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Sample records for automated medical image

  1. Automated medical image segmentation techniques

    Directory of Open Access Journals (Sweden)

    Sharma Neeraj

    2010-01-01

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

  2. A Semi-automated Approach to Improve the Efficiency of Medical Imaging Segmentation for Haptic Rendering.

    Science.gov (United States)

    Banerjee, Pat; Hu, Mengqi; Kannan, Rahul; Krishnaswamy, Srinivasan

    2017-08-01

    The Sensimmer platform represents our ongoing research on simultaneous haptics and graphics rendering of 3D models. For simulation of medical and surgical procedures using Sensimmer, 3D models must be obtained from medical imaging data, such as magnetic resonance imaging (MRI) or computed tomography (CT). Image segmentation techniques are used to determine the anatomies of interest from the images. 3D models are obtained from segmentation and their triangle reduction is required for graphics and haptics rendering. This paper focuses on creating 3D models by automating the segmentation of CT images based on the pixel contrast for integrating the interface between Sensimmer and medical imaging devices, using the volumetric approach, Hough transform method, and manual centering method. Hence, automating the process has reduced the segmentation time by 56.35% while maintaining the same accuracy of the output at ±2 voxels.

  3. Automated endoscopic navigation and advisory system from medical image

    Science.gov (United States)

    Kwoh, Chee K.; Khan, Gul N.; Gillies, Duncan F.

    1999-05-01

    , which is developed to obtain the relative depth of the colon surface in the image by assuming a point light source very close to the camera. If we assume the colon has a shape similar to a tube, then a reasonable approximation of the position of the center of the colon (lumen) will be a function of the direction in which the majority of the normal vectors of shape are pointing. The second layer is the control layer and at this level, a decision model must be built for endoscope navigation and advisory system. The system that we built is the models of probabilistic networks that create a basic, artificial intelligence system for navigation in the colon. We have constructed the probabilistic networks from correlated objective data using the maximum weighted spanning tree algorithm. In the construction of a probabilistic network, it is always assumed that the variables starting from the same parent are conditionally independent. However, this may not hold and will give rise to incorrect inferences. In these cases, we proposed the creation of a hidden node to modify the network topology, which in effect models the dependency of correlated variables, to solve the problem. The conditional probability matrices linking the hidden node to its neighbors are determined using a gradient descent method which minimizing the objective cost function. The error gradients can be treated as updating messages and ca be propagated in any direction throughout any singly connected network to adjust the network parameters. With the above two- level approach, we have been able to build an automated endoscope navigation and advisory system successfully.

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

    International Nuclear Information System (INIS)

    Mizuta, Shinobu; Urayama, Shin-ichi; Zoroofi, R.A.; Uyama, Chikao

    1998-01-01

    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)

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

    Science.gov (United States)

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

    2011-01-01

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

  6. Automating the segmentation of medical images for the production of voxel tomographic computational models

    International Nuclear Information System (INIS)

    Caon, M.

    2001-01-01

    Radiation dosimetry for the diagnostic medical imaging procedures performed on humans requires anatomically accurate, computational models. These may be constructed from medical images as voxel-based tomographic models. However, they are time consuming to produce and as a consequence, there are few available. This paper discusses the emergence of semi-automatic segmentation techniques and describes an application (iRAD) written in Microsoft Visual Basic that allows the bitmap of a medical image to be segmented interactively and semi-automatically while displayed in Microsoft Excel. iRAD will decrease the time required to construct voxel models. Copyright (2001) Australasian College of Physical Scientists and Engineers in Medicine

  7. Integrating spatial fuzzy clustering with level set methods for automated medical image segmentation.

    Science.gov (United States)

    Li, Bing Nan; Chui, Chee Kong; Chang, Stephen; Ong, S H

    2011-01-01

    The performance of the level set segmentation is subject to appropriate initialization and optimal configuration of controlling parameters, which require substantial manual intervention. A new fuzzy level set algorithm is proposed in this paper to facilitate medical image segmentation. It is able to directly evolve from the initial segmentation by spatial fuzzy clustering. The controlling parameters of level set evolution are also estimated from the results of fuzzy clustering. Moreover the fuzzy level set algorithm is enhanced with locally regularized evolution. Such improvements facilitate level set manipulation and lead to more robust segmentation. Performance evaluation of the proposed algorithm was carried on medical images from different modalities. The results confirm its effectiveness for medical image segmentation. Copyright © 2010 Elsevier Ltd. All rights reserved.

  8. A novel level set model with automated initialization and controlling parameters for medical image segmentation.

    Science.gov (United States)

    Liu, Qingyi; Jiang, Mingyan; Bai, Peirui; Yang, Guang

    2016-03-01

    In this paper, a level set model without the need of generating initial contour and setting controlling parameters manually is proposed for medical image segmentation. The contribution of this paper is mainly manifested in three points. First, we propose a novel adaptive mean shift clustering method based on global image information to guide the evolution of level set. By simple threshold processing, the results of mean shift clustering can automatically and speedily generate an initial contour of level set evolution. Second, we devise several new functions to estimate the controlling parameters of the level set evolution based on the clustering results and image characteristics. Third, the reaction diffusion method is adopted to supersede the distance regularization term of RSF-level set model, which can improve the accuracy and speed of segmentation effectively with less manual intervention. Experimental results demonstrate the performance and efficiency of the proposed model for medical image segmentation. Copyright © 2015 Elsevier Ltd. All rights reserved.

  9. 3D deeply supervised network for automated segmentation of volumetric medical images.

    Science.gov (United States)

    Dou, Qi; Yu, Lequan; Chen, Hao; Jin, Yueming; Yang, Xin; Qin, Jing; Heng, Pheng-Ann

    2017-10-01

    While deep convolutional neural networks (CNNs) have achieved remarkable success in 2D medical image segmentation, it is still a difficult task for CNNs to segment important organs or structures from 3D medical images owing to several mutually affected challenges, including the complicated anatomical environments in volumetric images, optimization difficulties of 3D networks and inadequacy of training samples. In this paper, we present a novel and efficient 3D fully convolutional network equipped with a 3D deep supervision mechanism to comprehensively address these challenges; we call it 3D DSN. Our proposed 3D DSN is capable of conducting volume-to-volume learning and inference, which can eliminate redundant computations and alleviate the risk of over-fitting on limited training data. More importantly, the 3D deep supervision mechanism can effectively cope with the optimization problem of gradients vanishing or exploding when training a 3D deep model, accelerating the convergence speed and simultaneously improving the discrimination capability. Such a mechanism is developed by deriving an objective function that directly guides the training of both lower and upper layers in the network, so that the adverse effects of unstable gradient changes can be counteracted during the training procedure. We also employ a fully connected conditional random field model as a post-processing step to refine the segmentation results. We have extensively validated the proposed 3D DSN on two typical yet challenging volumetric medical image segmentation tasks: (i) liver segmentation from 3D CT scans and (ii) whole heart and great vessels segmentation from 3D MR images, by participating two grand challenges held in conjunction with MICCAI. We have achieved competitive segmentation results to state-of-the-art approaches in both challenges with a much faster speed, corroborating the effectiveness of our proposed 3D DSN. Copyright © 2017 Elsevier B.V. All rights reserved.

  10. Medical Imaging.

    Science.gov (United States)

    Barker, M. C. J.

    1996-01-01

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

  11. Medical imaging

    CERN Document Server

    Townsend, David W

    1996-01-01

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

  12. Automated identification of dementia using medical imaging: a survey from a pattern classification perspective.

    Science.gov (United States)

    Zheng, Chuanchuan; Xia, Yong; Pan, Yongsheng; Chen, Jinhu

    2016-03-01

    In this review paper, we summarized the automated dementia identification algorithms in the literature from a pattern classification perspective. Since most of those algorithms consist of both feature extraction and classification, we provide a survey on three categories of feature extraction methods, including the voxel-, vertex- and ROI-based ones, and four categories of classifiers, including the linear discriminant analysis, Bayes classifiers, support vector machines, and artificial neural networks. We also compare the reported performance of many recently published dementia identification algorithms. Our comparison shows that many algorithms can differentiate the Alzheimer's disease (AD) from elderly normal with a largely satisfying accuracy, whereas distinguishing the mild cognitive impairment from AD or elderly normal still remains a major challenge.

  13. 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.

  14. 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.

  15. Handling Big Data in Medical Imaging: Iterative Reconstruction with Large-Scale Automated Parallel Computation.

    Science.gov (United States)

    Lee, Jae H; Yao, Yushu; Shrestha, Uttam; Gullberg, Grant T; Seo, Youngho

    2014-11-01

    The primary goal of this project is to implement the iterative statistical image reconstruction algorithm, in this case maximum likelihood expectation maximum (MLEM) used for dynamic cardiac single photon emission computed tomography, on Spark/GraphX. This involves porting the algorithm to run on large-scale parallel computing systems. Spark is an easy-to- program software platform that can handle large amounts of data in parallel. GraphX is a graph analytic system running on top of Spark to handle graph and sparse linear algebra operations in parallel. The main advantage of implementing MLEM algorithm in Spark/GraphX is that it allows users to parallelize such computation without any expertise in parallel computing or prior knowledge in computer science. In this paper we demonstrate a successful implementation of MLEM in Spark/GraphX and present the performance gains with the goal to eventually make it useable in clinical setting.

  16. Automated assessment of joint synovitis activity from medical ultrasound and power doppler examinations using image processing and machine learning methods

    Directory of Open Access Journals (Sweden)

    Rafal Cupek

    2016-11-01

    Full Text Available Objectives : Rheumatoid arthritis is the most common rheumatic disease with arthritis, and causes substantial functional disability in approximately 50% patients after 10 years. Accurate measurement of the disease activity is crucial to provide an adequate treatment and care to the patients. The aim of this study is focused on a computer aided diagnostic system that supports an assessment of synovitis severity. Material and methods : This paper focus on a computer aided diagnostic system that was developed within joint Polish–Norwegian research project related to the automated assessment of the severity of synovitis. Semiquantitative ultrasound with power Doppler is a reliable and widely used method of assessing synovitis. Synovitis is estimated by ultrasound examiner using the scoring system graded from 0 to 3. Activity score is estimated on the basis of the examiner’s experience or standardized ultrasound atlases. The method needs trained medical personnel and the result can be affected by a human error. Results : The porotype of a computer-aided diagnostic system and algorithms essential for an analysis of ultrasonic images of finger joints are main scientific output of the MEDUSA project. Medusa Evaluation System prototype uses bone, skin, joint and synovitis area detectors for mutual structural model based evaluation of synovitis. Finally, several algorithms that support the semi-automatic or automatic detection of the bone region were prepared as well as a system that uses the statistical data processing approach in order to automatically localize the regions of interest. Conclusions : Semiquantitative ultrasound with power Doppler is a reliable and widely used method of assessing synovitis. Activity score is estimated on the basis of the examiner’s experience and the result can be affected by a human error. In this paper we presented the MEDUSA project which is focused on a computer aided diagnostic system that supports an

  17. 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

  18. 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....

  19. Generative Interpretation of Medical Images

    DEFF Research Database (Denmark)

    Stegmann, Mikkel Bille

    2004-01-01

    This thesis describes, proposes and evaluates methods for automated analysis and quantification of medical images. A common theme is the usage of generative methods, which draw inference from unknown images by synthesising new images having shape, pose and appearance similar to the analysed images....... The theoretical framework for fulfilling these goals is based on the class of Active Appearance Models, which has been explored and extended in case studies involving cardiac and brain magnetic resonance images (MRI), and chest radiographs. Topics treated include model truncation, model compression using wavelets......, handling of non-Gaussian variation by means of cluster analysis, correction of respiratory noise in cardiac MRI, and the extensions to multi-slice two-dimensional time-series and bi-temporal three-dimensional models. The medical applications include automated estimation of: left ventricular ejection...

  20. AUTOMATION OF IMAGE DATA PROCESSING

    Directory of Open Access Journals (Sweden)

    Preuss Ryszard

    2014-12-01

    Full Text Available This article discusses the current capabilities of automate processing of the image data on the example of using PhotoScan software by Agisoft . At present, image data obtained by various registration systems (metric and non - metric cameras placed on airplanes , satellites , or more often on UAVs is used to create photogrammetric products. Multiple registrations of object or land area (large groups of photos are captured are usually performed in order to eliminate obscured area as well as to raise the final accuracy of the photogrammetric product. Because of such a situation t he geometry of the resulting image blocks is far from the typical configuration of images . For fast images georeferencing automatic image matching algorithms are currently applied . They can create a model of a block in the local coordinate system or using initial exterior orientation and measured control points can provide image georeference in an external reference frame. In the case of non - metric image application, it is also possible to carry out self - calibration process at this stage . Image matching algorithm is also used in generation of dense point clouds reconstructing spatial shape of the object ( area. In subsequent processing steps it is possible to obtain typical photogrammetric products such as orthomosaic , DSM or DTM and a photorealistic solid model of an object . All aforementioned processing steps are implemented in a single program in contrary to standard commercial software dividing all steps into dedicated modules . I mage processing leading to final geo referenced products can be fully automated including sequential implementation of the processing steps at predetermined control parameters . The paper presents the practical results of the application fully automatic generation of othomosaic for both images obtained by a metric Vexell camera and a block of images acquired by a non - metric UAV system.

  1. Autoradiography and automated image analysis

    International Nuclear Information System (INIS)

    Vardy, P.H.; Willard, A.G.

    1982-01-01

    Limitations with automated image analysis and the solution of problems encountered are discussed. With transmitted light, unstained plastic sections with planar profiles should be used. Stains potentiate signal so that television registers grains as falsely larger areas of low light intensity. Unfocussed grains in paraffin sections will not be seen by image analysers due to change in darkness and size. With incident illumination, the use of crossed polars, oil objectives and an oil filled light trap continuous with the base of the slide will reduce glare. However this procedure so enormously attenuates the light reflected by silver grains, that detection may be impossible. Autoradiographs should then be photographed and the negative images of silver grains on film analysed automatically using transmitted light

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

    International Nuclear Information System (INIS)

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

    1987-01-01

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

  3. Medical Imaging System

    Science.gov (United States)

    1991-01-01

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

  4. Automated image segmentation using information theory

    International Nuclear Information System (INIS)

    Hibbard, L.S.

    2001-01-01

    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 -Σ x p(x)log 2 p(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 Σ x p(x)log 2 {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. Digital medical imaging

    International Nuclear Information System (INIS)

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

    1989-01-01

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

  6. 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...

  7. Medical Imaging: A Review

    Science.gov (United States)

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

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

  8. Processing of medical images

    International Nuclear Information System (INIS)

    Restrepo, A.

    1998-01-01

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

  9. 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...

  10. Automated image enhancement using power law transformations

    Indian Academy of Sciences (India)

    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 ...

