WorldWideScience

Sample records for automated medical image

  1. Automated Functional Analysis in Dynamic Medical Imaging

    Czech Academy of Sciences Publication Activity Database

    Tichý, Ondřej

    Praha : Katedra matematiky, FSv ČVUT v Praze, 2012, s. 19-20. [Aplikovaná matematika – Rektorysova soutěž. Praha (CZ), 07.12.2012] Institutional support: RVO:67985556 Keywords : Factor Analysis * Dynamic Sequence * Scintigraphy Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2012/AS/tichy-automated functional analysis in dynamic medical imaging.pdf

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

    Science.gov (United States)

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

    2014-03-01

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

  5. Automated, non-linear registration between 3-dimensional brain map and medical head image

    International Nuclear Information System (INIS)

    In this paper, we propose an automated, non-linear registration method between 3-dimensional medical head image and brain map in order to efficiently extract the regions of interest. In our method, input 3-dimensional image is registered into a reference image extracted from a brain map. The problems to be solved are automated, non-linear image matching procedure, and cost function which represents the similarity between two images. Non-linear matching is carried out by dividing the input image into connected partial regions, transforming the partial regions preserving connectivity among the adjacent images, evaluating the image similarity between the transformed regions of the input image and the correspondent regions of the reference image, and iteratively searching the optimal transformation of the partial regions. In order to measure the voxelwise similarity of multi-modal images, a cost function is introduced, which is based on the mutual information. Some experiments using MR images presented the effectiveness of the proposed method. (author)

  6. 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

  7. Medical imaging

    International Nuclear Information System (INIS)

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

  8. Medical imaging

    CERN Document Server

    Townsend, David W

    1996-01-01

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

  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. Automated ship image acquisition

    Science.gov (United States)

    Hammond, T. R.

    2008-04-01

    The experimental Automated Ship Image Acquisition System (ASIA) collects high-resolution ship photographs at a shore-based laboratory, with minimal human intervention. The system uses Automatic Identification System (AIS) data to direct a high-resolution SLR digital camera to ship targets and to identify the ships in the resulting photographs. The photo database is then searchable using the rich data fields from AIS, which include the name, type, call sign and various vessel identification numbers. The high-resolution images from ASIA are intended to provide information that can corroborate AIS reports (e.g., extract identification from the name on the hull) or provide information that has been omitted from the AIS reports (e.g., missing or incorrect hull dimensions, cargo, etc). Once assembled into a searchable image database, the images can be used for a wide variety of marine safety and security applications. This paper documents the author's experience with the practicality of composing photographs based on AIS reports alone, describing a number of ways in which this can go wrong, from errors in the AIS reports, to fixed and mobile obstructions and multiple ships in the shot. The frequency with which various errors occurred in automatically-composed photographs collected in Halifax harbour in winter time were determined by manual examination of the images. 45% of the images examined were considered of a quality sufficient to read identification markings, numbers and text off the entire ship. One of the main technical challenges for ASIA lies in automatically differentiating good and bad photographs, so that few bad ones would be shown to human users. Initial attempts at automatic photo rating showed 75% agreement with manual assessments.

  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. Automating Shallow Seismic Imaging

    Energy Technology Data Exchange (ETDEWEB)

    Steeples, Don W.

    2004-12-09

    This seven-year, shallow-seismic reflection research project had the aim of improving geophysical imaging of possible contaminant flow paths. Thousands of chemically contaminated sites exist in the United States, including at least 3,700 at Department of Energy (DOE) facilities. Imaging technologies such as shallow seismic reflection (SSR) and ground-penetrating radar (GPR) sometimes are capable of identifying geologic conditions that might indicate preferential contaminant-flow paths. Historically, SSR has been used very little at depths shallower than 30 m, and even more rarely at depths of 10 m or less. Conversely, GPR is rarely useful at depths greater than 10 m, especially in areas where clay or other electrically conductive materials are present near the surface. Efforts to image the cone of depression around a pumping well using seismic methods were only partially successful (for complete references of all research results, see the full Final Technical Report, DOE/ER/14826-F), but peripheral results included development of SSR methods for depths shallower than one meter, a depth range that had not been achieved before. Imaging at such shallow depths, however, requires geophone intervals of the order of 10 cm or less, which makes such surveys very expensive in terms of human time and effort. We also showed that SSR and GPR could be used in a complementary fashion to image the same volume of earth at very shallow depths. The primary research focus of the second three-year period of funding was to develop and demonstrate an automated method of conducting two-dimensional (2D) shallow-seismic surveys with the goal of saving time, effort, and money. Tests involving the second generation of the hydraulic geophone-planting device dubbed the ''Autojuggie'' showed that large numbers of geophones can be placed quickly and automatically and can acquire high-quality data, although not under rough topographic conditions. In some easy

  15. Color Medical Image Analysis

    CERN Document Server

    Schaefer, Gerald

    2013-01-01

    Since the early 20th century, medical imaging has been dominated by monochrome imaging modalities such as x-ray, computed tomography, ultrasound, and magnetic resonance imaging. As a result, color information has been overlooked in medical image analysis applications. Recently, various medical imaging modalities that involve color information have been introduced. These include cervicography, dermoscopy, fundus photography, gastrointestinal endoscopy, microscopy, and wound photography. However, in comparison to monochrome images, the analysis of color images is a relatively unexplored area. The multivariate nature of color image data presents new challenges for researchers and practitioners as the numerous methods developed for monochrome images are often not directly applicable to multichannel images. The goal of this volume is to summarize the state-of-the-art in the utilization of color information in medical image analysis.

  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. 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.

  18. [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

  19. 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...

  20. 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.

  1. 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.

  2. RFID Module For Medical Automation Robot

    OpenAIRE

    Mikkonen, Mikko

    2015-01-01

    The objective of this Master’s thesis was to design a RFID reader module for a medical automation robot. The task was commissioned by Ginolis Oy. The topic of the thesis came from the company. The idea was to create a device that can be integrated in all of the company's current and future robotic devices. Future plans need to be taken into account too. An RFID reader should work in a way that there is a possibility to integrate it in the future, for example in a manually operated portable de...

  3. Medical ultrasound imaging

    DEFF Research Database (Denmark)

    Jensen, Jørgen Arendt

    2007-01-01

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

  4. Automated image segmentation using information theory

    International Nuclear Information System (INIS)

    Full text: Our development of automated contouring of CT images for RT planning is based on maximum a posteriori (MAP) analyses of region textures, edges, and prior shapes, and assumes stationary Gaussian distributions for voxel textures and contour shapes. Since models may not accurately represent image data, it would be advantageous to compute inferences without relying on models. The relative entropy (RE) from information theory can generate inferences based solely on the similarity of probability distributions. The entropy of a distribution of a random variable X is defined as -Σx p(x)log2p(x) for all the values x which X may assume. The RE (Kullback-Liebler divergence) of two distributions p(X), q(X), over X is Σx p(x)log2{p(x)/q(x)}. The RE is a kind of 'distance' between p,q, equaling zero when p=q and increasing as p,q are more different. Minimum-error MAP and likelihood ratio decision rules have RE equivalents: minimum error decisions obtain with functions of the differences between REs of compared distributions. One applied result is the contour ideally separating two regions is that which maximizes the relative entropy of the two regions' intensities. A program was developed that automatically contours the outlines of patients in stereotactic headframes, a situation most often requiring manual drawing. The relative entropy of intensities inside the contour (patient) versus outside (background) was maximized by conjugate gradient descent over the space of parameters of a deformable contour. shows the computed segmentation of a patient from headframe backgrounds. This program is particularly useful for preparing images for multimodal image fusion. Relative entropy and allied measures of distribution similarity provide automated contouring criteria that do not depend on statistical models of image data. This approach should have wide utility in medical image segmentation applications. Copyright (2001) Australasian College of Physical Scientists and

  5. 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...

  6. Medical Images Remote Consultation

    Science.gov (United States)

    Ferraris, Maurizio; Frixione, Paolo; Squarcia, Sandro

    Teleconsultation of digital images among different medical centers is now a reality. The problem to be solved is how to interconnect all the clinical diagnostic devices in a hospital in order to allow physicians and health physicists, working in different places, to discuss on interesting clinical cases visualizing the same diagnostic images at the same time. Applying World Wide Web technologies, the proposed system can be easily used by people with no specific computer knowledge providing a verbose help to guide the user through the right steps of execution. Diagnostic images are retrieved from a relational database or from a standard DICOM-PACS through the DICOM-WWW gateway allowing connection of the usual Web browsers to DICOM applications via the HTTP protocol. The system, which is proposed for radiotherapy implementation, where radiographies play a fundamental role, can be easily converted to different field of medical applications where a remote access to secure data are compulsory.

  7. 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

  8. 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

  9. Medical imaging systems

    Energy Technology Data Exchange (ETDEWEB)

    Frangioni, John V. (Wayland, MA)

    2012-07-24

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

  10. 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.

  11. 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.

  12. 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.

  13. Close Clustering Based Automated Color Image Annotation

    CERN Document Server

    Garg, Ankit; Asawa, Krishna

    2010-01-01

    Most image-search approaches today are based on the text based tags associated with the images which are mostly human generated and are subject to various kinds of errors. The results of a query to the image database thus can often be misleading and may not satisfy the requirements of the user. In this work we propose our approach to automate this tagging process of images, where image results generated can be fine filtered based on a probabilistic tagging mechanism. We implement a tool which helps to automate the tagging process by maintaining a training database, wherein the system is trained to identify certain set of input images, the results generated from which are used to create a probabilistic tagging mechanism. Given a certain set of segments in an image it calculates the probability of presence of particular keywords. This probability table is further used to generate the candidate tags for input images.

  14. 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.

  15. Radiographic examination takes on an automated image

    International Nuclear Information System (INIS)

    Automation can be effectively applied to nondestructive testing (NDT). Until recently, film radiography used in NDT was largely a manual process, involving the shooting of a series of x-rays, manually positioned and manually processed. In other words, much radiographic work is being done the way it was over 50 years ago. Significant advances in automation have changed the face of manufacturing, and industry has shared in the benefits brought by such progress. The handling of parts, which was once responsible for a large measure of labor costs, is now assigned to robotic equipment. In nondestructive testing processes, some progress has been achieved in automation - for example, in real-time imaging systems. However, only recently have truly automated NDT begun to emerge. There are two major reasons to introduce automation into NDT - reliability and productivity. Any process or technique that can improve the reliability of parts testing could easily justify the capital investments required

  16. Classification in Medical Imaging

    DEFF Research Database (Denmark)

    Chen, Chen

    detection in a cardiovascular disease study. The third focus is to deepen the understanding of classification mechanism by visualizing the knowledge learned by a classifier. More specifically, to build the most typical patterns recognized by the Fisher's linear discriminant rule with applications......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...

  17. 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....... Automated graylevel mapping is used in combination with a contrast-weighted form of frequency-diversity speckle reduction. In clinical studies, the techniques have yielded mean CNR improvements of 3.2 dB above ordinary frequency-diversity imaging and 5.6 dB over sharper conventional images, with no post...

  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 ... People with diabetes should always wear a medical alert bracelet or necklace that emergency medical workers will ...

  19. Close Clustering Based Automated Color Image Annotation

    OpenAIRE

    Garg, Ankit; Dwivedi, Rahul; Asawa, Krishna

    2010-01-01

    Most image-search approaches today are based on the text based tags associated with the images which are mostly human generated and are subject to various kinds of errors. The results of a query to the image database thus can often be misleading and may not satisfy the requirements of the user. In this work we propose our approach to automate this tagging process of images, where image results generated can be fine filtered based on a probabilistic tagging mechanism. We implement a tool which...

  20. Registration of Multimodal Medical Images

    OpenAIRE

    H. Costin; Cr. Rotariu

    2010-01-01

    Medical images are increasingly being used within healthcare for diagnosis, planning treatment, guiding treatment and monitoring disease progression. Within medical research (e.g. neuroscience research) they are used to investigate disease processes and understand normal development and ageing. Technically, medical imaging mainly processes missing, ambiguous, complementary, redundant and distorted data. In this paper, we propose a set of MR-CT image registration methods by using spatial model...

  1. Image processing in medical ultrasound

    DEFF Research Database (Denmark)

    Hemmsen, Martin Christian

    This Ph.D project addresses image processing in medical ultrasound and seeks to achieve two major scientific goals: First to develop an understanding of the most significant factors influencing image quality in medical ultrasound, and secondly to use this knowledge to develop image processing...... multiple imaging setups. This makes the system well suited for development of new processing methods and for clinical evaluations, where acquisition of the exact same scan location for multiple methods is important. The second project addressed implementation, development and evaluation of SASB using a...... 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...

  2. 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)

  3. 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

  4. 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...

  5. 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.

  6. 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 ...

  7. Visual perception and medical imaging

    International Nuclear Information System (INIS)

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

  8. Medical Image Registration Based Retrieval

    Directory of Open Access Journals (Sweden)

    Swarnambiga AYYACHAMY

    2013-02-01

    Full Text Available This paper presents a quantitative evaluation of state-of-the art intensity based image registration with retrieval methods applied to medical images. The purpose of this study is to access the stability of these methods for medical image analysis. The accuracy of this medical image retrieval with affine based registration and without registration is evaluated using observer study. For retrieval without registration and with registration, we examine the performance of various transform methods for the retrieval of medical images by extracting the features. This helps for the early diagnosis. The technique used for retrieval of medical images were a set of 2-D discrete Fourier transform (DFT, discrete cosine transform (DCT, discrete wavelet transform (DWT, Complex wavelet transform (CWT, and rotated complex wavelet filters (RCWF were implemented and examined for MRI imaging modalities. Especially RCWF gives texture information strongly oriented in six different directions (45° apart from the complex wavelet transform. Experimental results indicate that the DWT method perform well in retrieval of medical images. The method also retains the comparable levels of computational complexity. Then the experimental evaluation is carried by calculating the precision and recall values. It is found that DWT performs well for retrieval without registration and CWT with affine performs well in registration based retrieval with efficiency of 92% from retrieval efficiency 83% of DWT without registration. This helps in classification as before registration and after registration especially for clinical treatment and diagnosis.

  9. Medical Imaging 4: Image formation

    International Nuclear Information System (INIS)

    This book contains papers relating to the 1990 meeting of The International Society for Optical Engineering. Included are the following papers: Effect of protective layer on Resolution Properties of Photostimulable Phosphor Detector for Digital Radiographic System, Neural Network Scatter Correction Technique for Digital Radiography, Use of Computer Radiography for Portal Imaging

  10. 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.

  11. 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

  12. 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

  13. 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

  14. Automated image analysis of uterine cervical images

    Science.gov (United States)

    Li, Wenjing; Gu, Jia; Ferris, Daron; Poirson, Allen

    2007-03-01

    Cervical Cancer is the second most common cancer among women worldwide and the leading cause of cancer mortality of women in developing countries. If detected early and treated adequately, cervical cancer can be virtually prevented. Cervical precursor lesions and invasive cancer exhibit certain morphologic features that can be identified during a visual inspection exam. Digital imaging technologies allow us to assist the physician with a Computer-Aided Diagnosis (CAD) system. In colposcopy, epithelium that turns white after application of acetic acid is called acetowhite epithelium. Acetowhite epithelium is one of the major diagnostic features observed in detecting cancer and pre-cancerous regions. Automatic extraction of acetowhite regions from cervical images has been a challenging task due to specular reflection, various illumination conditions, and most importantly, large intra-patient variation. This paper presents a multi-step acetowhite region detection system to analyze the acetowhite lesions in cervical images automatically. First, the system calibrates the color of the cervical images to be independent of screening devices. Second, the anatomy of the uterine cervix is analyzed in terms of cervix region, external os region, columnar region, and squamous region. Third, the squamous region is further analyzed and subregions based on three levels of acetowhite are identified. The extracted acetowhite regions are accompanied by color scores to indicate the different levels of acetowhite. The system has been evaluated by 40 human subjects' data and demonstrates high correlation with experts' annotations.

  15. 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

  16. 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

  17. 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 ...

  18. 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.

  19. Evaluation Of Medical Fluoroscopy Imaging

    International Nuclear Information System (INIS)

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

  20. Medical image telecommunication

    International Nuclear Information System (INIS)

    After years of waiting for Picture Archiving and Communication Systems (PACS) to become technologically mature and readily available at competitive costs, it appears that the ingredients are now available for producing at least the telecommunication component of the PACS. They are as follows: 1. A variety of pathways now exist for long-distance high-speed digital data transmission at acceptable costs. 2. Developments in computer technology and keen competition in the microcomputer and video display markets have markedly reduced to costs for components of digital data terminals. 3. The volume of native digitally acquired images is expanding yearly, whereas at the same time the pressure for converting images acquired in analog format to digital format is increasing. 4. The advantages of and potential for processing and storing imaging data in digital format are becoming more widely recognized. These factors, individually and collectively, favor the successful applications of image telecommunication to the field of diagnostic imaging. The authors have attempted to provide an overview of the subject and the basics of this emerging technology

  1. 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.

  2. Stereoscopic medical imaging collaboration system

    Science.gov (United States)

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

    2007-02-01

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

  3. Quantitative information in medical imaging

    International Nuclear Information System (INIS)

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

  4. Medical gamma ray imaging

    Science.gov (United States)

    Osborne, Louis S.; Lanza, Richard C.

    1984-01-01

    A method and apparatus for determining the distribution of a position-emitting radioisotope into an object, the apparatus consisting of a wire mesh radiation converter, an ionizable gas for propagating ionization events caused by electrodes released by the converter, a drift field, a spatial position detector and signal processing circuitry for correlating near-simultaneous ionization events and determining their time differences, whereby the position sources of back-to-back collinear radiation can be located and a distribution image constructed.

  5. Quantification of Structure from Medical Images

    DEFF Research Database (Denmark)

    Qazi, Arish Asif

    In this thesis, we present automated methods that quantify information from medical images; information that is intended to assist and enable clinicians gain a better understanding of the underlying pathology. The first part of the thesis presents methods that analyse the articular cartilage...... information beyond that of traditional morphometric measures. The thesis also proposes a fully automatic and generic statistical framework for identifying biologically interpretable regions of difference (ROD) between two groups of biological objects, attributed by anatomical differences or changes relating...... to pathology, without a priori knowledge about the location, extent, or topology of the ROD. Based on quantifications from both morphometric and textural based imaging markers, our method has identified the most pathological regions in the articular cartilage. The remaining part of the thesis...

  6. Automated Algorithm for Carotid Lumen Segmentation and 3D Reconstruction in B-mode images

    OpenAIRE

    Jorge M. S. Pereira; João Manuel R. S. Tavares

    2011-01-01

    The B-mode image system is one of the most popular systems used in the medical area; however it imposes several difficulties in the image segmentation process due to low contrast and noise. Although these difficulties, this image mode is often used in the study and diagnosis of the carotid artery diseases.In this paper, it is described the a novel automated algorithm for carotid lumen segmentation and 3-D reconstruction in B- mode images.

