present state of angioplasty, interventional radiology in the urinary tract.

  14. BioImage Suite: An integrated medical image analysis suite: An update

    OpenAIRE

    Papademetris, Xenophon; Jackowski, Marcel P; Rajeevan, Nallakkandi; DiStasio, Marcello; Okuda, Hirohito; Constable, R. Todd; Staib, Lawrence H.

    2006-01-01

    BioImage Suite is an NIH-supported medical image analysis software suite developed at Yale. It leverages both the Visualization Toolkit (VTK) and the Insight Toolkit (ITK) and it includes many additional algorithms for image analysis especially in the areas of segmentation, registration, diffusion weighted image processing and fMRI analysis. BioImage Suite has a user-friendly user interface developed in the Tcl scripting language. A final beta version is freely available for download 1

  15. Automated 3D-Objectdocumentation on the Base of an Image Set

    Directory of Open Access Journals (Sweden)

    Sebastian Vetter

    2011-12-01

    Full Text Available Digital stereo-photogrammetry allows users an automatic evaluation of the spatial dimension and the surface texture of objects. The integration of image analysis techniques simplifies the automation of evaluation of large image sets and offers a high accuracy [1]. Due to the substantial similarities of stereoscopic image pairs, correlation techniques provide measurements of subpixel precision for corresponding image points. With the help of an automated point search algorithm in image sets identical points are used to associate pairs of images to stereo models and group them. The found identical points in all images are basis for calculation of the relative orientation of each stereo model as well as defining the relation of neighboured stereo models. By using proper filter strategies incorrect points are removed and the relative orientation of the stereo model can be made automatically. With the help of 3D-reference points or distances at the object or a defined distance of camera basis the stereo model is orientated absolute. An adapted expansion- and matching algorithm offers the possibility to scan the object surface automatically. The result is a three dimensional point cloud; the scan resolution depends on image quality. With the integration of the iterative closest point- algorithm (ICP these partial point clouds are fitted to a total point cloud. In this way, 3D-reference points are not necessary. With the help of the implemented triangulation algorithm a digital surface models (DSM can be created. The texturing can be made automatically by the usage of the images that were used for scanning the object surface. It is possible to texture the surface model directly or to generate orthophotos automatically. By using of calibrated digital SLR cameras with full frame sensor a high accuracy can be reached. A big advantage is the possibility to control the accuracy and quality of the 3d-objectdocumentation with the resolution of the images. The

  16. 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

  17. Automated measurement of parameters related to the deformities of lower limbs based on x-rays images.

    Science.gov (United States)

    Wojciechowski, Wadim; Molka, Adrian; Tabor, Zbisław

    2016-03-01

    Measurement of the deformation of the lower limbs in the current standard full-limb X-rays images presents significant challenges to radiologists and orthopedists. The precision of these measurements is deteriorated because of inexact positioning of the leg during image acquisition, problems with selecting reliable anatomical landmarks in projective X-ray images, and inevitable errors of manual measurements. The influence of the random errors resulting from the last two factors on the precision of the measurement can be reduced if an automated measurement method is used instead of a manual one. In the paper a framework for an automated measurement of various metric and angular quantities used in the description of the lower extremity deformation in full-limb frontal X-ray images is described. The results of automated measurements are compared with manual measurements. These results demonstrate that an automated method can be a valuable alternative to the manual measurements.

  18. 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.

  19. 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...... source into the proximal ends of the first optical fibers, wherein the first optical coupler comprises a plurality of lens elements including a first lens element and a second lens element, each of the plurality of lens elements comprising a primary surface facing a distal end of the first optical...... coupler, and a secondary surface facing a proximal end of the first optical coupler....

  20. Wavelet Thresholding Techniques in Despeckling of Medical Ultrasound Images

    Directory of Open Access Journals (Sweden)

    R.Vanithamani

    2014-01-01

    Full Text Available This paper presents a review of wavelet thresholding techniques for despeckling of medical ultrasound images. An ultrasound image is first transformed into wavelet domain and then the wavelet coefficients are processed by different wavelet thresholding techniques. The denoised image is obtained by taking the inverse wavelet transform of the modified wavelet coefficients. The performance of the techniques reviewed in this paper is evaluated using the image quality assessment parameters such as Peak Signal to Noise Ratio (PSNR, Edge Preservation Index (EPI and Correlation Coefficient (CoC.The practical implementation of this work is to determine the effective wavelet thresholding technique that compromises between edge preservation and noise suppression.

  1. Medical Image distribution and visualization in a hospital using CORBA.

    Science.gov (United States)

    Moreno, Ramon Alfredo; do Santos, Marcelo; Bertozzo, Nivaldo; de Sa Rebelo, Marina; Furuie, Sergio S; Gutierrez, Marco A

    2008-01-01

    In this work it is presented the solution adopted by the Heart Institute (InCor) of Sao Paulo for medical image distribution and visualization inside the hospital's intranet as part of the PACS system. A CORBA-based image server was developed to distribute DICOM images across the hospital together with the images' report. The solution adopted allows the decoupling of the server implementation and the client. This gives the advantage of reusing the same solution in different implementation sites. Currently, the PACS system is being used on two different hospitals each one with three different environments: development, prototype and production.

  2. 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...... Field H and a 7 MHz, 128-elements, linear array transducer with lambda/2-spacing. MV is compared to the conventional delay-and-sum (DS) beamformer with Boxcar and Hanning weights. Furthermore, the PW images are compared to the a conventional ultrasound image, obtained from a linear scan sequence...

  3. Principles of medical imaging with emphasis on tomography

    International Nuclear Information System (INIS)

    Medical imaging with ionizing and non-ionizing radiations belongs to the class of problems known as indirect sensing. This article is concerned with imaging methods known as image reconstruction from projections or computerized tomography. A brief comparative study of the theory is presented. Depending on the nature and modes of propagation of the employed radiation, methods are discussed either under transmission tomography (with gamma rays and X rays) or emission tomography (with gamma rays and positrons). Magnetic resonance Imaging (MRI) is described as resonant absorption and re-emission of radiofrequency energy. (author)

  4. Comment on "Perspectives of medical X-ray imaging"

    CERN Document Server

    Taibi, A; Tuffanelli, A; Gambaccini, M

    2002-01-01

    In the paper 'Perspectives of medical X-ray imaging' (Nucl. Instr. and Meth. A 466 (2001) 99) the infer, from simple approximations, that the use of HOPG monochromator has no advantage in mammography compared to existing systems. We show that in order to compare imaging properties of different X-ray sources it is necessary to evaluate the spectra after the attenuation of the tissue to be imaged. Indeed, quasi-monochromatic X-ray sources have the potential to enhance image contrast and to reduce patient dose.

  5. Automated volume of interest delineation and rendering of cone beam CT images in interventional cardiology

    Science.gov (United States)

    Lorenz, Cristian; Schäfer, Dirk; Eshuis, Peter; Carroll, John; Grass, Michael

    2012-02-01

    Interventional C-arm systems allow the efficient acquisition of 3D cone beam CT images. They can be used for intervention planning, navigation, and outcome assessment. We present a fast and completely automated volume of interest (VOI) delineation for cardiac interventions, covering the whole visceral cavity including mediastinum and lungs but leaving out rib-cage and spine. The problem is addressed in a model based approach. The procedure has been evaluated on 22 patient cases and achieves an average surface error below 2mm. The method is able to cope with varying image intensities, varying truncations due to the limited reconstruction volume, and partially with heavy metal and motion artifacts.

  6. Semi-automated Digital Imaging and Processing System for Measuring Lake Ice Thickness

    Science.gov (United States)

    Singh, Preetpal

    Canada is home to thousands of freshwater lakes and rivers. Apart from being sources of infinite natural beauty, rivers and lakes are an important source of water, food and transportation. The northern hemisphere of Canada experiences extreme cold temperatures in the winter resulting in a freeze up of regional lakes and rivers. Frozen lakes and rivers tend to offer unique opportunities in terms of wildlife harvesting and winter transportation. Ice roads built on frozen rivers and lakes are vital supply lines for industrial operations in the remote north. Monitoring the ice freeze-up and break-up dates annually can help predict regional climatic changes. Lake ice impacts a variety of physical, ecological and economic processes. The construction and maintenance of a winter road can cost millions of dollars annually. A good understanding of ice mechanics is required to build and deem an ice road safe. A crucial factor in calculating load bearing capacity of ice sheets is the thickness of ice. Construction costs are mainly attributed to producing and maintaining a specific thickness and density of ice that can support different loads. Climate change is leading to warmer temperatures causing the ice to thin faster. At a certain point, a winter road may not be thick enough to support travel and transportation. There is considerable interest in monitoring winter road conditions given the high construction and maintenance costs involved. Remote sensing technologies such as Synthetic Aperture Radar have been successfully utilized to study the extent of ice covers and record freeze-up and break-up dates of ice on lakes and rivers across the north. Ice road builders often used Ultrasound equipment to measure ice thickness. However, an automated monitoring system, based on machine vision and image processing technology, which can measure ice thickness on lakes has not been thought of. Machine vision and image processing techniques have successfully been used in manufacturing

  7. Quality Control in Automated Manufacturing Processes – Combined Features for Image Processing

    Directory of Open Access Journals (Sweden)

    B. Kuhlenkötter

    2006-01-01

    Full Text Available In production processes the use of image processing systems is widespread. Hardware solutions and cameras respectively are available for nearly every application. One important challenge of image processing systems is the development and selection of appropriate algorithms and software solutions in order to realise ambitious quality control for production processes. This article characterises the development of innovative software by combining features for an automatic defect classification on product surfaces. The artificial intelligent method Support Vector Machine (SVM is used to execute the classification task according to the combined features. This software is one crucial element for the automation of a manually operated production process. 

  8. Medical image of the week: expiratory imaging accentuates mosaic attenuation

    OpenAIRE

    Arteaga VA; Knox KS

    2013-01-01

    A 66 year old female presented with cough, fever and marked shortness of breath. Infectious work up was found to be negative. An inspiratory high resolution thoracic CT (HRCT) image (A) shows faint groundglass and mosaic lung attenuation with subtle centrilobular ill-defined nodules. However, an image obtained on expiration (B) shows more obvious mosaic attenuation which suggesting air-trapping. Due to progressive dyspnea, a lung biopsy was performed and revealed a bronchiolocentric cellu...