  11. Automated image enhancement using power law transformations

    Indian Academy of Sciences (India)

    Abstract. 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 ...

  12. Automated imaging system for single molecules

    Science.gov (United States)

    Schwartz, David Charles; Runnheim, Rodney; Forrest, Daniel

    2012-09-18

    There is provided a high throughput automated single molecule image collection and processing system that requires minimal initial user input. The unique features embodied in the present disclosure allow automated collection and initial processing of optical images of single molecules and their assemblies. Correct focus may be automatically maintained while images are collected. Uneven illumination in fluorescence microscopy is accounted for, and an overall robust imaging operation is provided yielding individual images prepared for further processing in external systems. Embodiments described herein are useful in studies of any macromolecules such as DNA, RNA, peptides and proteins. The automated image collection and processing system and method of same may be implemented and deployed over a computer network, and may be ergonomically optimized to facilitate user interaction.

  13. ARTIP: Automated Radio Telescope Image Processing Pipeline

    Science.gov (United States)

    Sharma, Ravi; Gyanchandani, Dolly; Kulkarni, Sarang; Gupta, Neeraj; Pathak, Vineet; Pande, Arti; Joshi, Unmesh

    2018-02-01

    The Automated Radio Telescope Image Processing Pipeline (ARTIP) automates the entire process of flagging, calibrating, and imaging for radio-interferometric data. ARTIP starts with raw data, i.e. a measurement set and goes through multiple stages, such as flux calibration, bandpass calibration, phase calibration, and imaging to generate continuum and spectral line images. Each stage can also be run independently. The pipeline provides continuous feedback to the user through various messages, charts and logs. It is written using standard python libraries and the CASA package. The pipeline can deal with datasets with multiple spectral windows and also multiple target sources which may have arbitrary combinations of flux/bandpass/phase calibrators.

  14. 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.

  15. Automated UMLS-based comparison of medical forms.

    Directory of Open Access Journals (Sweden)

    Martin Dugas

    Full Text Available Medical forms are very heterogeneous: on a European scale there are thousands of data items in several hundred different systems. To enable data exchange for clinical care and research purposes there is a need to develop interoperable documentation systems with harmonized forms for data capture. A prerequisite in this harmonization process is comparison of forms. So far--to our knowledge--an automated method for comparison of medical forms is not available. A form contains a list of data items with corresponding medical concepts. An automatic comparison needs data types, item names and especially item with these unique concept codes from medical terminologies. The scope of the proposed method is a comparison of these items by comparing their concept codes (coded in UMLS. Each data item is represented by item name, concept code and value domain. Two items are called identical, if item name, concept code and value domain are the same. Two items are called matching, if only concept code and value domain are the same. Two items are called similar, if their concept codes are the same, but the value domains are different. Based on these definitions an open-source implementation for automated comparison of medical forms in ODM format with UMLS-based semantic annotations was developed. It is available as package compareODM from http://cran.r-project.org. To evaluate this method, it was applied to a set of 7 real medical forms with 285 data items from a large public ODM repository with forms for different medical purposes (research, quality management, routine care. Comparison results were visualized with grid images and dendrograms. Automated comparison of semantically annotated medical forms is feasible. Dendrograms allow a view on clustered similar forms. The approach is scalable for a large set of real medical forms.

  16. Automated UMLS-based comparison of medical forms.

    Science.gov (United States)

    Dugas, Martin; Fritz, Fleur; Krumm, Rainer; Breil, Bernhard

    2013-01-01

    Medical forms are very heterogeneous: on a European scale there are thousands of data items in several hundred different systems. To enable data exchange for clinical care and research purposes there is a need to develop interoperable documentation systems with harmonized forms for data capture. A prerequisite in this harmonization process is comparison of forms. So far--to our knowledge--an automated method for comparison of medical forms is not available. A form contains a list of data items with corresponding medical concepts. An automatic comparison needs data types, item names and especially item with these unique concept codes from medical terminologies. The scope of the proposed method is a comparison of these items by comparing their concept codes (coded in UMLS). Each data item is represented by item name, concept code and value domain. Two items are called identical, if item name, concept code and value domain are the same. Two items are called matching, if only concept code and value domain are the same. Two items are called similar, if their concept codes are the same, but the value domains are different. Based on these definitions an open-source implementation for automated comparison of medical forms in ODM format with UMLS-based semantic annotations was developed. It is available as package compareODM from http://cran.r-project.org. To evaluate this method, it was applied to a set of 7 real medical forms with 285 data items from a large public ODM repository with forms for different medical purposes (research, quality management, routine care). Comparison results were visualized with grid images and dendrograms. Automated comparison of semantically annotated medical forms is feasible. Dendrograms allow a view on clustered similar forms. The approach is scalable for a large set of real medical forms.

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

    International Nuclear Information System (INIS)

    Ben Abdallah, M.; Malek, J.; Tourki, R.; Krissian, K.

    2011-01-01

    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.

  18. Classification in Medical Imaging

    DEFF Research Database (Denmark)

    Chen, Chen

    Classification is extensively used in the context of medical image analysis for the purpose of diagnosis or prognosis. In order to classify image content correctly, one needs to extract efficient features with discriminative properties and build classifiers based on these features. In addition...... to segment breast tissue and pectoral muscle area from the background in mammogram. The second focus is the choices of metric and its influence to the feasibility of a classifier, especially on k-nearest neighbors (k-NN) algorithm, with medical applications on breast cancer prediction and calcification...

  19. Medical Office Automation Using Multifunction Distributed Intelligence Computer Systems

    Science.gov (United States)

    Radcliffe, Robert A.

    1983-01-01

    Medical industry focus will soon dramatically shift away from towards and -oriented . computers are presently available at microcomputer prices, with a performance level, flexibility, and sophistication which far outstrips that of and computer systems being touted today for automating medical office activities. Continued investment in and computer systems for medical office automation appears shortsighted in light of clear trends in both the medical and computer industries toward systems which must accommodate advanced communications, graphics, and integrated diagnostic equipment capabilities.

  20. 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

  1. Semi-automated Image Processing for Preclinical Bioluminescent Imaging.

    Science.gov (United States)

    Slavine, Nikolai V; McColl, Roderick W

    Bioluminescent imaging is a valuable noninvasive technique for investigating tumor dynamics and specific biological molecular events in living animals to better understand the effects of human disease in animal models. The purpose of this study was to develop and test a strategy behind automated methods for bioluminescence image processing from the data acquisition to obtaining 3D images. In order to optimize this procedure a semi-automated image processing approach with multi-modality image handling environment was developed. To identify a bioluminescent source location and strength we used the light flux detected on the surface of the imaged object by CCD cameras. For phantom calibration tests and object surface reconstruction we used MLEM algorithm. For internal bioluminescent sources we used the diffusion approximation with balancing the internal and external intensities on the boundary of the media and then determined an initial order approximation for the photon fluence we subsequently applied a novel iterative deconvolution method to obtain the final reconstruction result. We find that the reconstruction techniques successfully used the depth-dependent light transport approach and semi-automated image processing to provide a realistic 3D model of the lung tumor. Our image processing software can optimize and decrease the time of the volumetric imaging and quantitative assessment. The data obtained from light phantom and lung mouse tumor images demonstrate the utility of the image reconstruction algorithms and semi-automated approach for bioluminescent image processing procedure. We suggest that the developed image processing approach can be applied to preclinical imaging studies: characteristics of tumor growth, identify metastases, and potentially determine the effectiveness of cancer treatment.

  2. [The study of medical supplies automation replenishment algorithm in hospital on medical supplies supplying chain].

    Science.gov (United States)

    Sheng, Xi

    2012-07-01

    The thesis aims to study the automation replenishment algorithm in hospital on medical supplies supplying chain. The mathematical model and algorithm of medical supplies automation replenishment are designed through referring to practical data form hospital on the basis of applying inventory theory, greedy algorithm and partition algorithm. The automation replenishment algorithm is proved to realize automatic calculation of the medical supplies distribution amount and optimize medical supplies distribution scheme. A conclusion could be arrived that the model and algorithm of inventory theory, if applied in medical supplies circulation field, could provide theoretical and technological support for realizing medical supplies automation replenishment of hospital on medical supplies supplying chain.

  3. Medical imaging systems

    Science.gov (United States)

    Frangioni, John V [Wayland, MA

    2012-07-24

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

  4. Automated Segmentation of Cardiac Magnetic Resonance Images

    DEFF Research Database (Denmark)

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

    2001-01-01

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

  5. Complex automated medication systems reduce medication administration errors in a Danish acute medical unit.

    Science.gov (United States)

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

    2018-03-24

    The objective of this study was to evaluate the effectiveness of two automated medication systems in reducing medication administration errors. The study was a controlled before-and-after study and included three observation periods with collection of data during a 3-week period as initial baseline and two subsequent follow-up periods at 10 and 20 months. The study was conducted in two Danish acute medical units. Two automated medication systems were implemented: (i) a complex automated medication system (cAMS) consisting of an automated dispensing cabinet, automated unit-dose dispensing and barcode medication administration (BCMA) and (ii) a non-patient-specific automated medication system (npsAMS) consisting of automated unit-dose dispensing and BCMA. The occurrence of administration errors and sub-types; procedural and clinical errors were observed. The proportion of errors was calculated by dividing the number of doses with one or more errors with the number of opportunities for errors. Difference-in-difference analysis using logistic regression was used to assess changes in proportion of errors. Compared with control, the cAMS reduced the overall risk of administration errors in the intervention unit, (odds ratio (OR) 0.53; 95% confidence interval (CI) 0.27-0.90) and procedural errors were significantly reduced as well (OR 0.44; 95% CI 0.126-0.94). The npsAMS effectively reduced the clinical errors in the intervention ward (OR 0.38; 95% CI 0.15-0.96). In line with previous research, this study found that technological interventions in the medication administration process could reduce the occurrence of medication errors.

  6. Wavelets in medical imaging

    International Nuclear Information System (INIS)

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

    2012-01-01

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

  7. 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.

  8. 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...

  9. Machine learning and medical imaging

    CERN Document Server

    Shen, Dinggang; Sabuncu, Mert

    2016-01-01

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

  10. Automated landmark-guided deformable image registration

    International Nuclear Information System (INIS)

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

    2015-01-01

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

  11. Automated landmark-guided deformable image registration.

    Science.gov (United States)

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

    2015-01-07

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

  12. Medical image registration for analysis

    International Nuclear Information System (INIS)

    Petrovic, V.

    2006-01-01

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

  13. 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.

  14. Information processing in medical imaging

    International Nuclear Information System (INIS)

    Bacharach, S.L.

    1986-01-01

    The Information Processing in Medical Imaging Conference is a biennial conference, held alternately in Europe and in the United States of America. The subject of the conference is the use of computers and mathematics in medical imaging, the evaluation of new imaging techniques, image processing, image analysis, diagnostic decision-making and related fields. This volume contains analyses of in vivo digital images from nuclear medicine, ultrasound, magnetic resonance, computerized tomography, digital radiography, etc. The conference brings together expert researchers in the field and the proceedings represent the leading biennial update of developments in the field of medical image processing. (Auth.)

  15. Automated Aesthetic Analysis of Photographic Images.

    Science.gov (United States)

    Aydın, Tunç Ozan; Smolic, Aljoscha; Gross, Markus

    2015-01-01

    We present a perceptually calibrated system for automatic aesthetic evaluation of photographic images. Our work builds upon the concepts of no-reference image quality assessment, with the main difference being our focus on rating image aesthetic attributes rather than detecting image distortions. In contrast to the recent attempts on the highly subjective aesthetic judgment problems such as binary aesthetic classification and the prediction of an image's overall aesthetics rating, our method aims on providing a reliable objective basis of comparison between aesthetic properties of different photographs. To that end our system computes perceptually calibrated ratings for a set of fundamental and meaningful aesthetic attributes, that together form an "aesthetic signature" of an image. We show that aesthetic signatures can still be used to improve upon the current state-of-the-art in automatic aesthetic judgment, but also enable interesting new photo editing applications such as automated aesthetic analysis, HDR tone mapping evaluation, and providing aesthetic feedback during multi-scale contrast manipulation.

  16. PS-022 Complex automated medication systems reduce medication administration error rates in an acute medical ward

    DEFF Research Database (Denmark)

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

    2017-01-01

    the medication administration error rate in comparison with current practice. Material and methods This was a controlled before and after study with follow-up after 7 and 14 months. The study was conducted in two acute medical hospital wards. Two automated medication systems were tested: (1) automated dispensing...... cabinet, automated dispensing and barcode medication administration; (2) non-patient specific automated dispensing and barcode medication administration. The occurrence of administration errors was observed in three 3 week periods. The error rates were calculated by dividing the number of doses with one....... The complex automated medication system effectively reduced the overall risk of administration errors in the intervention ward (OR 0.53, 95% CI 0.27–0.90), and the procedural error rate was also significantly reduced (OR 0.44, 95% CI 0.126–0.94). The non-patient specific automated medication system...

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

    Science.gov (United States)

    Bergrath, Sebastian; Rossaint, Rolf; Lenssen, Niklas; Fitzner, Christina; Skorning, Max

    2013-01-16

    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. 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. 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 transmission (26 vs. 22 min, p = 0.011), but ambulance

  18. 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

  19. Frontiers in medical imaging technology

    International Nuclear Information System (INIS)

    Iinuma, Takeshi

    1992-01-01

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

  20. The physics of medical imaging

    CERN Document Server

    1988-01-01

    The Physics of Medical Imaging reviews the scientific basis and physical principles underpinning imaging in medicine. It covers the major imaging methods of x-radiology, nuclear medicine, ultrasound, and nuclear magnetic resonance, and considers promising new techniques. Following these reviews are several thematic chapters that cover the mathematics of medical imaging, image perception, computational requirements, and techniques. Throughout the book, the author encourages readers to consider key questions concerning imaging. This profusely illustrated and extensively indexed text is accessible to graduate physical scientists, advanced undergraduates, and research students. It logically complements books on applications of imaging techniques in medicine, making it useful for clinicians as well.

  1. Trends in medical image processing

    International Nuclear Information System (INIS)

    Robilotta, C.C.

    1987-01-01

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

  2. Medical alert bracelet (image)

    Science.gov (United States)

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

  3. Image processing in medical ultrasound

    DEFF Research Database (Denmark)

    Hemmsen, Martin Christian

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

  4. Automated Image Analysis Corrosion Working Group Update: February 1, 2018

    Energy Technology Data Exchange (ETDEWEB)

    Wendelberger, James G. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2018-02-01

    These are slides for the automated image analysis corrosion working group update. The overall goals were: automate the detection and quantification of features in images (faster, more accurate), how to do this (obtain data, analyze data), focus on Laser Scanning Confocal Microscope (LCM) data (laser intensity, laser height/depth, optical RGB, optical plus laser RGB).