  7. 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

  8. Army medical imaging system: ARMIS

    International Nuclear Information System (INIS)

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

  9. Invitation to medical image processing

    International Nuclear Information System (INIS)

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

  10. Medical imaging and planning

    International Nuclear Information System (INIS)

    How can we reconcile the impressive progress of medical technologies with the no less impressive problems of health insurance systems. Are policies of imagery diffusion and policies of cost-containment simultaneously compatible. The author, based on a historical and prospective approach, believes they are. Whether we consider the sanitary map (carte sanitaire) in France which is an explicit method of rationing, or global budgeting which is an implicit one, we must revise our present methods of planning because they have become obsolete. The Committee for Assessement of Technological Innovation at the Assistance Publique of Paris (CEDIT) is an example of a more refined mechanism, associated with regional planning within the Plan Directeur of the Paris Teaching Hospitals for the 1985-1989 period. The probable evolution of the health insurance system in France, as well as more competition between the private and public hospitals lead the author to propose greater flexibility in planning for imagery, knowing that it is impossible to know what that particular technology will consist of in thirteen years from now in the year 2000, but it will certainly be the core of the future hospital, whether diagnostic or therapeutic

  11. 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

  12. Advantages of semiconductor CZT for medical imaging

    Science.gov (United States)

    Wagenaar, Douglas J.; Parnham, Kevin; Sundal, Bjorn; Maehlum, Gunnar; Chowdhury, Samir; Meier, Dirk; Vandehei, Thor; Szawlowski, Marek; Patt, Bradley E.

    2007-09-01

    Cadmium zinc telluride (CdZnTe, or CZT) is a room-temperature semiconductor radiation detector that has been developed in recent years for a variety of applications. CZT has been investigated for many potential uses in medical imaging, especially in the field of single photon emission computed tomography (SPECT). CZT can also be used in positron emission tomography (PET) as well as photon-counting and integration-mode x-ray radiography and computed tomography (CT). The principal advantages of CZT are 1) direct conversion of x-ray or gamma-ray energy into electron-hole pairs; 2) energy resolution; 3) high spatial resolution and hence high space-bandwidth product; 4) room temperature operation, stable performance, high density, and small volume; 5) depth-of-interaction (DOI) available through signal processing. These advantages will be described in detail with examples from our own CZT systems. The ability to operate at room temperature, combined with DOI and very small pixels, make the use of multiple, stationary CZT "mini-gamma cameras" a realistic alternative to today's large Anger-type cameras that require motion to obtain tomographic sampling. The compatibility of CZT with Magnetic Resonance Imaging (MRI)-fields is demonstrated for a new type of multi-modality medical imaging, namely SPECT/MRI. For pre-clinical (i.e., laboratory animal) imaging, the advantages of CZT lie in spatial and energy resolution, small volume, automated quality control, and the potential for DOI for parallax removal in pinhole imaging. For clinical imaging, the imaging of radiographically dense breasts with CZT enables scatter rejection and hence improved contrast. Examples of clinical breast images with a dual-head CZT system are shown.

  13. 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...

  14. 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.

  15. Computer vision in medical imaging

    CERN Document Server

    Chen, C H

    2013-01-01

    The major progress in computer vision allows us to make extensive use of medical imaging data to provide us better diagnosis, treatment and predication of diseases. Computer vision can exploit texture, shape, contour and prior knowledge along with contextual information from image sequence and provide 3D and 4D information that helps with better human understanding. Many powerful tools have been available through image segmentation, machine learning, pattern classification, tracking, reconstruction to bring much needed quantitative information not easily available by trained human specialists

  16. 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...

  17. 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 ...

  18. Automated quantitative image analysis of nanoparticle assembly

    Science.gov (United States)

    Murthy, Chaitanya R.; Gao, Bo; Tao, Andrea R.; Arya, Gaurav

    2015-05-01

    The ability to characterize higher-order structures formed by nanoparticle (NP) assembly is critical for predicting and engineering the properties of advanced nanocomposite materials. Here we develop a quantitative image analysis software to characterize key structural properties of NP clusters from experimental images of nanocomposites. This analysis can be carried out on images captured at intermittent times during assembly to monitor the time evolution of NP clusters in a highly automated manner. The software outputs averages and distributions in the size, radius of gyration, fractal dimension, backbone length, end-to-end distance, anisotropic ratio, and aspect ratio of NP clusters as a function of time along with bootstrapped error bounds for all calculated properties. The polydispersity in the NP building blocks and biases in the sampling of NP clusters are accounted for through the use of probabilistic weights. This software, named Particle Image Characterization Tool (PICT), has been made publicly available and could be an invaluable resource for researchers studying NP assembly. To demonstrate its practical utility, we used PICT to analyze scanning electron microscopy images taken during the assembly of surface-functionalized metal NPs of differing shapes and sizes within a polymer matrix. PICT is used to characterize and analyze the morphology of NP clusters, providing quantitative information that can be used to elucidate the physical mechanisms governing NP assembly.The ability to characterize higher-order structures formed by nanoparticle (NP) assembly is critical for predicting and engineering the properties of advanced nanocomposite materials. Here we develop a quantitative image analysis software to characterize key structural properties of NP clusters from experimental images of nanocomposites. This analysis can be carried out on images captured at intermittent times during assembly to monitor the time evolution of NP clusters in a highly automated

  19. Information processing in medical imaging

    International Nuclear Information System (INIS)

    Fast-track conference proceedings. State-of-the-art research. Up-to-date results. This book constitutes the refereed proceedings of the 22nd International Conference on Information Processing in Medical Imaging, IPMI 2011, held at Kloster Irsee, Germany, in July 2011. The 24 full papers and 39 poster papers included in this volume were carefully reviewed and selected from 224 submissions. The papers are organized in topical sections on segmentation, statistical methods, shape analysis, registration, diffusion imaging, disease progression modeling, and computer aided diagnosis. The poster sessions deal with segmentation, shape analysis, statistical methods, image reconstruction, microscopic image analysis, computer aided diagnosis, diffusion imaging, functional brain analysis, registration and other related topics.

  20. The future of medical imaging

    International Nuclear Information System (INIS)

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

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. Archimedes, an archive of medical images.

    Science.gov (United States)

    Tahmoush, Dave; Samet, Hanan

    2006-01-01

    We present a medical image and medical record database for the storage, research, transmission, and evaluation of medical images. Medical images from any source that supports the DICOM standard can be stored and accessed, as well as associated analysis and annotations. Retrieval is based on patient info, date, doctor's annotations, features in the images, or a spatial combination. This database supports the secure transmission of sensitive data for tele-medicine and follows all HIPPA regulations. PMID:17238733

  6. Archimedes, an Archive of Medical Images

    OpenAIRE

    Tahmoush, Dave; Samet, Hanan

    2006-01-01

    We present a medical image and medical record database for the storage, research, transmission, and evaluation of medical images. Medical images from any source that supports the DICOM standard can be stored and accessed, as well as associated analysis and annotations. Retrieval is based on patient info, date, doctor’s annotations, features in the images, or a spatial combination. This database supports the secure transmission of sensitive data for tele-medicine and follows all HIPPA regulati...

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

    Science.gov (United States)

    Huang, H K

    2014-01-01

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

  8. 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

  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 is...... neither optimal nor complete and merely serves as an additional input for comprehending the algorithms. It is no secret that this book is written by two authors. The keen reader will therefore note changes in style and language throughout the text....

  10. 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.

  11. 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 ...

  12. 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 ...

  13. 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

  14. 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

  15. 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

  16. 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.

  17. Automated feature extraction and classification from image sources

    Science.gov (United States)

    U.S. Geological Survey

    1995-01-01

    The U.S. Department of the Interior, U.S. Geological Survey (USGS), and Unisys Corporation have completed a cooperative research and development agreement (CRADA) to explore automated feature extraction and classification from image sources. The CRADA helped the USGS define the spectral and spatial resolution characteristics of airborne and satellite imaging sensors necessary to meet base cartographic and land use and land cover feature classification requirements and help develop future automated geographic and cartographic data production capabilities. The USGS is seeking a new commercial partner to continue automated feature extraction and classification research and development.

  18. 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

  19. 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.

  20. An automated medication system reduces errors in the medication administration process: results from a Danish hospital study

    DEFF Research Database (Denmark)

    Risør, Bettina Wulff; Lisby, Marianne; Sørensen, Jan

    2015-01-01

    Abstract Objectives: Improvements in a hospital's medication administration process might reduce the prevalence of medication errors and improve patient safety. The objective of this study was to evaluate the success of an automated medication system in reducing medication administration errors...... number of doses (opportunities for errors). Logistic regression was used to assess changes in error rates after implementation of the automated medication system with time, group, and interaction between time and group as independent variables. The estimated parameter for the interaction term was...... the control ward. The overall risk of errors was reduced by 57% in the intervention ward compared with the control ward (OR 0.43; 95% CI 0.30 to 0.63). Conclusions: The automated medication system reduced the error rate of the medication administration process and thus improved patient safety in the...

  1. Automated de-identification of free-text medical records

    Directory of Open Access Journals (Sweden)

    Long William J

    2008-07-01

    Full Text Available Abstract Background Text-based patient medical records are a vital resource in medical research. In order to preserve patient confidentiality, however, the U.S. Health Insurance Portability and Accountability Act (HIPAA requires that protected health information (PHI be removed from medical records before they can be disseminated. Manual de-identification of large medical record databases is prohibitively expensive, time-consuming and prone to error, necessitating automatic methods for large-scale, automated de-identification. Methods We describe an automated Perl-based de-identification software package that is generally usable on most free-text medical records, e.g., nursing notes, discharge summaries, X-ray reports, etc. The software uses lexical look-up tables, regular expressions, and simple heuristics to locate both HIPAA PHI, and an extended PHI set that includes doctors' names and years of dates. To develop the de-identification approach, we assembled a gold standard corpus of re-identified nursing notes with real PHI replaced by realistic surrogate information. This corpus consists of 2,434 nursing notes containing 334,000 words and a total of 1,779 instances of PHI taken from 163 randomly selected patient records. This gold standard corpus was used to refine the algorithm and measure its sensitivity. To test the algorithm on data not used in its development, we constructed a second test corpus of 1,836 nursing notes containing 296,400 words. The algorithm's false negative rate was evaluated using this test corpus. Results Performance evaluation of the de-identification software on the development corpus yielded an overall recall of 0.967, precision value of 0.749, and fallout value of approximately 0.002. On the test corpus, a total of 90 instances of false negatives were found, or 27 per 100,000 word count, with an estimated recall of 0.943. Only one full date and one age over 89 were missed. No patient names were missed in either

  2. 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

  3. Semantic annotation system for medical images

    OpenAIRE

    Κόλιας, Βασίλειος

    2011-01-01

    Nowadays,hospitals are equipped with high resolution medical imaging systems such as MRI, CT that help the radiologists to make more accurate diagnosis. However these systems cannot give any information of the explicit content that is on the image pixels. The vast amount of images that are produced in hospitals is processed mainly by the medical ...

  4. Medical Image Denoising Using Bilateral Filter

    Directory of Open Access Journals (Sweden)

    Devanand Bhonsle

    2012-07-01

    Full Text Available Medical image processing is used for the diagnosis of diseases by the physicians or radiologists. Noise is introduced to the medical images due to various factors in medical imaging. Noise corrupts the medical images and the quality of the images degrades. This degradation includes suppression of edges, structural details, blurring boundaries etc. To diagnose diseases edge and details preservation are very important. Medical image denoising can help the physicians to diagnose the diseases. Medical images include MRI, CT scan, x-ray images, ultrasound images etc. In this paper we implemented bilateral filtering for medical image denoising. Its formulation & implementation are easy but the performance of bilateral filter depends upon its parameter. Therefore for obtaining the optimum result parameter must be estimated. We have applied bilateral filtering on medical images which are corrupted by additive white Gaussian noise with different values of variances. It is a nonlinear and local technique that preserves the features while smoothing the images. It removes the additive white Gaussian noise effectively but its performance is poor in removing salt and pepper noise.

  5. Medical Imaging Physics, 4th Edition

    Science.gov (United States)

    Hendee, William R.; Ritenour, E. Russell

    2002-05-01

    This comprehensive publication covers all aspects of image formation in modern medical imaging modalities, from radiography, fluoroscopy, and computed tomography, to magnetic resonance imaging and ultrasound. It addresses the techniques and instrumentation used in the rapidly changing field of medical imaging. Now in its fourth edition, this text provides the reader with the tools necessary to be comfortable with the physical principles, equipment, and procedures used in diagnostic imaging, as well as appreciate the capabilities and limitations of the technologies.

  6. Lesion Contrast Enhancement in Medical Ultrasound Imaging

    DEFF Research Database (Denmark)

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

    1997-01-01

    . Automated graylevel mapping is used in combination with a contrast-weighted form of frequency-diversity speckle reduction. In clinical studies, the techniques have yielded mean CNR improvements of 3.2 dB above ordinary frequency-diversity imaging and 5.6 dB over sharper conventional images, with no post-processing...

  7. 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

  8. 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.

  9. Medical imaging and augmented reality. Proceedings

    International Nuclear Information System (INIS)

    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.)

  10. 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...

  11. Critiquing Physician Decision Making Using Data from Automated Medical Records: Assessing the Limitations

    OpenAIRE

    Van Der Lei, Johan; Musen, Mark A.; van der Does, Emiel; Manintveld, Arie J.

    1990-01-01

    This paper describes the evaluation of a critiquing system, HYPERCRITIC, that relies on automated medical records for its data input. The purpose of HYPERCRITIC is to offer comments to general practitioners on their treatment of hypertension. HYPERCRITIC has access to the data stored in a primary-care information system that supports a fully automated medical record. Medical records of 20 patients with hypertension were submitted to both physicians and HYPERCRITIC. The critique generated by t...

  12. 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...

  13. Tooling Techniques Enhance Medical Imaging

    Science.gov (United States)

    2012-01-01

    mission. The manufacturing techniques developed to create the components have yielded innovations advancing medical imaging, transportation security, and even energy efficiency.

  14. 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

  15. 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.

  16. Morphological Techniques for Medical Images: A Review

    Directory of Open Access Journals (Sweden)

    Isma Irum

    2012-08-01

    Full Text Available Image processing is playing a very important role in medical imaging with its versatile applications and features towards the development of computer aided diagnostic systems, automatic detections of abnormalities and enhancement in ultrasonic, computed tomography, magnetic resonance images and lots more applications. Medical images morphology is a field of study where the medical images are observed and processed on basis of geometrical and changing structures. Medical images morphological techniques has been reviewed in this study underlying the some human organ images, the associated diseases and processing techniques to address some anatomical problem detection. Images of Human brain, bone, heart, carotid, iris, lesion, liver and lung have been discussed in this study.

  17. 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.

  18. Organization and visualization of medical images in radiotherapy

    International Nuclear Information System (INIS)

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

  19. Automated medical diagnosis with fuzzy stochastic models: monitoring chronic diseases.

    Science.gov (United States)

    Jeanpierre, Laurent; Charpillet, François

    2004-01-01

    As the world population ages, the patients per physician ratio keeps on increasing. This is even more important in the domain of chronic pathologies where people are usually monitored for years and need regular consultations. To address this problem, we propose an automated system to monitor a patient population, detecting anomalies in instantaneous data and in their temporal evolution, so that it could alert physicians. By handling the population of healthy patients autonomously and by drawing the physicians' attention to the patients-at-risk, the system allows physicians to spend comparatively more time with patients who need their services. In such a system, the interaction between the patients, the diagnosis module, and the physicians is very important. We have based this system on a combination of stochastic models, fuzzy filters, and strong medical semantics. We particularly focused on a particular tele-medicine application: the Diatelic Project. Its objective is to monitor chronic kidney-insufficient patients and to detect hydration troubles. During two years, physicians from the ALTIR have conducted a prospective randomized study of the system. This experiment clearly shows that the proposed system is really beneficial to the patients' health. PMID:15520535

  20. [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

  1. Automating proliferation rate estimation from Ki-67 histology images

    Science.gov (United States)

    Al-Lahham, Heba Z.; Alomari, Raja S.; Hiary, Hazem; Chaudhary, Vipin

    2012-03-01

    Breast cancer is the second cause of women death and the most diagnosed female cancer in the US. Proliferation rate estimation (PRE) is one of the prognostic indicators that guide the treatment protocols and it is clinically performed from Ki-67 histopathology images. Automating PRE substantially increases the efficiency of the pathologists. Moreover, presenting a deterministic and reproducible proliferation rate value is crucial to reduce inter-observer variability. To that end, we propose a fully automated CAD system for PRE from the Ki-67 histopathology images. This CAD system is based on a model of three steps: image pre-processing, image clustering, and nuclei segmentation and counting that are finally followed by PRE. The first step is based on customized color modification and color-space transformation. Then, image pixels are clustered by K-Means depending on the features extracted from the images derived from the first step. Finally, nuclei are segmented and counted using global thresholding, mathematical morphology and connected component analysis. Our experimental results on fifty Ki-67-stained histopathology images show a significant agreement between our CAD's automated PRE and the gold standard's one, where the latter is an average between two observers' estimates. The Paired T-Test, for the automated and manual estimates, shows ρ = 0.86, 0.45, 0.8 for the brown nuclei count, blue nuclei count, and proliferation rate, respectively. Thus, our proposed CAD system is as reliable as the pathologist estimating the proliferation rate. Yet, its estimate is reproducible.

  2. 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.

  3. 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.

  4. 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.

  5. A survey of medical diagnostic imaging technologies

    Energy Technology Data Exchange (ETDEWEB)

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

    1991-10-01

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

  6. 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.

  7. 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

  8. 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.

  9. Current perspectives in medical image perception

    OpenAIRE

    Elizabeth A Krupinski

    2010-01-01

    Medical images constitute a core portion of the information a physician utilizes to render diagnostic and treatment decisions. At a fundamental level, this diagnostic process involves two basic processes: visually inspecting the image (visual perception) and rendering an interpretation (cognition). The likelihood of error in the interpretation of medical images is, unfortunately, not negligible. Errors do occur, and patients’ lives are impacted, underscoring our need to understand how physici...

  10. The physics of medical imaging

    International Nuclear Information System (INIS)

    A state of the art collection of papers is presented, describing the physical principles underlying imaging techniques useful in diagnostic medicine. Some historical perspective and speculation for the future are set out. The subject is dealt with under the following headings:-diagnostic radiology with x-rays, quality assurance and image improvement in diagnostic radiology with x-rays, x-ray transmission computed tomography, clinical applications of computerized tomography in radiotherapy planning, the physics of radioisotope imaging, diagnostic ultrasound, spatially localised nuclear magnetic resonance, physical aspects of infra-red imaging, electrical impedance imaging, diaphanography imaging, mathematics of image formation and image processing, perception and interpretation of images, computer requirements of imaging systems, radiation hazards and relative roles of imaging modalities. (UK)

  11. 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.