  9. Automation of Axisymmetric Drop Shape Analysis Using Digital Image Processing

    Science.gov (United States)

    Cheng, Philip Wing Ping

    The Axisymmetric Drop Shape Analysis - Profile (ADSA-P) technique, as initiated by Rotenberg, is a user -oriented scheme to determine liquid-fluid interfacial tensions and contact angles from the shape of axisymmetric menisci, i.e., from sessile as well as pendant drops. The ADSA -P program requires as input several coordinate points along the drop profile, the value of the density difference between the bulk phases, and gravity. The solution yields interfacial tension and contact angle. Although the ADSA-P technique was in principle complete, it was found that it was of very limited practical use. The major difficulty with the method is the need for very precise coordinate points along the drop profile, which, up to now, could not be obtained readily. In the past, the coordinate points along the drop profile were obtained by manual digitization of photographs or negatives. From manual digitization data, the surface tension values obtained had an average error of +/-5% when compared with literature values. Another problem with the ADSA-P technique was that the computer program failed to converge for the case of very elongated pendant drops. To acquire the drop profile coordinates automatically, a technique which utilizes recent developments in digital image acquisition and analysis was developed. In order to determine the drop profile coordinates as precisely as possible, the errors due to optical distortions were eliminated. In addition, determination of drop profile coordinates to pixel and sub-pixel resolution was developed. It was found that high precision could be obtained through the use of sub-pixel resolution and a spline fitting method. The results obtained using the automatic digitization technique in conjunction with ADSA-P not only compared well with the conventional methods, but also outstripped the precision of conventional methods considerably. To solve the convergence problem of very elongated pendant drops, it was found that the reason for the

  10. Medical Imaging Image Quality Assessment with Monte Carlo Methods

    Science.gov (United States)

    Michail, C. M.; Karpetas, G. E.; Fountos, G. P.; Kalyvas, N. I.; Martini, Niki; Koukou, Vaia; Valais, I. G.; Kandarakis, I. S.

    2015-09-01

    The aim of the present study was to assess image quality of PET scanners through a thin layer chromatography (TLC) plane source. The source was simulated using a previously validated Monte Carlo model. The model was developed by using the GATE MC package and reconstructed images obtained with the STIR software for tomographic image reconstruction, with cluster computing. The PET scanner simulated in this study was the GE DiscoveryST. A plane source consisted of a TLC plate, was simulated by a layer of silica gel on aluminum (Al) foil substrates, immersed in 18F-FDG bath solution (1MBq). Image quality was assessed in terms of the Modulation Transfer Function (MTF). MTF curves were estimated from transverse reconstructed images of the plane source. Images were reconstructed by the maximum likelihood estimation (MLE)-OSMAPOSL algorithm. OSMAPOSL reconstruction was assessed by using various subsets (3 to 21) and iterations (1 to 20), as well as by using various beta (hyper) parameter values. MTF values were found to increase up to the 12th iteration whereas remain almost constant thereafter. MTF improves by using lower beta values. The simulated PET evaluation method based on the TLC plane source can be also useful in research for the further development of PET and SPECT scanners though GATE simulations.

  11. Medical image of the week: sarcoidosis

    Directory of Open Access Journals (Sweden)

    Knox KS

    2013-02-01

    Full Text Available A 42 year old African-American man from Indianapolis presented with cough and skin lesions. ACE level was elevated at 86 μg/L. Spirometry was normal except for a diffusing capacity 52% of predicted. Imaging was suggestive of sarcoidosis versus granulomatous infection. Bronchoscopy with bronchoalveolar lavage cytospin revealed a lymphocytic alveolitis (27% lymphocytes with a CD4:CD8 ratio of 6.2:1 by flow cytometry. Biopsy showed classic noncaseating granulomas and no organisms supporting the diagnosis of sarcoidosis. The patient’s symptoms and radiographic findings improved with 20 mg prednisone every other day for 3 months duration.

  12. 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.

  13. Establishing advanced practice for medical imaging in New Zealand

    International Nuclear Information System (INIS)

    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

  14. Contourlet Transform Based Method For Medical Image Denoising

    Directory of Open Access Journals (Sweden)

    Abbas H. Hassin AlAsadi

    2015-02-01

    Full Text Available Noise is an important factor of the medical image quality, because the high noise of medical imaging will not give us the useful information of the medical diagnosis. Basically, medical diagnosis is based on normal or abnormal information provided diagnose conclusion. In this paper, we proposed a denoising algorithm based on Contourlet transform for medical images. Contourlet transform is an extension of the wavelet transform in two dimensions using the multiscale and directional filter banks. The Contourlet transform has the advantages of multiscale and time-frequency-localization properties of wavelets, but also provides a high degree of directionality. For verifying the denoising performance of the Contourlet transform, two kinds of noise are added into our samples; Gaussian noise and speckle noise. Soft thresholding value for the Contourlet coefficients of noisy image is computed. Finally, the experimental results of proposed algorithm are compared with the results of wavelet transform. We found that the proposed algorithm has achieved acceptable results compared with those achieved by wavelet transform.

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

    International Nuclear Information System (INIS)

    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

  16. Automated reconstruction of standing posture panoramas from multi-sector long limb x-ray images

    Science.gov (United States)

    Miller, Linzey; Trier, Caroline; Ben-Zikri, Yehuda K.; Linte, Cristian A.

    2016-03-01

    Due to the digital X-ray imaging system's limited field of view, several individual sector images are required to capture the posture of an individual in standing position. These images are then "stitched together" to reconstruct the standing posture. We have created an image processing application that automates the stitching, therefore minimizing user input, optimizing workflow, and reducing human error. The application begins with pre-processing the input images by removing artifacts, filtering out isolated noisy regions, and amplifying a seamless bone edge. The resulting binary images are then registered together using a rigid-body intensity based registration algorithm. The identified registration transformations are then used to map the original sector images into the panorama image. Our method focuses primarily on the use of the anatomical content of the images to generate the panoramas as opposed to using external markers employed to aid with the alignment process. Currently, results show robust edge detection prior to registration and we have tested our approach by comparing the resulting automatically-stitched panoramas to the manually stitched panoramas in terms of registration parameters, target registration error of homologous markers, and the homogeneity of the digitally subtracted automatically- and manually-stitched images using 26 patient datasets.

  17. A Spiral And Discipline-Oriented Curriculum In Medical Imaging

    DEFF Research Database (Denmark)

    Wilhjelm, Jens E.; Hanson, Lars G.; Henneberg, Kaj-Åge;

    2011-01-01

    This contribution describes and evaluates an experimental combination of a spiral and discipline-oriented curriculum implemented in the bachelor’s and master’s program in Medicine and Technology. The implementation in the master’s program is in the form of a study line in Medical Imaging and Radi......This contribution describes and evaluates an experimental combination of a spiral and discipline-oriented curriculum implemented in the bachelor’s and master’s program in Medicine and Technology. The implementation in the master’s program is in the form of a study line in Medical Imaging...

  18. Software Agent with Reinforcement Learning Approach for Medical Image Segmentation

    Institute of Scientific and Technical Information of China (English)

    Mahsa Chitsaz; Chaw Seng Woo

    2011-01-01

    Many image segmentation solutions are problem-based. Medical images have very similar grey level and texture among the interested objects. Therefore, medical image segmentation requires improvements although there have been researches done since the last few decades. We design a self-learning framework to extract several objects of interest simultaneously from Computed Tomography (CT) images. Our segmentation method has a learning phase that is based on reinforcement learning (RL) system. Each RL agent works on a particular sub-image of an input image to find a suitable value for each object in it. The RL system is define by state, action and reward. We defined some actions for each state in the sub-image. A reward function computes reward for each action of the RL agent. Finally, the valuable information, from discovering all states of the interest objects, will be stored in a Q-matrix and the final result can be applied in segmentation of similar images. The experimental results for cranial CT images demonstrated segmentation accuracy above 95%.

  19. Medical Image Classification Using Genetic Optimized Elman Network

    Directory of Open Access Journals (Sweden)

    T. Baranidharan

    2012-01-01

    Full Text Available Problem statement: Advancements in the internet and digital images have resulted in a huge database of images. Most of the current search engines found in the web depends only on images that can be retrieved using metadata, which generates a lot of unwanted results in the results got. Content-Based Image Retrieval (CBIR system is the utilization of computer vision techniques in the predicament of image retrieval. In other words, it is used for searching and retrieving of the right digital image among a huge database using query image. CBIR finds extensive applications in the field of medicine as it helps medical professionals in diagnosis and plan treatment. Approach: Various methods have been proposed for CBIR using the images low level features like histogram, color, texture and shape. Similarly various classification algorithms like Naive Bayes classifier, Support Vector Machine, Decision tree induction algorithms and Neural Network based classifiers have been studied extensively. In this study it is proposed to extract global features using Hilbert Transform (HT, select features based on the correlation of the extracted vectors with respect to the class label and propose a enhanced Elman Neural Network Genetic Algorithm Optimized Elman (GAOE Neural Network. Results and Conclusion: The proposed method for feature extraction and the classification algorithm was tested on a dataset consisting of 180 medical images. The classification accuracy of 92.22% was obtained in the proposed method.

  20. Directive Antenna for Ultrawideband Medical Imaging Systems

    Directory of Open Access Journals (Sweden)

    Amin M. Abbosh

    2008-01-01

    Full Text Available A compact and directive ultrawideband antenna is presented in this paper. The antenna is in the form of an antipodal tapered slot with resistive layers to improve its directivity and to reduce its backward radiation. The antenna operates over the frequency band from 3.1 GHz to more than 10.6 GHz. It features a directive radiation with a peak gain which is between 4 dBi and 11 dBi in the specified band. The time domain performance of the antenna shows negligible distortion. This makes it suitable for the imaging systems which require a very short pulse for transmission/reception. The effect of the multilayer human body on the performance of the antenna is also studied. The breast model is used for this purpose. It is shown that the antenna has more than 90% fidelity factor when it works in free space, whereas the fidelity factor decreases as the signal propagates inside the human body. However, even inside the human body, the fidelity factor is still larger than 70% revealing the possibility of using the proposed antenna in biomedical imaging systems.

  1. Sfm_georef: Automating image measurement of ground control points for SfM-based projects

    Science.gov (United States)

    James, Mike R.