  5. Intelligent distributed medical image management

    Science.gov (United States)

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

    1995-05-01

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

  6. Medical imaging 4

    International Nuclear Information System (INIS)

    Loew, M.H.

    1990-01-01

    This book is covered under the following topics: human visual pattern recognition, fractals, rules, and segments, three-dimensional image processing, MRI, MRI and mammography, clinical applications 1, angiography, image processing systems, image processing poster session

  7. Medical imaging 4

    Energy Technology Data Exchange (ETDEWEB)

    Loew, M.H. (George Washington Univ., Washington, DC (United States))

    1990-01-01

    This book is covered under the following topics: human visual pattern recognition, fractals, rules, and segments, three-dimensional image processing, MRI, MRI and mammography, clinical applications 1, angiography, image processing systems, image processing poster session.

  8. Medical Imaging with Neural Networks

    International Nuclear Information System (INIS)

    Pattichis, C.; Cnstantinides, A.

    1994-01-01

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

  9. Visual perception and medical imaging

    International Nuclear Information System (INIS)

    Jaffe, C.C.

    1985-01-01

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

  10. Medical hyperspectral imaging: a review

    Science.gov (United States)

    Lu, Guolan; Fei, Baowei

    2014-01-01

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

  11. Implementing hospital library automation: the GaIN project. Georgia Interactive Network for Medical Information.

    Science.gov (United States)

    Rankin, J A; McInnis, K A; Rosner, A L

    1995-01-01

    The GaIN (Georgia Interactive Network for Medical Information) Hospital Libraries' Local Automation Project was a one-year, grant-funded initiative to implement an integrated library system in three Georgia hospitals. The purpose of the project was to install the library systems, describe the steps in hospital library automation, and identify issues and barriers related to automation in small libraries. The participating hospitals included a small, a medium, and a large institution. The steps and time required for project implementation were documented in order to develop a decision checklist. Although library automation proved a desirable approach for improving collection accessibility, simplifying daily routines, and improving the library's image in the hospital, planners must be sure to consider equipment as well as software support, staffing for the conversion, and training of the library staff and end users. PMID:7581184

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

    Science.gov (United States)

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

    2012-01-01

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

  13. Automated detection of medication administration errors in neonatal intensive care.

    Science.gov (United States)

    Li, Qi; Kirkendall, Eric S; Hall, Eric S; Ni, Yizhao; Lingren, Todd; Kaiser, Megan; Lingren, Nataline; Zhai, Haijun; Solti, Imre; Melton, Kristin

    2015-10-01

    To improve neonatal patient safety through automated detection of medication administration errors (MAEs) in high alert medications including narcotics, vasoactive medication, intravenous fluids, parenteral nutrition, and insulin using the electronic health record (EHR); to evaluate rates of MAEs in neonatal care; and to compare the performance of computerized algorithms to traditional incident reporting for error detection. We developed novel computerized algorithms to identify MAEs within the EHR of all neonatal patients treated in a level four neonatal intensive care unit (NICU) in 2011 and 2012. We evaluated the rates and types of MAEs identified by the automated algorithms and compared their performance to incident reporting. Performance was evaluated by physician chart review. In the combined 2011 and 2012 NICU data sets, the automated algorithms identified MAEs at the following rates: fentanyl, 0.4% (4 errors/1005 fentanyl administration records); morphine, 0.3% (11/4009); dobutamine, 0 (0/10); and milrinone, 0.3% (5/1925). We found higher MAE rates for other vasoactive medications including: dopamine, 11.6% (5/43); epinephrine, 10.0% (289/2890); and vasopressin, 12.8% (54/421). Fluid administration error rates were similar: intravenous fluids, 3.2% (273/8567); parenteral nutrition, 3.2% (649/20124); and lipid administration, 1.3% (203/15227). We also found 13 insulin administration errors with a resulting rate of 2.9% (13/456). MAE rates were higher for medications that were adjusted frequently and fluids administered concurrently. The algorithms identified many previously unidentified errors, demonstrating significantly better sensitivity (82% vs. 5%) and precision (70% vs. 50%) than incident reporting for error recognition. Automated detection of medication administration errors through the EHR is feasible and performs better than currently used incident reporting systems. Automated algorithms may be useful for real-time error identification and

  14. 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.

  15. Automated Medical Record Tracking System for the Ridge Hospital ...

    African Journals Online (AJOL)

    This paper employs the systems analysis and design approach (also known as systems development lifecycle) to design and develop an automated medical records tracking system. This proposed system is a case study at the Ridge Hospital, Ghana. The system is limited to the tracking and management of in patients\\' ...

  16. 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......, segmented from MR images of the knee. The cartilage tissue is considered to be a key determinant in the onset of Osteoarthritis (OA), a degenerative joint disease, with no known cure. The primary obstacle has been the dependence on radiography as the ‘gold standard’ for detecting the manifestation...... of cartilage changes. This is an indirect assessment, since the cartilage is not visible on xrays. We propose Cartilage Homogeneity, quantified from MR images, as a marker for detection of the early biochemical alterations in the articular cartilage. We show that homogeneity provides accuracy, sensitivity...

  17. 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

  18. Localized energy-based normalization of medical images: application to chest radiography

    NARCIS (Netherlands)

    Philipsen, R.H.H.M.; Maduskar, P.; Hogeweg, L.E.; Melendez Rodriguez, J.C.; Sanchez Gutierrez, C.I.; Ginneken, B. van

    2015-01-01

    Automated quantitative analysis systems for medical images often lack the capability to successfully process images from multiple sources. Normalization of such images prior to further analysis is a possible solution to this limitation. This work presents a general method to normalize medical images

  19. Automated mapping of the intertidal beach from video images

    NARCIS (Netherlands)

    Uunk, L.; Uunk, L.; Wijnberg, Kathelijne Mariken; Morelissen, R.; Morelissen, R.

    2010-01-01

    This paper presents a fully automated procedure to derive the intertidal beach bathymetry on a daily basis from video images of low-sloping beaches that are characterised by the intermittent emergence of intertidal bars. Bathymetry data are obtained by automated and repeated mapping of shorelines

  20. Automated image analysis of the pathological lung in CT

    NARCIS (Netherlands)

    Sluimer, Ingrid Christine

    2005-01-01

    The general objective of the thesis is automation of the analysis of the pathological lung from CT images. Specifically, we aim for automated detection and classification of abnormalities in the lung parenchyma. We first provide a review of computer analysis techniques applied to CT of the

  1. Machine Learning for Medical Imaging.

    Science.gov (United States)

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

    2017-01-01

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

  2. Machine Learning for Medical Imaging

    Science.gov (United States)

    Korfiatis, Panagiotis; Akkus, Zeynettin; Kline, Timothy L.

    2017-01-01

    Machine learning is a technique for recognizing patterns that can be applied to medical images. Although it is a powerful tool that can help in rendering medical diagnoses, it can be misapplied. Machine learning typically begins with the machine learning algorithm system computing the image features that are believed to be of importance in making the prediction or diagnosis of interest. The machine learning algorithm system then identifies the best combination of these image features for classifying the image or computing some metric for the given image region. There are several methods that can be used, each with different strengths and weaknesses. There are open-source versions of most of these machine learning methods that make them easy to try and apply to images. Several metrics for measuring the performance of an algorithm exist; however, one must be aware of the possible associated pitfalls that can result in misleading metrics. More recently, deep learning has started to be used; this method has the benefit that it does not require image feature identification and calculation as a first step; rather, features are identified as part of the learning process. Machine learning has been used in medical imaging and will have a greater influence in the future. Those working in medical imaging must be aware of how machine learning works. ©RSNA, 2017 PMID:28212054

  3. Medical imaging and the Internet

    International Nuclear Information System (INIS)

    Jones, D.N.; Carr, P.

    1995-01-01

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

  4. Java advanced medical image toolkit

    International Nuclear Information System (INIS)

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

    2002-01-01

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

  5. Compressive sensing in medical imaging.

    Science.gov (United States)

    Graff, Christian G; Sidky, Emil Y

    2015-03-10

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

  6. Medical image telecommunication

    International Nuclear Information System (INIS)

    Handmaker, H.; Bennington, J.L.; Lloyd, R.W.; Caspe, R.A.

    1986-01-01

    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

  7. Developments in medical imaging techniques

    International Nuclear Information System (INIS)

    Kramer, Cornelis

    1979-01-01

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

  8. Watermarking patient data in encrypted medical images

    Indian Academy of Sciences (India)

    Watermarking is an important technology for these topics. Medical images play a significant role in diagnosis of many diseases. Doctors diagnose from medical images, so more care is required to hide patient information in medical images without affecting quality of image. A Region of Interest (ROI) of a medical image is an.

  9. Automated feature extraction and classification from image sources

    Science.gov (United States)

    ,

    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.

  10. Novel medical image enhancement algorithms

    Science.gov (United States)

    Agaian, Sos; McClendon, Stephen A.

    2010-01-01

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

  11. Medical imaging V

    International Nuclear Information System (INIS)

    Loew, M.H.

    1991-01-01

    This book is covered under the following topics: preprocessing and enhancement 1-3; segmentation, feature extraction, and detection 1-2; hardware and software systems for display; and user interface; MRI; MRI and PET; 3-D; image reconstruction, modeling, description, and coding; and knowledge-based methods

  12. Medical imaging V

    Energy Technology Data Exchange (ETDEWEB)

    Loew, M.H.

    1991-01-01

    This book is covered under the following topics: preprocessing and enhancement 1-3; segmentation, feature extraction, and detection 1-2; hardware and software systems for display; and user interface; MRI; MRI and PET; 3-D; image reconstruction, modeling, description, and coding; and knowledge-based methods.

  13. Medical Imaging Informatics.

    Science.gov (United States)

    Hsu, William; El-Saden, Suzie; Taira, Ricky K

    2016-01-01

    Imaging is one of the most important sources of clinically observable evidence that provides broad coverage, can provide insight on low-level scale properties, is noninvasive, has few side effects, and can be performed frequently. Thus, imaging data provides a viable observable that can facilitate the instantiation of a theoretical understanding of a disease for a particular patient context by connecting imaging findings to other biologic parameters in the model (e.g., genetic, molecular, symptoms, and patient survival). These connections can help inform their possible states and/or provide further coherent evidence. The field of radiomics is particularly dedicated to this task and seeks to extract quantifiable measures wherever possible. Example properties of investigation include genotype characterization, histopathology parameters, metabolite concentrations, vascular proliferation, necrosis, cellularity, and oxygenation. Important issues within the field include: signal calibration, spatial calibration, preprocessing methods (e.g., noise suppression, motion correction, and field bias correction), segmentation of target anatomic/pathologic entities, extraction of computed features, and inferencing methods connecting imaging features to biological states.

  14. Improving outpatient primary medication adherence with physician guided, automated dispensing

    Directory of Open Access Journals (Sweden)

    Moroshek JG

    2017-01-01

    Full Text Available Jacob G Moroshek1,2 1Bioinformatics and Computational Biology, 2Carlson School of Management, University of Minnesota, Minneapolis, MN, USA Background: Physician dispensing, different from pharmacist dispensing, is a way for practitioners to supply their patients with medications, at the point of care. The InstyMeds dispenser and logistics system can automate much of the dispensing, insurance adjudication, inventory management, and regulatory reporting that is required of physician dispensing. Objective: To understand the percentage of patients that exhibit primary adherence to medication in the outpatient setting when choosing InstyMeds. Method: The InstyMeds dispensing database was de-identified and analyzed for primary adherence. This is the ratio of patients who dispensed their medication to those who received an eligible prescription. Results: The average InstyMeds emergency department installation has a primary adherence rate of 91.7%. The maximum rate for an installed device was 98.5%. Conclusion: Although national rates of primary adherence have been found to be in the range of 70%, automated physician dispensing vastly improves the rate of adherence. Improved adherence should lead to better patient outcomes, fewer return visits, and lower healthcare costs. Keywords: automated dispensing, adherence, compliance, medication, physician dispensing, InstyMeds

  15. Recent progress in medical imaging technology

    International Nuclear Information System (INIS)

    Endo, Masahiro

    2004-01-01

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

  16. 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.

  17. Automated Medical Supply Chain Management: A Remedy for Logistical Shortcomings

    Science.gov (United States)

    2016-08-01

    AU/ACSC/2016 AIR COMMAND AND STAFF COLLEGE DISTANCE LEARNING AIR UNIVERSITY AUTOMATED MEDICAL SUPPLY CHAIN MANAGEMENT: A REMEDY FOR...Technology Workflow,” 18 November 2011, accessed 10 July 2016, http://www.mobileaspects.com/ blog /2011/11/18/evaluating-tissue-tracking- technology-solutions...Technology Workflow. November 18, 2011. http://www.mobileaspects.com/ blog /2011/11/18/evaluating-tissue-tracking-technology- solutions-part-2

  18. Medical record automation at the Los Alamos Scientific Laboratory

    International Nuclear Information System (INIS)

    Hogle, G.O.; Grier, R.S.

    1979-01-01

    With the increase in population at the Los Alamos Scientific Laboratory and the growing concern over employee health, especially concerning the effects of the work environment, the Occupational Medicine Group decided to automate its medical record keeping system to meet these growing demands. With this computer system came not only the ability for long-term study of the work environment verses employee health, but other benefits such as more comprehensive records, increased legibility, reduced physician time, and better records management

  19. Automated Detection of Optic Disc in Fundus Images

    Science.gov (United States)

    Burman, R.; Almazroa, A.; Raahemifar, K.; Lakshminarayanan, V.

    Optic disc (OD) localization is an important preprocessing step in the automated image detection of fundus image infected with glaucoma. An Interval Type-II fuzzy entropy based thresholding scheme along with Differential Evolution (DE) is applied to determine the location of the OD in the right of left eye retinal fundus image. The algorithm, when applied to 460 fundus images from the MESSIDOR dataset, shows a success rate of 99.07 % for 217 normal images and 95.47 % for 243 pathological images. The mean computational time is 1.709 s for normal images and 1.753 s for pathological images. These results are important for automated detection of glaucoma and for telemedicine purposes.

  20. Image processing for medical use

    International Nuclear Information System (INIS)

    Ohashi, Akinami; Iinuma, Kazuhiro

    1991-01-01

    Increasing role of diagnostic imaging is a well-established trend in medical practice. A variety of imaging techniques, such as magnetic resonance imaging, X-ray computed tomography, and ultrasound, are used, and the data obtained are displayed with increasing frequency by means of image processing. This paper focuses on three-dimensional imaging acquired by the following methods: (1) stereoscopic imaging with either binocular parallax or movement parallax, (2) multi planar reconstruction in axial, coronal, sagittal, and/or oblique views, (3) surface imaging with wire, surface, or voxell method, and (4) synthesis imaging reconstructed by axial, coronal, or sagittal view. The application of neural network, which has recently received attention, is mentioned. To provide such digital imaging data, integrated information system for image processing, retrieval, and transmission is required. Picture archiving and communication system is thus developing to improve diagnostic ability and efficiency, and economic efficiency. In the future, the development of new diagnostic equipments, integrated and systematized imaging diagnosis, and image processing-assisted diagnostics and therapeutics would be achieved. (N.K.)