  12. Fuzzy emotional semantic analysis and automated annotation of scene images.

    Science.gov (United States)

    Cao, Jianfang; Chen, Lichao

    2015-01-01

    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. PMID:25838818

  13. 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.

  14. 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...

  15. 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.

  16. 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)

  17. Medical image analysis with artificial neural networks.

    Science.gov (United States)

    Jiang, J; Trundle, P; Ren, J

    2010-12-01

    Given that neural networks have been widely reported in the research community of medical imaging, we provide a focused literature survey on recent neural network developments in computer-aided diagnosis, medical image segmentation and edge detection towards visual content analysis, and medical image registration for its pre-processing and post-processing, with the aims of increasing awareness of how neural networks can be applied to these areas and to provide a foundation for further research and practical development. Representative techniques and algorithms are explained in detail to provide inspiring examples illustrating: (i) how a known neural network with fixed structure and training procedure could be applied to resolve a medical imaging problem; (ii) how medical images could be analysed, processed, and characterised by neural networks; and (iii) how neural networks could be expanded further to resolve problems relevant to medical imaging. In the concluding section, a highlight of comparisons among many neural network applications is included to provide a global view on computational intelligence with neural networks in medical imaging. PMID:20713305

  18. 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...

  19. 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

  20. An automated and simple method for brain MR image extraction

    OpenAIRE

    Zhu Zixin; Liu Jiafeng; Zhang Haiyan; Li Haiyun

    2011-01-01

    Abstract Background The extraction of brain tissue from magnetic resonance head images, is an important image processing step for the analyses of neuroimage data. The authors have developed an automated and simple brain extraction method using an improved geometric active contour model. Methods The method uses an improved geometric active contour model which can not only solve the boundary leakage problem but also is less sensitive to intensity inhomogeneity. The method defines the initial fu...

  1. A Data Acquisition System for Medical Imaging

    International Nuclear Information System (INIS)

    A data acquisition system for medical imaging applications is presented. Developed at CPPM, it provides high performance generic data acquisition and processing capabilities. The DAQ system is based on the PICMG xTCA standard and is composed of 1 up to 10 cards in a single rack, each one with 2 Altera Stratix IV FPGAs and a Fast Mezzanine Connector (FMC). Several mezzanines have been produced, each one with different functionalities. Some examples are: a mezzanine capable of receiving 36 optical fibres with up to 180 Gbps sustained data rates or a mezzanine with 12 x 5 Gbps input links, 12 x 5 Gbps output links and an SFP+ connector for control purposes. Several rack sizes are also available, thus making the system scalable from a one card desktop system useful for development purpose up to a full featured rack mounted DAQ for high end applications. Depending on the application, boards may exchange data at speeds of up to 25.6 Gbps bidirectional sustained rates in a double star topology through back-plane connections. Also, front panel optical fibres can be used when higher rates are required by the application. The system may be controlled by a standard Ethernet connection, thus providing easy integration with control computers and avoiding the need for drivers. Two control systems are foreseen. A Socket connection provides easy interaction with automation software regardless of the operating system used for the control PC. Moreover a web server may run on the Envision cards and provide an easy intuitive user interface. The system and its different components will be introduced. Some preliminary measurements with high speed signal links will be presented as well as the signal conditioning used to allow these rates. (authors)

  2. Automated Archiving of Archaeological Aerial Images

    Directory of Open Access Journals (Sweden)

    Michael Doneus

    2016-03-01

    Full Text Available The main purpose of any aerial photo archive is to allow quick access to images based on content and location. Therefore, next to a description of technical parameters and depicted content, georeferencing of every image is of vital importance. This can be done either by identifying the main photographed object (georeferencing of the image content or by mapping the center point and/or the outline of the image footprint. The paper proposes a new image archiving workflow. The new pipeline is based on the parameters that are logged by a commercial, but cost-effective GNSS/IMU solution and processed with in-house-developed software. Together, these components allow one to automatically geolocate and rectify the (oblique aerial images (by a simple planar rectification using the exterior orientation parameters and to retrieve their footprints with reasonable accuracy, which is automatically stored as a vector file. The data of three test flights were used to determine the accuracy of the device, which turned out to be better than 1° for roll and pitch (mean between 0.0 and 0.21 with a standard deviation of 0.17–0.46 and better than 2.5° for yaw angles (mean between 0.0 and −0.14 with a standard deviation of 0.58–0.94. This turned out to be sufficient to enable a fast and almost automatic GIS-based archiving of all of the imagery.

  3. 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

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

    Energy Technology Data Exchange (ETDEWEB)

    Wells, J; Wilson, J; Zhang, Y; Samei, E; Ravin, Carl E. [Advanced Imaging Laboratories, Duke Clinical Imaging Physics Group, Department of Radiology, Duke University Medical Center, Durham, NC (United States)

    2014-06-01

    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

  5. 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.

  6. 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.

  7. Medical imaging and augmented reality. Proceedings

    International Nuclear Information System (INIS)

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

  8. 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

  9. Automated planning of breast radiotherapy using cone beam CT imaging

    Energy Technology Data Exchange (ETDEWEB)

    Amit, Guy [Radiation Medicine Program, Princess Margaret Cancer Centre, Toronto, Ontario M5G2M9 (Canada); Purdie, Thomas G., E-mail: tom.purdie@rmp.uhn.ca [Radiation Medicine Program, Princess Margaret Cancer Centre, Toronto, Ontario M5G2M9 (Canada); Department of Radiation Oncology, University of Toronto, Toronto, Ontario M5S 3E2 (Canada); Techna Institute, University Health Network, University of Toronto, Toronto, Ontario M5G 1P5 (Canada)

    2015-02-15

    Purpose: Develop and clinically validate a methodology for using cone beam computed tomography (CBCT) imaging in an automated treatment planning framework for breast IMRT. Methods: A technique for intensity correction of CBCT images was developed and evaluated. The technique is based on histogram matching of CBCT image sets, using information from “similar” planning CT image sets from a database of paired CBCT and CT image sets (n = 38). Automated treatment plans were generated for a testing subset (n = 15) on the planning CT and the corrected CBCT. The plans generated on the corrected CBCT were compared to the CT-based plans in terms of beam parameters, dosimetric indices, and dose distributions. Results: The corrected CBCT images showed considerable similarity to their corresponding planning CTs (average mutual information 1.0±0.1, average sum of absolute differences 185 ± 38). The automated CBCT-based plans were clinically acceptable, as well as equivalent to the CT-based plans with average gantry angle difference of 0.99°±1.1°, target volume overlap index (Dice) of 0.89±0.04 although with slightly higher maximum target doses (4482±90 vs 4560±84, P < 0.05). Gamma index analysis (3%, 3 mm) showed that the CBCT-based plans had the same dose distribution as plans calculated with the same beams on the registered planning CTs (average gamma index 0.12±0.04, gamma <1 in 99.4%±0.3%). Conclusions: The proposed method demonstrates the potential for a clinically feasible and efficient online adaptive breast IMRT planning method based on CBCT imaging, integrating automation.

  10. 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...

  11. Medical Image Processing with Graphics Hardware

    OpenAIRE

    Enders, Frank

    2009-01-01

    The advancements in medical imaging over the past decades have been remarkable and so is the relevance for today's medical procedures. The various imaging techniques have significantly improved both diagnosis and treatment. New insights have been gained and new therapy approaches have been developed. However, these advancements come at high costs. The required hardware and infrastructure are getting increasingly expensive. The enormous amount of data, generated by the scanners, needs to be st...

  12. 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

  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. Information Retrieval Technique in Medical Imaging Technology

    Directory of Open Access Journals (Sweden)

    Azrulhizam Shapi'i

    2011-01-01

    Full Text Available The medical field at present is an example for appropriate innovation in the information technology sector where it can bring benefits to physicians and patients and also the medical tools to prevent disease.  Among the examples of innovation in information technology are in the field of medical imaging technology, laser technology, nanotechnology and others. As we know, medical imaging technology is very important because it can help medical experts in conducting research on patients.  A medical image is known as DICOM.  DICOM format is unique, it is not only contain the image of the patient, but it also contains information related to the patient. This paper will show the development of software to retrieve the information from the digital x-ray image (DICOM. Software developed using Netbeans and library used was pixelmed library. This software is then tested with a number of patient data. Results showed that the software is able to find the information contained in the patient x-ray images accurately.

  15. An Automated Image Processing System for Concrete Evaluation

    Energy Technology Data Exchange (ETDEWEB)

    Baumgart, C.W.; Cave, S.P.; Linder, K.E.

    1998-11-23

    AlliedSignal Federal Manufacturing & Technologies (FM&T) was asked to perform a proof-of-concept study for the Missouri Highway and Transportation Department (MHTD), Research Division, in June 1997. The goal of this proof-of-concept study was to ascertain if automated scanning and imaging techniques might be applied effectively to the problem of concrete evaluation. In the current evaluation process, a concrete sample core is manually scanned under a microscope. Voids (or air spaces) within the concrete are then detected visually by a human operator by incrementing the sample under the cross-hairs of a microscope and by counting the number of "pixels" which fall within a void. Automation of the scanning and image analysis processes is desired to improve the speed of the scanning process, to improve evaluation consistency, and to reduce operator fatigue. An initial, proof-of-concept image analysis approach was successfully developed and demonstrated using acquired black and white imagery of concrete samples. In this paper, the automated scanning and image capture system currently under development will be described and the image processing approach developed for the proof-of-concept study will be demonstrated. A development update and plans for future enhancements are also presented.

  16. An Automated, Image Processing System for Concrete Evaluation

    International Nuclear Information System (INIS)

    Allied Signal Federal Manufacturing ampersand Technologies (FM ampersand T) was asked to perform a proof-of-concept study for the Missouri Highway and Transportation Department (MHTD), Research Division, in June 1997. The goal of this proof-of-concept study was to ascertain if automated scanning and imaging techniques might be applied effectively to the problem of concrete evaluation. In the current evaluation process, a concrete sample core is manually scanned under a microscope. Voids (or air spaces) within the concrete are then detected visually by a human operator by incrementing the sample under the cross-hairs of a microscope and by counting the number of ''pixels'' which fall within a void. Automation of the scanning and image analysis processes is desired to improve the speed of the scanning process, to improve evaluation consistency, and to reduce operator fatigue. An initial, proof-of-concept image analysis approach was successfully developed and demonstrated using acquired black and white imagery of concrete samples. In this paper, the automated scanning and image capture system currently under development will be described and the image processing approach developed for the proof-of-concept study will be demonstrated. A development update and plans for future enhancements are also presented

  17. 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.

  18. Image processing for medical diagnosis using CNN

    Energy Technology Data Exchange (ETDEWEB)

    Arena, Paolo E-mail: parena@dees.unict.it; Basile, Adriano; Bucolo, Maide; Fortuna, Luigi

    2003-01-21

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

  19. 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.

  20. Image processing for medical diagnosis using CNN

    International Nuclear Information System (INIS)

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

  1. 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...

  2. Automated Image Registration Using Morphological Region of Interest Feature Extraction

    Science.gov (United States)

    Plaza, Antonio; LeMoigne, Jacqueline; Netanyahu, Nathan S.

    2005-01-01

    With the recent explosion in the amount of remotely sensed imagery and the corresponding interest in temporal change detection and modeling, image registration has become increasingly important as a necessary first step in the integration of multi-temporal and multi-sensor data for applications such as the analysis of seasonal and annual global climate changes, as well as land use/cover changes. The task of image registration can be divided into two major components: (1) the extraction of control points or features from images; and (2) the search among the extracted features for the matching pairs that represent the same feature in the images to be matched. Manual control feature extraction can be subjective and extremely time consuming, and often results in few usable points. Automated feature extraction is a solution to this problem, where desired target features are invariant, and represent evenly distributed landmarks such as edges, corners and line intersections. In this paper, we develop a novel automated registration approach based on the following steps. First, a mathematical morphology (MM)-based method is used to obtain a scale-orientation morphological profile at each image pixel. Next, a spectral dissimilarity metric such as the spectral information divergence is applied for automated extraction of landmark chips, followed by an initial approximate matching. This initial condition is then refined using a hierarchical robust feature matching (RFM) procedure. Experimental results reveal that the proposed registration technique offers a robust solution in the presence of seasonal changes and other interfering factors. Keywords-Automated image registration, multi-temporal imagery, mathematical morphology, robust feature matching.

  3. Anniversary paper: evaluation of medical imaging systems.

    Science.gov (United States)

    Krupinski, Elizabeth A; Jiang, Yulei

    2008-02-01

    Medical imaging used to be primarily within the domain of radiology, but with the advent of virtual pathology slides and telemedicine, imaging technology is expanding in the healthcare enterprise. As new imaging technologies are developed, they must be evaluated to assess the impact and benefit on patient care. The authors review the hierarchical model of the efficacy of diagnostic imaging systems by Fryback and Thornbury [Med. Decis. Making 11, 88-94 (1991)] as a guiding principle for system evaluation. Evaluation of medical imaging systems encompasses everything from the hardware and software used to acquire, store, and transmit images to the presentation of images to the interpreting clinician. Evaluation of medical imaging systems can take many forms, from the purely technical (e.g., patient dose measurement) to the increasingly complex (e.g., determining whether a new imaging method saves lives and benefits society). Evaluation methodologies cover a broad range, from receiver operating characteristic (ROC) techniques that measure diagnostic accuracy to timing studies that measure image-interpretation workflow efficiency. The authors review briefly the history of the development of evaluation methodologies and review ROC methodology as well as other types of evaluation methods. They discuss unique challenges in system evaluation that face the imaging community today and opportunities for future advances. PMID:18383686

  4. 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.

  5. 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

  6. 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.

  7. 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.

  8. 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.

  9. 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

  10. 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.

  11. 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.

  12. Multi-channel medical imaging system

    Energy Technology Data Exchange (ETDEWEB)

    Frangioni, John V

    2013-12-31

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

  13. Teaching about the Physics of Medical Imaging

    Science.gov (United States)

    Zollman, Dean; McBride, Dyan; Murphy, Sytil; Aryal, Bijaya; Kalita, Spartak; Wirjawan, Johannes v. d.

    2010-07-01

    Even before the discovery of X-rays, attempts at non-invasive medical imaging required an understanding of fundamental principles of physics. Students frequently do not see these connections because they are not taught in beginning physics courses. To help students understand that physics and medical imaging are closely connected, we have developed a series of active learning units. For each unit we begin by studying how students transfer their knowledge from traditional physics classes and everyday experiences to medical applications. Then, we build instructional materials to take advantage of the students' ability to use their existing learning and knowledge resources. Each of the learning units involves a combination of hands-on activities, which present analogies, and interactive computer simulations. Our learning units introduce students to the contemporary imaging techniques of CT scans, magnetic resonance imaging (MRI), positron emission tomography (PET), and wavefront aberrometry. The project's web site is http://web.phys.ksu.edu/mmmm/.

  14. Medical Image Retrieval: Past and Present

    Science.gov (United States)

    Hwang, Kyung Hoon; Lee, Haejun

    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 retrieval systems combined with semantic systems are required. PMID:22509468

  15. 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.

  16. 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

  17. Image Registration in Medical Image Processing -An Overview

    OpenAIRE

    Dr.P.Latha; Baby D. Dayana; N. Meffiya

    2014-01-01

    Image registration the process is very difficult problem facing in medical field . The process of image registration is an automatic or manual procedure. It tries to find similar points between two images and align themto minimize the “error”, i.e. distance measure between twoimages.The dataset can be multiple photographs like MRI,spect,CT scan images from different times ,depths or viewpoints.The purpose of this paper is to provide a overall information about the exis...

  18. 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.

  19. Immediate structured visual search for medical images.

    Science.gov (United States)

    Simonyan, Karen; Zisserman, Andrew; Criminisi, Antonio

    2011-01-01

    The objective of this work is a scalable, real-time visual search engine for medical images. In contrast to existing systems that retrieve images that are globally similar to a query image, we enable the user to select a query Region Of Interest (ROI) and automatically detect the corresponding regions within all returned images. This allows the returned images to be ranked on the content of the ROI, rather than the entire image. Our contribution is two-fold: (i) immediate retrieval - the data is appropriately pre-processed so that the search engine returns results in real-time for any query image and ROI; (ii) structured output - returning ROIs with a choice of ranking functions. The retrieval performance is assessed on a number of annotated queries for images from the IRMA X-ray dataset and compared to a baseline. PMID:22003711

  20. Perspectives of medical X-ray imaging

    Science.gov (United States)

    Freudenberger, J.; Hell, E.; Knüpfer, W.

    2001-06-01

    While X-ray image intensifiers (XII), storage phosphor screens and film-screen systems are still the work horses of medical imaging, large flat panel solid state detectors using either scintillators and amorphous silicon photo diode arrays (FD-Si), or direct X-ray conversion in amorphous selenium are reaching maturity. The main advantage with respect to image quality and low patient dose of the XII and FD-Si systems is caused by the rise of the Detector Quantum Efficiency originating from the application of thick needle-structured phosphor X-ray absorbers. With the detectors getting closer to an optimal state, further progress in medical X-ray imaging requires an improvement of the usable source characteristics. The development of clinical monochromatic X-ray sources of high power would not only allow an improved contrast-to-dose ratio by allowing smaller average photon energies in applications but would also lead to new imaging techniques.

  1. Perspectives of medical X-ray imaging

    International Nuclear Information System (INIS)

    While X-ray image intensifiers (XII), storage phosphor screens and film-screen systems are still the work horses of medical imaging, large flat panel solid state detectors using either scintillators and amorphous silicon photo diode arrays (FD-Si), or direct X-ray conversion in amorphous selenium are reaching maturity. The main advantage with respect to image quality and low patient dose of the XII and FD-Si systems is caused by the rise of the Detector Quantum Efficiency originating from the application of thick needle-structured phosphor X-ray absorbers. With the detectors getting closer to an optimal state, further progress in medical X-ray imaging requires an improvement of the usable source characteristics. The development of clinical monochromatic X-ray sources of high power would not only allow an improved contrast-to-dose ratio by allowing smaller average photon energies in applications but would also lead to new imaging techniques

  2. Perspectives of medical X-ray imaging

    Energy Technology Data Exchange (ETDEWEB)

    Freudenberger, J. E-mail: joerg.freudenberger@med.siemens.de; Hell, E.; Knuepfer, W

    2001-06-21

    While X-ray image intensifiers (XII), storage phosphor screens and film-screen systems are still the work horses of medical imaging, large flat panel solid state detectors using either scintillators and amorphous silicon photo diode arrays (FD-Si), or direct X-ray conversion in amorphous selenium are reaching maturity. The main advantage with respect to image quality and low patient dose of the XII and FD-Si systems is caused by the rise of the Detector Quantum Efficiency originating from the application of thick needle-structured phosphor X-ray absorbers. With the detectors getting closer to an optimal state, further progress in medical X-ray imaging requires an improvement of the usable source characteristics. The development of clinical monochromatic X-ray sources of high power would not only allow an improved contrast-to-dose ratio by allowing smaller average photon energies in applications but would also lead to new imaging techniques.