    2016-04-01

    Deriving accurate DEM and orthomosaic image products from UAV surveys generally involves the use of multiple ground control points (GCPs). Here, we demonstrate the automated collection of GCP image measurements for SfM-MVS processed projects, using sfm_georef software (James & Robson, 2012; http://www.lancaster.ac.uk/staff/jamesm/software/sfm_georef.htm). Sfm_georef was originally written to provide geo-referencing procedures for SfM-MVS projects. It has now been upgraded with a 3-D patch-based matching routine suitable for automating GCP image measurement in both aerial and ground-based (oblique) projects, with the aim of reducing the time required for accurate geo-referencing. Sfm_georef is compatible with a range of SfM-MVS software and imports the relevant files that describe the image network, including camera models and tie points. 3-D survey measurements of ground control are then provided, either for natural features or artificial targets distributed over the project area. Automated GCP image measurement is manually initiated through identifying a GCP position in an image by mouse click; the GCP is then represented by a square planar patch in 3-D, textured from the image and oriented parallel to the local topographic surface (as defined by the 3-D positions of nearby tie points). Other images are then automatically examined by projecting the patch into the images (to account for differences in viewing geometry) and carrying out a sub-pixel normalised cross-correlation search in the local area. With two or more observations of a GCP, its 3-D co-ordinates are then derived by ray intersection. With the 3-D positions of three or more GCPs identified, an initial geo-referencing transform can be derived to relate the SfM-MVS co-ordinate system to that of the GCPs. Then, if GCPs are symmetric and identical, image texture from one representative GCP can be used to search automatically for all others throughout the image set. Finally, the GCP observations can be

  2. ATOM - an OMERO add-on for automated import of image data

    Directory of Open Access Journals (Sweden)

    Lipp Peter

    2011-10-01

    Full Text Available Abstract Background Modern microscope platforms are able to generate multiple gigabytes of image data in a single experimental session. In a routine research laboratory workflow, these data are initially stored on the local acquisition computer from which files need to be transferred to the experimenter's (remote image repository (e.g., DVDs, portable hard discs or server-based storage because of limited local data storage. Although manual solutions for this migration, such as OMERO - a client-server software for visualising and managing large amounts of image data - exist, this import process may be a time-consuming and tedious task. Findings We have developed ATOM, a Java-based and thus platform-independent add-on for OMERO enabling automated transfer of image data from a wide variety of acquisition software packages into OMERO. ATOM provides a graphical user interface and allows pre-organisation of experimental data for the transfer. Conclusions ATOM is a convenient extension of the OMERO software system. An automated interface to OMERO will be a useful tool for scientists working with file formats supported by the Bio-Formats file format library, a platform-independent library for reading the most common file formats of microscope images.

  3. Towards Automated Three-Dimensional Tracking of Nephrons through Stacked Histological Image Sets.

    Science.gov (United States)

    Bhikha, Charita; Andreasen, Arne; Christensen, Erik I; Letts, Robyn F R; Pantanowitz, Adam; Rubin, David M; Thomsen, Jesper S; Zhai, Xiao-Yue

    2015-01-01

    An automated approach for tracking individual nephrons through three-dimensional histological image sets of mouse and rat kidneys is presented. In a previous study, the available images were tracked manually through the image sets in order to explore renal microarchitecture. The purpose of the current research is to reduce the time and effort required to manually trace nephrons by creating an automated, intelligent system as a standard tool for such datasets. The algorithm is robust enough to isolate closely packed nephrons and track their convoluted paths despite a number of nonideal, interfering conditions such as local image distortions, artefacts, and interstitial tissue interference. The system comprises image preprocessing, feature extraction, and a custom graph-based tracking algorithm, which is validated by a rule base and a machine learning algorithm. A study of a selection of automatically tracked nephrons, when compared with manual tracking, yields a 95% tracking accuracy for structures in the cortex, while those in the medulla have lower accuracy due to narrower diameter and higher density. Limited manual intervention is introduced to improve tracking, enabling full nephron paths to be obtained with an average of 17 manual corrections per mouse nephron and 58 manual corrections per rat nephron.

  4. Towards Automated Three-Dimensional Tracking of Nephrons through Stacked Histological Image Sets

    Directory of Open Access Journals (Sweden)

    Charita Bhikha

    2015-01-01

    Full Text Available An automated approach for tracking individual nephrons through three-dimensional histological image sets of mouse and rat kidneys is presented. In a previous study, the available images were tracked manually through the image sets in order to explore renal microarchitecture. The purpose of the current research is to reduce the time and effort required to manually trace nephrons by creating an automated, intelligent system as a standard tool for such datasets. The algorithm is robust enough to isolate closely packed nephrons and track their convoluted paths despite a number of nonideal, interfering conditions such as local image distortions, artefacts, and interstitial tissue interference. The system comprises image preprocessing, feature extraction, and a custom graph-based tracking algorithm, which is validated by a rule base and a machine learning algorithm. A study of a selection of automatically tracked nephrons, when compared with manual tracking, yields a 95% tracking accuracy for structures in the cortex, while those in the medulla have lower accuracy due to narrower diameter and higher density. Limited manual intervention is introduced to improve tracking, enabling full nephron paths to be obtained with an average of 17 manual corrections per mouse nephron and 58 manual corrections per rat nephron.

  5. 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.

  6. Infrared medical image visualization and anomalies analysis method

    Science.gov (United States)

    Gong, Jing; Chen, Zhong; Fan, Jing; Yan, Liang

    2015-12-01

    Infrared medical examination finds the diseases through scanning the overall human body temperature and obtaining the temperature anomalies of the corresponding parts with the infrared thermal equipment. In order to obtain the temperature anomalies and disease parts, Infrared Medical Image Visualization and Anomalies Analysis Method is proposed in this paper. Firstly, visualize the original data into a single channel gray image: secondly, turn the normalized gray image into a pseudo color image; thirdly, a method of background segmentation is taken to filter out background noise; fourthly, cluster those special pixels with the breadth-first search algorithm; lastly, mark the regions of the temperature anomalies or disease parts. The test is shown that it's an efficient and accurate way to intuitively analyze and diagnose body disease parts through the temperature anomalies.

  7. Transmission and storage of medical images with patient information.

    Science.gov (United States)

    Acharya U, Rajendra; Subbanna Bhat, P; Kumar, Sathish; Min, Lim Choo

    2003-07-01

    Digital watermarking is a technique of hiding specific identification data for copyright authentication. This technique is adapted here for interleaving patient information with medical images, to reduce storage and transmission overheads. The text data is encrypted before interleaving with images to ensure greater security. The graphical signals are interleaved with the image. Two types of error control-coding techniques are proposed to enhance reliability of transmission and storage of medical images interleaved with patient information. Transmission and storage scenarios are simulated with and without error control coding and a qualitative as well as quantitative interpretation of the reliability enhancement resulting from the use of various commonly used error control codes such as repetitive, and (7,4) Hamming code is provided.

  8. Spatial Information Based Medical Image Registration using Mutual Information

    Directory of Open Access Journals (Sweden)

    Benzheng Wei

    2011-06-01

    Full Text Available Image registration is a valuable technique for medical diagnosis and treatment. Due to the inferiority of image registration using maximum mutual information, a new hybrid method of multimodality medical image registration based on mutual information of spatial information is proposed. The new measure that combines mutual information, spatial information and feature characteristics, is proposed. Edge points are used as features, obtained from a morphology gradient detector. Feature characteristics like location, edge strength and orientation are taken into account to compute a joint probability distribution of corresponding edge points in two images. Mutual information based on this function is minimized to find the best alignment parameters. Finally, the translation parameters are calculated by using a modified Particle Swarm Optimization (MPSO algorithm. The experimental results demonstrate the effectiveness of the proposed registration scheme.

  9. Novel medical imaging technologies for disease diagnosis and treatment

    Science.gov (United States)

    Olego, Diego

    2009-03-01

    New clinical approaches for disease diagnosis, treatment and monitoring will rely on the ability of simultaneously obtaining anatomical, functional and biological information. Medical imaging technologies in combination with targeted contrast agents play a key role in delivering with ever increasing temporal and spatial resolution structural and functional information about conditions and pathologies in cardiology, oncology and neurology fields among others. This presentation will review the clinical motivations and physics challenges in on-going developments of new medical imaging techniques and the associated contrast agents. Examples to be discussed are: *The enrichment of computer tomography with spectral sensitivity for the diagnosis of vulnerable sclerotic plaque. *Time of flight positron emission tomography for improved resolution in metabolic characterization of pathologies. *Magnetic particle imaging -a novel imaging modality based on in-vivo measurement of the local concentration of iron oxide nano-particles - for blood perfusion measurement with better sensitivity, spatial resolution and 3D real time acquisition. *Focused ultrasound for therapy delivery.

  10. Medical image of the week: cutaenous coccidioidomycosis

    Directory of Open Access Journals (Sweden)

    Beatty N

    2015-11-01

    Full Text Available No abstract available. Article truncated at 150 words. A 46-year-old Hispanic man with no known past medical history presents to his primary care physician for a progressively worsening “rash” located over his right thigh. Patient described the lesion as raised, scaly, and itchy. It has been “growing” for the past one year and started out as a small “pimple”. Patient denied any trauma to the effected region over this time period. Surgical history was significant for a splenectomy 15 years prior that was needed after a traumatic accident. He works in construction and lives in southern Arizona. He denied alcohol, tobacco and or illicit drug use. Patient has attempted to treat this skin lesion with over the counter hydrocortisone ointment with no relief. He denied any other associated symptoms including fever/chills, headache, vision changes, night sweats, weight loss, cough, shortness of breath, and or joint pains. Vital signs were stable upon presentation. Physical exam was entirely benign other ...

  11. Medical image of the week: lung entrapment

    Directory of Open Access Journals (Sweden)

    Natt B

    2016-07-01

    Full Text Available No abstract available. Article truncated at 150 words. A 74-year-old woman with a history of breast cancer 10 years ago treated with lumpectomy and radiation presented for evaluation of shortness of breath. She was diagnosed with left sided pleural effusion which was recurrent requiring multiple thoracenteses. There was increased pleural fludeoxyglucose (FDG uptake on PET-CT indicative of recurrent metastatic disease. She underwent a medical pleuroscopy since the pleural effusion analysis did not reveal malignant cells although the suspicion was high and tunneled pleural catheter placement as adjuvant chemotherapy was initiated. Figure 1 shows a pleurscopic view of the collapsed left lung and the effusion in the left hemi thorax. Figure 2 shows extensive involvement of the visceral pleura with metastatic disease preventing complete lung inflation. Figure 3 shows persistent pneumothorax-ex-vacuo despite pleural catheter placement confirming the diagnosis of entrapment. Incomplete lung inflation can be due to pleural disease, endobronchial lesions or chronic telecasts. Lung entrapment and trapped lung ...