  1. 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.

  2. Army medical imaging system: ARMIS

    International Nuclear Information System (INIS)

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

    1987-01-01

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

  3. Invitation to medical image processing

    International Nuclear Information System (INIS)

    Kitasaka, Takayuki; Suenaga, Yasuhito; Mori, Kensaku

    2010-01-01

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

  4. [Medical image, telemedicine and medical teleassistance].

    Science.gov (United States)

    Rubies-Feijoo, Carles; Salas-Fernández, Tomás; Moya-Olvera, Francesc; Guanyabens-Calvet, Joan

    2010-02-01

    The use of Information Communication and Technology (ICT) in medical image and telemedicine, can help improve the quality of life and well-being of citizens (patients and professionals) and overcome the challenges facing the health system, benefiting all parties involved in the health system (patients, professionals, administration, health providers, insurance and industry); ICT will not be the solution by itself, but certainly the solution will pass through ICT. It needs a strong political and clinical directing flexible strategies, aiming to contribute to the realization of care of higher quality and human care leadership. 2010 Elsevier España S.L. All rights reserved.

  5. Physics instrumentation for medical imaging

    International Nuclear Information System (INIS)

    Townsend, D.W.

    1993-01-01

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

  6. Motion correction in medical imaging.

    OpenAIRE

    Smith, Rhodri

    2017-01-01

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

  7. 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.

  8. 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

  9. Enhanced Adherence in Patients Using an Automated Home Medication Dispenser.

    Science.gov (United States)

    Hoffmann, Charles; Schweighardt, Anne; Conn, Kelly M; Nelson, Dallas; Barbano, Richard; Marshall, Frederick; Brown, Jack

    2017-07-24

    Many factors contribute to medication nonadherence including psychological and memory disorders, aging, and pill burden. The Automated Home Medication Dispenser (AHMD) is a medication management system intended to help solve unintentional medication nonadherence. The purpose of this study was to determine if use of the AHMD improved medication adherence. We conducted a 6-month prospective, feasibility study assessing use of the AHMD in 21 patient-caregiver dyads. Patients were referred by their physician because of poor medication adherence and included if they resided in Rochester, NY and on at least two medications in pill form. Pill counts were performed at baseline to assess previous adherence. Prospective medication adherence was assessed using AHMD recorded dosing information. A paired t-test was used to compare previous and prospective adherence. The mean age of patients was 75.1 years. Fifteen patients (71.4%) and eight caregivers (38.1%) were women; half (47.6%) of caregivers lived with the patient. The most common patient comorbidities were hypertension (76.2%) and memory disorder (61.9%). Mean adherence increased from 49.0% at baseline to 96.8% after 6 months of AHMD use (p < .001). In a cohort of unintentionally nonadherent patients, use of the AHMD for 6 months significantly improved medication adherence.

  10. Improving medical stores management through automation and effective communication.

    Science.gov (United States)

    Kumar, Ashok; Cariappa, M P; Marwaha, Vishal; Sharma, Mukti; Arora, Manu

    2016-01-01

    Medical stores management in hospitals is a tedious and time consuming chore with limited resources tasked for the purpose and poor penetration of Information Technology. The process of automation is slow paced due to various inherent factors and is being challenged by the increasing inventory loads and escalating budgets for procurement of drugs. We carried out an indepth case study at the Medical Stores of a tertiary care health care facility. An iterative six step Quality Improvement (QI) process was implemented based on the Plan-Do-Study-Act (PDSA) cycle. The QI process was modified as per requirement to fit the medical stores management model. The results were evaluated after six months. After the implementation of QI process, 55 drugs of the medical store inventory which had expired since 2009 onwards were replaced with fresh stock by the suppliers as a result of effective communication through upgraded database management. Various pending audit objections were dropped due to the streamlined documentation and processes. Inventory management improved drastically due to automation, with disposal orders being initiated four months prior to the expiry of drugs and correct demands being generated two months prior to depletion of stocks. The monthly expense summary of drugs was now being done within ten days of the closing month. Improving communication systems within the hospital with vendor database management and reaching out to clinicians is important. Automation of inventory management requires to be simple and user-friendly, utilizing existing hardware. Physical stores monitoring is indispensable, especially due to the scattered nature of stores. Staff training and standardized documentation protocols are the other keystones for optimal medical store management.

  11. Introduction to Medical Image Analysis

    DEFF Research Database (Denmark)

    Paulsen, Rasmus Reinhold; Moeslund, Thomas B.

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

  12. Introduction to Medical Image Analysis

    DEFF Research Database (Denmark)

    Paulsen, Rasmus Reinhold; Moeslund, Thomas B.

    2011-01-01

    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......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...

  13. Automated Registration Of Images From Multiple Sensors

    Science.gov (United States)

    Rignot, Eric J. M.; Kwok, Ronald; Curlander, John C.; Pang, Shirley S. N.

    1994-01-01

    Images of terrain scanned in common by multiple Earth-orbiting remote sensors registered automatically with each other and, where possible, on geographic coordinate grid. Simulated image of terrain viewed by sensor computed from ancillary data, viewing geometry, and mathematical model of physics of imaging. In proposed registration algorithm, simulated and actual sensor images matched by area-correlation technique.

  14. The future of medical imaging

    International Nuclear Information System (INIS)

    Maidment, A. D. A.

    2010-01-01

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

  15. Moonshot Acceleration Factor: Medical Imaging.

    Science.gov (United States)

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

    2017-11-01

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

  16. 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.

  17. Cardiac imaging: working towards fully-automated machine analysis & interpretation.

    Science.gov (United States)

    Slomka, Piotr J; Dey, Damini; Sitek, Arkadiusz; Motwani, Manish; Berman, Daniel S; Germano, Guido

    2017-03-01

    Non-invasive imaging plays a critical role in managing patients with cardiovascular disease. Although subjective visual interpretation remains the clinical mainstay, quantitative analysis facilitates objective, evidence-based management, and advances in clinical research. This has driven developments in computing and software tools aimed at achieving fully automated image processing and quantitative analysis. In parallel, machine learning techniques have been used to rapidly integrate large amounts of clinical and quantitative imaging data to provide highly personalized individual patient-based conclusions. Areas covered: This review summarizes recent advances in automated quantitative imaging in cardiology and describes the latest techniques which incorporate machine learning principles. The review focuses on the cardiac imaging techniques which are in wide clinical use. It also discusses key issues and obstacles for these tools to become utilized in mainstream clinical practice. Expert commentary: Fully-automated processing and high-level computer interpretation of cardiac imaging are becoming a reality. Application of machine learning to the vast amounts of quantitative data generated per scan and integration with clinical data also facilitates a move to more patient-specific interpretation. These developments are unlikely to replace interpreting physicians but will provide them with highly accurate tools to detect disease, risk-stratify, and optimize patient-specific treatment. However, with each technological advance, we move further from human dependence and closer to fully-automated machine interpretation.

  18. Automated image enhancement using power law transformations

    Indian Academy of Sciences (India)

    Automatically enhancing contrast of an image has been a challenging task since the digital image can represent variety of scene types. Trifonov et al (2001) performed automatic contrast enhancement by automatically determining the measure of central tendency of the brightness histogram of an image and shifting and ...

  19. 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

  20. Machine Learning in Medical Imaging.

    Science.gov (United States)

    Giger, Maryellen L

    2018-03-01

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

  1. 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

  2. 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.

  3. Automated medical follow-up and delayed industrial risks

    International Nuclear Information System (INIS)

    Smith, M.E.

    In response to increasing demand for human data to identify social, environmental, and occupational influences upon health, Statistics Canada has been organizing existing files of vital and health records to facilitate such studies on a national scale. In particular, the development of a Canadian Mortality Data Base file, the initiation of the National Cancer Incidence system, and the development of new computer techniques have helped reduce the cost and increase the scale and efficiency of automated medical follow-up to produce statistics of sickness or death attributable to environmental factors. Specific occupational studies now in progress serve to illustrate the methods, practical difficulties, potential size, and products from such investigations

  4. Automated Acquisition and Analysis of Digital Radiographic Images

    International Nuclear Information System (INIS)

    Poland, R.

    1999-01-01

    Engineers at the Savannah River Technology Center have designed, built, and installed a fully automated small field-of-view, lens-coupled, digital radiography imaging system. The system is installed in one of the Savannah River Site''s production facilities to be used for the evaluation of production components. Custom software routines developed for the system automatically acquire, enhance, and diagnostically evaluate critical geometric features of various components that have been captured radiographically. Resolution of the digital radiograms and accuracy of the acquired measurements approaches 0.001 inches. To date, there has been zero deviation in measurement repeatability. The automated image acquisition methodology will be discussed, unique enhancement algorithms will be explained, and the automated routines for measuring the critical component features will be presented. An additional feature discussed is the independent nature of the modular software components, which allows images to be automatically acquired, processed, and evaluated by the computer in the background, while the operator reviews other images on the monitor. System components were also a key in gaining the required image resolution. System factors such as scintillator selection, x-ray source energy, optical components and layout, as well as geometric unsharpness issues are considered in the paper. Finally the paper examines the numerous quality improvement factors and cost saving advantages that will be realized at the Savannah River Site due to the implementation of the Automated Pinch Weld Analysis System (APWAS)

  5. Automated ion imaging with the NanoSIMS ion microprobe

    Science.gov (United States)

    Gröner, E.; Hoppe, P.

    2006-07-01

    Automated ion imaging systems developed for Cameca IMS3f and IMS6f ion microprobes are very useful for the analysis of large numbers of presolar dust grains, in particular with respect to the identification of rare types of presolar grains. The application of these systems is restricted to the study of micrometer-sized grains, thereby by-passing the major fraction of presolar grains which are sub-micrometer in size. The new generation Cameca NanoSIMS 50 ion microprobe combines high spatial resolution, high sensitivity, and simultaneous detection of up to 6 isotopes which makes the NanoSIMS an unprecedented tool for the analysis of presolar materials. Here, we report on the development of a fully automated ion imaging system for the NanoSIMS at MPI for Chemistry in order to extend its analytical capabilities further. The ion imaging consists of five steps: (i) Removal of surface contamination on the area of interest. (ii) Secondary ion image acquisition of up to 5 isotopes in multi-detection. (iii) Automated particle recognition in a pre-selected image. (iv) Automated measurement of all recognised particles with appropriate raster sizes and measurement times. (v) Stage movement to new area and repetition of steps (ii)-(iv).

  6. Automated ion imaging with the NanoSIMS ion microprobe

    International Nuclear Information System (INIS)

    Groener, E.; Hoppe, P.

    2006-01-01

    Automated ion imaging systems developed for Cameca IMS3f and IMS6f ion microprobes are very useful for the analysis of large numbers of presolar dust grains, in particular with respect to the identification of rare types of presolar grains. The application of these systems is restricted to the study of micrometer-sized grains, thereby by-passing the major fraction of presolar grains which are sub-micrometer in size. The new generation Cameca NanoSIMS 50 ion microprobe combines high spatial resolution, high sensitivity, and simultaneous detection of up to 6 isotopes which makes the NanoSIMS an unprecedented tool for the analysis of presolar materials. Here, we report on the development of a fully automated ion imaging system for the NanoSIMS at MPI for Chemistry in order to extend its analytical capabilities further. The ion imaging consists of five steps: (i) Removal of surface contamination on the area of interest. (ii) Secondary ion image acquisition of up to 5 isotopes in multi-detection. (iii) Automated particle recognition in a pre-selected image. (iv) Automated measurement of all recognised particles with appropriate raster sizes and measurement times. (v) Stage movement to new area and repetition of steps (ii)-(iv)

  7. Automated image registration for FDOPA PET studies

    International Nuclear Information System (INIS)

    Kang-Ping Lin; Sung-Cheng Huang, Dan-Chu Yu; Melega, W.; Barrio, J.R.; Phelps, M.E.

    1996-01-01

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

  8. FULLY AUTOMATED IMAGE ORIENTATION IN THE ABSENCE OF TARGETS

    Directory of Open Access Journals (Sweden)

    C. Stamatopoulos

    2012-07-01

    Full Text Available Automated close-range photogrammetric network orientation has traditionally been associated with the use of coded targets in the object space to allow for an initial relative orientation (RO and subsequent spatial resection of the images. Over the past decade, automated orientation via feature-based matching (FBM techniques has attracted renewed research attention in both the photogrammetry and computer vision (CV communities. This is largely due to advances made towards the goal of automated relative orientation of multi-image networks covering untargetted (markerless objects. There are now a number of CV-based algorithms, with accompanying open-source software, that can achieve multi-image orientation within narrow-baseline networks. From a photogrammetric standpoint, the results are typically disappointing as the metric integrity of the resulting models is generally poor, or even unknown, while the number of outliers within the image matching and triangulation is large, and generally too large to allow relative orientation (RO via the commonly used coplanarity equations. On the other hand, there are few examples within the photogrammetric research field of automated markerless camera calibration to metric tolerances, and these too are restricted to narrow-baseline, low-convergence imaging geometry. The objective addressed in this paper is markerless automatic multi-image orientation, maintaining metric integrity, within networks that incorporate wide-baseline imagery. By wide-baseline we imply convergent multi-image configurations with convergence angles of up to around 90°. An associated aim is provision of a fast, fully automated process, which can be performed without user intervention. For this purpose, various algorithms require optimisation to allow parallel processing utilising multiple PC cores and graphics processing units (GPUs.

  9. Army Medical Imaging System - ARMIS

    Science.gov (United States)

    1992-08-08

    Melvin P. Siedband Frank C. Grenzow Craig A. Heilman James R. Gray Huilian Zhang A ... NTtS CFA?•I " U ; J C l A t j. University of Wisconsin _. I e...Medical Imaging System - ARMIS Contract # 6.AUTHOR(S) Melvin P. Siedband James R. Gray DAMDI7-88C-8058 Frank C. Grenzow Huilian Zhang 63807A Craig A...its use is inconsistent to the people who must manage it. The consistency of the Macin- tosh operating system permits easier staff training as imaging

  10. Current status on image processing in medical fields in Japan

    International Nuclear Information System (INIS)

    Atsumi, Kazuhiko

    1979-01-01

    Information on medical images are classified in the two patterns. 1) off-line images on films-x-ray films, cell image, chromosome image etc. 2) on-line images detected through sensors, RI image, ultrasonic image, thermogram etc. These images are divided into three characteristic, two dimensional three dimensional and dynamic images. The research on medical image processing have been reported in several meeting in Japan and many fields on images have been studied on RI, thermogram, x-ray film, x-ray-TV image, cancer cell, blood cell, bacteria, chromosome, ultrasonics, and vascular image. Processing on TI image useful and easy because of their digital displays. Software on smoothing, restoration (iterative approximation), fourier transformation, differentiation and subtration. Image on stomach and chest x-ray films have been processed automatically utilizing computer system. Computed Tomography apparatuses have been already developed in Japan and automated screening instruments on cancer cells and recently on blood cells classification have been also developed. Acoustical holography imaging and moire topography have been also studied in Japan. (author)

  11. 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.