  3. 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.

  4. Bioresponsive nanosensors in medical imaging

    OpenAIRE

    Schellenberger, Eyk

    2009-01-01

    Superparamagnetic iron oxide nanoparticles have been established as sensitive probes for magnetic resonance imaging (MRI). While the majority of specific nanosensors are based on sterically stabilized iron oxide particles, the focus of this review is on the use of very small iron oxide particles (VSOPs) that are electrostatically stabilized by an anionic citrate acid shell. We used VSOPs to develop target-specific as well as protease-activatable nanosensors for molecular MRI.

  5. Bioresponsive nanosensors in medical imaging.

    Science.gov (United States)

    Schellenberger, Eyk

    2010-02-01

    Superparamagnetic iron oxide nanoparticles have been established as sensitive probes for magnetic resonance imaging (MRI). While the majority of specific nanosensors are based on sterically stabilized iron oxide particles, the focus of this review is on the use of very small iron oxide particles (VSOPs) that are electrostatically stabilized by an anionic citrate acid shell. We used VSOPs to develop target-specific as well as protease-activatable nanosensors for molecular MRI. PMID:19846442

  6. Medical images storage using discrete cosine transform

    International Nuclear Information System (INIS)

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

  7. 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...

  8. DICOM Metadata repository for technical information in digital medical images

    International Nuclear Information System (INIS)

    The diagnostic medical image contains, apart from the pixel data, a detailed description of how the image was produced. The information reveals details on image geometry, radiation data as well as more complex quality index in a varying degree, mostly dependent on the age of the equipment. There is no simple way to retrieve, process and display this data in a general image workstation. Material and Methods. Since November 2004 a DICOM metadata repository has been used to record image header parameters. The automated data extraction, storage and display are based on simple standard programming and have performed without malfunction since the start, today containing metadata from 18 million images. Results. The data in the metadata repository has been used in dose optimization for a Computed Radiography image plate system, analyzing the exposure index and making use of the possibilities to organize the data in examinations, projections as well as examination rooms. Analysis of exposure index in the context of these parameters shows promising qualities as it makes detection of dosimetric problems as well as follow-up of dose adjustments simpler. Current work is aimed at creating a vendor independent platform and to further develop methods to support dose optimization for flat panel direct digital detectors and computed tomography (CT) systems. The possibilities to detect equipment malfunction will be further investigated

  9. 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)

  10. Automating PACS quality control with the Vanderbilt image processing enterprise resource

    Science.gov (United States)

    Esparza, Michael L.; Welch, E. Brian; Landman, Bennett A.

    2012-02-01

    Precise image acquisition is an integral part of modern patient care and medical imaging research. Periodic quality control using standardized protocols and phantoms ensures that scanners are operating according to specifications, yet such procedures do not ensure that individual datasets are free from corruption; for example due to patient motion, transient interference, or physiological variability. If unacceptable artifacts are noticed during scanning, a technologist can repeat a procedure. Yet, substantial delays may be incurred if a problematic scan is not noticed until a radiologist reads the scans or an automated algorithm fails. Given scores of slices in typical three-dimensional scans and widevariety of potential use cases, a technologist cannot practically be expected inspect all images. In large-scale research, automated pipeline systems have had great success in achieving high throughput. However, clinical and institutional workflows are largely based on DICOM and PACS technologies; these systems are not readily compatible with research systems due to security and privacy restrictions. Hence, quantitative quality control has been relegated to individual investigators and too often neglected. Herein, we propose a scalable system, the Vanderbilt Image Processing Enterprise Resource (VIPER) to integrate modular quality control and image analysis routines with a standard PACS configuration. This server unifies image processing routines across an institutional level and provides a simple interface so that investigators can collaborate to deploy new analysis technologies. VIPER integrates with high performance computing environments has successfully analyzed all standard scans from our institutional research center over the course of the last 18 months.

  11. 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.

  12. Knowledge requirements for automated inference of medical textbook markup.

    OpenAIRE

    Berrios, D. C.; Kehler, A.; Fagan, L. M.

    1999-01-01

    Indexing medical text in journals or textbooks requires a tremendous amount of resources. We tested two algorithms for automatically indexing nouns, noun-modifiers, and noun phrases, and inferring selected binary relations between UMLS concepts in a textbook of infectious disease. Sixty-six percent of nouns and noun-modifiers and 81% of noun phrases were correctly matched to UMLS concepts. Semantic relations were identified with 100% specificity and 94% sensitivity. For some medical sub-domai...

  13. 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

  14. 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...

  15. 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...

  16. HVS-based medical image compression

    International Nuclear Information System (INIS)

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

  17. AUTOMATED DATA ANALYSIS FOR CONSECUTIVE IMAGES FROM DROPLET COMBUSTION EXPERIMENTS

    Directory of Open Access Journals (Sweden)

    Christopher Lee Dembia

    2012-09-01

    Full Text Available A simple automated image analysis algorithm has been developed that processes consecutive images from high speed, high resolution digital images of burning fuel droplets. The droplets burn under conditions that promote spherical symmetry. The algorithm performs the tasks of edge detection of the droplet’s boundary using a grayscale intensity threshold, and shape fitting either a circle or ellipse to the droplet’s boundary. The results are compared to manual measurements of droplet diameters done with commercial software. Results show that it is possible to automate data analysis for consecutive droplet burning images even in the presence of a significant amount of noise from soot formation. An adaptive grayscale intensity threshold provides the ability to extract droplet diameters for the wide range of noise encountered. In instances where soot blocks portions of the droplet, the algorithm manages to provide accurate measurements if a circle fit is used instead of an ellipse fit, as an ellipse can be too accommodating to the disturbance.

  18. Automated curved planar reformation of 3D spine images

    International Nuclear Information System (INIS)

    Traditional techniques for visualizing anatomical structures are based on planar cross-sections from volume images, such as images obtained by computed tomography (CT) or magnetic resonance imaging (MRI). However, planar cross-sections taken in the coordinate system of the 3D image often do not provide sufficient or qualitative enough diagnostic information, because planar cross-sections cannot follow curved anatomical structures (e.g. arteries, colon, spine, etc). Therefore, not all of the important details can be shown simultaneously in any planar cross-section. To overcome this problem, reformatted images in the coordinate system of the inspected structure must be created. This operation is usually referred to as curved planar reformation (CPR). In this paper we propose an automated method for CPR of 3D spine images, which is based on the image transformation from the standard image-based to a novel spine-based coordinate system. The axes of the proposed spine-based coordinate system are determined on the curve that represents the vertebral column, and the rotation of the vertebrae around the spine curve, both of which are described by polynomial models. The optimal polynomial parameters are obtained in an image analysis based optimization framework. The proposed method was qualitatively and quantitatively evaluated on five CT spine images. The method performed well on both normal and pathological cases and was consistent with manually obtained ground truth data. The proposed spine-based CPR benefits from reduced structural complexity in favour of improved feature perception of the spine. The reformatted images are diagnostically valuable and enable easier navigation, manipulation and orientation in 3D space. Moreover, reformatted images may prove useful for segmentation and other image analysis tasks

  19. Medical imaging. A continuous (r)evolution

    International Nuclear Information System (INIS)

    This article proposes an overview of the principles, evolutions, development, recent innovations, applications, benefits and drawbacks of the various techniques of medical imaging: X rays (fast acquisition, low cost, risks related to ionizing radiations, aid to diagnosis), ultrasounds (portability, real time imaging, low cost, image quality depending on the operator, monitoring or resistance to insulin, detection of the first signs of Alzheimer disease), nuclear medicine (high detection sensitivity but low spatial resolution, use of radioactivity, measurement of bone density, use for detection and for care), magnetic resonance image (no negative biological effect, relatively long acquisition time and high cost, application in soft tissues), the magneto encephalography or MEG (non invasive brain image, high time accuracy, but relatively high cost), and fluorescence (non invasive, real time imaging, but only visible at low depth for now)

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

    International Nuclear Information System (INIS)

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

  1. Automated Dsm Extraction from Uav Images and Performance Analysis

    Science.gov (United States)

    Rhee, S.; Kim, T.

    2015-08-01

    As technology evolves, unmanned aerial vehicles (UAVs) imagery is being used from simple applications such as image acquisition to complicated applications such as 3D spatial information extraction. Spatial information is usually provided in the form of a DSM or point cloud. It is important to generate very dense tie points automatically from stereo images. In this paper, we tried to apply stereo image-based matching technique developed for satellite/aerial images to UAV images, propose processing steps for automated DSM generation and to analyse the possibility of DSM generation. For DSM generation from UAV images, firstly, exterior orientation parameters (EOPs) for each dataset were adjusted. Secondly, optimum matching pairs were determined. Thirdly, stereo image matching was performed with each pair. Developed matching algorithm is based on grey-level correlation on pixels applied along epipolar lines. Finally, the extracted match results were united with one result and the final DSM was made. Generated DSM was compared with a reference DSM from Lidar. Overall accuracy was 1.5 m in NMAD. However, several problems have to be solved in future, including obtaining precise EOPs, handling occlusion and image blurring problems. More effective interpolation technique needs to be developed in the future.

  2. 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...

  3. APES Beamforming Applied to Medical Ultrasound Imaging

    DEFF Research Database (Denmark)

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

    2009-01-01

    Recently, adaptive beamformers have been introduced to medical ultrasound imaging. The primary focus has been on the minimum variance (MV) (or Capon) beamformer. This work investigates an alternative but closely related beamformer, the Amplitude and Phase Estimation (APES) beamformer. APES offers...

  4. 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.

  5. 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

  6. 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 892.2010 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES RADIOLOGY DEVICES Diagnostic Devices § 892.2010 Medical image storage device. (a) Identification. A medical image storage device...

  7. 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 892.2040 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES RADIOLOGY DEVICES Diagnostic Devices § 892.2040 Medical image hardcopy device. (a) Identification. A medical image hardcopy...

  8. 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.

  9. 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

  10. Automating the Photogrammetric Bridging Based on MMS Image Sequence Processing

    Science.gov (United States)

    Silva, J. F. C.; Lemes Neto, M. C.; Blasechi, V.

    2014-11-01

    The photogrammetric bridging or traverse is a special bundle block adjustment (BBA) for connecting a sequence of stereo-pairs and of determining the exterior orientation parameters (EOP). An object point must be imaged in more than one stereo-pair. In each stereo-pair the distance ratio between an object and its corresponding image point varies significantly. We propose to automate the photogrammetric bridging based on a fully automatic extraction of homologous points in stereo-pairs and on an arbitrary Cartesian datum to refer the EOP and tie points. The technique uses SIFT algorithm and the keypoint matching is given by similarity descriptors of each keypoint based on the smallest distance. All the matched points are used as tie points. The technique was applied initially to two pairs. The block formed by four images was treated by BBA. The process follows up to the end of the sequence and it is semiautomatic because each block is processed independently and the transition from one block to the next depends on the operator. Besides four image blocks (two pairs), we experimented other arrangements with block sizes of six, eight, and up to twenty images (respectively, three, four, five and up to ten bases). After the whole image pairs sequence had sequentially been adjusted in each experiment, a simultaneous BBA was run so to estimate the EOP set of each image. The results for classical ("normal case") pairs were analyzed based on standard statistics regularly applied to phototriangulation, and they show figures to validate the process.

  11. 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. PMID:27085311

  12. 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...... agreement between the four pathologists and the VG app was κ=0.71. CONCLUSION: In conclusion, the Visiopharm VG app is able to measure the thickness of a sub-epithelial collagenous band in colon biopsies with an accuracy comparable to the performance of a pathologist and thereby provides a promising...

  13. A special designed library for medical imaging applications

    International Nuclear Information System (INIS)

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

  14. 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

  15. 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.

  16. 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.

  17. Improving the Security of the Medical Images

    Directory of Open Access Journals (Sweden)

    Ahmed Mahmood

    2013-10-01

    Full Text Available Applying security to the transmitted medical images is important to protect the privacy of patients. Secure transmission requires cryptography, and watermarking to achieve confidentiality, and data integrity. Improving cryptography part needs to use an encryption algorithm that stands for a long time against different attacks. The proposed method is based on number theory and uses Chinese remainder theorem as a backbone. This approach achieves high level of security and stands against different attacks for a long time. On watermarking part, the medical image is divided into two regions: a region of interest (ROI and a region of background (ROB. The pixel values of the ROI contain the important information so this region must not experience any change. The proposed watermarking technique is based on dividing the medical image in to blocks and inserting the watermark to the ROI by shifting the blocks. Then, an equivalent number of blocks in the ROB are removed. This approach can be considered as lossless since it does not affect on the ROI, also it does not increase the image size. In addition, it can stand against some watermarking attacks such cropping, and noise

  18. 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

  19. 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.

  20. 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.

  1. 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

  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. 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

  4. Pancreas++ : Automated Quantification of Pancreatic Islet Cells in Microscopy Images

    Directory of Open Access Journals (Sweden)

    StuartMaudsley

    2013-01-01

    Full Text Available The microscopic image analysis of pancreatic Islet of Langerhans morphology is crucial for the investigation of diabetes and metabolic diseases. Besides the general size of the islet, the percentage and relative position of glucagon-containing alpha-, and insulin-containing beta-cells is also important for pathophysiological analyses, especially in rodents. Hence, the ability to identify, quantify and spatially locate peripheral and ‘involuted’ alpha-cells in the islet core is an important analytical goal. There is a dearth of software available for the automated and sophisticated positional-quantification of multiple cell types in the islet core. Manual analytical methods for these analyses, while relatively accurate, can suffer from a slow throughput rate as well as user-based biases. Here we describe a newly developed pancreatic islet analytical software program, Pancreas++, which facilitates the fully-automated, non-biased, and highly reproducible investigation of islet area and alpha- and beta-cell quantity as well as position within the islet for either single or large batches of fluorescent images. We demonstrate the utility and accuracy of Pancreas++ by comparing its performance to other pancreatic islet size and cell type (alpha, beta quantification methods. Our Pancreas++ analysis was significantly faster than other methods, while still retaining low error rates and a high degree of result correlation with the manually generated reference standard.

  5. 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...

  6. 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

  7. 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.

  8. 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.

  9. 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...

  10. 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.

  11. Prospective imaging systems in medical radiodiagnosis

    International Nuclear Information System (INIS)

    Demands laid on visualization systems in medical radiodiagnostics are to increase functions such as: image resolution, contrast sensitivity, and size of the visualized portion of the human body. The aim is to achieve this with a reduced radiation exposure. The achievement of the slated aims and the generation of X-ray pictures of a higher quality may be advanced greatly by modern electronic image and amplification components - semiconductor optoelectronic sensing units (CCD), discrete channel electron multipliers (channel plates). (author). 4 figs., 22 refs

  12. Improving the Security of the Medical Images

    OpenAIRE

    Ahmed Mahmood; Tarfa Hamed; Charlie Obimbo; Robert Dony

    2013-01-01

    Applying security to the transmitted medical images is important to protect the privacy of patients. Secure transmission requires cryptography, and watermarking to achieve confidentiality, and data integrity. Improving cryptography part needs to use an encryption algorithm that stands for a long time against different attacks. The proposed method is based on number theory and uses Chinese remainder theorem as a backbone. This approach achieves high level of security and stands against differe...

  13. 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.

  14. Curve Matching with Applications in Medical Imaging

    OpenAIRE

    Bauer, Martin; Bruveris, Martins; Harms, Philipp; Møller-Andersen, Jakob

    2015-01-01

    In the recent years, Riemannian shape analysis of curves and surfaces has found several applications in medical image analysis. In this paper we present a numerical discretization of second order Sobolev metrics on the space of regular curves in Euclidean space. This class of metrics has several desirable mathematical properties. We propose numerical solutions for the initial and boundary value problems of finding geodesics. These two methods are combined in a Riemannian gradient-based optimi...

  15. 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.

  16. 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.

  17. Medical Image Denoising using Adaptive Threshold Based on Contourlet Transform

    CERN Document Server

    Satheesh, S; 10.5121/acij.2011.2205

    2011-01-01

    Image denoising has become an essential exercise in medical imaging especially the Magnetic Resonance Imaging (MRI). This paper proposes a medical image denoising algorithm using contourlet transform. Numerical results show that the proposed algorithm can obtained higher peak signal to noise ratio (PSNR) than wavelet based denoising algorithms using MR Images in the presence of AWGN.

  18. 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.

  19. 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 Section 892.2020 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES RADIOLOGY DEVICES Diagnostic Devices § 892.2020 Medical image communications device. (a) Identification. A medical...

  20. 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

  1. Image Processing for Automated Analysis of the Fluorescence In-Situ Hybridization (FISH) Microscopic Images

    Czech Academy of Sciences Publication Activity Database

    Schier, Jan; Kovář, Bohumil; Kočárek, E.; Kuneš, Michal

    Berlin Heidelberg: Springer-Verlag, 2011, s. 622-633. (Lecture Notes in Computer Science ). ISBN 978-3-642-24081-2. [5th International Conference, ICHIT 2011. Daejeon (KR), 22.09.2011-24.09.2011] R&D Projects: GA TA ČR TA01010931 Institutional research plan: CEZ:AV0Z10750506 Keywords : fluorescence in-situ hybridization * image processing * image segmentation Subject RIV: IN - Informatics, Computer Science http://library.utia.cas.cz/separaty/2011/ZS/shier-image processing for automated analysis of the fluorescence in-situ hybridization (fish) microscopic images.pdf

  2. Image-based path planning for automated virtual colonoscopy navigation

    Science.gov (United States)

    Hong, Wei

    2008-03-01

    Virtual colonoscopy (VC) is a noninvasive method for colonic polyp screening, by reconstructing three-dimensional models of the colon using computerized tomography (CT). In virtual colonoscopy fly-through navigation, it is crucial to generate an optimal camera path for efficient clinical examination. In conventional methods, the centerline of the colon lumen is usually used as the camera path. In order to extract colon centerline, some time consuming pre-processing algorithms must be performed before the fly-through navigation, such as colon segmentation, distance transformation, or topological thinning. In this paper, we present an efficient image-based path planning algorithm for automated virtual colonoscopy fly-through navigation without the requirement of any pre-processing. Our algorithm only needs the physician to provide a seed point as the starting camera position using 2D axial CT images. A wide angle fisheye camera model is used to generate a depth image from the current camera position. Two types of navigational landmarks, safe regions and target regions are extracted from the depth images. Camera position and its corresponding view direction are then determined using these landmarks. The experimental results show that the generated paths are accurate and increase the user comfort during the fly-through navigation. Moreover, because of the efficiency of our path planning algorithm and rendering algorithm, our VC fly-through navigation system can still guarantee 30 FPS.