  12. Medical image of the week: acute epiglottitis

    Directory of Open Access Journals (Sweden)

    Desai C

    2013-09-01

    Full Text Available No abstract available. Article truncated after 150 words. A 24 year old man without a significant past medical history presented with a 3 day history of sore throat, fever and less than 24 hour history of pain with breathing and swallowing secretions. He was intubated using fiberoptic nasopharyngoscopy in the emergency department due to stridor with a 6.0 mm endotracheal tube until successfully extubated five days later. Initially he was treated with broad spectrum antibiotics and methylprednisolone 40 mg intravenously every 12 hours. A CT scan of the neck did not show an epiglottic abscess. Acute epiglottitis in adults appears to have a rising incidence with an associated mortality of 7% that is related to Haemophilus influenzae type b, as well as other miscellaneous pathogens, mechanical injury or smoke inhalation. Risk factors associated with obstruction are drooling, rapid onset of symptoms, evidence of abscess formation and a history of diabetes mellitus. Epiglottic abscess is infrequent sequelae of acute …

  13. Medical image of the week: phytobezoar

    Directory of Open Access Journals (Sweden)

    Hansra A

    2016-01-01

    Full Text Available No abstract available. Article truncated after 150 words. A 10-year-old boy with a history of non-verbal autism presented to the hospital with symptoms of chronic malnourishment. He was recently started on a specific carbohydrate rich diet, as outlined by a popular mainstream nutrition book, with hopes of improvement in adverse behavior. Prior to the start of this new diet, he consistently demonstrated an increased craving for food and was described to have an insatiable appetite. Though he was relatively non-verbal at baseline, he intermittently voiced his hunger and associated abdominal pain. A supine abdominal radiograph obtained immediately after admission showed a moderate gastric distension with a significant stool burden. Follow-up radiographs of the abdomen were obtained after two days of medical attempts to clear out the gastrointestinal system. The supine frontal radiograph at this time showed a massively distended stomach with a mottled appearance and considerable mass effect on the transverse colon (Figure 1. The interpreting pediatric radiologist ...

  14. Medical image of the week: renal infarction

    Directory of Open Access Journals (Sweden)

    August J

    2015-04-01

    Full Text Available No abstract available. Article truncated at 150 words. A 79-year-old woman with past medical history of persistent atrial fibrillation not on anticoagulation, coronary artery disease, hypertension, diabetes, and hyperlipidemia presented with right flank pain accompanied by nausea and vomiting for two days. Laboratory studies showed leukocytosis with creatinine of 1.2. Urinalysis was negative for signs of infection and red blood cells. However, despite being on analgesic, she continued to have flank pain. The patient subsequent underwent CT scan of the abdomen and pelvis the next day, which showed that the majority of the right kidney was infarcted. Interestingly, there were two right-sided renal arteries and a thrombus was seen in the inferior main right renal artery. The superior pole of the right kidney was preserved as a result of the patent accessory renal artery. Due to delayed presentation of more than 48 hours after onset of pain, the tissue could not be re-vascularized by vascular surgery. Her renal ...

  15. Medical image of the week: panloubular emphysema

    Directory of Open Access Journals (Sweden)

    Mathur A

    2015-08-01

    Full Text Available No abstract available. Article truncated after 150 words. A 60 year old female, non-smoker with a past medical history of chronic rhinosinusitis with nasal polyps presented with an eight year history of productive cough and dyspnea. Previous treatment with inhaled corticosteroids, courses of systemic corticosteroids and antibiotics provided modest improvement in her symptoms. Pulmonary function testing revealed a severe obstructive ventilatory defect without significant bronchodilator response and reduced diffusing capacity (DLCO. Chest x-ray surprisingly revealed lower lobe predominant emphysematous changes (Figure 1. Alpha-1-antitrypsin level was within normal range at 137 mg/dL. Panlobular emphysema represents permanent destruction of the entire acinus distal to the respiratory bronchioles and is more likely to affect the lower lobes compared to centrilobular emphysema (1. Panlobular emphysema is associated with alpha-1-antitrypsin deficiency, intravenous drug abuse specifically with methylphenidate and methadone, Swyer-James syndrome, and obliterative bronchiolitis. Whether this pattern is seen as part of normal senescence in non-smoking individuals remains controversial (2. Panlobular emphysema may ...

  16. Medical image of the week: Pancoast tumor

    Directory of Open Access Journals (Sweden)

    Des Champs E

    2015-08-01

    Full Text Available No abstract available. Article truncated at 150 words. A 39 year-old man presented to the Emergency Department with right shoulder, back and abdominal pain. He had no significant medical problems except for a 20 pack-year history of smoking. Laboratory work and an abdominal ultrasound were unremarkable and he was discharged. Approximately one week later he returned to the Emergency Department with persistent right shoulder and back pain and mild numbness and tingling of the second, third and fourth digits of his right hand. He also described weakness of his right upper eyelid and noticed he was sweating only on the left side of his face. On physical exam, anisocoria was noted with the right pupil being smaller than the left pupil. A chest x-ray and right shoulder x-ray revealed extensive pleural and parenchymal mass in the right apex and tracheal deviation to the left (Figures 1 and 2. A CT chest with contrast showed findings consistent with extensive ...

  17. Medical image of the week: bronchopleural fistula

    Directory of Open Access Journals (Sweden)

    Desai H

    2016-09-01

    Full Text Available No abstract available. Article truncated at 150 words. A 58-year-old man with past medical history significant for chronic smoking and seizures was referred to the emergency room after a chest x-ray done by his primary care physician for evaluation of cough showed a hydropneumothorax. His symptoms included dry cough for past 2 months without fever, chills or other associated symptoms. He did not have any thoracic procedures performed and had no past history of recurrent infections. He was hemodynamically stable. Physical examination was only significant with decreased breath sounds on the right side of the chest. Thoracic CT with contrast was performed which showed complete collapse of the right lower lobe, near complete collapse of right middle lobe as well as an air-fluid level. There was a suspicion of a direct communication between bronchi and pleural space at the posterior lateral margin of the collapsed right lower lobe (Figure 1. The presence of bronchopleural fistula (BPF was confirmed ...

  18. Medical image of the week: splenic infarction

    Directory of Open Access Journals (Sweden)

    Casey DJ

    2016-08-01

    Full Text Available No abstract available. Article truncated after 150 words. A 52-year-old Hispanic woman with a past medical history significant for Type 1 Diabetes Mellitus, hypertension, and rheumatoid arthritis presented with left upper quadrant pain for one day. Her review of systems was positive for bloating, severe epigastric and left upper quadrant tenderness that radiated to the back and left shoulder, nausea with non-bilious emesis, and diarrhea for one day prior to admission. Physical exam only revealed epigastric and left upper quadrant tenderness to light palpation without rebound or guarding. Abdominal computed tomography of the abdomen demonstrated a new acute or subacute splenic infarct with no clear evidence of an embolic source in the abdomen or pelvis (Figure 1. Echocardiogram with bubble study and contrast did not demonstrate valve abnormalities, cardiac mass, vegetation, valve or wall motion abnormalities and no evidence of patent foramen ovale. Splenic infarction should be suspected when patients present with sharp, acute left upper quadrant pain ...

  19. Medical image of the week: eosphageal perforation

    Directory of Open Access Journals (Sweden)

    Bilal J

    2015-04-01

    Full Text Available No abstract available. Article truncated after 150 words. A 74 year old man with a past medical history of esophageal strictures status post dilatation, coronary artery disease status post CABG, and atrial fibrillation presented to hospital with complaints of severe chest pain that began after the consumption of tortilla chips one hour prior to presentation. Electrocardiogram and cardiac enzymes were not consistent with acute coronary syndrome. Chest X-ray was consistent with a widened mediastinal silhouette. Contrast esophogram was negative for extra luminal extravasation. CT scan of the chest with oral contrast demonstrated thickening of the mid-thoracic esophagus with an extra-luminal focus of gas in the mediastinum along with fluid along the inferior aspect of the esophagus (Figures 1 and 2. These findings were concerning for esophageal perforation. The patient was taken to the operating room for endoscopy which showed micro perforation in mid-esophagus. Esophageal perforation remains a highly morbid condition. Mortality rates are based predominantly on time of ...

  20. Medical image of the week: expiratory imaging accentuates mosaic attenuation

    Directory of Open Access Journals (Sweden)

    Arteaga VA

    2013-05-01

    Full Text Available A 66 year old female presented with cough, fever and marked shortness of breath. Infectious work up was found to be negative. An inspiratory high resolution thoracic CT (HRCT image (A shows faint groundglass and mosaic lung attenuation with subtle centrilobular ill-defined nodules. However, an image obtained on expiration (B shows more obvious mosaic attenuation which suggesting air-trapping. Due to progressive dyspnea, a lung biopsy was performed and revealed a bronchiolocentric cellular interstitial pneumonia with non-caseating granuloma consistent with subacute hypersensitivity pneumonitis.

  1. An Automated and Intelligent Medical Decision Support System for Brain MRI Scans Classification.

    Directory of Open Access Journals (Sweden)

    Muhammad Faisal Siddiqui

    Full Text Available A wide interest has been observed in the medical health care applications that interpret neuroimaging scans by machine learning systems. This research proposes an intelligent, automatic, accurate, and robust classification technique to classify the human brain magnetic resonance image (MRI as normal or abnormal, to cater down the human error during identifying the diseases in brain MRIs. In this study, fast discrete wavelet transform (DWT, principal component analysis (PCA, and least squares support vector machine (LS-SVM are used as basic components. Firstly, fast DWT is employed to extract the salient features of brain MRI, followed by PCA, which reduces the dimensions of the features. These reduced feature vectors also shrink the memory storage consumption by 99.5%. At last, an advanced classification technique based on LS-SVM is applied to brain MR image classification using reduced features. For improving the efficiency, LS-SVM is used with non-linear radial basis function (RBF kernel. The proposed algorithm intelligently determines the optimized values of the hyper-parameters of the RBF kernel and also applied k-fold stratified cross validation to enhance the generalization of the system. The method was tested by 340 patients' benchmark datasets of T1-weighted and T2-weighted scans. From the analysis of experimental results and performance comparisons, it is observed that the proposed medical decision support system outperformed all other modern classifiers and achieves 100% accuracy rate (specificity/sensitivity 100%/100%. Furthermore, in terms of computation time, the proposed technique is significantly faster than the recent well-known methods, and it improves the efficiency by 71%, 3%, and 4% on feature extraction stage, feature reduction stage, and classification stage, respectively. These results indicate that the proposed well-trained machine learning system has the potential to make accurate predictions about brain abnormalities

  2. An Automated and Intelligent Medical Decision Support System for Brain MRI Scans Classification.

    Science.gov (United States)