  12. Automated designation of tie-points for image-to-image coregistration.

    Science.gov (United States)

    R.E. Kennedy; W.B. Cohen

    2003-01-01

    Image-to-image registration requires identification of common points in both images (image tie-points: ITPs). Here we describe software implementing an automated, area-based technique for identifying ITPs. The ITP software was designed to follow two strategies: ( I ) capitalize on human knowledge and pattern recognition strengths, and (2) favour robustness in many...

  13. 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...

  14. Gallium-68 in Medical Imaging.

    Science.gov (United States)

    Martiniova, Lucia; Palatis, Louis De; Etchebehere, Elba; Ravizzini, Gregory

    2016-01-01

    Over the past several years, Positron Emission Tomography (PET) imaging agents labeled with ;68Gallium (68Ga) have undergone a significant increase in clinical utilization. 68Ga is conveniently produced from a germanium-68/gallium-68 (68Ge/68Ga) generator. Because of the compact size and ease of use of the generator, 68Ga labeled compounds may be more cost-effective than PET radioisotopes that are cyclotron-produced. The convenient half-life of 68Ga (T1/2=68 min) provides sufficient radioactivity for various PET imaging applications, while delivering acceptable radiation doses to patients. This chapter summarizes the emerging clinical utilization of 68Ga-based radiotracers in medical imaging. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

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

    Science.gov (United States)

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

    2016-03-01

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

  16. 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.

  17. Automated hybridization/imaging device for fluorescent multiplex DNA sequencing

    Science.gov (United States)

    Weiss, Robert B.; Kimball, Alvin W.; Gesteland, Raymond F.; Ferguson, F. Mark; Dunn, Diane M.; Di Sera, Leonard J.; Cherry, Joshua L.

    1995-01-01

    A method is disclosed for automated multiplex sequencing of DNA with an integrated automated imaging hybridization chamber system. This system comprises an hybridization chamber device for mounting a membrane containing size-fractionated multiplex sequencing reaction products, apparatus for fluid delivery to the chamber device, imaging apparatus for light delivery to the membrane and image recording of fluorescence emanating from the membrane while in the chamber device, and programmable controller apparatus for controlling operation of the system. The multiplex reaction products are hybridized with a probe, then an enzyme (such as alkaline phosphatase) is bound to a binding moiety on the probe, and a fluorogenic substrate (such as a benzothiazole derivative) is introduced into the chamber device by the fluid delivery apparatus. The enzyme converts the fluorogenic substrate into a fluorescent product which, when illuminated in the chamber device with a beam of light from the imaging apparatus, excites fluorescence of the fluorescent product to produce a pattern of hybridization. The pattern of hybridization is imaged by a CCD camera component of the imaging apparatus to obtain a series of digital signals. These signals are converted by the controller apparatus into a string of nucleotides corresponding to the nucleotide sequence an automated sequence reader. The method and apparatus are also applicable to other membrane-based applications such as colony and plaque hybridization and Southern, Northern, and Western blots.

  18. Radioisotopes and medical imaging in Sri Lanka

    International Nuclear Information System (INIS)

    Jayasinghe, J.M.A.C.

    1993-01-01

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

  19. An Automated, Image Processing System for Concrete Evaluation

    International Nuclear Information System (INIS)

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

    1998-01-01

    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

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

    International Nuclear Information System (INIS)

    Wells, J; Wilson, J; Zhang, Y; Samei, E; Ravin, Carl E.

    2014-01-01

    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

  1. 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.

  2. Automated Pointing of Cardiac Imaging Catheters.

    Science.gov (United States)

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

    2013-12-31

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

  3. 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.

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

    International Nuclear Information System (INIS)

    Shahidi, Shoaleh; Bahrampour, Ehsan; Soltanimehr, Elham; Zamani, Ali; Oshagh, Morteza; Moattari, Marzieh; Mehdizadeh, Alireza

    2014-01-01

    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

  5. 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.

  6. 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

  7. Tools for automating the imaging of zebrafish larvae.

    Science.gov (United States)

    Pulak, Rock

    2016-03-01

    The VAST BioImager system is a set of tools developed for zebrafish researchers who require the collection of images from a large number of 2-7 dpf zebrafish larvae. The VAST BioImager automates larval handling, positioning and orientation tasks. Color images at about 10 μm resolution are collected from the on-board camera of the system. If images of greater resolution and detail are required, this system is mounted on an upright microscope, such as a confocal or fluorescence microscope, to utilize their capabilities. The system loads a larvae, positions it in view of the camera, determines orientation using pattern recognition analysis, and then more precisely positions to user-defined orientation for optimal imaging of any desired tissue or organ system. Multiple images of the same larva can be collected. The specific part of each larva and the desired orientation and position is identified by the researcher and an experiment defining the settings and a series of steps can be saved and repeated for imaging of subsequent larvae. The system captures images, then ejects and loads another larva from either a bulk reservoir, a well of a 96 well plate using the LP Sampler, or individually targeted larvae from a Petri dish or other container using the VAST Pipettor. Alternative manual protocols for handling larvae for image collection are tedious and time consuming. The VAST BioImager automates these steps to allow for greater throughput of assays and screens requiring high-content image collection of zebrafish larvae such as might be used in drug discovery and toxicology studies. Copyright © 2015 The Author. Published by Elsevier Inc. All rights reserved.

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

    Directory of Open Access Journals (Sweden)

    О. E. Prokopchenko

    2015-09-01

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

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

    Directory of Open Access Journals (Sweden)

    O. Ye. Prokopchenko

    2015-10-01

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

  10. Roles of medical image processing in medical physics

    International Nuclear Information System (INIS)

    Arimura, Hidetaka

    2011-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Zhu Zixin

    2011-09-01

    Full Text Available 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 function as a binary level set function to improve computational efficiency. The method is applied to both our data and Internet brain MR data provided by the Internet Brain Segmentation Repository. Results The results obtained from our method are compared with manual segmentation results using multiple indices. In addition, the method is compared to two popular methods, Brain extraction tool and Model-based Level Set. Conclusions The proposed method can provide automated and accurate brain extraction result with high efficiency.

  12. 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.

  13. Medical imaging and augmented reality. Proceedings

    International Nuclear Information System (INIS)

    Dohi, Takeyoshi; Sakuma, Ichiro; Liao, Hongen

    2008-01-01

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

  14. Image mosaicing for automated pipe scanning

    International Nuclear Information System (INIS)

    Summan, Rahul; Dobie, Gordon; Guarato, Francesco; MacLeod, Charles; Marshall, Stephen; Pierce, Gareth; Forrester, Cailean; Bolton, Gary

    2015-01-01

    Remote visual inspection (RVI) is critical for the inspection of the interior condition of pipelines particularly in the nuclear and oil and gas industries. Conventional RVI equipment produces a video which is analysed online by a trained inspector employing expert knowledge. Due to the potentially disorientating nature of the footage, this is a time intensive and difficult activity. In this paper a new probe for such visual inspections is presented. The device employs a catadioptric lens coupled with feature based structure from motion to create a 3D model of the interior surface of a pipeline. Reliance upon the availability of image features is mitigated through orientation and distance estimates from an inertial measurement unit and encoder respectively. Such a model affords a global view of the data thus permitting a greater appreciation of the nature and extent of defects. Furthermore, the technique estimates the 3D position and orientation of the probe thus providing information to direct remedial action. Results are presented for both synthetic and real pipe sections. The former enables the accuracy of the generated model to be assessed while the latter demonstrates the efficacy of the technique in a practice

  15. Image mosaicing for automated pipe scanning

    Energy Technology Data Exchange (ETDEWEB)

    Summan, Rahul, E-mail: rahul.summan@strath.ac.uk; Dobie, Gordon, E-mail: rahul.summan@strath.ac.uk; Guarato, Francesco, E-mail: rahul.summan@strath.ac.uk; MacLeod, Charles, E-mail: rahul.summan@strath.ac.uk; Marshall, Stephen, E-mail: rahul.summan@strath.ac.uk; Pierce, Gareth [Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow, G1 1XW (United Kingdom); Forrester, Cailean [Inspectahire Instrument Company Ltd, Units 10 -12 Whitemyres Business Centre, Whitemyres Avenue, Aberdeen, AB16 6HQ (United Kingdom); Bolton, Gary [National Nuclear Laboratory, Chadwick House, Warrington Road, Birchwood Park, Warrington, WA3 6AE (United Kingdom)

    2015-03-31

    Remote visual inspection (RVI) is critical for the inspection of the interior condition of pipelines particularly in the nuclear and oil and gas industries. Conventional RVI equipment produces a video which is analysed online by a trained inspector employing expert knowledge. Due to the potentially disorientating nature of the footage, this is a time intensive and difficult activity. In this paper a new probe for such visual inspections is presented. The device employs a catadioptric lens coupled with feature based structure from motion to create a 3D model of the interior surface of a pipeline. Reliance upon the availability of image features is mitigated through orientation and distance estimates from an inertial measurement unit and encoder respectively. Such a model affords a global view of the data thus permitting a greater appreciation of the nature and extent of defects. Furthermore, the technique estimates the 3D position and orientation of the probe thus providing information to direct remedial action. Results are presented for both synthetic and real pipe sections. The former enables the accuracy of the generated model to be assessed while the latter demonstrates the efficacy of the technique in a practice.

  16. 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

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

    Science.gov (United States)

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

    2017-12-01

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

  18. Automated imaging dark adaptometer for investigating hereditary retinal degenerations

    Science.gov (United States)

    Azevedo, Dario F. G.; Cideciyan, Artur V.; Regunath, Gopalakrishnan; Jacobson, Samuel G.

    1995-05-01

    We designed and built an automated imaging dark adaptometer (AIDA) to increase accuracy, reliability, versatility and speed of dark adaptation testing in patients with hereditary retinal degenerations. AIDA increases test accuracy by imaging the ocular fundus for precise positioning of bleaching and stimulus lights. It improves test reliability by permitting continuous monitoring of patient fixation. Software control of stimulus presentation provides broad testing versatility without sacrificing speed. AIDA promises to facilitate the measurement of dark adaptation in studies of the pathophysiology of retinal degenerations and in future treatment trials of these diseases.

  19. Organization and visualization of medical images in radiotherapy

    International Nuclear Information System (INIS)

    Lorang, T.

    2001-05-01

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

  20. Prevalence of medication administration errors in two medical units with automated prescription and dispensing.

    Science.gov (United States)

    Rodriguez-Gonzalez, Carmen Guadalupe; Herranz-Alonso, Ana; Martin-Barbero, Maria Luisa; Duran-Garcia, Esther; Durango-Limarquez, Maria Isabel; Hernández-Sampelayo, Paloma; Sanjurjo-Saez, Maria

    2012-01-01

    To identify the frequency of medication administration errors and their potential risk factors in units using a computerized prescription order entry program and profiled automated dispensing cabinets. Prospective observational study conducted within two clinical units of the Gastroenterology Department in a 1537-bed tertiary teaching hospital in Madrid (Spain). Medication errors were measured using the disguised observation technique. Types of medication errors and their potential severity were described. The correlation between potential risk factors and medication errors was studied to identify potential causes. In total, 2314 medication administrations to 73 patients were observed: 509 errors were recorded (22.0%)-68 (13.4%) in preparation and 441 (86.6%) in administration. The most frequent errors were use of wrong administration techniques (especially concerning food intake (13.9%)), wrong reconstitution/dilution (1.7%), omission (1.4%), and wrong infusion speed (1.2%). Errors were classified as no damage (95.7%), no damage but monitoring required (2.3%), and temporary damage (0.4%). Potential clinical severity could not be assessed in 1.6% of cases. The potential risk factors morning shift, evening shift, Anatomical Therapeutic Chemical medication class antacids, prokinetics, antibiotics and immunosuppressants, oral administration, and intravenous administration were associated with a higher risk of administration errors. No association was found with variables related to understaffing or nurse's experience. Medication administration errors persist in units with automated prescription and dispensing. We identified a need to improve nurses' working procedures and to implement a Clinical Decision Support tool that generates recommendations about scheduling according to dietary restrictions, preparation of medication before parenteral administration, and adequate infusion rates.

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

    Science.gov (United States)

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

    2014-09-01

    The field of anatomic pathology has experienced major changes over the last decade. Virtual microscopy (VM) systems have allowed experts in pathology and other biomedical areas to work in a safer and more collaborative way. VMs are automated systems capable of digitizing microscopic samples that were traditionally examined one by one. The possibility of having digital copies reduces the risk of damaging original samples, and also makes it easier to distribute copies among other pathologists. This article describes the development of an automated high-resolution whole slide imaging (WSI) system tailored to the needs and problems encountered in digital imaging for pathology, from hardware control to the full digitization of samples. The system has been built with an additional digital monochromatic camera together with the color camera by default and LED transmitted illumination (RGB). Monochrome cameras are the preferred method of acquisition for fluorescence microscopy. The system is able to digitize correctly and form large high resolution microscope images for both brightfield and fluorescence. The quality of the digital images has been quantified using three metrics based on sharpness, contrast and focus. It has been proved on 150 tissue samples of brain autopsies, prostate biopsies and lung cytologies, at five magnifications: 2.5×, 10×, 20×, 40×, and 63×. The article is focused on the hardware set-up and the acquisition software, although results of the implemented image processing techniques included in the software and applied to the different tissue samples are also presented. © 2014 Wiley Periodicals, Inc.

  2. 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.

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

    International Nuclear Information System (INIS)

    Lee, Jung Hyung; Rhee, Chang Soo; Lee, Sung Moon; Kim, Hong; Woo, Sung Ku; Suh, Soo Jhi

    1994-01-01

    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

  4. Automated curved planar reformation of 3D spine images

    International Nuclear Information System (INIS)

    Vrtovec, Tomaz; Likar, Bostjan; Pernus, Franjo

    2005-01-01

    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

  5. 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.