  3. Texture-Based Automated Lithological Classification Using Aeromagenetic Anomaly Images

    Science.gov (United States)

    Shankar, Vivek

    2009-01-01

    This report consists of a thesis submitted to the faculty of the Department of Electrical and Computer Engineering, in partial fulfillment of the requirements for the degree of Master of Science, Graduate College, The University of Arizona, 2004 Aeromagnetic anomaly images are geophysical prospecting tools frequently used in the exploration of metalliferous minerals and hydrocarbons. The amplitude and texture content of these images provide a wealth of information to geophysicists who attempt to delineate the nature of the Earth's upper crust. These images prove to be extremely useful in remote areas and locations where the minerals of interest are concealed by basin fill. Typically, geophysicists compile a suite of aeromagnetic anomaly images, derived from amplitude and texture measurement operations, in order to obtain a qualitative interpretation of the lithological (rock) structure. Texture measures have proven to be especially capable of capturing the magnetic anomaly signature of unique lithological units. We performed a quantitative study to explore the possibility of using texture measures as input to a machine vision system in order to achieve automated classification of lithological units. This work demonstrated a significant improvement in classification accuracy over random guessing based on a priori probabilities. Additionally, a quantitative comparison between the performances of five classes of texture measures in their ability to discriminate lithological units was achieved.

  4. Automated target recognition technique for image segmentation and scene analysis

    Science.gov (United States)

    Baumgart, Chris W.; Ciarcia, Christopher A.

    1994-03-01

    Automated target recognition (ATR) software has been designed to perform image segmentation and scene analysis. Specifically, this software was developed as a package for the Army's Minefield and Reconnaissance and Detector (MIRADOR) program. MIRADOR is an on/off road, remote control, multisensor system designed to detect buried and surface- emplaced metallic and nonmetallic antitank mines. The basic requirements for this ATR software were the following: (1) an ability to separate target objects from the background in low signal-noise conditions; (2) an ability to handle a relatively high dynamic range in imaging light levels; (3) the ability to compensate for or remove light source effects such as shadows; and (4) the ability to identify target objects as mines. The image segmentation and target evaluation was performed using an integrated and parallel processing approach. Three basic techniques (texture analysis, edge enhancement, and contrast enhancement) were used collectively to extract all potential mine target shapes from the basic image. Target evaluation was then performed using a combination of size, geometrical, and fractal characteristics, which resulted in a calculated probability for each target shape. Overall results with this algorithm were quite good, though there is a tradeoff between detection confidence and the number of false alarms. This technology also has applications in the areas of hazardous waste site remediation, archaeology, and law enforcement.

  5. 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

  6. The quest for standards in medical imaging

    Energy Technology Data Exchange (ETDEWEB)

    Gibaud, Bernard, E-mail: bernard.gibaud@irisa.fr [INSERM, VisAGeS U746 Unit/Project, Faculty of Medicine, Campus de Villejean, F-35043 Rennes (France); INRIA, VisAGeS U746 Unit/Project, IRISA, Campus de Beaulieu, F-35042 Rennes (France); University of Rennes I-CNRS UMR 6074, IRISA, Campus de Beaulieu, F-35042 Rennes (France)

    2011-05-15

    This article focuses on standards supporting interoperability and system integration in the medical imaging domain. We introduce the basic concepts and actors and we review the most salient achievements in this domain, especially with the DICOM standard, and the definition of IHE integration profiles. We analyze and discuss what was successful, and what could still be more widely adopted by industry. We then sketch out a perspective of what should be done next, based on our vision of new requirements for the next decade. In particular, we discuss the challenges of a more explicit sharing of image and image processing semantics, and we discuss the help that semantic web technologies (and especially ontologies) may bring to achieving this goal.

  7. The quest for standards in medical imaging

    International Nuclear Information System (INIS)

    This article focuses on standards supporting interoperability and system integration in the medical imaging domain. We introduce the basic concepts and actors and we review the most salient achievements in this domain, especially with the DICOM standard, and the definition of IHE integration profiles. We analyze and discuss what was successful, and what could still be more widely adopted by industry. We then sketch out a perspective of what should be done next, based on our vision of new requirements for the next decade. In particular, we discuss the challenges of a more explicit sharing of image and image processing semantics, and we discuss the help that semantic web technologies (and especially ontologies) may bring to achieving this goal.

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

    International Nuclear Information System (INIS)

    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.)

  9. 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.)

  10. 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

  11. Model attraction in medical image object recognition

    Science.gov (United States)

    Tascini, Guido; Zingaretti, Primo

    1995-04-01

    This paper presents as new approach to image recognition based on a general attraction principle. A cognitive recognition is governed by a 'focus on attention' process that concentrates on the visual data subset of task- relevant type only. Our model-based approach combines it with another process, focus on attraction, which concentrates on the transformations of visual data having relevance for the matching. The recognition process is characterized by an intentional evolution of the visual data. This chain of image transformations is viewed as driven by an attraction field that attempts to reduce the distance between the image-point and the model-point in the feature space. The field sources are determined during a learning phase, by supplying the system with a training set. The paper describes a medical interpretation case in the feature space, concerning human skin lesions. The samples of the training set, supplied by the dermatologists, allow the system to learn models of lesions in terms of features such as hue factor, asymmetry factor, and asperity factor. The comparison of the visual data with the model derives the trend of image transformations, allowing a better definition of the given image and its classification. The algorithms are implemented in C language on a PC equipped with Matrox Image Series IM-1280 acquisition and processing boards. The work is now in progress.

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

    Directory of Open Access Journals (Sweden)

    Meng KuanLin

    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.

  13. A compact automated radionuclide separation system for nuclear medical applications

    International Nuclear Information System (INIS)

    We have constructed an instrument for the rapid chromatographic separation of clinically useful quantities of radionuclides for use in diagnostic or therapeutic nuclear medicine. The modular system consists of a laptop computer controller and driver software, an interface module, and a separation module comprising a high speed syringe pump, multiport valves, and miniature chromatographic columns. The small size (13 x 13 x 25 cm) of the separation module simplifies shielding and the remote computer controlled operation minimises radiation exposure to personnel. This instrument is well suited for use in radionuclide generators as separations can be performed rapidly (about 5 min) with decontamination factors of 106 achieved by using recent advances in resin-based separation methods. Separation columns can be selected for the purification of 90Y, 212/213Bi, or 186/188Re for radiotherapy or 99mTc, 201Tl, 18F, or 111In for diagnostic imaging. Experiments describing the separation of 212Bi from 224Ra and its daughters in nitric acid media by extraction chromatography will be discussed, as will μCi to mCi-scale separations of other therapeutic radionuclides

  14. 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...

  15. 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...

  16. 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

  17. 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

  18. 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

  19. 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

  20. Automated microaneurysm detection algorithms applied to diabetic retinopathy retinal images

    Directory of Open Access Journals (Sweden)

    Akara Sopharak

    2013-07-01

    Full Text Available Diabetic retinopathy is the commonest cause of blindness in working age people. It is characterised and graded by the development of retinal microaneurysms, haemorrhages and exudates. The damage caused by diabetic retinopathy can be prevented if it is treated in its early stages. Therefore, automated early detection can limit the severity of the disease, improve the follow-up management of diabetic patients and assist ophthalmologists in investigating and treating the disease more efficiently. This review focuses on microaneurysm detection as the earliest clinically localised characteristic of diabetic retinopathy, a frequently observed complication in both Type 1 and Type 2 diabetes. Algorithms used for microaneurysm detection from retinal images are reviewed. A number of features used to extract microaneurysm are summarised. Furthermore, a comparative analysis of reported methods used to automatically detect microaneurysms is presented and discussed. The performance of methods and their complexity are also discussed.

  1. 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

  2. Medical image archive node simulation and architecture

    Science.gov (United States)

    Chiang, Ted T.; Tang, Yau-Kuo

    1996-05-01

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

  3. 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

  4. X-ray detectors in medical imaging

    International Nuclear Information System (INIS)

    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 Gd2O2S) 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

  5. 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.

  6. Fingerprint verification on medical image reporting system.

    Science.gov (United States)

    Chen, Yen-Cheng; Chen, Liang-Kuang; Tsai, Ming-Dar; Chiu, Hou-Chang; Chiu, Jainn-Shiun; Chong, Chee-Fah

    2008-03-01

    The healthcare industry is recently going through extensive changes, through adoption of robust, interoperable healthcare information technology by means of electronic medical records (EMR). However, a major concern of EMR is adequate confidentiality of the individual records being managed electronically. Multiple access points over an open network like the Internet increases possible patient data interception. The obligation is on healthcare providers to procure information security solutions that do not hamper patient care while still providing the confidentiality of patient information. Medical images are also part of the EMR which need to be protected from unauthorized users. This study integrates the techniques of fingerprint verification, DICOM object, digital signature and digital envelope in order to ensure that access to the hospital Picture Archiving and Communication System (PACS) or radiology information system (RIS) is only by certified parties. PMID:18178287

  7. Automated Imaging and Analysis of the Hemagglutination Inhibition Assay.

    Science.gov (United States)

    Nguyen, Michael; Fries, Katherine; Khoury, Rawia; Zheng, Lingyi; Hu, Branda; Hildreth, Stephen W; Parkhill, Robert; Warren, William

    2016-04-01

    The hemagglutination inhibition (HAI) assay quantifies the level of strain-specific influenza virus antibody present in serum and is the standard by which influenza vaccine immunogenicity is measured. The HAI assay endpoint requires real-time monitoring of rapidly evolving red blood cell (RBC) patterns for signs of agglutination at a rate of potentially thousands of patterns per day to meet the throughput needs for clinical testing. This analysis is typically performed manually through visual inspection by highly trained individuals. However, concordant HAI results across different labs are challenging to demonstrate due to analyst bias and variability in analysis methods. To address these issues, we have developed a bench-top, standalone, high-throughput imaging solution that automatically determines the agglutination states of up to 9600 HAI assay wells per hour and assigns HAI titers to 400 samples in a single unattended 30-min run. Images of the tilted plates are acquired as a function of time and analyzed using algorithms that were developed through comprehensive examination of manual classifications. Concordance testing of the imaging system with eight different influenza antigens demonstrates 100% agreement between automated and manual titer determination with a percent difference of ≤3.4% for all cases. PMID:26464422

  8. Automated transient detection in the STEREO Heliospheric Imagers.

    Science.gov (United States)

    Barnard, Luke; Scott, Chris; Owens, Mat; Lockwood, Mike; Tucker-Hood, Kim; Davies, Jackie

    2014-05-01

    Since the launch of the twin STEREO satellites, the heliospheric imagers (HI) have been used, with good results, in tracking transients of solar origin, such as Coronal Mass Ejections (CMEs), out far into the heliosphere. A frequently used approach is to build a "J-map", in which multiple elongation profiles along a constant position angle are stacked in time, building an image in which radially propagating transients form curved tracks in the J-map. From this the time-elongation profile of a solar transient can be manually identified. This is a time consuming and laborious process, and the results are subjective, depending on the skill and expertise of the investigator. Therefore, it is desirable to develop an automated algorithm for the detection and tracking of the transient features observed in HI data. This is to some extent previously covered ground, as similar problems have been encountered in the analysis of coronagraph data and have led to the development of products such as CACtus etc. We present the results of our investigation into the automated detection of solar transients observed in J-maps formed from HI data. We use edge and line detection methods to identify transients in the J-maps, and then use kinematic models of the solar transient propagation (such as the fixed-phi and harmonic mean geometric models) to estimate the solar transients properties, such as transient speed and propagation direction, from the time-elongation profile. The effectiveness of this process is assessed by comparison of our results with a set of manually identified CMEs, extracted and analysed by the Solar Storm Watch Project. Solar Storm Watch is a citizen science project in which solar transients are identified in J-maps formed from HI data and tracked multiple times by different users. This allows the calculation of a consensus time-elongation profile for each event, and therefore does not suffer from the potential subjectivity of an individual researcher tracking an

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

    Science.gov (United States)

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

    2013-01-01

    Digital Imaging Processing (DIP) requires data extraction and output from a visualization tool to be consistent. Data handling and transmission between the server and a user is a systematic process in service interpretation. The use of integrated medical services for management and viewing of imaging data in combination with a mobile visualization tool can be greatly facilitated by data analysis and interpretation. This paper presents an integrated mobile application and DIP service, called M-DIP. The objective of the system is to (1) automate the direct data tiling, conversion, pre-tiling of brain images from Medical Imaging NetCDF (MINC), Neuroimaging Informatics Technology Initiative (NIFTI) to RAW formats; (2) speed up querying of imaging measurement; and (3) display high-level of images with three dimensions in real world coordinates. In addition, M-DIP provides the ability to work on a mobile or tablet device without any software installation using web-based protocols. M-DIP implements three levels of architecture with a relational middle-layer database, a stand-alone DIP server, and a mobile application logic middle level realizing user interpretation for direct querying and communication. This imaging software has the ability to display biological imaging data at multiple zoom levels and to increase its quality to meet users' expectations. Interpretation of bioimaging data is facilitated by an interface analogous to online mapping services using real world coordinate browsing. This allows mobile devices to display multiple datasets simultaneously from a remote site. M-DIP can be used as a measurement repository that can be accessed by any network environment, such as a portable mobile or tablet device. In addition, this system and combination with mobile applications are establishing a virtualization tool in the neuroinformatics field to speed interpretation services. PMID:23847587

  11. Evaluating Modelling Approaches for Medical Image Annotations

    CERN Document Server

    Opitz, Jasmin; Sattler, Ulrike

    2010-01-01

    Information system designers face many challenges w.r.t. selecting appropriate semantic technologies and deciding on a modelling approach for their system. However, there is no clear methodology yet to evaluate "semantically enriched" information systems. In this paper we present a case study on different modelling approaches for annotating medical images and introduce a conceptual framework that can be used to analyse the fitness of information systems and help designers to spot the strengths and weaknesses of various modelling approaches as well as managing trade-offs between modelling effort and their potential benefits.

  12. Fast fluid registration of medical images

    DEFF Research Database (Denmark)

    Bro-Nielsen, Morten; Gramkow, Claus

    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 of the...... velocity field of the fluid. Using the linearity of this deformation we derive a convolution filter which we use in a scale-space framework. We also demonstrate that the `demon'-based registration method of (Thirion, 1996) can be seen as an approximation to the fluid registration method and point to...

  13. 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)

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

    International Nuclear Information System (INIS)

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

  15. Developing a Medical Image Content Repository for E-Learning

    OpenAIRE

    Hsiao, Chia-Hung; Hsu, Tien-Cheng; Chang, Jing Ning; Stephen J.H. Yang; Young, Shuenn-Tsong; Chu, Woei Chyn

    2006-01-01

    The integration of medical informatics and e-learning systems could provide many advanced applications including training, knowledge management, telemedicine, etc. Currently, both the domains of e-learning and medical image have sophisticated specifications and standards. It is a great challenge to bring about integration. In this paper, we describe the development of a Web interface for searching and viewing medical images that are stored in standard medical image servers. With the creation ...

  16. ANALYSIS OF WATERMARKING TECHNIQUES FOR MEDICAL IMAGES PRESERVING ROI

    OpenAIRE

    Sonika C. Rathi; Vandana S. Inamdar

    2012-01-01

    Telemedicine is a well-known application, where enormous amount of medical data need to be securely transfer over the public network and manipulate effectively. Medical image watermarking is an appropriate method used for enhancing security and authentication of medical data, which is crucial and used for further diagnosis and reference. This paper discusses the available medical image watermarking methods for protecting and authenticating medical data. The paper focuses on alg...

  17. 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.

  18. 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...

  19. 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...

  20. 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...

  1. A Grid Information Infrastructure for Medical Image Analysis

    OpenAIRE

    Rogulin, D.; F. Estrella(UWE); Hauer, T.; McClatchey, R.; Solomonides, T

    2004-01-01

    The storage and manipulation of digital images and the analysis of the information held in those images are essential requirements for next-generation medical information systems. The medical community has been exploring collaborative approaches for managing image data and exchanging knowledge and Grid technology [1] is a promising approach to enabling distributed analysis across medical institutions and for developing new collaborative and cooperative approaches for image analysis without th...

  2. Automated CT marker segmentation for image registration in radionuclide therapy

    International Nuclear Information System (INIS)

    In this paper a novel, automated CT marker segmentation technique for image registration is described. The technique, which is based on analysing each CT slice contour individually, treats the cross sections of the external markers as protrusions of the slice contour. Knowledge-based criteria, using the shape and dimensions of the markers, are defined to enable marker identification and segmentation. Following segmentation, the three-dimensional (3D) markers' centroids are localized using an intensity-weighted algorithm. Finally, image registration is performed using a least-squares fit algorithm. The technique was applied to both simulated and patient studies. The patients were undergoing 131I-mIBG radionuclide therapy with each study comprising several 99mTc single photon emission computed tomography (SPECT) scans and one CT marker scan. The mean residual 3D registration errors (±1 SD) computed for the simulated and patient studies were 1.8±0.3 mm and 4.3±0.5 mm respectively. (author)

  3. 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.

  4. 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

  5. 21 CFR 892.2030 - Medical image digitizer.

    Science.gov (United States)

    2010-04-01

    ... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Medical image digitizer. 892.2030 Section 892.2030 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES RADIOLOGY DEVICES Diagnostic Devices § 892.2030 Medical image digitizer....

  6. The conversion of synchrotron radiation biomedical and medical images into DICOM images

    Science.gov (United States)

    Wang, Yunling; Sun, Jianyong; Sun, Jianqi; Zhang, Jianguo

    2014-03-01

    With Synchrotron Radiation light source, there was a lot of imaging methods being developed to perform biomedical and medical imaging researches such as X-ray absorption imaging, phase-contrast imaging and micro-CT imaging. In this presentation, we present an approach to transform a various kinds of SR images into proper DICOM images so that to use a rich of medical processing display software to process and display SR biomedical and medical images. The new generated SR DICOM images can be transferred, stored, processed and displayed by using most of commercial medical imaging software.

  7. 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.

  8. 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

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

    DEFF Research Database (Denmark)

    Gutte, Henrik; Jakobsson, David; Olofsson, Fredrik; Ohlsson, Mattias; Valind, Sven; Loft, Annika; Edenbrandt, Lars; Kjaer, Andreas

    2007-01-01

    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......PURPOSE: To develop a completely automated method based on image processing techniques and artificial neural networks for the interpretation of combined [(18)F]fluorodeoxyglucose (FDG) positron emission tomography (PET) and computed tomography (CT) images for the diagnosis and staging of lung...... standard' image interpretation. The training group was used in the development of the automated method. The image processing techniques included algorithms for segmentation of the lungs based on the CT images and detection of lesions in the PET images. Lung boundaries from the CT images were used for...