    Siddiqui, Muhammad Faisal; Reza, Ahmed Wasif; Kanesan, Jeevan

    2015-01-01

    A wide interest has been observed in the medical health care applications that interpret neuroimaging scans by machine learning systems. This research proposes an intelligent, automatic, accurate, and robust classification technique to classify the human brain magnetic resonance image (MRI) as normal or abnormal, to cater down the human error during identifying the diseases in brain MRIs. In this study, fast discrete wavelet transform (DWT), principal component analysis (PCA), and least squares support vector machine (LS-SVM) are used as basic components. Firstly, fast DWT is employed to extract the salient features of brain MRI, followed by PCA, which reduces the dimensions of the features. These reduced feature vectors also shrink the memory storage consumption by 99.5%. At last, an advanced classification technique based on LS-SVM is applied to brain MR image classification using reduced features. For improving the efficiency, LS-SVM is used with non-linear radial basis function (RBF) kernel. The proposed algorithm intelligently determines the optimized values of the hyper-parameters of the RBF kernel and also applied k-fold stratified cross validation to enhance the generalization of the system. The method was tested by 340 patients' benchmark datasets of T1-weighted and T2-weighted scans. From the analysis of experimental results and performance comparisons, it is observed that the proposed medical decision support system outperformed all other modern classifiers and achieves 100% accuracy rate (specificity/sensitivity 100%/100%). Furthermore, in terms of computation time, the proposed technique is significantly faster than the recent well-known methods, and it improves the efficiency by 71%, 3%, and 4% on feature extraction stage, feature reduction stage, and classification stage, respectively. These results indicate that the proposed well-trained machine learning system has the potential to make accurate predictions about brain abnormalities from the

  3. A Review of Fully Automated Techniques for Brain Tumor Detection From MR Images

    Directory of Open Access Journals (Sweden)

    Anjum Hayat Gondal

    2013-02-01

    Full Text Available Radiologists use medical images to diagnose diseases precisely. However, identification of brain tumor from medical images is still a critical and complicated job for a radiologist. Brain tumor identification form magnetic resonance imaging (MRI consists of several stages. Segmentation is known to be an essential step in medical imaging classification and analysis. Performing the brain MR images segmentation manually is a difficult task as there are several challenges associated with it. Radiologist and medical experts spend plenty of time for manually segmenting brain MR images, and this is a non-repeatable task. In view of this, an automatic segmentation of brain MR images is needed to correctly segment White Matter (WM, Gray Matter (GM and Cerebrospinal Fluid (CSF tissues of brain in a shorter span of time. The accurate segmentation is crucial as otherwise the wrong identification of disease can lead to severe consequences. Taking into account the aforesaid challenges, this research is focused towards highlighting the strengths and limitations of the earlier proposed segmentation techniques discussed in the contemporary literature. Besides summarizing the literature, the paper also provides a critical evaluation of the surveyed literature which reveals new facets of research. However, articulating a new technique is beyond the scope of this paper.

  4. Identification of Suited Quality Metrics for Natural and Medical Images

    Directory of Open Access Journals (Sweden)

    Kirti V. Thakur

    2016-06-01

    Full Text Available To assess quality of the denoised image is one of the important task in image denoising application.Numerous quality metrics are proposed by researchers with their particular characteristics till today. In practice, image acquisition system is different for natural and medical images. Hence noise introduced in these images is also different in nature. Considering this fact, authors in this paper tried to identify the suited quality metrics for Gaussian, speckle and Poisson corrupted natural, ultrasound and X-ray images respectively. In this paper, sixteen different quality metrics from full reference category are evaluated with respect to noise variance and suited quality metric for particular type of noise is identified. Strong need to develop noise dependent quality metric is also identified in this work.

  5. Watermarking of ultrasound medical images in teleradiology using compressed watermark.

    Science.gov (United States)

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

    2016-01-01

    The open accessibility of Internet-based medical images in teleradialogy face security threats due to the nonsecured communication media. This paper discusses the spatial domain watermarking of ultrasound medical images for content authentication, tamper detection, and lossless recovery. For this purpose, the image is divided into two main parts, the region of interest (ROI) and region of noninterest (RONI). The defined ROI and its hash value are combined as watermark, lossless compressed, and embedded into the RONI part of images at pixel's least significant bits (LSBs). The watermark lossless compression and embedding at pixel's LSBs preserve image diagnostic and perceptual qualities. Different lossless compression techniques including Lempel-Ziv-Welch (LZW) were tested for watermark compression. The performances of these techniques were compared based on more bit reduction and compression ratio. LZW was found better than others and used in tamper detection and recovery watermarking of medical images (TDARWMI) scheme development to be used for ROI authentication, tamper detection, localization, and lossless recovery. TDARWMI performance was compared and found to be better than other watermarking schemes.

  6. Digital Topology and Geometry in Medical Imaging: A Survey.

    Science.gov (United States)

    Saha, Punam K; Strand, Robin; Borgefors, Gunilla

    2015-09-01

    Digital topology and geometry refers to the use of topologic and geometric properties and features for images defined in digital grids. Such methods have been widely used in many medical imaging applications, including image segmentation, visualization, manipulation, interpolation, registration, surface-tracking, object representation, correction, quantitative morphometry etc. Digital topology and geometry play important roles in medical imaging research by enriching the scope of target outcomes and by adding strong theoretical foundations with enhanced stability, fidelity, and efficiency. This paper presents a comprehensive yet compact survey on results, principles, and insights of methods related to digital topology and geometry with strong emphasis on understanding their roles in various medical imaging applications. Specifically, this paper reviews methods related to distance analysis and path propagation, connectivity, surface-tracking, image segmentation, boundary and centerline detection, topology preservation and local topological properties, skeletonization, and object representation, correction, and quantitative morphometry. A common thread among the topics reviewed in this paper is that their theory and algorithms use the principle of digital path connectivity, path propagation, and neighborhood analysis.

  7. Watermarking of ultrasound medical images in teleradiology using compressed watermark.

    Science.gov (United States)

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

    2016-01-01

    The open accessibility of Internet-based medical images in teleradialogy face security threats due to the nonsecured communication media. This paper discusses the spatial domain watermarking of ultrasound medical images for content authentication, tamper detection, and lossless recovery. For this purpose, the image is divided into two main parts, the region of interest (ROI) and region of noninterest (RONI). The defined ROI and its hash value are combined as watermark, lossless compressed, and embedded into the RONI part of images at pixel's least significant bits (LSBs). The watermark lossless compression and embedding at pixel's LSBs preserve image diagnostic and perceptual qualities. Different lossless compression techniques including Lempel-Ziv-Welch (LZW) were tested for watermark compression. The performances of these techniques were compared based on more bit reduction and compression ratio. LZW was found better than others and used in tamper detection and recovery watermarking of medical images (TDARWMI) scheme development to be used for ROI authentication, tamper detection, localization, and lossless recovery. TDARWMI performance was compared and found to be better than other watermarking schemes. PMID:26839914

  8. Integrating medical imaging analyses through a high-throughput bundled resource imaging system

    Science.gov (United States)

    Covington, Kelsie; Welch, E. Brian; Jeong, Ha-Kyu; Landman, Bennett A.

    2011-03-01

    Exploitation of advanced, PACS-centric image analysis and interpretation pipelines provides well-developed storage, retrieval, and archival capabilities along with state-of-the-art data providence, visualization, and clinical collaboration technologies. However, pursuit of integrated medical imaging analysis through a PACS environment can be limiting in terms of the overhead required to validate, evaluate and integrate emerging research technologies. Herein, we address this challenge through presentation of a high-throughput bundled resource imaging system (HUBRIS) as an extension to the Philips Research Imaging Development Environment (PRIDE). HUBRIS enables PACS-connected medical imaging equipment to invoke tools provided by the Java Imaging Science Toolkit (JIST) so that a medical imaging platform (e.g., a magnetic resonance imaging scanner) can pass images and parameters to a server, which communicates with a grid computing facility to invoke the selected algorithms. Generated images are passed back to the server and subsequently to the imaging platform from which the images can be sent to a PACS. JIST makes use of an open application program interface layer so that research technologies can be implemented in any language capable of communicating through a system shell environment (e.g., Matlab, Java, C/C++, Perl, LISP, etc.). As demonstrated in this proof-of-concept approach, HUBRIS enables evaluation and analysis of emerging technologies within well-developed PACS systems with minimal adaptation of research software, which simplifies evaluation of new technologies in clinical research and provides a more convenient use of PACS technology by imaging scientists.

  9. Medical image of the week: Leriche syndrome

    Directory of Open Access Journals (Sweden)

    Berlinberg A

    2016-02-01

    Full Text Available No abstract available. Article truncated at 150 words. A 68-year-old man with GOLD stage 4 COPD was admitted to the Intensive Care Unit for worsening hypoxic and hypercarbic respiratory failure. The patient was treated with steroids for COPD exacerbation, and required continuous BIPAP. On hospital day 2 concern arose for possible pulmonary embolism given worsening oxygenation despite BIPAP, and a thoracic CT angiogram was performed. On imaging, an incidental finding was discovered that the patient had complete occlusion of his aortic artery at the level of the renal arteries with extensive collaterals throughout the abdomen (Figure 1. The patient had palpable pulses in both feet and extremities were warm to touch bilaterally with recovered circulation, as verified on CT runoff (Figure 2. Vascular surgery was consulted, and a decision was made for no surgical intervention given the extensive collateral system and likely chronic time course. On further questioning the patient had limited ability to ambulate due to claudication. ...

  10. Medical Imaging for Understanding Sleep Regulation

    Science.gov (United States)

    Wong, Kenneth

    2011-10-01

    Sleep is essential for the health of the nervous system. Lack of sleep has a profound negative effect on cognitive ability and task performance. During sustained military operations, soldiers often suffer from decreased quality and quantity of sleep, increasing their susceptibility to neurological problems and limiting their ability to perform the challenging mental tasks that their missions require. In the civilian sector, inadequate sleep and overt sleep pathology are becoming more common, with many detrimental impacts. There is a strong need for new, in vivo studies of human brains during sleep, particularly the initial descent from wakefulness. Our research team is investigating sleep using a combination of magnetic resonance imaging (MRI), positron emission tomography (PET), and electroencephalography (EEG). High resolution MRI combined with PET enables localization of biochemical processes (e.g., metabolism) to anatomical structures. MRI methods can also be used to examine functional connectivity among brain regions. Neural networks are dynamically reordered during different sleep stages, reflecting the disconnect with the waking world and the essential yet unconscious brain activity that occurs during sleep.[4pt] In collaboration with Linda Larson-Prior, Washington University; Alpay Ozcan, Virginia Tech; Seong Mun, Virginia Tech; and Zang-Hee Cho, Gachon University.