  6. Automated Processing of Zebrafish Imaging Data: A Survey

    Science.gov (United States)

    Dickmeis, Thomas; Driever, Wolfgang; Geurts, Pierre; Hamprecht, Fred A.; Kausler, Bernhard X.; Ledesma-Carbayo, María J.; Marée, Raphaël; Mikula, Karol; Pantazis, Periklis; Ronneberger, Olaf; Santos, Andres; Stotzka, Rainer; Strähle, Uwe; Peyriéras, Nadine

    2013-01-01

    Abstract Due to the relative transparency of its embryos and larvae, the zebrafish is an ideal model organism for bioimaging approaches in vertebrates. Novel microscope technologies allow the imaging of developmental processes in unprecedented detail, and they enable the use of complex image-based read-outs for high-throughput/high-content screening. Such applications can easily generate Terabytes of image data, the handling and analysis of which becomes a major bottleneck in extracting the targeted information. Here, we describe the current state of the art in computational image analysis in the zebrafish system. We discuss the challenges encountered when handling high-content image data, especially with regard to data quality, annotation, and storage. We survey methods for preprocessing image data for further analysis, and describe selected examples of automated image analysis, including the tracking of cells during embryogenesis, heartbeat detection, identification of dead embryos, recognition of tissues and anatomical landmarks, and quantification of behavioral patterns of adult fish. We review recent examples for applications using such methods, such as the comprehensive analysis of cell lineages during early development, the generation of a three-dimensional brain atlas of zebrafish larvae, and high-throughput drug screens based on movement patterns. Finally, we identify future challenges for the zebrafish image analysis community, notably those concerning the compatibility of algorithms and data formats for the assembly of modular analysis pipelines. PMID:23758125

  7. Automated image analysis for quantification of filamentous bacteria

    DEFF Research Database (Denmark)

    Fredborg, M.; Rosenvinge, F. S.; Spillum, E.

    2015-01-01

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

  8. Automated rice leaf disease detection using color image analysis

    Science.gov (United States)

    Pugoy, Reinald Adrian D. L.; Mariano, Vladimir Y.

    2011-06-01

    In rice-related institutions such as the International Rice Research Institute, assessing the health condition of a rice plant through its leaves, which is usually done as a manual eyeball exercise, is important to come up with good nutrient and disease management strategies. In this paper, an automated system that can detect diseases present in a rice leaf using color image analysis is presented. In the system, the outlier region is first obtained from a rice leaf image to be tested using histogram intersection between the test and healthy rice leaf images. Upon obtaining the outlier, it is then subjected to a threshold-based K-means clustering algorithm to group related regions into clusters. Then, these clusters are subjected to further analysis to finally determine the suspected diseases of the rice leaf.

  9. Crowdsourcing and Automated Retinal Image Analysis for Diabetic Retinopathy.

    Science.gov (United States)

    Mudie, Lucy I; Wang, Xueyang; Friedman, David S; Brady, Christopher J

    2017-09-23

    As the number of people with diabetic retinopathy (DR) in the USA is expected to increase threefold by 2050, the need to reduce health care costs associated with screening for this treatable disease is ever present. Crowdsourcing and automated retinal image analysis (ARIA) are two areas where new technology has been applied to reduce costs in screening for DR. This paper reviews the current literature surrounding these new technologies. Crowdsourcing has high sensitivity for normal vs abnormal images; however, when multiple categories for severity of DR are added, specificity is reduced. ARIAs have higher sensitivity and specificity, and some commercial ARIA programs are already in use. Deep learning enhanced ARIAs appear to offer even more improvement in ARIA grading accuracy. The utilization of crowdsourcing and ARIAs may be a key to reducing the time and cost burden of processing images from DR screening.

  10. Automated tracking of the vascular tree on DSA images

    International Nuclear Information System (INIS)

    Alperin, N.; Hoffmann, K.R.; Doi, K.

    1990-01-01

    Determination of the vascular tree structure is important for reconstruction of three-dimensional vascular tree from biplane images, for assessment of the significance of a lesion, and for planning treatment for arteriovenous malformation. To automate these analyses, the authors of this paper are developing a method to determine the vascular tree structure from digital subtraction angiography (DSA) images. The authors have previously described a vessel tracking method, based on the double-square-box technique. To improve the tracking accuracy, they have developed and integrated with the previous method a connectivity test and guided-sector-search technique. The connectivity test, based on region growing techniques, eliminates tracking across nonvessel regions. The guided sector-search method incorporates information from a larger are of the image to guide the search for the next tracking point

  11. Automated Identification of Fiducial Points on 3D Torso Images

    Directory of Open Access Journals (Sweden)

    Manas M. Kawale

    2013-01-01

    Full Text Available Breast reconstruction is an important part of the breast cancer treatment process for many women. Recently, 2D and 3D images have been used by plastic surgeons for evaluating surgical outcomes. Distances between different fiducial points are frequently used as quantitative measures for characterizing breast morphology. Fiducial points can be directly marked on subjects for direct anthropometry, or can be manually marked on images. This paper introduces novel algorithms to automate the identification of fiducial points in 3D images. Automating the process will make measurements of breast morphology more reliable, reducing the inter- and intra-observer bias. Algorithms to identify three fiducial points, the nipples, sternal notch, and umbilicus, are described. The algorithms used for localization of these fiducial points are formulated using a combination of surface curvature and 2D color information. Comparison of the 3D coordinates of automatically detected fiducial points and those identified manually, and geodesic distances between the fiducial points are used to validate algorithm performance. The algorithms reliably identified the location of all three of the fiducial points. We dedicate this article to our late colleague and friend, Dr. Elisabeth K. Beahm. Elisabeth was both a talented plastic surgeon and physician-scientist; we deeply miss her insight and her fellowship.

  12. A survey of medical diagnostic imaging technologies

    International Nuclear Information System (INIS)

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

    1991-10-01

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

  13. 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.

  14. 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.

  15. Medication Administration Errors in Nursing Homes Using an Automated Medication Dispensing System

    Science.gov (United States)

    van den Bemt, Patricia M.L.A.; Idzinga, Jetske C.; Robertz, Hans; Kormelink, Dennis Groot; Pels, Neske

    2009-01-01

    Objective To identify the frequency of medication administration errors as well as their potential risk factors in nursing homes using a distribution robot. Design The study was a prospective, observational study conducted within three nursing homes in the Netherlands caring for 180 individuals. Measurements Medication errors were measured using the disguised observation technique. Types of medication errors were described. The correlation between several potential risk factors and the occurrence of medication errors was studied to identify potential causes for the errors. Results In total 2,025 medication administrations to 127 clients were observed. In these administrations 428 errors were observed (21.2%). The most frequently occurring types of errors were use of wrong administration techniques (especially incorrect crushing of medication and not supervising the intake of medication) and wrong time errors (administering the medication at least 1 h early or late).The potential risk factors female gender (odds ratio (OR) 1.39; 95% confidence interval (CI) 1.05–1.83), ATC medication class antibiotics (OR 11.11; 95% CI 2.66–46.50), medication crushed (OR 7.83; 95% CI 5.40–11.36), number of dosages/day/client (OR 1.03; 95% CI 1.01–1.05), nursing home 2 (OR 3.97; 95% CI 2.86–5.50), medication not supplied by distribution robot (OR 2.92; 95% CI 2.04–4.18), time classes “7–10 am” (OR 2.28; 95% CI 1.50–3.47) and “10 am-2 pm” (OR 1.96; 1.18–3.27) and day of the week “Wednesday” (OR 1.46; 95% CI 1.03–2.07) are associated with a higher risk of administration errors. Conclusions Medication administration in nursing homes is prone to many errors. This study indicates that the handling of the medication after removing it from the robot packaging may contribute to this high error frequency, which may be reduced by training of nurse attendants, by automated clinical decision support and by measures to reduce workload. PMID:19390109

  16. Machine learning approaches in medical image analysis

    DEFF Research Database (Denmark)

    de Bruijne, Marleen

    2016-01-01

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

  17. 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

  18. An overview of medical image data base

    International Nuclear Information System (INIS)

    Nishihara, Eitaro

    1992-01-01

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

  19. A Data Acquisition System for Medical Imaging

    International Nuclear Information System (INIS)

    Abellan, Carlos; Cachemiche, Jean-Pierre; Rethore, Frederic; Morel, Christian

    2013-06-01

    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)

  20. Special Issue on “Medical Imaging and Image Processing”

    Directory of Open Access Journals (Sweden)

    Yudong Zhang

    2014-12-01

    Full Text Available Over the last decade, Medical Imaging has become an essential component in many fields of bio-medical research and clinical practice. Biologists study cells and generate 3D confocal microscopy data sets, virologists generate 3D reconstructions of viruses from micrographs, radiologists identify and quantify tumors from MRI and CT scans, and neuroscientists detect regional metabolic brain activity from PET and functional MRI scans. On the other hand, Image Processing includes the analysis, enhancement, and display of images captured via various medical imaging technologies. Image reconstruction and modeling techniques allow instant processing of 2D signals to create 3D images. In addition, image processing and analysis can be used to determine the diameter, volume, and vasculature of a tumor or organ, flow parameters of blood or other fluids, and microscopic changes that have not previously been discernible.[...

  1. Medical imaging and augmented reality. Proceedings

    International Nuclear Information System (INIS)

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

    2006-01-01

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

  2. Mathematics and computer science in medical imaging

    International Nuclear Information System (INIS)

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

    1987-01-01

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

  3. 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.

  4. Adaptive Beamforming for Medical Ultrasound Imaging

    DEFF Research Database (Denmark)

    Holfort, Iben Kraglund

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

  5. Automated and unsupervised detection of malarial parasites in microscopic images

    Directory of Open Access Journals (Sweden)

    Purwar Yashasvi

    2011-12-01

    Full Text Available Abstract Background Malaria is a serious infectious disease. According to the World Health Organization, it is responsible for nearly one million deaths each year. There are various techniques to diagnose malaria of which manual microscopy is considered to be the gold standard. However due to the number of steps required in manual assessment, this diagnostic method is time consuming (leading to late diagnosis and prone to human error (leading to erroneous diagnosis, even in experienced hands. The focus of this study is to develop a robust, unsupervised and sensitive malaria screening technique with low material cost and one that has an advantage over other techniques in that it minimizes human reliance and is, therefore, more consistent in applying diagnostic criteria. Method A method based on digital image processing of Giemsa-stained thin smear image is developed to facilitate the diagnostic process. The diagnosis procedure is divided into two parts; enumeration and identification. The image-based method presented here is designed to automate the process of enumeration and identification; with the main advantage being its ability to carry out the diagnosis in an unsupervised manner and yet have high sensitivity and thus reducing cases of false negatives. Results The image based method is tested over more than 500 images from two independent laboratories. The aim is to distinguish between positive and negative cases of malaria using thin smear blood slide images. Due to the unsupervised nature of method it requires minimal human intervention thus speeding up the whole process of diagnosis. Overall sensitivity to capture cases of malaria is 100% and specificity ranges from 50-88% for all species of malaria parasites. Conclusion Image based screening method will speed up the whole process of diagnosis and is more advantageous over laboratory procedures that are prone to errors and where pathological expertise is minimal. Further this method

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

    Science.gov (United States)

    Park, Jungkap; Rosania, Gus R; Shedden, Kerby A; Nguyen, Mandee; Lyu, Naesung; Saitou, Kazuhiro

    2009-01-01

    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 to scientific research

  7. 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

  8. Automated exploration of the radio plasma imager data

    Science.gov (United States)

    Galkin, Ivan; Reinisch, Bodo; Grinstein, Georges; Khmyrov, Grigori; Kozlov, Alexander; Huang, Xueqin; Fung, Shing

    2004-12-01

    As research instruments with large information capacities become a reality, automated systems for intelligent data analysis become a necessity. Scientific archives containing huge volumes of data preclude manual manipulation or intervention and require automated exploration and mining that can at least preclassify information in categories. The large data set from the radio plasma imager (RPI) instrument on board the IMAGE satellite shows a critical need for such exploration in order to identify and archive features of interest in the volumes of visual information. In this research we have developed such a preclassifier through a model of preattentive vision capable of detecting and extracting traces of echoes from the RPI plasmagrams. The overall design of our model complies with Marr's paradigm of vision, where elements of increasing perceptual strength are built bottom up under the Gestalt constraints of good continuation and smoothness. The specifics of the RPI data, however, demanded extension of this paradigm to achieve greater robustness for signature analysis. Our preattentive model now employs a feedback neural network that refines alignment of the oriented edge elements (edgels) detected in the plasmagram image by subjecting them to collective global-scale optimization. The level of interaction between the oriented edgels is determined by their distance and mutual orientation in accordance with the Yen and Finkel model of the striate cortex that encompasses findings in psychophysical studies of human vision. The developed models have been implemented in an operational system "CORPRAL" (Cognitive Online RPI Plasmagram Ranking Algorithm) that currently scans daily submissions of the RPI plasmagrams for the presence of echo traces. Qualifying plasmagrams are tagged in the mission database, making them available for a variety of queries. We discuss CORPRAL performance and its impact on scientific analysis of RPI data.

  9. 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.

  10. 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.

  11. Image processing for medical diagnosis using CNN

    Science.gov (United States)

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

    2003-01-01

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

  12. Image processing for medical diagnosis using CNN

    International Nuclear Information System (INIS)

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

    2003-01-01

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

  13. Silhouette-based approach of 3D image reconstruction for automated image acquisition using robotic arm

    Science.gov (United States)

    Azhar, N.; Saad, W. H. M.; Manap, N. A.; Saad, N. M.; Syafeeza, A. R.

    2017-06-01

    This study presents the approach of 3D image reconstruction using an autonomous robotic arm for the image acquisition process. A low cost of the automated imaging platform is created using a pair of G15 servo motor connected in series to an Arduino UNO as a main microcontroller. Two sets of sequential images were obtained using different projection angle of the camera. The silhouette-based approach is used in this study for 3D reconstruction from the sequential images captured from several different angles of the object. Other than that, an analysis based on the effect of different number of sequential images on the accuracy of 3D model reconstruction was also carried out with a fixed projection angle of the camera. The effecting elements in the 3D reconstruction are discussed and the overall result of the analysis is concluded according to the prototype of imaging platform.

  14. 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

  15. Automated regional behavioral analysis for human brain images.

    Science.gov (United States)

    Lancaster, Jack L; Laird, Angela R; Eickhoff, Simon B; Martinez, Michael J; Fox, P Mickle; Fox, Peter T

    2012-01-01

    Behavioral categories of functional imaging experiments along with standardized brain coordinates of associated activations were used to develop a method to automate regional behavioral analysis of human brain images. Behavioral and coordinate data were taken from the BrainMap database (http://www.brainmap.org/), which documents over 20 years of published functional brain imaging studies. A brain region of interest (ROI) for behavioral analysis can be defined in functional images, anatomical images or brain atlases, if images are spatially normalized to MNI or Talairach standards. Results of behavioral analysis are presented for each of BrainMap's 51 behavioral sub-domains spanning five behavioral domains (Action, Cognition, Emotion, Interoception, and Perception). For each behavioral sub-domain the fraction of coordinates falling within the ROI was computed and compared with the fraction expected if coordinates for the behavior were not clustered, i.e., uniformly distributed. When the difference between these fractions is large behavioral association is indicated. A z-score ≥ 3.0 was used to designate statistically significant behavioral association. The left-right symmetry of ~100K activation foci was evaluated by hemisphere, lobe, and by behavioral sub-domain. Results highlighted the classic left-side dominance for language while asymmetry for most sub-domains (~75%) was not statistically significant. Use scenarios were presented for anatomical ROIs from the Harvard-Oxford cortical (HOC) brain atlas, functional ROIs from statistical parametric maps in a TMS-PET study, a task-based fMRI study, and ROIs from the ten "major representative" functional networks in a previously published resting state fMRI study. Statistically significant behavioral findings for these use scenarios were consistent with published behaviors for associated anatomical and functional regions.