  10. 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...

  11. A new database for medical images and information

    Science.gov (United States)

    Tahmoush, Dave; Samet, Hanan

    2007-03-01

    We present a medical image and medical record database for the storage, research, transmission, and evaluation of medical images, as well as tele-medicine applications. Any medical image from a source that supports the DICOM standard can be stored and accessed, as well as associated analysis and annotations. Information and image retrieval can be done based on patient info, date, doctor's annotations, features in the images, or a spatial combination of features. Secure access and transmission is addressed for tele-medicine applications. This database application follows all HIPPA regulations.

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

    OpenAIRE

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

    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 sy...

  13. Invariant image description for the improvement of medical diagnostics

    OpenAIRE

    Nagel, Joachim H.

    1994-01-01

    In summary, invariant image description has proven to be an extremely successful tool for medical image processing and has already contributed significantly to the improvement of clinical diagnostics. The technique has been widely acknowledged as being superior to other methods of image registration. Further applications, not limited to medical diagnostics, are to be expected.

  14. 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,...

  15. 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

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

    International Nuclear Information System (INIS)

    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

  17. 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.

  18. Medical Image Matching and Retrieval using Discrete Sine Transform

    Directory of Open Access Journals (Sweden)

    SASI KUMAR.M

    2010-12-01

    Full Text Available Visual information has been extensively used in the areas of multimedia, medical imaging and other numerous applications. Management of these visual information is challenging as the quantity of data available is very huge. Current utilization of available medical databases is limited due to the issues in retrieval of thenecessary images from a huge repository. In this paper we propose a novel image matching scheme using Discrete Sine Transform and decision tree classification techniques for classification of the given input medical image. Our system classifies the images based on the similarity of the images.

  19. 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.

  20. 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. PMID:26729128

  1. Exploiting image registration for automated resonance assignment in NMR

    International Nuclear Information System (INIS)

    Analysis of protein NMR data involves the assignment of resonance peaks in a number of multidimensional data sets. To establish resonance assignment a three-dimensional search is used to match a pair of common variables, such as chemical shifts of the same spin system, in different NMR spectra. We show that by displaying the variables to be compared in two-dimensional plots the process can be simplified. Moreover, by utilizing a fast Fourier transform cross-correlation algorithm, more common to the field of image registration or pattern matching, we can automate this process. Here, we use sequential NMR backbone assignment as an example to show that the combination of correlation plots and segmented pattern matching establishes fast backbone assignment in fifteen proteins of varying sizes. For example, the 265-residue RalBP1 protein was 95.4 % correctly assigned in 10 s. The same concept can be applied to any multidimensional NMR data set where analysis comprises the comparison of two variables. This modular and robust approach offers high efficiency with excellent computational scalability and could be easily incorporated into existing assignment software

  2. Automating patient safety incident reporting to improve healthcare quality in the defence medical services.

    Science.gov (United States)

    Lamb, Di; Piper, N

    2015-12-01

    There are many reasons for poor compliance with patient safety incident reporting in the UK. The Defence Medical Services has made a significant investment to address the culture and process by which risk to patient safety is managed within its organisation. This paper describes the decision process and technical considerations in the design of an automated reporting system together with the implementation procedure aimed to maximise compliance. The elimination of inherent weaknesses in feedback mechanisms from the three Armed Forces, which had been uniquely different, ensured the quality of data improved, which enabled resources to be prioritised that would also have a direct impact upon the quality of patient care. PMID:26400974

  3. 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

  4. 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.

  5. 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 ofmedical images. The presented algorithms will beapplied to images. This work presents a new methodthat combines image cryptography, data hiding andSteganography technique for denoised and safeimage transmission purpose. In This method weencrypt the original image with two sharesmechanism encryption algorithm then embed theencrypted image with patient information by usinglossless data embedding technique with data hidingmethod after that for more security. We applysteganography by encrypted image of any othermedical image as cover image and embeddedimages as secrete image with the private key. Inreceiver side when the message is arrived then weapply the inverse methods in reverse order to get theoriginal image and patient information and toremove noise we extract the image before thedecryption of message. We have applied and showedthe results of our method to medical images.

  6. ANALYSIS OF WATERMARKING TECHNIQUES FOR MEDICAL IMAGES PRESERVING ROI

    Directory of Open Access Journals (Sweden)

    Sonika C. Rathi

    2012-05-01

    Full Text Available Telemedicine is a well-known application, where enormous amount of medical data need to be securely transfer over the public network and manipulate effectively. Medical image watermarking is an appropriate method used for enhancing security and authentication of medical data, which is crucial and used for further diagnosis and reference. This paper discusses the available medical image watermarking methods for protecting and authenticating medical data. The paper focuses on algorithms for application of watermarking technique on Region of Non Interest (RONI of the medical image preserving Region of Interest (ROI. The medical images can be transferred securely by embedding watermarks in RONI allowing verification of the legitimate changes at the receiving end without affecting ROI.

  7. 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...

  8. 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...

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

    International Nuclear Information System (INIS)

    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

  10. 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.

  11. Signal Processing in Medical Ultrasound B-mode Imaging

    International Nuclear Information System (INIS)

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

  12. Using Hausdorff Distance for New Medical Image Annotation

    CERN Document Server

    Bouslimi, Riadh

    2012-01-01

    Medical images annotation is most of the time a repetitive hard task. Collecting old similar annotations and assigning them to new medical images may not only enhance the annotation process, but also reduce ambiguity caused by repetitive annotations. The goal of this work is to propose an approach based on Hausdorff distance able to compute similarity between a new medical image and old stored images. User has to choose then one of the similar images and annotations related to the selected one are assigned to the new one.

  13. Performance and Analysis of the Automated Semantic Object and Spatial Relationships Extraction in Traffic Images

    OpenAIRE

    Wang Hui Hui

    2013-01-01

    Extraction and representation of spatial relations semantics among objects are important as it can convey important information about the image and to further increase the confidence in image understanding which contributes to richer querying and retrieval facilities. This paper discusses the performance of the automated object spatial relationships semantic information extraction as proposed. Experiments have been conducted to demonstrate that the proposed automated object spatial relations...

  14. 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

  15. Automatic Multilevel Medical Image Annotation and Retrieval

    OpenAIRE

    Mueen, A.; Zainuddin, R.; Baba, M. Sapiyan

    2007-01-01

    Image retrieval at the semantic level mostly depends on image annotation or image classification. Image annotation performance largely depends on three issues: (1) automatic image feature extraction; (2) a semantic image concept modeling; (3) algorithm for semantic image annotation. To address first issue, multilevel features are extracted to construct the feature vector, which represents the contents of the image. To address second issue, domain-dependent concept hierarchy is constructed for...

  16. 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.

  17. 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)

  18. 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 ...

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

    International Nuclear Information System (INIS)

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

  20. 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.

  1. 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

  2. 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

  3. 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

  4. 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 ...

  5. Boundary value problems and medical imaging

    International Nuclear Information System (INIS)

    The application of appropriate transform pairs, such as the Fourier, the Laplace, the sine, the cosine and the Mellin transforms, provides the most well known method for constructing analytical solutions to a large class of physically significant boundary value problems. However, this method has several limitations. In particular, it requires the given PDE, domain and boundary conditions to be separable, and also may not be applicable if the given boundary value problem is non-self-adjoint. Furthermore, it expresses the solution as either an integral or an infinite series, neither of which are uniformly convergent on the boundary of the domain (for nonvanishing boundary conditions), which renders such expressions unsuitable for numerical computations. Here, we review a method recently introduced by the first author which can be applied to certain nonseparable and non-self-adjoint problems. Furthermore, this method expresses the solution as an integral in the complex plane which is uniformly convergent on the boundary of the domain. This method, which also suggests new numerical techniques, is illustrated for both evolution and elliptic PDEs. Athough this method was first applied to certain nonlinear PDEs called integrable and was originally formulated in terms of the so-called Lax pairs, it can actually be applied to linear PDEs without the need to analyse the associated Lax pair. The existence of Lax pairs is used here in order to motivate a related development, namely the emergence of a novel formalism for analysing certain inverse problems arising in medical imaging. Examples include PET and SPECT

  6. On the development of expertise in interpreting medical images

    Science.gov (United States)

    Krupinsky, Elizabeth A.

    2012-03-01

    Medical images represent a core portion of the information clinicians utilize to render diagnostic and treatment decisions. Fundamentally, viewing a medical image involves two basic processes - visually inspecting the image (visual perception) and rendering an interpretation (cognition). The interpretation is often followed by a recommendation. The likelihood of error in the interpretation of medical images is unfortunately not negligible. Errors occur and patients' lives are impacted. Thus we need to understand how clinicians interact with the information in an image during the interpretation process. We also need to understand how clinicians develop expertise throughout their careers and why some people are better at interpreting medical images than others. If we can better understand how expertise develops, perhaps we can develop better training programs, incorporate more effective ways of teaching image interpretation into the medical school and residency curriculums, and create new tools that would enhance and perhaps speed up the learning process. With improved understanding we can also develop ways to further improve decision-making in general and at every level of the medical imaging profession, thus improving patient care. The science of medical image perception is dedicated to understanding and improving the clinical interpretation process.

  7. 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.

  8. 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...

  9. Semantic support for medical image search and retrieval

    OpenAIRE

    Wei, W; Barnaghi, PM

    2007-01-01

    The need for annotating digital image data is recognised in a variety of different medical information systems, covering both professional and educational usage of medical imaging. Due to the high recall and low precision attribute of keyword-based search, multimedia information search and retrieval based on textual descriptions is not always an efficient and sufficient solution, particularly for specific applications such as the medical diagnosis information systems. On the other hand, using...

  10. Study on Medical Image Processing Technologies Based on DICOM

    OpenAIRE

    Peijiang Chen

    2012-01-01

    DICOM is an international standard for the storage and transmission of medical image. With the popularity of pictorial and computerized medical equipments and the development of hospital management information system, the standard is widely used. The technologies of medical image display and processing based on DICOM standard are studied. On the basis of analyzing the DICOM standards and file formats, the general idea of converting between the DICOM format and BMP format is brought forward, a...

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

    OpenAIRE

    Čabarkapa Slobodan; Zajić Goran; Pavlović Milan; Slavković Nikola; Reljin Nikola; Kragović Milanko

    2009-01-01

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

  12. 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.

  13. 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)

  14. 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.

  15. Synthetic Aperture Imaging in Medical Ultrasound

    DEFF Research Database (Denmark)

    Nikolov, Svetoslav; Gammelmark, Kim; Pedersen, Morten;

    2004-01-01

    Synthetic Aperture (SA) ultrasound imaging is a relatively new and unexploited imaging technique. The images are perfectly focused both in transmit and receive, and have a better resolution and higher dynamic range than conventional ultrasound images. The blood flow can be estimated from SA images...

  16. 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.

  17. 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

  18. 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.

  19. Images in Rheumatology: a multimedia program for medical education.

    OpenAIRE

    Nashel, D J; Martin, J J

    1992-01-01

    In recent years, undergraduate medical education has benefited from the use of computer-based instructional programs. However, in the case of clinical and postgraduate medical education there is a scarcity of such programs, particularly those with access to high-resolution images. Having a fundamental knowledge base of disease-associated images is crucial for the physicians during the diagnostic process. To fill this gap in clinical instruction in the rheumatic diseases, Images in Rheumatolog...

  20. 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...

  1. 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.

  2. Research about Three Dimensional Reconstruction of Medical Image

    Directory of Open Access Journals (Sweden)

    Qiechun Chen

    2013-02-01

    Full Text Available In this paper, through comparison of different reconstruction algorithms for volume rendering, we put forward Ray Casting algorithm as the scheme of 3D reconstruction of medical image. We improved the image synthesis operator, and combined section sampling mode to reconstruct the image. Finally we rendered images on GPU. By using improved operator, we not only made the rendering speed accelerated, but also made the quality of rendering images improved.

  3. Research about Three Dimensional Reconstruction of Medical Image

    OpenAIRE

    Qiechun Chen; Guangyuan Zhang; Xin Wang; Linan Fan

    2013-01-01

    In this paper, through comparison of different reconstruction algorithms for volume rendering, we put forward Ray Casting algorithm as the scheme of 3D reconstruction of medical image. We improved the image synthesis operator, and combined section sampling mode to reconstruct the image. Finally we rendered images on GPU. By using improved operator, we not only made the rendering speed accelerated, but also made the quality of rendering images improved.

  4. 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

  5. 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

  6. OPTIMAX 2014 - Radiation dose and image quality optimisation in medical imaging

    OpenAIRE

    Hogg, Peter; Lança, Luís

    2015-01-01

    Medical imaging is a powerful diagnostic tool. Consequently, the number of medical images taken has increased vastly over the past few decades. The most common medical imaging techniques use X-radiation as the primary investigative tool. The main limitation of using X-radiation is associated with the risk of developing cancers. Alongside this, technology has advanced and more centres now use CT scanners; these can incur significant radiation burdens compared with traditional X-ray imaging ...

  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. 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...

  9. 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...

  10. 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

  11. Automated defect recognition method based on neighbor layer slice images of ICT

    International Nuclear Information System (INIS)

    The current automated defect recognition of industrial computerized tomography(ICT) slice images is mostly carried out in individual image. Certain false detections would exist for some isolated noises can not be wiped off without considering the information of neighbor layer images. To solve this problem,a new automated defect recognition method is presented based on a two-step analysis of consecutive slice images. First, all potential defects are segmented using a classic method in each image. Second, real defects and false defects are recognized by all potential defect matching of neighbor layer images in two steps based on the continuity of real defects characteristic and the non-continuity of false defects between the neighbor images. The method is verified by experiments and results prove that the real defects can be detected with high probability and false detections can be reduced effectively. (authors)

  12. 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.

  13. FCM Algorithm for Medical Image Segmentation Using HMRF.

    OpenAIRE

    Rajeev V R; Dr Sreeja Mole S S

    2013-01-01

    Clustering of data is a method by which large sets of data are grouped into clusters of smaller sets of similar data. Fuzzy c-means (FCM) clustering algorithm is one of the most commonly used unsupervised clustering technique in the field of medical imaging. Medical image segmentation refers to the segmentation of known anatomic structures from medical images. Fuzzy C-means (FCM) is a method of clustering which allows one piece of data to belong to two or more clusters. Fuzzy logic is a multi...

  14. 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.

  15. Automated recognition of cell phenotypes in histology images based on membrane- and nuclei-targeting biomarkers

    International Nuclear Information System (INIS)

    Three-dimensional in vitro culture of cancer cells are used to predict the effects of prospective anti-cancer drugs in vivo. In this study, we present an automated image analysis protocol for detailed morphological protein marker profiling of tumoroid cross section images. Histologic cross sections of breast tumoroids developed in co-culture suspensions of breast cancer cell lines, stained for E-cadherin and progesterone receptor, were digitized and pixels in these images were classified into five categories using k-means clustering. Automated segmentation was used to identify image regions composed of cells expressing a given biomarker. Synthesized images were created to check the accuracy of the image processing system. Accuracy of automated segmentation was over 95% in identifying regions of interest in synthesized images. Image analysis of adjacent histology slides stained, respectively, for Ecad and PR, accurately predicted regions of different cell phenotypes. Image analysis of tumoroid cross sections from different tumoroids obtained under the same co-culture conditions indicated the variation of cellular composition from one tumoroid to another. Variations in the compositions of cross sections obtained from the same tumoroid were established by parallel analysis of Ecad and PR-stained cross section images. Proposed image analysis methods offer standardized high throughput profiling of molecular anatomy of tumoroids based on both membrane and nuclei markers that is suitable to rapid large scale investigations of anti-cancer compounds for drug development

  16. Developing a medical image content repository for e-learning.

    Science.gov (United States)

    Hsiao, Chia-Hung; Hsu, Tien-Cheng; Chang, Jing Ning; Yang, Stephen J H; Young, Shuenn-Tsong; Chu, Woei Chyn

    2006-09-01

    The integration of medical informatics and e-learning systems could provide many advanced applications including training, knowledge management, telemedicine, etc. Currently, both the domains of e-learning and medical image have sophisticated specifications and standards. It is a great challenge to bring about integration. In this paper, we describe the development of a Web interface for searching and viewing medical images that are stored in standard medical image servers. With the creation of a Web solution, we have reduced the overheads of integration. We have packaged Digital Imaging and Communications in Medicine (DICOM) network services as a component that can be used via a Web server. The Web server constitutes a content repository for searching, editing, and storing Web-based medical image content. This is a simple method by which the use of Picture Archiving and Communication System (PACS) can be extended. We show that the content repository can easily interact and integrate with a learning system. With the integration, the user can easily generate and assign medical image content for e-learning. A Web solution might be the simplest way for system integration. The demonstration in this paper should be useful as a method of expanding the usage of medical information. The construction of a Web-based repository and integrated with a learning system may be also applicable to other domains. PMID:16710797

  17. Automated striatal uptake analysis of 18F-FDOPA PET images applied to Parkinson's disease patients

    International Nuclear Information System (INIS)

    6-[18F]Fluoro-L-DOPA (FDOPA) is a radiopharmaceutical valuable for assessing the presynaptic dopaminergic function when used with positron emission tomography (PET). More specifically, the striatal-to-occipital ratio (SOR) of FDOPA uptake images has been extensively used as a quantitative parameter in these PET studies. Our aim was to develop an easy, automated method capable of performing objective analysis of SOR in FDOPA PET images of Parkinson's disease (PD) patients. Brain images from FDOPA PET studies of 21 patients with PD and 6 healthy subjects were included in our automated striatal analyses. Images of each individual were spatially normalized into an FDOPA template. Subsequently, the image slice with the highest level of basal ganglia activity was chosen among the series of normalized images. Also, the immediate preceding and following slices of the chosen image were then selected. Finally, the summation of these three images was used to quantify and calculate the SOR values. The results obtained by automated analysis were compared with manual analysis by a trained and experienced image processing technologist. The SOR values obtained from the automated analysis had a good agreement and high correlation with manual analysis. The differences in caudate, putamen, and striatum were -0.023, -0.029, and -0.025, respectively; correlation coefficients 0.961, 0.957, and 0.972, respectively. We have successfully developed a method for automated striatal uptake analysis of FDOPA PET images. There was no significant difference between the SOR values obtained from this method and using manual analysis. Yet it is an unbiased time-saving and cost-effective program and easy to implement on a personal computer. (author)

  18. Creation of Anatomically Accurate Computer-Aided Design (CAD) Solid Models from Medical Images

    Science.gov (United States)

    Stewart, John E.; Graham, R. Scott; Samareh, Jamshid A.; Oberlander, Eric J.; Broaddus, William C.