  11. Medical image of the week: Pott's disease

    Directory of Open Access Journals (Sweden)

    Thao C

    2015-07-01

    Full Text Available No abstract available. Article truncated at 150 words. A 22 year-old man with a history of asthma presented with a two-month history of progressive right upper extremity weakness with back pain, weight loss, and night sweats. CT scan of the chest revealed mass-like infiltrative mass in the right lung apex with mediastinal and hilar lymphadenopathy (Figure 1. An MRI cervical spine showed a large infiltrating process at the right medial lung apex with vertebral body compression (Figure 2. A CT-guided lung biopsy was performed and it showed necrotizing granulomatous inflammation (Figure 3. Pott’s disease was diagnosed and the patient started on anti-tuberculous treatment with a good recovery. Pott’s disease is a common cause of spinal infection and its clinical presentations are nonspecific. Early findings on imaging may reveal loss of vertebral body height, bone sequestration, sclerosis, and paraspinal mass with calcification (1. A diagnosis of this condition must be made early as prompt treatment may reduce significant morbidity ...

  12. Medical image of the week: scleroderma

    Directory of Open Access Journals (Sweden)

    Arteaga VA

    2015-04-01

    Full Text Available No abstract available. Article truncated at 150 words. A 56-year-old man presents with cough and dyspnea. Pertinent history is significant for scleroderma. A complete blood count and differential count were unremarkable. A chest radiograph was obtained (Figure 1. Based on overall imaging and clinical history, the chest x-ray findings are highly suggest interstitial lung disease likely related to scleroderma and a recommendation for high resolution chest CT was made. Progressive systemic sclerosis (scleroderma is an autoimmune connective tissue disease that affects 30-50 year old women more often than men and is characterized by the overproduction of collagen which can lead to fibrosis which includes the lungs, skin, and may also affect visceral organs (1. In the hands, vasculitis and Raynaud's phenomenon may lead to distal tapering (2. Although acro-osteolysis or distal tuft resorption can be seen in a wide variety of disorders, it may be present in up to 80% of patients with scleroderma. High-resolution chest CT is ...

  13. Automated classification of optical coherence tomography images of human atrial tissue.

    Science.gov (United States)

    Gan, Yu; Tsay, David; Amir, Syed B; Marboe, Charles C; Hendon, Christine P

    2016-10-01

    Tissue composition of the atria plays a critical role in the pathology of cardiovascular disease, tissue remodeling, and arrhythmogenic substrates. Optical coherence tomography (OCT) has the ability to capture the tissue composition information of the human atria. In this study, we developed a region-based automated method to classify tissue compositions within human atria samples within OCT images. We segmented regional information without prior information about the tissue architecture and subsequently extracted features within each segmented region. A relevance vector machine model was used to perform automated classification. Segmentation of human atrial ex vivo datasets was correlated with trichrome histology and our classification algorithm had an average accuracy of 80.41% for identifying adipose, myocardium, fibrotic myocardium, and collagen tissue compositions. PMID:26926869

  14. Automated Line Tracking of lambda-DNA for Single-Molecule Imaging

    CERN Document Server

    Guan, Juan; Granick, Steve

    2011-01-01

    We describe a straightforward, automated line tracking method to visualize within optical resolution the contour of linear macromolecules as they rearrange shape as a function of time by Brownian diffusion and under external fields such as electrophoresis. Three sequential stages of analysis underpin this method: first, "feature finding" to discriminate signal from noise; second, "line tracking" to approximate those shapes as lines; third, "temporal consistency check" to discriminate reasonable from unreasonable fitted conformations in the time domain. The automated nature of this data analysis makes it straightforward to accumulate vast quantities of data while excluding the unreliable parts of it. We implement the analysis on fluorescence images of lambda-DNA molecules in agarose gel to demonstrate its capability to produce large datasets for subsequent statistical analysis.

  15. Estimation of urinary stone composition by automated processing of CT images

    CERN Document Server

    Chevreau, Grégoire; Conort, Pierre; Renard-Penna, Raphaëlle; Mallet, Alain; Daudon, Michel; Mozer, Pierre; 10.1007/s00240-009-0195-3

    2009-01-01

    The objective of this article was developing an automated tool for routine clinical practice to estimate urinary stone composition from CT images based on the density of all constituent voxels. A total of 118 stones for which the composition had been determined by infrared spectroscopy were placed in a helical CT scanner. A standard acquisition, low-dose and high-dose acquisitions were performed. All voxels constituting each stone were automatically selected. A dissimilarity index evaluating variations of density around each voxel was created in order to minimize partial volume effects: stone composition was established on the basis of voxel density of homogeneous zones. Stone composition was determined in 52% of cases. Sensitivities for each compound were: uric acid: 65%, struvite: 19%, cystine: 78%, carbapatite: 33.5%, calcium oxalate dihydrate: 57%, calcium oxalate monohydrate: 66.5%, brushite: 75%. Low-dose acquisition did not lower the performances (P < 0.05). This entirely automated approach eliminat...

  16. A method for the automated detection phishing websites through both site characteristics and image analysis

    Science.gov (United States)

    White, Joshua S.; Matthews, Jeanna N.; Stacy, John L.

    2012-06-01

    Phishing website analysis is largely still a time-consuming manual process of discovering potential phishing sites, verifying if suspicious sites truly are malicious spoofs and if so, distributing their URLs to the appropriate blacklisting services. Attackers increasingly use sophisticated systems for bringing phishing sites up and down rapidly at new locations, making automated response essential. In this paper, we present a method for rapid, automated detection and analysis of phishing websites. Our method relies on near real-time gathering and analysis of URLs posted on social media sites. We fetch the pages pointed to by each URL and characterize each page with a set of easily computed values such as number of images and links. We also capture a screen-shot of the rendered page image, compute a hash of the image and use the Hamming distance between these image hashes as a form of visual comparison. We provide initial results demonstrate the feasibility of our techniques by comparing legitimate sites to known fraudulent versions from Phishtank.com, by actively introducing a series of minor changes to a phishing toolkit captured in a local honeypot and by performing some initial analysis on a set of over 2.8 million URLs posted to Twitter over a 4 days in August 2011. We discuss the issues encountered during our testing such as resolvability and legitimacy of URL's posted on Twitter, the data sets used, the characteristics of the phishing sites we discovered, and our plans for future work.

  17. An Automated Images-to-Graphs Framework for High Resolution Connectomics

    Directory of Open Access Journals (Sweden)

    William R Gray Roncal

    2015-08-01

    Full Text Available Reconstructing a map of neuronal connectivity is a critical challenge in contemporary neuroscience. Recent advances in high-throughput serial section electron microscopy (EM have produced massive 3D image volumes of nanoscale brain tissue for the first time. The resolution of EM allows for individual neurons and their synaptic connections to be directly observed. Recovering neuronal networks by manually tracing each neuronal process at this scale is unmanageable, and therefore researchers are developing automated image processing modules. Thus far, state-of-the-art algorithms focus only on the solution to a particular task (e.g., neuron segmentation or synapse identification. In this manuscript we present the first fully automated images-to-graphs pipeline (i.e., a pipeline that begins with an imaged volume of neural tissue and produces a brain graph without any human interaction. To evaluate overall performance and select the best parameters and methods, we also develop a metric to assess the quality of the output graphs. We evaluate a set of algorithms and parameters, searching possible operating points to identify the best available brain graph for our assessment metric. Finally, we deploy a reference end-to-end version of the pipeline on a large, publicly available data set. This provides a baseline result and framework for community analysis and future algorithm development and testing. All code and data derivatives have been made publicly available toward eventually unlocking new biofidelic computational primitives and understanding of neuropathologies.

  18. MAGNETIC RESONANCE IMAGING COMPATIBLE ROBOTIC SYSTEM FOR FULLY AUTOMATED BRACHYTHERAPY SEED PLACEMENT

    Science.gov (United States)

    Muntener, Michael; Patriciu, Alexandru; Petrisor, Doru; Mazilu, Dumitru; Bagga, Herman; Kavoussi, Louis; Cleary, Kevin; Stoianovici, Dan

    2011-01-01

    Objectives To introduce the development of the first magnetic resonance imaging (MRI)-compatible robotic system capable of automated brachytherapy seed placement. Methods An MRI-compatible robotic system was conceptualized and manufactured. The entire robot was built of nonmagnetic and dielectric materials. The key technology of the system is a unique pneumatic motor that was specifically developed for this application. Various preclinical experiments were performed to test the robot for precision and imager compatibility. Results The robot was fully operational within all closed-bore MRI scanners. Compatibility tests in scanners of up to 7 Tesla field intensity showed no interference of the robot with the imager. Precision tests in tissue mockups yielded a mean seed placement error of 0.72 ± 0.36 mm. Conclusions The robotic system is fully MRI compatible. The new technology allows for automated and highly accurate operation within MRI scanners and does not deteriorate the MRI quality. We believe that this robot may become a useful instrument for image-guided prostate interventions. PMID:17169653

  19. AUTOMATED DETECTION OF OIL DEPOTS FROM HIGH RESOLUTION IMAGES: A NEW PERSPECTIVE

    Directory of Open Access Journals (Sweden)

    A. O. Ok

    2015-03-01

    Full Text Available This paper presents an original approach to identify oil depots from single high resolution aerial/satellite images in an automated manner. The new approach considers the symmetric nature of circular oil depots, and it computes the radial symmetry in a unique way. An automated thresholding method to focus on circular regions and a new measure to verify circles are proposed. Experiments are performed on six GeoEye-1 test images. Besides, we perform tests on 16 Google Earth images of an industrial test site acquired in a time series manner (between the years 1995 and 2012. The results reveal that our approach is capable of detecting circle objects in very different/difficult images. We computed an overall performance of 95.8% for the GeoEye-1 dataset. The time series investigation reveals that our approach is robust enough to locate oil depots in industrial environments under varying illumination and environmental conditions. The overall performance is computed as 89.4% for the Google Earth dataset, and this result secures the success of our approach compared to a state-of-the-art approach.