  16. Leadership and power in medical imaging

    International Nuclear Information System (INIS)

    Yielder, Jill

    2006-01-01

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

  17. Deep Learning in Medical Image Analysis

    Science.gov (United States)

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

    2016-01-01

    The computer-assisted analysis for better interpreting images have been longstanding issues in the medical imaging field. On the image-understanding front, recent advances in machine learning, especially, in the way of deep learning, have made a big leap to help identify, classify, and quantify patterns in medical images. Specifically, exploiting hierarchical feature representations learned solely from data, instead of handcrafted features mostly designed based on domain-specific knowledge, lies at the core of the advances. In that way, deep learning is rapidly proving to be the state-of-the-art foundation, achieving enhanced performances in various medical applications. In this article, we introduce the fundamentals of deep learning methods; review their successes to image registration, anatomical/cell structures detection, tissue segmentation, computer-aided disease diagnosis or prognosis, and so on. We conclude by raising research issues and suggesting future directions for further improvements. PMID:28301734

  18. 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

  19. Multispectral imaging for medical diagnosis

    Science.gov (United States)

    Anselmo, V. J.

    1977-01-01

    Photography technique determines amount of morbidity present in tissue. Imaging apparatus incorporates numerical filtering. Overall system operates in near-real time. Information gained from this system enables physician to understand extent of injury and leads to accelerated treatment.

  20. Multi-channel medical imaging system

    Science.gov (United States)

    Frangioni, John V

    2013-12-31

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

  1. Overview of deep learning in medical imaging.

    Science.gov (United States)

    Suzuki, Kenji

    2017-09-01

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

  2. Feature Detector and Descriptor for Medical Images

    Science.gov (United States)

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

    2009-02-01

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

  3. Automated region definition for cardiac nitrogen-13-ammonia PET imaging.

    Science.gov (United States)

    Muzik, O; Beanlands, R; Wolfe, E; Hutchins, G D; Schwaiger, M

    1993-02-01

    In combination with PET, the tracer 13N-ammonia can be employed for the noninvasive quantification of myocardial perfusion at rest and after pharmacological stress. The purpose of this study was to develop an analysis method for the quantification of regional myocardial blood flow in the clinical setting. The algorithm includes correction for patient motion, an automated definition of multiple regions and display of absolute flows in polar map format. The effects of partial volume and blood to tissue cross-contamination were accounted for by optimizing the radial position of regions to meet fundamental assumptions of the kinetic model. In order to correct for motion artifacts, the myocardial displacement was manually determined based on edge-enhanced images. The obtained results exhibit the capability of the presented algorithm to noninvasively assess regional myocardial perfusion in the clinical environment.

  4. Automated drug dispensing system reduces medication errors in an intensive care setting.

    Science.gov (United States)

    Chapuis, Claire; Roustit, Matthieu; Bal, Gaëlle; Schwebel, Carole; Pansu, Pascal; David-Tchouda, Sandra; Foroni, Luc; Calop, Jean; Timsit, Jean-François; Allenet, Benoît; Bosson, Jean-Luc; Bedouch, Pierrick

    2010-12-01

    We aimed to assess the impact of an automated dispensing system on the incidence of medication errors related to picking, preparation, and administration of drugs in a medical intensive care unit. We also evaluated the clinical significance of such errors and user satisfaction. Preintervention and postintervention study involving a control and an intervention medical intensive care unit. Two medical intensive care units in the same department of a 2,000-bed university hospital. Adult medical intensive care patients. After a 2-month observation period, we implemented an automated dispensing system in one of the units (study unit) chosen randomly, with the other unit being the control. The overall error rate was expressed as a percentage of total opportunities for error. The severity of errors was classified according to National Coordinating Council for Medication Error Reporting and Prevention categories by an expert committee. User satisfaction was assessed through self-administered questionnaires completed by nurses. A total of 1,476 medications for 115 patients were observed. After automated dispensing system implementation, we observed a reduced percentage of total opportunities for error in the study compared to the control unit (13.5% and 18.6%, respectively; perror (20.4% and 13.5%; perror showed a significant impact of the automated dispensing system in reducing preparation errors (perrors caused no harm (National Coordinating Council for Medication Error Reporting and Prevention category C). The automated dispensing system did not reduce errors causing harm. Finally, the mean for working conditions improved from 1.0±0.8 to 2.5±0.8 on the four-point Likert scale. The implementation of an automated dispensing system reduced overall medication errors related to picking, preparation, and administration of drugs in the intensive care unit. Furthermore, most nurses favored the new drug dispensation organization.

  5. Improved Interactive Medical-Imaging System

    Science.gov (United States)

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

    2003-01-01

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

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

    Science.gov (United States)

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

    2016-02-01

    Segmentation of an ultrasound image into functional tissues is of great importance to clinical diagnosis of breast cancer. However, many studies are found to segment only the mass of interest and not all major tissues. Differences and inconsistencies in ultrasound interpretation call for an automated segmentation method to make results operator-independent. Furthermore, manual segmentation of entire three-dimensional (3D) ultrasound volumes is time-consuming, resource-intensive, and clinically impractical. Here, we propose an automated algorithm to segment 3D ultrasound volumes into three major tissue types: cyst/mass, fatty tissue, and fibro-glandular tissue. To test its efficacy and consistency, the proposed automated method was employed on a database of 21 cases of whole breast ultrasound. Experimental results show that our proposed method not only distinguishes fat and non-fat tissues correctly, but performs well in classifying cyst/mass. Comparison of density assessment between the automated method and manual segmentation demonstrates good consistency with an accuracy of 85.7%. Quantitative comparison of corresponding tissue volumes, which uses overlap ratio, gives an average similarity of 74.54%, consistent with values seen in MRI brain segmentations. Thus, our proposed method exhibits great potential as an automated approach to segment 3D whole breast ultrasound volumes into functionally distinct tissues that may help to correct ultrasound speed of sound aberrations and assist in density based prognosis of breast cancer. Copyright © 2015 Elsevier B.V. All rights reserved.

  7. Medication incidents related to automated dose dispensing in community pharmacies and hospitals - A reporting system study

    NARCIS (Netherlands)

    K.C. Cheung (Ka Chun); P.M.L.A. van den Bemt (Patricia); M.L. Bouvy (Marcel); M.E. Wensing (Michel); P.A. de Smet (Peter)

    2014-01-01

    textabstractIntroduction: Automated dose dispensing (ADD) is being introduced in several countries and the use of this technology is expected to increase as a growing number of elderly people need to manage their medication at home. ADD aims to improve medication safety and treatment adherence, but

  8. Medication incidents related to automated dose dispensing in community pharmacies and hospitals - A reporting system study

    NARCIS (Netherlands)

    Cheung, Ka Chun; Van Den Bemt, Patricia M L A; Bouvy, Marcel L.; Wensing, Michel; De Smet, Peter A G M

    2014-01-01

    Introduction: Automated dose dispensing (ADD) is being introduced in several countries and the use of this technology is expected to increase as a growing number of elderly people need to manage their medication at home. ADD aims to improve medication safety and treatment adherence, but it may

  9. Medication incidents related to automated dose dispensing in community pharmacies and hospitals - a reporting system study

    NARCIS (Netherlands)

    Cheung, K.C.; Bemt, P.M. van den; Bouvy, M.L.; Wensing, M.J.; Smet, P.A. de

    2014-01-01

    INTRODUCTION: Automated dose dispensing (ADD) is being introduced in several countries and the use of this technology is expected to increase as a growing number of elderly people need to manage their medication at home. ADD aims to improve medication safety and treatment adherence, but it may

  10. Use of organoboranes in modern medical imaging

    International Nuclear Information System (INIS)

    Kabalka, G.W.

    1991-01-01

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

  11. Cascaded Window Memoization for Medical Imaging

    OpenAIRE

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

    2011-01-01

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

  12. Automated Image Analysis of Offshore Infrastructure Marine Biofouling

    Directory of Open Access Journals (Sweden)

    Kate Gormley

    2018-01-01

    Full Text Available In the UK, some of the oldest oil and gas installations have been in the water for over 40 years and have considerable colonisation by marine organisms, which may lead to both industry challenges and/or potential biodiversity benefits (e.g., artificial reefs. The project objective was to test the use of an automated image analysis software (CoralNet on images of marine biofouling from offshore platforms on the UK continental shelf, with the aim of (i training the software to identify the main marine biofouling organisms on UK platforms; (ii testing the software performance on 3 platforms under 3 different analysis criteria (methods A–C; (iii calculating the percentage cover of marine biofouling organisms and (iv providing recommendations to industry. Following software training with 857 images, and testing of three platforms, results showed that diversity of the three platforms ranged from low (in the central North Sea to moderate (in the northern North Sea. The two central North Sea platforms were dominated by the plumose anemone Metridium dianthus; and the northern North Sea platform showed less obvious species domination. Three different analysis criteria were created, where the method of selection of points, number of points assessed and confidence level thresholds (CT varied: (method A random selection of 20 points with CT 80%, (method B stratified random of 50 points with CT of 90% and (method C a grid approach of 100 points with CT of 90%. Performed across the three platforms, the results showed that there were no significant differences across the majority of species and comparison pairs. No significant difference (across all species was noted between confirmed annotations methods (A, B and C. It was considered that the software performed well for the classification of the main fouling species in the North Sea. Overall, the study showed that the use of automated image analysis software may enable a more efficient and consistent

  13. 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 ...

  14. A Domain Specific Language for Performance Evaluation of Medical Imaging Systems

    NARCIS (Netherlands)

    van den Berg, Freek; Remke, Anne Katharina Ingrid; Haverkort, Boudewijn R.H.M.; Turau, Volker; Kwiatkowska, Marta; Mangharam, Rahul; Weyer, Christoph

    2014-01-01

    We propose iDSL, a domain specific language and toolbox for performance evaluation of Medical Imaging Systems. iDSL provides transformations to MoDeST models, which are in turn converted into UPPAAL and discrete-event MODES models. This enables automated performance evaluation by means of model

  15. Deep Learning in Medical Image Analysis.

    Science.gov (United States)

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

    2017-06-21

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

  16. Monte Carlo simulations of medical imaging modalities

    Energy Technology Data Exchange (ETDEWEB)

    Estes, G.P. [Los Alamos National Lab., NM (United States)

    1998-09-01

    Because continuous-energy Monte Carlo radiation transport calculations can be nearly exact simulations of physical reality (within data limitations, geometric approximations, transport algorithms, etc.), it follows that one should be able to closely approximate the results of many experiments from first-principles computations. This line of reasoning has led to various MCNP studies that involve simulations of medical imaging modalities and other visualization methods such as radiography, Anger camera, computerized tomography (CT) scans, and SABRINA particle track visualization. It is the intent of this paper to summarize some of these imaging simulations in the hope of stimulating further work, especially as computer power increases. Improved interpretation and prediction of medical images should ultimately lead to enhanced medical treatments. It is also reasonable to assume that such computations could be used to design new or more effective imaging instruments.

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

    Science.gov (United States)

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

    2018-02-01

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

  18. A hierarchical SVG image abstraction layer for medical imaging

    Science.gov (United States)

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

    2010-03-01

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

  19. Use of mobile devices for medical imaging.

    Science.gov (United States)

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

    2014-12-01

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

  20. 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

    2016-09-07

    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

  1. Image of psychiatry among medical community.

    Science.gov (United States)

    Jiloha, R C

    1989-10-01

    Psychiatry as a medical discipline has been variously described. Even among medical community psychiatry was looked down upon as medical speciality. After World War II when psychiatry's importance was realized for total treatment, its image was supposed to have improved. In the light of these ups and downs a survey of medical community consisting of 5000 doctors was conducted results of which reveal that the role of psychiatry is favourable. Respondent's comments and criticism were constructive and consistent. Important facts highlighted by this survey are that the undergraduate training in psychiatry is inadequate and the general public carries a frightening image about psychiatry according to the medical men. Therefore, it is suggested that medicos need more exposure to psychiatry and undergraduate training in psychiatry needs to be revised.

  2. Automated segmentation and geometrical modeling of the tricuspid aortic valve in 3D echocardiographic images.

    Science.gov (United States)

    Pouch, Alison M; Wang, Hongzhi; Takabe, Manabu; Jackson, Benjamin M; Sehgal, Chandra M; Gorman, Joseph H; Gorman, Robert C; Yushkevich, Paul A

    2013-01-01

    The aortic valve has been described with variable anatomical definitions, and the consistency of 2D manual measurement of valve dimensions in medical image data has been questionable. Given the importance of image-based morphological assessment in the diagnosis and surgical treatment of aortic valve disease, there is considerable need to develop a standardized framework for 3D valve segmentation and shape representation. Towards this goal, this work integrates template-based medial modeling and multi-atlas label fusion techniques to automatically delineate and quantitatively describe aortic leaflet geometry in 3D echocardiographic (3DE) images, a challenging task that has been explored only to a limited extent. The method makes use of expert knowledge of aortic leaflet image appearance, generates segmentations with consistent topology, and establishes a shape-based coordinate system on the aortic leaflets that enables standardized automated measurements. In this study, the algorithm is evaluated on 11 3DE images of normal human aortic leaflets acquired at mid systole. The clinical relevance of the method is its ability to capture leaflet geometry in 3DE image data with minimal user interaction while producing consistent measurements of 3D aortic leaflet geometry.

  3. Medical images storage using discrete cosine transform

    International Nuclear Information System (INIS)

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

    2010-01-01

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

  4. Structural analysis in medical imaging

    International Nuclear Information System (INIS)

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

    1987-01-01

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

  5. 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.

  6. Automated image analysis of microstructure changes in metal alloys

    Science.gov (United States)

    Hoque, Mohammed E.; Ford, Ralph M.; Roth, John T.