    1999-01-01

    Most surgical instrumentation and implants used in the world today are designed with sophisticated Computer-Aided Design (CAD)/Computer-Aided Manufacturing (CAM) software. This software automates the mechanical development of a product from its conceptual design through manufacturing. CAD software also provides a means of manipulating solid models prior to Finite Element Modeling (FEM). Few surgical products are designed in conjunction with accurate CAD models of human anatomy because of the difficulty with which these models are created. We have developed a novel technique that creates anatomically accurate, patient specific CAD solids from medical images in a matter of minutes.

  19. 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

  20. 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

  1. Medical image of the week: prozac eyes

    OpenAIRE

    Shetty S; Patel S; Knox KS

    2015-01-01

    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 ...

  2. 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...

  3. 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...

  4. Medical Image Compression using Wavelet Decomposition for Prediction Method

    Directory of Open Access Journals (Sweden)

    S. M. Ramesh

    2010-01-01

    Full Text Available 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 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.

  6. 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

  7. 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...

  8. Automated synthesis of image processing procedures using AI planning techniques

    Science.gov (United States)

    Chien, Steve; Mortensen, Helen

    1994-01-01

    This paper describes the Multimission VICAR (Video Image Communication and Retrieval) Planner (MVP) (Chien 1994) system, which uses artificial intelligence planning techniques (Iwasaki & Friedland, 1985, Pemberthy & Weld, 1992, Stefik, 1981) to automatically construct executable complex image processing procedures (using models of the smaller constituent image processing subprograms) in response to image processing requests made to the JPL Multimission Image Processing Laboratory (MIPL). The MVP system allows the user to specify the image processing requirements in terms of the various types of correction required. Given this information, MVP derives unspecified required processing steps and determines appropriate image processing programs and parameters to achieve the specified image processing goals. This information is output as an executable image processing program which can then be executed to fill the processing request.

  9. 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...

  10. 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...

  11. Automated examination notification of Emergency Department images in a picture archiving and communication system

    OpenAIRE

    Andriole, Katherine P.; Avrin, David E.; Weber, Ellen; Luth, David M.; Bazzill, Todd M.

    2001-01-01

    This study compares the timeliness of radiology interpretation of Emergency Department (ED) imaging examinations in a picture archiving and communication system (PACS) before and after implementation of an automated paging system for notification of image availability. An alphanumeric pager for each radiology subspecialty (chest, pediatrics, bone, neuroradiology, and body) was used to alert the responsible radiologist that an ED imaging examination is available to be viewed on the PACS. The p...

  12. Automated Analysis of Fluorescence Microscopy Images to Identify Protein-Protein Interactions

    OpenAIRE

    Morrell-Falvey, J. L.; Qi, H.; Doktycz, M. J.; Venkatraman, S.

    2006-01-01

    The identification of protein interactions is important for elucidating biological networks. One obstacle in comprehensive interaction studies is the analyses of large datasets, particularly those containing images. Development of an automated system to analyze an image-based protein interaction dataset is needed. Such an analysis system is described here, to automatically extract features from fluorescence microscopy images obtained from a bacterial protein interaction assay. These features ...

  13. NeuronMetrics: Software for Semi-Automated Processing of Cultured-Neuron Images

    OpenAIRE

    Narro, Martha L.; Yang, Fan; Kraft, Robert; Wenk, Carola; Efrat, Alon; Restifo, Linda L.

    2007-01-01

    Using primary cell culture to screen for changes in neuronal morphology requires specialized analysis software. We developed NeuronMetrics™ for semi-automated, quantitative analysis of two-dimensional (2D) images of fluorescently labeled cultured neurons. It skeletonizes the neuron image using two complementary image-processing techniques, capturing fine terminal neurites with high fidelity. An algorithm was devised to span wide gaps in the skeleton. NeuronMetrics uses a novel strategy based ...

  14. Computing support for advanced medical data analysis and imaging

    CERN Document Server

    Wiślicki, W; Białas, P; Czerwiński, E; Kapłon, Ł; Kochanowski, A; Korcyl, G; Kowal, J; Kowalski, P; Kozik, T; Krzemień, W; Molenda, M; Moskal, P; Niedźwiecki, S; Pałka, M; Pawlik, M; Raczyński, L; Rudy, Z; Salabura, P; Sharma, N G; Silarski, M; Słomski, A; Smyrski, J; Strzelecki, A; Wieczorek, A; Zieliński, M; Zoń, N

    2014-01-01

    We discuss computing issues for data analysis and image reconstruction of PET-TOF medical scanner or other medical scanning devices producing large volumes of data. Service architecture based on the grid and cloud concepts for distributed processing is proposed and critically discussed.

  15. 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.

  16. Chimenea and other tools: Automated imaging of multi-epoch radio-synthesis data with CASA

    Science.gov (United States)

    Staley, T. D.; Anderson, G. E.

    2015-11-01

    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, of the sort typically acquired for transient surveys or follow-up. The algorithm aims to improve upon standard imaging pipelines by utilizing iterative RMS-estimation and automated source-detection to avoid so called 'Clean-bias', and makes 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. While targeted at automated imaging, the drive-casa interface can also be used to automate interaction with any of the CASA subroutines from a generic Python process. Additionally, these packages may be of wider technical interest beyond radio-astronomy, since they demonstrate use of the Python library pexpect to emulate terminal interaction with an external process. This approach allows for rapid development of a Python interface to any legacy or externally-maintained pipeline which accepts command-line input, without requiring alterations to the original code.

  17. A method for fast automated microscope image stitching.

    Science.gov (United States)

    Yang, Fan; Deng, Zhen-Sheng; Fan, Qiu-Hong

    2013-05-01

    Image stitching is an important technology to produce a panorama or larger image by combining several images with overlapped areas. In many biomedical researches, image stitching is highly desirable to acquire a panoramic image which represents large areas of certain structures or whole sections, while retaining microscopic resolution. In this study, we develop a fast normal light microscope image stitching algorithm based on feature extraction. At first, an algorithm of scale-space reconstruction of speeded-up robust features (SURF) was proposed to extract features from the images to be stitched with a short time and higher repeatability. Then, the histogram equalization (HE) method was employed to preprocess the images to enhance their contrast for extracting more features. Thirdly, the rough overlapping zones of the images preprocessed were calculated by phase correlation, and the improved SURF was used to extract the image features in the rough overlapping areas. Fourthly, the features were corresponded by matching algorithm and the transformation parameters were estimated, then the images were blended seamlessly. Finally, this procedure was applied to stitch normal light microscope images to verify its validity. Our experimental results demonstrate that the improved SURF algorithm is very robust to viewpoint, illumination, blur, rotation and zoom of the images and our method is able to stitch microscope images automatically with high precision and high speed. Also, the method proposed in this paper is applicable to registration and stitching of common images as well as stitching the microscope images in the field of virtual microscope for the purpose of observing, exchanging, saving, and establishing a database of microscope images. PMID:23465523

  18. 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...

  19. 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

  20. Automated image analysis of lateral lumber X-rays by a form model

    International Nuclear Information System (INIS)

    Development of a software for fully automated image analysis of lateral lumbar spine X-rays. Material and method: Using the concept of active shape models, we developed a software that produces a form model of the lumbar spine from lateral lumbar spine radiographs and runs an automated image segmentation. This model is able to detect lumbar vertebrae automatically after the filtering of digitized X-ray images. The model was trained with 20 lateral lumbar spine radiographs with no pathological findings before we evaluated the software with 30 further X-ray images which were sorted by image quality ranging from one (best) to three (worst). There were 10 images for each quality. Results: Image recognition strongly depended on image quality. In group one 52 and in group two 51 out of 60 vertebral bodies including the sacrum were recognized, but in group three only 18 vertebral bodies were properly identified. Conclusion: Fully automated and reliable recognition of vertebral bodies from lateral spine radiographs using the concept of active shape models is possible. The precision of this technique is limited by the superposition of different structures. Further improvements are necessary. Therefore standardized image quality and enlargement of the training data set are required. (orig.)

  1. Synchrotrons and their applications in medical imaging and therapy

    International Nuclear Information System (INIS)

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

  2. 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.)

  3. 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.)

  4. Histogram analysis with automated extraction of brain-tissue region from whole-brain CT images

    OpenAIRE

    Kondo, Masatoshi; Yamashita, Koji; Yoshiura, Takashi; Hiwatash, Akio; Shirasaka, Takashi; Arimura, Hisao; Nakamura, Yasuhiko; Honda, Hiroshi

    2015-01-01

    To determine whether an automated extraction of the brain-tissue region from CT images is useful for the histogram analysis of the brain-tissue region was studied. We used the CT images of 11 patients. We developed an automatic brain-tissue extraction algorithm. We evaluated the similarity index of this automated extraction method relative to manual extraction, and we compared the mean CT number of all extracted pixels and the kurtosis and skewness of the distribution of CT numbers of all ext...

  5. 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.

  6. 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...

  7. 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...

  8. An Enhanced Approach for Medical Brain Image Enhancement

    Directory of Open Access Journals (Sweden)

    J. Umamaheswari

    2012-01-01

    Full Text Available Problem statement: One of the most common degradations in medical images is their poor contrast quality and noise. The DICOM image consists of speckle (multiplicative noise. While the image is enhanced, the multiplicative noise present in the image is also enhanced. Approach: This study describes the hybrid method to improve the image quality of Digital Imaging and Communications in Medicine (DICOM images. The idea of image enhancement technique is to improve the quality of an image for early diagnosis. Then followed by a noise reduction using speckle reduction anisotropic filter. This suggests the use of contrast enhancement methods as an attempt to modify the intensity distribution of the image and to reduce the multiplicative noise. Results: In this research study, a new approach for DICOM image is done by applying contrast stretching and anisotropic diffusion where denoising of multiplicative noise is carried out and the level of contrast is improved. The quality of the image is enhanced and noise free for DICOM image analysis. The effectiveness of hybrid method is proved by quantitative approach. Conclusion and Recommendation: The performance of the proposed study is compared with the existing traditional algorithm and real time medical diagnosis image."

  9. 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. PMID:26414378

  10. 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...

  11. 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...

  12. 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)

  13. Automated method and system for the alignment and correlation of images from two different modalities

    Science.gov (United States)

    Giger, Maryellen L.; Chen, Chin-Tu; Armato, Samuel; Doi, Kunio

    1999-10-26

    A method and system for the computerized registration of radionuclide images with radiographic images, including generating image data from radiographic and radionuclide images of the thorax. Techniques include contouring the lung regions in each type of chest image, scaling and registration of the contours based on location of lung apices, and superimposition after appropriate shifting of the images. Specific applications are given for the automated registration of radionuclide lungs scans with chest radiographs. The method in the example given yields a system that spatially registers and correlates digitized chest radiographs with V/Q scans in order to correlate V/Q functional information with the greater structural detail of chest radiographs. Final output could be the computer-determined contours from each type of image superimposed on any of the original images, or superimposition of the radionuclide image data, which contains high activity, onto the radiographic chest image.

  14. 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.

  15. Factor analysis of images in medical diagnostics

    International Nuclear Information System (INIS)

    Factor analysis is based on the assumption that characteristics measured on a set of objects are the external manifestation of other latent variables - factors. The analysis allows to find the relations between the factors and the measured characteristics. Image components are sought which are expressed differently in different pictures. The method is demonstrated and documented on sets of images from dynamic radionuclide studies of the kidneys, livers and hearts. The importance of factor analysis for diagnosis consists in the selective imaging of partial anatomic structures which cannot be directly observed in the original pictures. The use of factor analysis is conditional on the use of efficient computer technology. (M.D.). 14 figs

  16. 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)

  17. 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)

  18. 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.

  19. Detectors for medical radioisotope imaging: demands and perspectives

    OpenAIRE

    Lopes, M. I.; Chepel, V.

    2004-01-01

    Radioisotope imaging is used to obtain information on biochemical processes in living organisms, being a tool of increasing importance for medical diagnosis. The improvement and expansion of these techniques depend on the progress attained in several areas, such as radionuclide production, radiopharmaceuticals, radiation detectors and image reconstruction algorithms. This review paper will be concerned only with the detector technology.

  20. 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...

  1. 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

  2. Getting a Clear Picture on Medical Imaging

    International Nuclear Information System (INIS)

    Diseases take on all shapes and forms, and some are easier to detect than others. Obvious outward growths like rashes and warts are quick to spot, but for some diseases and conditions more information is needed. Fortunately, nuclear medicine doctors today can use a wide range of modern imaging and diagnosis techniques and technologies to identify a variety of health conditions. SPECT, PET, MRI, CT, ECHO, fluoroscopy — the list of diagnosis techniques go on, but do you know what they actually are? Imaging techniques can be broken down into two basic categories: those that simply show the anatomy, known as radiology, and those that look at the physiology, on how the body functions, which is known as functional imaging. This article presents a breakdown of the two imaging disciplines and how some of the most common techniques work

  3. Medical imaging and the principal phacomatoses

    International Nuclear Information System (INIS)

    Because of involvement of several or more embryonic tissue layers, manifestations of phacomatoses are widely variable. Different imaging methods can be used to determine the various localizations of these conditions: cerebral, thoracic and abdominal

  4. Medical image reconstruction a conceptual tutorial

    CERN Document Server

    Zeng, Gengsheng

    2010-01-01

    This text introduces classical and modern image reconstruction technologies. It presents both analytical and iterative methods of these technologies and their applications in X-ray CT, SPECT, PET and MRI.

  5. 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.

  6. 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.

  7. 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.

  8. Medical Imaging of Mummies and Bog Bodies

    DEFF Research Database (Denmark)

    Lynnerup, Niels

    2010-01-01

    and bog bodies could be studied non-destructively. This article describes the history of mummy radiography and CT scanning, and some of the problems and opportunities involved in applying these techniques, derived for clinical use, on naturally and artificially preserved ancient human bodies. Unless...... severely degraded, bone is quite readily visualized, but accurate imaging of preserved soft tissues, and pathological lesions therein, may require considerable post-image capture processing of CT data....

  9. 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...

  10. 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)

  11. The Influence of Intensity Standardization on Medical Image Registration

    CERN Document Server

    Bagci, Ulas; Bai, Li

    2010-01-01

    Acquisition-to-acquisition signal intensity variations (non-standardness) are inherent in MR images. Standardization is a post processing method for correcting inter-subject intensity variations through transforming all images from the given image gray scale into a standard gray scale wherein similar intensities achieve similar tissue meanings. The lack of a standard image intensity scale in MRI leads to many difficulties in tissue characterizability, image display, and analysis, including image segmentation. This phenomenon has been documented well; however, effects of standardization on medical image registration have not been studied yet. In this paper, we investigate the influence of intensity standardization in registration tasks with systematic and analytic evaluations involving clinical MR images. We conducted nearly 20,000 clinical MR image registration experiments and evaluated the quality of registrations both quantitatively and qualitatively. The evaluations show that intensity variations between i...

  12. 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.

  13. Automated detection of cardiac phase from intracoronary ultrasound image sequences.

    Science.gov (United States)

    Sun, Zheng; Dong, Yi; Li, Mengchan

    2015-01-01

    Intracoronary ultrasound (ICUS) is a widely used interventional imaging modality in clinical diagnosis and treatment of cardiac vessel diseases. Due to cyclic cardiac motion and pulsatile blood flow within the lumen, there exist changes of coronary arterial dimensions and relative motion between the imaging catheter and the lumen during continuous pullback of the catheter. The action subsequently causes cyclic changes to the image intensity of the acquired image sequence. Information on cardiac phases is implied in a non-gated ICUS image sequence. A 1-D phase signal reflecting cardiac cycles was extracted according to cyclical changes in local gray-levels in ICUS images. The local extrema of the signal were then detected to retrieve cardiac phases and to retrospectively gate the image sequence. Results of clinically acquired in vivo image data showed that the average inter-frame dissimilarity of lower than 0.1 was achievable with our technique. In terms of computational efficiency and complexity, the proposed method was shown to be competitive when compared with the current methods. The average frame processing time was lower than 30 ms. We effectively reduced the effect of image noises, useless textures, and non-vessel region on the phase signal detection by discarding signal components caused by non-cardiac factors. PMID:26406038

  14. 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.

  15. 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

  16. 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...

  17. 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...

  18. 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 ...

  19. Review of hard copy systems for digital medical imaging

    Science.gov (United States)

    Apple, Bernard A.; Tennant, Mark H.; Thomas, Jule W., Jr.

    1996-03-01

    In this paper we review image requirements and the potential use of various printing technologies to record digital diagnostic radiographic information. An analysis of limitations and advantages of alternate imaging systems compared to current laser imager/silver halide film systems will be presented. The future move to digital radiology along with its hard copy requirements will also be discussed. The winning technologies in the market place will be determined by their ability to provide adequate image quality at low cost while meeting productivity, durability, and convenience requirements. The first technology to meet these requirements will have a tremendous advantage in the market place. Medical imaging hard copy is dominated by the use of silver halide media providing monochrome images of diagnostic image quality. As new digital medical imaging modalities have emerged they have opened the door to new hard copy technologies. These new technologies have been born and nurtured outside the medical market by small markets with high image quality requirements or by large markets with lower image quality requirements. The former have tended to provide high cost, high quality solutions and the latter low cost, low quality solutions. Silver halide media still dominates, at least in part, because it provides high image quality at a relatively low cost. Yet, the trend away from wet silver halide is evident. These new hard copy technologies are being tested to determine their applicability to the medical market and are finding niches where they provide value. A clear winner that provides the required image quality at low cost has yet to emerge.

  20. 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

  1. Super resolution technique and its potential usage in medical imaging

    OpenAIRE

    Chang, Yiu-chuen; 張耀泉

    2014-01-01

    Purpose: Medical imaging systems are used to scan patients to obtain valuable information for diseases diagnosis and assisting treatment. An ideal scanner should be sensitive enough to detect any trace amount of abnormal tissue at its early stage. With the continuous development of high-tech treatment systems such as Tomotherapy (manufactured by Tomo HD), the high-resolution imaging system is favorable to reduce the damage of normal tissue due to the image guidance of Mega-voltage beam be...

  2. 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...

  3. The library without walls: images, medical dictionaries, atlases, medical encyclopedias free on web.

    Science.gov (United States)

    Giglia, E

    2008-09-01

    The aim of this article was to present the ''reference room'' of the Internet, a real library without walls. The reader will find medical encyclopedias, dictionaries, atlases, e-books, images, and will also learn something useful about the use and reuse of images in a text and in a web site, according to the copyright law. PMID:18762749

  4. In-vivo synthetic aperture flow imaging in medical ultrasound

    DEFF Research Database (Denmark)

    Nikolov, Svetoslav; Jensen, Jørgen Arendt

    2003-01-01

    .2% and a mean relative bias of 3.4% using 24 pulse emissions at a flow angle of 45 degrees. The 24 emissions can be used for making a full-color flow map image. An in-vivo image of How in the carotid artery for a 29-year-old male also is presented. The full image is acquired using 24 emissions.......A new method for acquiring flow images using synthetic aperture techniques in medical ultrasound is presented. The new approach makes it possible to have a continuous acquisition of flow data throughout the whole image simultaneously, and this can significantly improve blood velocity estimation...