  20. Fully automated segmentation of left ventricle using dual dynamic programming in cardiac cine MR images

    Science.gov (United States)

    Jiang, Luan; Ling, Shan; Li, Qiang

    2016-03-01

    Cardiovascular diseases are becoming a leading cause of death all over the world. The cardiac function could be evaluated by global and regional parameters of left ventricle (LV) of the heart. The purpose of this study is to develop and evaluate a fully automated scheme for segmentation of LV in short axis cardiac cine MR images. Our fully automated method consists of three major steps, i.e., LV localization, LV segmentation at end-diastolic phase, and LV segmentation propagation to the other phases. First, the maximum intensity projection image along the time phases of the midventricular slice, located at the center of the image, was calculated to locate the region of interest of LV. Based on the mean intensity of the roughly segmented blood pool in the midventricular slice at each phase, end-diastolic (ED) and end-systolic (ES) phases were determined. Second, the endocardial and epicardial boundaries of LV of each slice at ED phase were synchronously delineated by use of a dual dynamic programming technique. The external costs of the endocardial and epicardial boundaries were defined with the gradient values obtained from the original and enhanced images, respectively. Finally, with the advantages of the continuity of the boundaries of LV across adjacent phases, we propagated the LV segmentation from the ED phase to the other phases by use of dual dynamic programming technique. The preliminary results on 9 clinical cardiac cine MR cases show that the proposed method can obtain accurate segmentation of LV based on subjective evaluation.

  1. Automated Adaptive Brightness in Wireless Capsule Endoscopy Using Image Segmentation and Sigmoid Function.

    Science.gov (United States)

    Shrestha, Ravi; Mohammed, Shahed K; Hasan, Md Mehedi; Zhang, Xuechao; Wahid, Khan A

    2016-08-01

    Wireless capsule endoscopy (WCE) plays an important role in the diagnosis of gastrointestinal (GI) diseases by capturing images of human small intestine. Accurate diagnosis of endoscopic images depends heavily on the quality of captured images. Along with image and frame rate, brightness of the image is an important parameter that influences the image quality which leads to the design of an efficient illumination system. Such design involves the choice and placement of proper light source and its ability to illuminate GI surface with proper brightness. Light emitting diodes (LEDs) are normally used as sources where modulated pulses are used to control LED's brightness. In practice, instances like under- and over-illumination are very common in WCE, where the former provides dark images and the later provides bright images with high power consumption. In this paper, we propose a low-power and efficient illumination system that is based on an automated brightness algorithm. The scheme is adaptive in nature, i.e., the brightness level is controlled automatically in real-time while the images are being captured. The captured images are segmented into four equal regions and the brightness level of each region is calculated. Then an adaptive sigmoid function is used to find the optimized brightness level and accordingly a new value of duty cycle of the modulated pulse is generated to capture future images. The algorithm is fully implemented in a capsule prototype and tested with endoscopic images. Commercial capsules like Pillcam and Mirocam were also used in the experiment. The results show that the proposed algorithm works well in controlling the brightness level accordingly to the environmental condition, and as a result, good quality images are captured with an average of 40% brightness level that saves power consumption of the capsule. PMID:27333609

  2. A computer-aided automated methodology for the detection and classification of occlusal caries from photographic color images.

    Science.gov (United States)

    Berdouses, Elias D; Koutsouri, Georgia D; Tripoliti, Evanthia E; Matsopoulos, George K; Oulis, Constantine J; Fotiadis, Dimitrios I

    2015-07-01

    The aim of this work is to present a computer-aided automated methodology for the assessment of carious lesions, according to the International Caries Detection and Assessment System (ICDAS II), which are located on the occlusal surfaces of posterior permanent teeth from photographic color tooth images. The proposed methodology consists of two stages: (a) the detection of regions of interest and (b) the classification of the detected regions according to ICDAS ΙΙ. In the first stage, pre-processing, segmentation and post-processing mechanisms were employed. For each pixel of the detected regions, a 15×15 neighborhood is used and a set of intensity-based and texture-based features were extracted. A correlation based technique was applied to select a subset of 36 features which were given as input into the classification stage, where five classifiers (J48, Random Tree, Random Forests, Support Vector Machines and Naïve Bayes) were compared to conclude to the best one, in our case, to Random Forests. The methodology was evaluated on a set of 103 digital color images where 425 regions of interest from occlusal surfaces of extracted permanent teeth were manually segmented and classified, based on visual assessments by two experts. The methodology correctly detected 337 out of 340 regions in the detection stage with accuracy of detection 80%. For the classification stage an overall accuracy 83% is achieved. The proposed methodology provides an objective and fully automated caries diagnostic system for occlusal carious lesions with similar or better performance of a trained dentist taking into consideration the available medical knowledge. PMID:25932969

  3. Medical Image Computing and Computer-Assisted Intervention - MICCAI 2006

    DEFF Research Database (Denmark)

    Nielsen, Mads; Sporring, Jon

    The two-volume set LNCS 4190 and LNCS 4191 constitute the refereed proceedings of the 9th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2006, held in Copenhagen, Denmark in October 2006. The program committee carefully selected 39 revised full papers...

  4. Synthetic Aperture Sequential Beamformation applied to medical imaging

    DEFF Research Database (Denmark)

    Hemmsen, Martin Christian; Hansen, Jens Munk; Jensen, Jørgen Arendt

    2012-01-01

    Synthetic Aperture Sequential Beamforming (SASB) is applied to medical ultrasound imaging using a multi element convex array transducer. The main motivation for SASB is to apply synthetic aperture techniques without the need for storing RF-data for a number of elements and hereby devise a system...

  5. Science means business: medical imaging shows colour of money

    CERN Multimedia

    Macfie, Rebecca

    2007-01-01

    Doctors have used x-ray machines for 100 years, but they remain an imprecise and limited diagnostic tool. But a team of Canterbury University researchers is aiming to revolutionise medical x-ray technology with high-precision colour imaging. (1,5 page)

  6. Detailed interrogation of trypanosome cell biology via differential organelle staining and automated image analysis

    Directory of Open Access Journals (Sweden)

    Wheeler Richard J

    2012-01-01

    Full Text Available Abstract Background Many trypanosomatid protozoa are important human or animal pathogens. The well defined morphology and precisely choreographed division of trypanosomatid cells makes morphological analysis a powerful tool for analyzing the effect of mutations, chemical insults and changes between lifecycle stages. High-throughput image analysis of micrographs has the potential to accelerate collection of quantitative morphological data. Trypanosomatid cells have two large DNA-containing organelles, the kinetoplast (mitochondrial DNA and nucleus, which provide useful markers for morphometric analysis; however they need to be accurately identified and often lie in close proximity. This presents a technical challenge. Accurate identification and quantitation of the DNA content of these organelles is a central requirement of any automated analysis method. Results We have developed a technique based on double staining of the DNA with a minor groove binding (4'', 6-diamidino-2-phenylindole (DAPI and a base pair intercalating (propidium iodide (PI or SYBR green fluorescent stain and color deconvolution. This allows the identification of kinetoplast and nuclear DNA in the micrograph based on whether the organelle has DNA with a more A-T or G-C rich composition. Following unambiguous identification of the kinetoplasts and nuclei the resulting images are amenable to quantitative automated analysis of kinetoplast and nucleus number and DNA content. On this foundation we have developed a demonstrative analysis tool capable of measuring kinetoplast and nucleus DNA content, size and position and cell body shape, length and width automatically. Conclusions Our approach to DNA staining and automated quantitative analysis of trypanosomatid morphology accelerated analysis of trypanosomatid protozoa. We have validated this approach using Leishmania mexicana, Crithidia fasciculata and wild-type and mutant Trypanosoma brucei. Automated analysis of T. brucei

  7. Medical imaging was boosted by the discovery of artificial radioactivity

    International Nuclear Information System (INIS)

    This article draws the history of medical imaging since the discovery of artificial radioactivity in 1934. The author reviews the PET (positron emission tomography) and MRI (magnetic resonance imaging) technologies and presents the recent progress in neuro-sciences that have been made possible by using these 2 technologies. Brain imaging has allowed to show: - the impact of emotions on logical mental processes and on mental performances, - the management of memory in the brain of talented quick reckoners, - the degeneration of neurons, and - the link between autism and the presence of structural and functional anomalies in the brain. (A.C.)

  8. Fuzzy Clustering Algorithms for Effective Medical Image Segmentation

    OpenAIRE

    Deepali Aneja; Tarun Kumar Rawat

    2013-01-01

    Medical image segmentation demands a segmentation algorithm which works against noise. The most popular algorithm used in image segmentation is Fuzzy C-Means clustering. It uses only intensity values for clustering which makes it highly sensitive to noise. The comparison of the three fundamental image segmentation methods based on fuzzy logic namely Fuzzy C-Means (FCM), Intuitionistic Fuzzy C-Means (IFCM), and Type-II Fuzzy C-Means (T2FCM) is presented in this paper. These algorithms are exe...

  9. 3D Medical Image Segmentation Based on Rough Set Theory

    Institute of Scientific and Technical Information of China (English)

    CHEN Shi-hao; TIAN Yun; WANG Yi; HAO Chong-yang

    2007-01-01

    This paper presents a method which uses multiple types of expert knowledge together in 3D medical image segmentation based on rough set theory. The focus of this paper is how to approximate a ROI (region of interest) when there are multiple types of expert knowledge. Based on rough set theory, the image can be split into three regions:positive regions; negative regions; boundary regions. With multiple knowledge we refine ROI as an intersection of all of the expected shapes with single knowledge. At last we show the results of implementing a rough 3D image segmentation and visualization system.

  10. Computer vision approaches to medical image analysis. Revised papers

    International Nuclear Information System (INIS)

    This book constitutes the thoroughly refereed post proceedings of the international workshop Computer Vision Approaches to Medical Image Analysis, CVAMIA 2006, held in Graz, Austria in May 2006 as a satellite event of the 9th European Conference on Computer Vision, EECV 2006. The 10 revised full papers and 11 revised poster papers presented together with 1 invited talk were carefully reviewed and selected from 38 submissions. The papers are organized in topical sections on clinical applications, image registration, image segmentation and analysis, and the poster session. (orig.)

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

    Energy Technology Data Exchange (ETDEWEB)

    Tobin, K.W.

    2004-06-01

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

  12. Automated diagnoses of attention deficit hyperactive disorder using magnetic resonance imaging

    Directory of Open Access Journals (Sweden)

    Ani eEloyan

    2012-08-01

    Full Text Available Successful automated diagnoses of attention deficit hyperactive disorder (ADHD using imaging and functional biomarkers would have fundamental consequences on the public health impact of the disease. In this work, we show results on the predictability of ADHD using imaging biomarkers and discuss the scientific and diagnostic impacts of the research. We created a prediction model using the landmark ADHD 200 data set focusing on resting state functional connectivity (rs-fc and structural brain imaging. We predicted ADHD status and subtype, obtained by behavioral examination, using imaging data, intelligence quotients and other covariates. The novel contributions of this manuscript include a thorough exploration of prediction and image feature extraction methodology on this form of data, including the use of singular value decompositions, CUR decompositions, random forest, gradient boosting, bagging, voxel-based morphometry and support vector machines as well as important insights into the value, and potentially lack thereof, of imaging biomarkers of disease. The key results include the CUR-based decomposition of the rs-fc-fMRI along with gradient boosting and the prediction algorithm based on a motor network parcellation and random forest algorithm. We conjecture that the CUR decomposition is largely diagnosing common population directions of head motion. Of note, a byproduct of this research is a potential automated method for detecting subtle in-scanner motion. The final prediction algorithm, a weighted combination of several algorithms, had an external test set specificity of 94% with sensitivity of 21%. The most promising imaging biomarker was a correlation graph from a motor network parcellation. In summary, we have undertaken a large-scale statistical exploratory prediction exercise on the unique ADHD 200 data set. The exercise produced several potential leads for future scientific exploration of the neurological basis of ADHD.