  5. Semi-automated discrimination of retinal pigmented epithelial cells in two-photon fluorescence images of mouse retinas

    OpenAIRE

    Nathan S. Alexander; Palczewska, Grazyna; Palczewski, Krzysztof

    2015-01-01

    Automated image segmentation is a critical step toward achieving a quantitative evaluation of disease states with imaging techniques. Two-photon fluorescence microscopy (TPM) has been employed to visualize the retinal pigmented epithelium (RPE) and provide images indicating the health of the retina. However, segmentation of RPE cells within TPM images is difficult due to small differences in fluorescence intensity between cell borders and cell bodies. Here we present a semi-automated method f...

  6. 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

  7. 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.

  8. 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.

  9. 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 ($\

  10. 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...

  11. 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.

  12. Silicon detectors applied to medical imaging

    International Nuclear Information System (INIS)

    In this laboratory we will see some to those characteristics of silicon detectors which make them very useful in the fields of Medical Physics. One of the application of these devices that we will work with is in detecting low energy X-ray radiation (from 6 to 30KeV). In this laboratory we will learn something of the aquisition system (LabVIEW), the readout system (PCI-1200 card, buffer, RX64 chip and the silicon detector on the printed circuit board) and the measurements of the X rays (coming from a radiation source) for different positions of the detector, in searching for improving the efficiency of detection

  13. Extraction of Prostatic Lumina and Automated Recognition for Prostatic Calculus Image Using PCA-SVM

    OpenAIRE

    D. Joshua Liao; Yusheng Huang; Xiaofen Xing; Hua Wang; Jian Liu; Hui Xiao; Zhuocai Wang; Xiaojun Ding; Xiangmin Xu

    2011-01-01

    Identification of prostatic calculi is an important basis for determining the tissue origin. Computation-assistant diagnosis of prostatic calculi may have promising potential but is currently still less studied. We studied the extraction of prostatic lumina and automated recognition for calculus images. Extraction of lumina from prostate histology images was based on local entropy and Otsu threshold recognition using PCA-SVM and based on the texture features of prostatic calculus. The SVM cla...

  14. 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.

  15. 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

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

    International Nuclear Information System (INIS)

    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

  17. 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 ...

  18. 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 ...

  19. Medical imaging 1995: Physiology and function from multidimensional images

    International Nuclear Information System (INIS)

    This conference was held February 27--28, 1995 in San Diego, California. The purpose of the conference was to provide a forum for exchange of state-of-the art information on physiologic imaging. This meeting is unique in bringing together the physicists, image processors, workstation developers, experts in image perception, and the experts of picture archiving and display. Individual papers have been processed separately for inclusion in the appropriate data bases

  20. 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.

  1. Progress in the robust automated segmentation of real cell images

    Science.gov (United States)

    Bamford, P.; Jackway, P.; Lovell, Brian

    1999-07-01

    We propose a collection of robust algorithms for the segmentation of cell images from Papanicolaou stained cervical smears (`Pap' smears). This problem is deceptively difficult and often results on laboratory datasets do not carry over to real world data. Our approach is in 3 parts. First, we segment the cytoplasm from the background using a novel method based on the Wilson and Spann multi-resolution framework. Second, we segment the nucleus from the cytoplasm using an active contour method, where the best contour is found by a global minimization method. Third, we implement a method to determine a confidence measure for the segmentation of each object. This uses a stability criterion over the regularization parameter (lambda) in the active contour. We present the results of thorough testing of the algorithms on large numbers of cell images. A database of 20,120 images is used for the segmentation tests and 18,718 images for the robustness tests.

  2. 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...

  3. Automated detection of BB pixel clusters in digital fluoroscopic images

    International Nuclear Information System (INIS)

    Small ball bearings (BBs) are often used to characterize and correct for geometric distortion of x-ray image intensifiers. For quantitative applications the number of BBs required for accurate distortion correction is prohibitively large for manual detection. A method to automatically determine the BB coordinates is described. The technique consists of image segmentation, pixel coalescing and centroid calculation. The dependence of calculated BB coordinates on segmentation threshold was also evaluated and found to be within the uncertainty of measurement. (author)

  4. 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.

  5. Validation of Supervised Automated Algorithm for Fast Quantitative Evaluation of Organ Motion on Magnetic Resonance Imaging

    International Nuclear Information System (INIS)

    Purpose: To validate a correlation coefficient template-matching algorithm applied to the supervised automated quantification of abdominal-pelvic organ motion captured on time-resolved magnetic resonance imaging. Methods and Materials: Magnetic resonance images of 21 patients across four anatomic sites were analyzed. Representative anatomic points of interest were chosen as surrogates for organ motion. The point of interest displacements across each image frame relative to baseline were quantified manually and through the use of a template-matching software tool, termed 'Motiontrack.' Automated and manually acquired displacement measures, as well as the standard deviation of intrafraction motion, were compared for each image frame and for each patient. Results: Discrepancies between the automated and manual displacements of ≥2 mm were uncommon, ranging in frequency of 0-9.7% (liver and prostate, respectively). The standard deviations of intrafraction motion measured with each method correlated highly (r = 0.99). Considerable interpatient variability in organ motion was demonstrated by a wide range of standard deviations in the liver (1.4-7.5 mm), uterus (1.1-8.4 mm), and prostate gland (0.8-2.7 mm). The automated algorithm performed successfully in all patients but 1 and substantially improved efficiency compared with manual quantification techniques (5 min vs. 60-90 min). Conclusion: Supervised automated quantification of organ motion captured on magnetic resonance imaging using a correlation coefficient template-matching algorithm was efficient, accurate, and may play an important role in off-line adaptive approaches to intrafraction motion management

  6. 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.

  7. 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...

  8. 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...

  9. Medical images of the hip joint

    International Nuclear Information System (INIS)

    Up-to date techniques of sectional imaging of selected planes and ultrasonic methods have contributed considerably to improved diagnostic accuracy in the identification of hip joint anomalies in infants. Even though these innovations deserve to be valued highly the more conventional diagnostic methods are far from being superfluous and continue to be used on a routine basis in radiology. The relevant methods of focussing and ranges of use for standard and special projections are therefore surveyed in the following. (orig./GDG)

  10. 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.

  11. Recent advances in radiology and medical imaging

    International Nuclear Information System (INIS)

    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

  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. Multispectral Image Road Extraction Based Upon Automated Map Conflation

    Science.gov (United States)

    Chen, Bin

    Road network extraction from remotely sensed imagery enables many important and diverse applications such as vehicle tracking, drone navigation, and intelligent transportation studies. There are, however, a number of challenges to road detection from an image. Road pavement material, width, direction, and topology vary across a scene. Complete or partial occlusions caused by nearby buildings, trees, and the shadows cast by them, make maintaining road connectivity difficult. The problems posed by occlusions are exacerbated with the increasing use of oblique imagery from aerial and satellite platforms. Further, common objects such as rooftops and parking lots are made of materials similar or identical to road pavements. This problem of common materials is a classic case of a single land cover material existing for different land use scenarios. This work addresses these problems in road extraction from geo-referenced imagery by leveraging the OpenStreetMap digital road map to guide image-based road extraction. The crowd-sourced cartography has the advantages of worldwide coverage that is constantly updated. The derived road vectors follow only roads and so can serve to guide image-based road extraction with minimal confusion from occlusions and changes in road material. On the other hand, the vector road map has no information on road widths and misalignments between the vector map and the geo-referenced image are small but nonsystematic. Properly correcting misalignment between two geospatial datasets, also known as map conflation, is an essential step. A generic framework requiring minimal human intervention is described for multispectral image road extraction and automatic road map conflation. The approach relies on the road feature generation of a binary mask and a corresponding curvilinear image. A method for generating the binary road mask from the image by applying a spectral measure is presented. The spectral measure, called anisotropy-tunable distance (ATD

  14. RADIOGRAPHIC MEDICAL IMAGE RETRIEVAL SYSTEM FOR BOTH ORGAN AND PATHOLOGY LEVEL USING BAG OF VISUAL WORDS

    OpenAIRE

    S. Malar Selvi; Kavitha, C.

    2014-01-01

    This research work is to develop an efficient and powerful medical search engine to classify and search the radiographic medical images. It focuses on bag of visual words image representation and a similarity matching technique to represent match and retrieve the similar images. This work addresses the issues in content based image retrieval for medical images. In this system can handles different categories of medical images in organ level and the pathology level for chest X-ray images. This...

  15. 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...

  16. Medical image of the week: vascular occlusion

    Directory of Open Access Journals (Sweden)

    Shapiro A

    2014-07-01

    Full Text Available The patient is a 39 year-old woman with no significant past medical history presenting with progressive left hand pain for five days. The patient denied a history of Raynaud’s phenomenon or clotting disorders. She had no radial pulse on presentation and angiogram showed severe complete occlusion of the radial and ulnar arteries (Figures 1 and 2. She had an initial partial response with intra-arterial verapamil and nitroglycerin but her hand ischemia did not improve on heparin or with intra-arterial tissue plasminogen activator. Autoimmune and coagulation work-ups were negative. Her left hand finger necrosis at time of discharge is shown (Figure 3. Further evaluation is ongoing for coagulation disorders.

  17. Medical image of the week: Westermark sign

    Directory of Open Access Journals (Sweden)

    Omar M

    2015-03-01

    Full Text Available A 71 year old man was evaluated in the Emergency Department for acute onset of dyspnea. On exam he was tachypneic, tachycardic and hypoxemic requiring 6 L/min of oxygen. He had recently underwent prostatectomy for prostate cancer. Past medical history was also significant for coronary artery disease treated with coronary bypass. The chest x-ray (Figure 1 shows unilateral oligemia concerning for a pulmonary embolus and the CT angiogram of the chest (Figure 2 confirms the diagnosis. While the chest radiograph is normal in the majority of pulmonary emboli, the ‘Westermark sign’ may be seen in up to 2% of the cases (1. It represents a focus of oligemia seen distal to a pulmonary embolism. The finding is a result of a combination of dilation of the pulmonary artery proximal to the thrombus and the collapse of the distal vasculature.

  18. Flexible medical image management using service-oriented architecture.

    Science.gov (United States)

    Shaham, Oded; Melament, Alex; Barak-Corren, Yuval; Kostirev, Igor; Shmueli, Noam; Peres, Yardena

    2012-01-01

    Management of medical images increasingly involves the need for integration with a variety of information systems. To address this need, we developed Content Management Offering (CMO), a platform for medical image management supporting interoperability through compliance with standards. CMO is based on the principles of service-oriented architecture, implemented with emphasis on three areas: clarity of business process definition, consolidation of service configuration management, and system scalability. Owing to the flexibility of this platform, a small team is able to accommodate requirements of customers varying in scale and in business needs. We describe two deployments of CMO, highlighting the platform's value to customers. CMO represents a flexible approach to medical image management, which can be applied to a variety of information technology challenges in healthcare and life sciences organizations. PMID:22874344

  19. Analysis of the journal articles of medical imaging by bibliometrics

    International Nuclear Information System (INIS)

    Purpose: To evaluate the development status, character and trends of medical imaging. Methods: The articles published on >, > and > from 1983 to 1996 were analyzed by bibliometrics and compared with the articles published on > and > of USA. Results: total numbers of the published articles were increasing gradually in these years. But, the rate of increase was not equal among different research fields. For example, the number of research articles of CT, MR and Interventional Radiography were increasing more quickly than that of X ray. It was also found that the development status and trends of medical imaging were different between China and America. Most research articles published in the journals of America in 1996 were about MR, whereas CT ranked first in china in the same year. Conclusion: Medical imaging develops very quickly in recent years. The emphasis of research and development has switched over from traditional X ray to new fields or techniques, such as Ct, MR and interventional radiology

  20. 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.

  1. 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

  2. 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.

  3. 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.

  4. 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)

  5. Comment on 'Perspectives of medical X-ray imaging'

    International Nuclear Information System (INIS)

    In the paper 'Perspectives of medical X-ray imaging' (Nucl. Instr. and Meth. A 466 (2001) 99) the authors 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

  6. Comment on ``Perspectives of medical X-ray imaging''

    Science.gov (United States)

    Taibi, A.; Baldelli, P.; Tuffanelli, A.; Gambaccini, M.

    2002-07-01

    In the paper "Perspectives of medical X-ray imaging" (Nucl. Instr. and Meth. A 466 (2001) 99) the authors 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.

  7. 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.

  8. 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

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. System and method for automated object detection in an image

    Science.gov (United States)

    Kenyon, Garrett T.; Brumby, Steven P.; George, John S.; Paiton, Dylan M.; Schultz, Peter F.

    2015-10-06

    A contour/shape detection model may use relatively simple and efficient kernels to detect target edges in an object within an image or video. A co-occurrence probability may be calculated for two or more edge features in an image or video using an object definition. Edge features may be differentiated between in response to measured contextual support, and prominent edge features may be extracted based on the measured contextual support. The object may then be identified based on the extracted prominent edge features.

  14. 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.

  15. 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

  16. 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

  17. 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)

  18. Semi-automated recognition of protozoa by image analysis

    OpenAIRE

    A.L. Amaral; Baptiste, C; Pons, M. N.; Nicolau, Ana; Lima, Nelson; Ferreira, E. C.; Mota, M.; H. Vivier

    1999-01-01

    A programme was created to semi-automatically analyse protozoal digitised images. Principal Component Analysis technique was used for species identification. After data collection and mathematical treatment, a threedimensional representation was generated and several protozoa (Opercularia, Colpidium, Tetrahymena, Prorodon, Glaucoma and Trachelophyllum) species could be positively identified.

  19. 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.

  20. 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%.

  1. Technical challenges for the construction of a medical image database

    Science.gov (United States)

    Ring, Francis J.; Ammer, Kurt; Wiecek, Boguslaw; Plassmann, Peter; Jones, Carl D.; Jung, Anna; Murawski, Piotr

    2005-10-01

    Infrared thermal imaging was first made available to medicine in the early 1960's. Despite a large number of research publications on the clinical application of the technique, the images have been largely qualitative. This is in part due to the imaging technology itself, and the problem of data exchange between different medical users, with different hardware. An Anglo Polish collaborative study was set up in 2001 to identify and resolve the sources of error and problems in medical thermal imaging. Standardisation of the patient preparation, imaging hardware, image capture and analysis has been studied and developed by the group. A network of specialist centres in Europe is planned to work to establish the first digital reference atlas of quantifiable images of the normal healthy human body. Further processing techniques can then be used to classify abnormalities found in disease states. The follow up of drug treatment has been successfully monitored in clinical trials with quantitative thermal imaging. The collection of normal reference images is in progress. This paper specifies the areas found to be the source of unwanted variables, and the protocols to overcome them.

  2. 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 ...

  3. Medical image of the week: asbestosis

    Directory of Open Access Journals (Sweden)

    Strawter C

    2014-12-01

    Full Text Available No abstract available. Article truncated at 150 words. A 76-year-old man with a past medical history of diabetes mellitus, hypertension, and an unspecified industrial-related asbestos exposure presented to the hospital after a syncopal episode and a ground level fall. A computed tomography (CT of the chest was performed on admission which revealed several abnormalities including multiple bilateral calcified pleural plaques, pleural thickening, peripheral groundglass opacities (GGO in the nondependent portion of the lungs and subpleural reticular and band like opacities. The patient unfortunately developed alcohol withdrawal and aspiration pneumonia requiring prolonged mechanical ventilation and was unable to provide additional details regarding his lung disease. Asbestos is a naturally occurring mineral that historically was praised for its versatility. Its properties including heat and electrical resistance, tensile strength, and insulating capabilities made it a common component in materials used in both commercial and domestic settings. Exposure to asbestos is linked to numerous respiratory diseases, including pleural and parenchymal disease, both ...

  4. 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 ...

  5. 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 …

  6. 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 ...

  7. Medical image of the week: spontaneous pneumomediastinum

    Directory of Open Access Journals (Sweden)

    Griffin L

    2016-03-01

    Full Text Available No abstract available. Article truncated at 150 words. A 24-year-old man with a past medical history significant for type I diabetes mellitus presented to the emergency department with complaints of nausea and vomiting for several days. He reported he had been on drinking alcohol heavily 4 days prior to presentation and subsequently had multiple episodes of vomiting. Initial laboratory evaluation was consistent with diabetic ketoacidosis (DKA. A routine chest x-ray was obtained to evaluate for an infectious etiology of his DKA and revealed pneumomediastinum and a small right apical pneumothorax (Figure 1. A CT scan of the chest was done and showed extensive pneumomediastinum as well as air tracking along the bronchovascular sheaths in the left lower lobe (Figure 2 and 3. It did not reveal evidence of esophageal injury. Spontaneous pneumomediastinum (SPM refers to pneumomediastinum that is not associated with noticeable cause such as esophageal rupture or trauma. It is typically a benign condition thought to be ...

  8. 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 ...

  9. 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 ...

  10. 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 ...

  11. 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 ...

  12. 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...

  13. 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.

  14. 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.

  15. 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.

  16. Detectors for medical radioisotope imaging: demands and perspectives

    Science.gov (United States)

    Lopes, M. I.; Chepel, V.

    2004-10-01

    Radioisotope imaging is used to obtain information on biochemical processes in living organisms, being a tool of increasing importance for medical diagnosis. The improvement and expansion of these techniques depend on the progress attained in several areas, such as radionuclide production, radiopharmaceuticals, radiation detectors and image reconstruction algorithms. This review paper will be concerned only with the detector technology. We will review in general terms the present status of medical radioisotope imaging instrumentation with the emphasis put on the developments of high-resolution gamma cameras and PET detector systems for scinti-mammography and animal imaging. The present trend to combine two or more modalities in a single machine in order to obtain complementary information will also be considered.

  17. Detectors for medical radioisotope imaging: demands and perspectives

    Energy Technology Data Exchange (ETDEWEB)

    Lopes, M.I. E-mail: isabel@lipc.fis.uc.pt; Chepel, V

    2004-11-01

    Radioisotope imaging is used to obtain information on biochemical processes in living organisms, being a tool of increasing importance for medical diagnosis. The improvement and expansion of these techniques depend on the progress attained in several areas, such as radionuclide production, radiopharmaceuticals, radiation detectors and image reconstruction algorithms. This review paper will be concerned only with the detector technology. We will review in general terms the present status of medical radioisotope imaging instrumentation with the emphasis put on the developments of high-resolution gamma cameras and PET detector systems for scinti-mammography and animal imaging. The present trend to combine two or more modalities in a single machine in order to obtain complementary information will also be considered.

  18. 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.

  19. 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...

  20. 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.