  13. Computer-assisted scheme for automated determination of imaging planes in cervical spinal cord MRI

    Science.gov (United States)

    Tsurumaki, Masaki; Tsai, Du-Yih; Lee, Yongbum; Sekiya, Masaru; Kazama, Kiyoko

    2009-02-01

    This paper presents a computerized scheme to assist MRI operators in accurate and rapid determination of sagittal sections for MRI exam of cervical spinal cord. The algorithm of the proposed scheme consisted of 6 steps: (1) extraction of a cervical vertebra containing spinal cord from an axial localizer image; (2) extraction of spinal cord with sagittal image from the extracted vertebra; (3) selection of a series of coronal localizer images corresponding to various, involved portions of the extracted spinal cord with sagittal image; (4) generation of a composite coronal-plane image from the obtained coronal images; (5) extraction of spinal cord from the obtained composite image; (6) determination of oblique sagittal sections from the detected location and gradient of the extracted spinal cord. Cervical spine images obtained from 25 healthy volunteers were used for the study. A perceptual evaluation was performed by five experienced MRI operators. Good agreement between the automated and manual determinations was achieved. By use of the proposed scheme, average execution time was reduced from 39 seconds/case to 1 second/case. The results demonstrate that the proposed scheme can assist MRI operators in performing cervical spinal cord MRI exam accurately and rapidly.

  14. Managing complex processing of medical image sequences by program supervision techniques

    Science.gov (United States)

    Crubezy, Monica; Aubry, Florent; Moisan, Sabine; Chameroy, Virginie; Thonnat, Monique; Di Paola, Robert

    1997-05-01

    Our objective is to offer clinicians wider access to evolving medical image processing (MIP) techniques, crucial to improve assessment and quantification of physiological processes, but difficult to handle for non-specialists in MIP. Based on artificial intelligence techniques, our approach consists in the development of a knowledge-based program supervision system, automating the management of MIP libraries. It comprises a library of programs, a knowledge base capturing the expertise about programs and data and a supervision engine. It selects, organizes and executes the appropriate MIP programs given a goal to achieve and a data set, with dynamic feedback based on the results obtained. It also advises users in the development of new procedures chaining MIP programs.. We have experimented the approach for an application of factor analysis of medical image sequences as a means of predicting the response of osteosarcoma to chemotherapy, with both MRI and NM dynamic image sequences. As a result our program supervision system frees clinical end-users from performing tasks outside their competence, permitting them to concentrate on clinical issues. Therefore our approach enables a better exploitation of possibilities offered by MIP and higher quality results, both in terms of robustness and reliability.

  15. Multiscale registration of medical images based on edge preserving scale space with application in image-guided radiation therapy

    International Nuclear Information System (INIS)

    Mutual information (MI) is a well-accepted similarity measure for image registration in medical systems. However, MI-based registration faces the challenges of high computational complexity and a high likelihood of being trapped into local optima due to an absence of spatial information. In order to solve these problems, multi-scale frameworks can be used to accelerate registration and improve robustness. Traditional Gaussian pyramid representation is one such technique but it suffers from contour diffusion at coarse levels which may lead to unsatisfactory registration results. In this work, a new multi-scale registration framework called edge preserving multiscale registration (EPMR) was proposed based upon an edge preserving total variation L1 norm (TV-L1) scale space representation. TV-L1 scale space is constructed by selecting edges and contours of images according to their size rather than the intensity values of the image features. This ensures more meaningful spatial information with an EPMR framework for MI-based registration. Furthermore, we design an optimal estimation of the TV-L1 parameter in the EPMR framework by training and minimizing the transformation offset between the registered pairs for automated registration in medical systems. We validated our EPMR method on both simulated mono- and multi-modal medical datasets with ground truth and clinical studies from a combined positron emission tomography/computed tomography (PET/CT) scanner. We compared our registration framework with other traditional registration approaches. Our experimental results demonstrated that our method outperformed other methods in terms of the accuracy and robustness for medical images. EPMR can always achieve a small offset value, which is closer to the ground truth both for mono-modality and multi-modality, and the speed can be increased 5–8% for mono-modality and 10–14% for multi-modality registration under the same condition. Furthermore, clinical application by

  16. An algorithm for automated ROI definition in water or epoxy-filled NEMA NU-2 image quality phantoms.

    Science.gov (United States)

    Pierce Ii, Larry A; Byrd, Darrin W; Elston, Brian F; Karp, Joel S; Sunderland, John J; Kinahan, Paul E

    2016-01-08

    Drawing regions of interest (ROIs) in positron emission tomography/computed tomography (PET/CT) scans of the National Electrical Manufacturers Association (NEMA) NU-2 Image Quality (IQ) phantom is a time-consuming process that allows for interuser variability in the measurements. In order to reduce operator effort and allow batch processing of IQ phantom images, we propose a fast, robust, automated algorithm for performing IQ phantom sphere localization and analysis. The algorithm is easily altered to accommodate different configurations of the IQ phantom. The proposed algorithm uses information from both the PET and CT image volumes in order to overcome the challenges of detecting the smallest spheres in the PET volume. This algorithm has been released as an open-source plug-in to the Osirix medical image viewing software package. We test the algorithm under various noise conditions, positions within the scanner, air bubbles in the phantom spheres, and scanner misalignment conditions. The proposed algorithm shows run-times between 3 and 4 min and has proven to be robust under all tested conditions, with expected sphere localization deviations of less than 0.2 mm and variations of PET ROI mean and maximum values on the order of 0.5% and 2%, respectively, over multiple PET acquisitions. We conclude that the proposed algorithm is stable when challenged with a variety of physical and imaging anomalies, and that the algorithm can be a valuable tool for those who use the NEMA NU-2 IQ phantom for PET/CT scanner acceptance testing and QA/QC.

  17. Multimodal Medical Image Fusion by Adaptive Manifold Filter

    Directory of Open Access Journals (Sweden)

    Peng Geng

    2015-01-01

    Full Text Available Medical image fusion plays an important role in diagnosis and treatment of diseases such as image-guided radiotherapy and surgery. The modified local contrast information is proposed to fuse multimodal medical images. Firstly, the adaptive manifold filter is introduced into filtering source images as the low-frequency part in the modified local contrast. Secondly, the modified spatial frequency of the source images is adopted as the high-frequency part in the modified local contrast. Finally, the pixel with larger modified local contrast is selected into the fused image. The presented scheme outperforms the guided filter method in spatial domain, the dual-tree complex wavelet transform-based method, nonsubsampled contourlet transform-based method, and four classic fusion methods in terms of visual quality. Furthermore, the mutual information values by the presented method are averagely 55%, 41%, and 62% higher than the three methods and those values of edge based similarity measure by the presented method are averagely 13%, 33%, and 14% higher than the three methods for the six pairs of source images.

  18. Multimodal Medical Image Fusion by Adaptive Manifold Filter.

    Science.gov (United States)

    Geng, Peng; Liu, Shuaiqi; Zhuang, Shanna

    2015-01-01

    Medical image fusion plays an important role in diagnosis and treatment of diseases such as image-guided radiotherapy and surgery. The modified local contrast information is proposed to fuse multimodal medical images. Firstly, the adaptive manifold filter is introduced into filtering source images as the low-frequency part in the modified local contrast. Secondly, the modified spatial frequency of the source images is adopted as the high-frequency part in the modified local contrast. Finally, the pixel with larger modified local contrast is selected into the fused image. The presented scheme outperforms the guided filter method in spatial domain, the dual-tree complex wavelet transform-based method, nonsubsampled contourlet transform-based method, and four classic fusion methods in terms of visual quality. Furthermore, the mutual information values by the presented method are averagely 55%, 41%, and 62% higher than the three methods and those values of edge based similarity measure by the presented method are averagely 13%, 33%, and 14% higher than the three methods for the six pairs of source images. PMID:26664494

  19. Medical Image Fusion via an Effective Wavelet-Based Approach

    Directory of Open Access Journals (Sweden)

    Park DongSun

    2010-01-01

    Full Text Available A novel wavelet-based approach for medical image fusion is presented, which is developed by taking into not only account the characteristics of human visual system (HVS but also the physical meaning of the wavelet coefficients. After the medical images to be fused are decomposed by the wavelet transform, different-fusion schemes for combining the coefficients are proposed: coefficients in low-frequency band are selected with a visibility-based scheme, and coefficients in high-frequency bands are selected with a variance based method. To overcome the presence of noise and guarantee the homogeneity of the fused image, all the coefficients are subsequently performed by a window-based consistency verification process. The fused image is finally constructed by the inverse wavelet transform with all composite coefficients. To quantitatively evaluate and prove the performance of the proposed method, series of experiments and comparisons with some existing fusion methods are carried out in the paper. Experimental results on simulated and real medical images indicate that the proposed method is effective and can get satisfactory fusion results.

  20. An eSnake model for medical image segmentation

    Institute of Scientific and Technical Information of China (English)

    L(U) Hongyu; YUAN Kehong; BAO Shanglian; ZU Donglin; DUAN Chaijie

    2005-01-01

    A novel scheme of external force for detecting the object boundary of medical image based on Snakes (active contours)is introduced in the paper. In our new method, an electrostatic field on a template plane above the original image plane is designed to form the map of the external force. Compared with the method of Gradient Vector Flow (GVF), our approach has clear physical meanings. It has stronger ability to conform to boundary concavities, is simple to implement, and reliable for shape segmenting. Additionally, our method has larger capture range for the external force and is useful for medical image preprocessing in various applications. Finally, by adding the balloon force to the electrostatic field model, our Snake is able to represent long tube-like shapes or shapes with significant protrusions or bifurcations, and it has the specialty to prevent Snake leaking from large gaps on image edge by using a two-stage segmentation technique introduced in this paper. The test of our models proves that our methods are robust, precise in medical image segmentation.