    2005-02-01

    The ability to identify and quantify changes in the microstructure of metal alloys is valuable in metal cutting and shaping applications. For example, certain metals, after being cryogenically and electrically treated, have shown large increases in their tool life when used in manufacturing cutting and shaping processes. However, the mechanisms of microstructure changes in alloys under various treatments, which cause them to behave differently, are not yet fully understood. The changes are currently evaluated in a semi-quantitative manner by visual inspection of images of the microstructure. This research applies pattern recognition technology to quantitatively measure the changes in microstructure and to validate the initial assertion of increased tool life under certain treatments. Heterogeneous images of aluminum and tungsten carbide of various categories were analyzed using a process including background correction, adaptive thresholding, edge detection and other algorithms for automated analysis of microstructures. The algorithms are robust across a variety of operating conditions. This research not only facilitates better understanding of the effects of electric and cryogenic treatment of these materials, but also their impact on tooling and metal-cutting processes.

  7. FPGA Accelerator for Wavelet-Based Automated Global Image Registration

    Directory of Open Access Journals (Sweden)

    Baofeng Li

    2009-01-01

    Full Text Available Wavelet-based automated global image registration (WAGIR is fundamental for most remote sensing image processing algorithms and extremely computation-intensive. With more and more algorithms migrating from ground computing to onboard computing, an efficient dedicated architecture of WAGIR is desired. In this paper, a BWAGIR architecture is proposed based on a block resampling scheme. BWAGIR achieves a significant performance by pipelining computational logics, parallelizing the resampling process and the calculation of correlation coefficient and parallel memory access. A proof-of-concept implementation with 1 BWAGIR processing unit of the architecture performs at least 7.4X faster than the CL cluster system with 1 node, and at least 3.4X than the MPM massively parallel machine with 1 node. Further speedup can be achieved by parallelizing multiple BWAGIR units. The architecture with 5 units achieves a speedup of about 3X against the CL with 16 nodes and a comparative speed with the MPM with 30 nodes. More importantly, the BWAGIR architecture can be deployed onboard economically.

  8. FPGA Accelerator for Wavelet-Based Automated Global Image Registration

    Directory of Open Access Journals (Sweden)

    Li Baofeng

    2009-01-01

    Full Text Available Abstract Wavelet-based automated global image registration (WAGIR is fundamental for most remote sensing image processing algorithms and extremely computation-intensive. With more and more algorithms migrating from ground computing to onboard computing, an efficient dedicated architecture of WAGIR is desired. In this paper, a BWAGIR architecture is proposed based on a block resampling scheme. BWAGIR achieves a significant performance by pipelining computational logics, parallelizing the resampling process and the calculation of correlation coefficient and parallel memory access. A proof-of-concept implementation with 1 BWAGIR processing unit of the architecture performs at least 7.4X faster than the CL cluster system with 1 node, and at least 3.4X than the MPM massively parallel machine with 1 node. Further speedup can be achieved by parallelizing multiple BWAGIR units. The architecture with 5 units achieves a speedup of about 3X against the CL with 16 nodes and a comparative speed with the MPM with 30 nodes. More importantly, the BWAGIR architecture can be deployed onboard economically.

  9. 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.

  10. A Hybrid Technique for Medical Image Segmentation

    Directory of Open Access Journals (Sweden)

    Alamgir Nyma

    2012-01-01

    Full Text Available Medical image segmentation is an essential and challenging aspect in computer-aided diagnosis and also in pattern recognition research. This paper proposes a hybrid method for magnetic resonance (MR image segmentation. We first remove impulsive noise inherent in MR images by utilizing a vector median filter. Subsequently, Otsu thresholding is used as an initial coarse segmentation method that finds the homogeneous regions of the input image. Finally, an enhanced suppressed fuzzy c-means is used to partition brain MR images into multiple segments, which employs an optimal suppression factor for the perfect clustering in the given data set. To evaluate the robustness of the proposed approach in noisy environment, we add different types of noise and different amount of noise to T1-weighted brain MR images. Experimental results show that the proposed algorithm outperforms other FCM based algorithms in terms of segmentation accuracy for both noise-free and noise-inserted MR images.

  11. Automated X-ray image analysis for cargo security: Critical review and future promise.

    Science.gov (United States)

    Rogers, Thomas W; Jaccard, Nicolas; Morton, Edward J; Griffin, Lewis D

    2017-01-01

    We review the relatively immature field of automated image analysis for X-ray cargo imagery. There is increasing demand for automated analysis methods that can assist in the inspection and selection of containers, due to the ever-growing volumes of traded cargo and the increasing concerns that customs- and security-related threats are being smuggled across borders by organised crime and terrorist networks. We split the field into the classical pipeline of image preprocessing and image understanding. Preprocessing includes: image manipulation; quality improvement; Threat Image Projection (TIP); and material discrimination and segmentation. Image understanding includes: Automated Threat Detection (ATD); and Automated Contents Verification (ACV). We identify several gaps in the literature that need to be addressed and propose ideas for future research. Where the current literature is sparse we borrow from the single-view, multi-view, and CT X-ray baggage domains, which have some characteristics in common with X-ray cargo.

  12. Achieving automated narrative text interpretation using phrases in the electronic medical record.

    Science.gov (United States)

    Murphy, S. N.; Barnett, G. O.

    1996-01-01

    Stereotypic phrases are used by clinicians throughout the medical record, as seen in an analysis of our COSTAR medical record database. These phrases are often associated with an underling semantic concept; for example the phrase CLEAR LUNGS may be linked with the concept "normal lung exam" for a particular physician. Formalizing these associations with concepts from the UMLS using the MEDPhrase application allowed us to automate interpretation of narrative text within our electronic medical record. PMID:8947723

  13. Medical imaging applications of amorphous silicon

    International Nuclear Information System (INIS)

    Mireshghi, A.; Drewery, J.S.; Hong, W.S.; Jing, T.; Kaplan, S.N.; Lee, H.K.; Perez-Mendez, V.

    1994-07-01

    Two dimensional hydrogenated amorphous silicon (a-Si:H) pixel arrays are good candidates as flat-panel imagers for applications in medical imaging. Various performance characteristics of these imagers are reviewed and compared with currently used equipments. An important component in the a-Si:H imager is the scintillator screen. A new approach for fabrication of high resolution CsI(Tl) scintillator layers, appropriate for coupling to a-Si:H arrays, are presented. For nuclear medicine applications, a new a-Si:H based gamma camera is introduced and Monte Carlo simulation is used to evaluate its performance

  14. Automated discrimination of lower and higher grade gliomas based on histopathological image analysis

    Directory of Open Access Journals (Sweden)

    Hojjat Seyed Mousavi

    2015-01-01

    Full Text Available Introduction: Histopathological images have rich structural information, are multi-channel in nature and contain meaningful pathological information at various scales. Sophisticated image analysis tools that can automatically extract discriminative information from the histopathology image slides for diagnosis remain an area of significant research activity. In this work, we focus on automated brain cancer grading, specifically glioma grading. Grading of a glioma is a highly important problem in pathology and is largely done manually by medical experts based on an examination of pathology slides (images. To complement the efforts of clinicians engaged in brain cancer diagnosis, we develop novel image processing algorithms and systems to automatically grade glioma tumor into two categories: Low-grade glioma (LGG and high-grade glioma (HGG which represent a more advanced stage of the disease. Results: We propose novel image processing algorithms based on spatial domain analysis for glioma tumor grading that will complement the clinical interpretation of the tissue. The image processing techniques are developed in close collaboration with medical experts to mimic the visual cues that a clinician looks for in judging of the grade of the disease. Specifically, two algorithmic techniques are developed: (1 A cell segmentation and cell-count profile creation for identification of Pseudopalisading Necrosis, and (2 a customized operation of spatial and morphological filters to accurately identify microvascular proliferation (MVP. In both techniques, a hierarchical decision is made via a decision tree mechanism. If either Pseudopalisading Necrosis or MVP is found present in any part of the histopathology slide, the whole slide is identified as HGG, which is consistent with World Health Organization guidelines. Experimental results on the Cancer Genome Atlas database are presented in the form of: (1 Successful detection rates of pseudopalisading necrosis

  15. Intelligent medical image processing by simulated annealing

    International Nuclear Information System (INIS)

    Ohyama, Nagaaki

    1992-01-01

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

  16. Automated force volume image processing for biological samples.

    Directory of Open Access Journals (Sweden)

    Pavel Polyakov

    2011-04-01

    Full Text Available Atomic force microscopy (AFM has now become a powerful technique for investigating on a molecular level, surface forces, nanomechanical properties of deformable particles, biomolecular interactions, kinetics, and dynamic processes. This paper specifically focuses on the analysis of AFM force curves collected on biological systems, in particular, bacteria. The goal is to provide fully automated tools to achieve theoretical interpretation of force curves on the basis of adequate, available physical models. In this respect, we propose two algorithms, one for the processing of approach force curves and another for the quantitative analysis of retraction force curves. In the former, electrostatic interactions prior to contact between AFM probe and bacterium are accounted for and mechanical interactions operating after contact are described in terms of Hertz-Hooke formalism. Retraction force curves are analyzed on the basis of the Freely Jointed Chain model. For both algorithms, the quantitative reconstruction of force curves is based on the robust detection of critical points (jumps, changes of slope or changes of curvature which mark the transitions between the various relevant interactions taking place between the AFM tip and the studied sample during approach and retraction. Once the key regions of separation distance and indentation are detected, the physical parameters describing the relevant interactions operating in these regions are extracted making use of regression procedure for fitting experiments to theory. The flexibility, accuracy and strength of the algorithms are illustrated with the processing of two force-volume images, which collect a large set of approach and retraction curves measured on a single biological surface. For each force-volume image, several maps are generated, representing the spatial distribution of the searched physical parameters as estimated for each pixel of the force-volume image.

  17. 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...

  18. Medical Image Registration and Surgery Simulation

    DEFF Research Database (Denmark)

    Bro-Nielsen, Morten

    1996-01-01

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

  19. 21 CFR 892.2040 - Medical image hardcopy device.

    Science.gov (United States)

    2010-04-01

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

  20. 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.

  1. Automated processing of webcam images for phenological classification.

    Directory of Open Access Journals (Sweden)

    Ludwig Bothmann

    Full Text Available Along with the global climate change, there is an increasing interest for its effect on phenological patterns such as start and end of the growing season. Scientific digital webcams are used for this purpose taking every day one or more images from the same natural motive showing for example trees or grassland sites. To derive phenological patterns from the webcam images, regions of interest are manually defined on these images by an expert and subsequently a time series of percentage greenness is derived and analyzed with respect to structural changes. While this standard approach leads to satisfying results and allows to determine dates of phenological change points, it is associated with a considerable amount of manual work and is therefore constrained to a limited number of webcams only. In particular, this forbids to apply the phenological analysis to a large network of publicly accessible webcams in order to capture spatial phenological variation. In order to be able to scale up the analysis to several hundreds or thousands of webcams, we propose and evaluate two automated alternatives for the definition of regions of interest, allowing for efficient analyses of webcam images. A semi-supervised approach selects pixels based on the correlation of the pixels' time series of percentage greenness with a few prototype pixels. An unsupervised approach clusters pixels based on scores of a singular value decomposition. We show for a scientific webcam that the resulting regions of interest are at least as informative as those chosen by an expert with the advantage that no manual action is required. Additionally, we show that the methods can even be applied to publicly available webcams accessed via the internet yielding interesting partitions of the analyzed images. Finally, we show that the methods are suitable for the intended big data applications by analyzing 13988 webcams from the AMOS database. All developed methods are implemented in the

  2. Aligning Islamic Spirituality to Medical Imaging.

    Science.gov (United States)

    Zainuddin, Zainul Ibrahim

    2017-10-01

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

  3. Medical Image Denoising Using Mixed Transforms

    Directory of Open Access Journals (Sweden)

    Jaleel Sadoon Jameel

    2018-02-01

    Full Text Available  In this paper,  a mixed transform method is proposed based on a combination of wavelet transform (WT and multiwavelet transform (MWT in order to denoise medical images. The proposed method consists of WT and MWT in cascade form to enhance the denoising performance of image processing. Practically, the first step is to add a noise to Magnetic Resonance Image (MRI or Computed Tomography (CT images for the sake of testing. The noisy image is processed by WT to achieve four sub-bands and each sub-band is treated individually using MWT before the soft/hard denoising stage. Simulation results show that a high peak signal to noise ratio (PSNR is improved significantly and the characteristic features are well preserved by employing mixed transform of WT and MWT due to their capability of separating noise signals from image signals. Moreover, the corresponding mean square error (MSE is decreased accordingly compared to other available methods.

  4. APES Beamforming Applied to Medical Ultrasound Imaging

    DEFF Research Database (Denmark)

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

    2009-01-01

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

  5. Body image and cosmetic medical treatments.

    Science.gov (United States)

    Sarwer, David B; Crerand, Canice E

    2004-01-01

    Cosmetic medical treatments have become increasingly popular over the past decade. The explosion in popularity can be attributed to several factors-the evolution of safer, minimally invasive procedures, increased mass media attention, and the greater willingness of individuals to undergo cosmetic procedures as a means to enhance physical appearance. Medical and mental health professionals have long been interested in understanding both the motivations for seeking a change in physical appearance as well as the psychological outcomes of these treatments. Body image has been thought to play a key role in the decision to seek cosmetic procedures, however, only recently have studies investigated the pre- and postoperative body image concerns of patients. While body image dissatisfaction may motivate the pursuit of cosmetic medical treatments, psychiatric disorders characterized by body image disturbances, such as body dysmorphic disorder and eating disorders, may be relatively common among these patients. Subsequent research on persons who alter their physical appearance through cosmetic medical treatments are likely provide important information on the nature of body image.

  6. HVS-based medical image compression

    International Nuclear Information System (INIS)

    Kai Xie; Jie Yang; Min Zhuyue; Liang Lixiao

    2005-01-01

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

  7. Automated Outcome Classification of Computed Tomography Imaging Reports for Pediatric Traumatic Brain Injury.

    Science.gov (United States)

    Yadav, Kabir; Sarioglu, Efsun; Choi, Hyeong Ah; Cartwright, Walter B; Hinds, Pamela S; Chamberlain, James M

    2016-02-01

    The authors have previously demonstrated highly reliable automated classification of free-text computed tomography (CT) imaging reports using a hybrid system that pairs linguistic (natural language processing) and statistical (machine learning) techniques. Previously performed for identifying the outcome of orbital fracture in unprocessed radiology reports from a clinical data repository, the performance has not been replicated for more complex outcomes. To validate automated outcome classification performance of a hybrid natural language processing (NLP) and machine learning system for brain CT imaging reports. The hypothesis was that our system has performance characteristics for identifying pediatric traumatic brain injury (TBI). This was a secondary analysis of a subset of 2,121 CT reports from the Pediatric Emergency Care Applied Research Network (PECARN) TBI study. For that project, radiologists dictated CT reports as free text, which were then deidentified and scanned as PDF documents. Trained data abstractors manually coded each report for TBI outcome. Text was extracted from the PDF files using optical character recognition. The data set was randomly split evenly for training and testing. Training patient reports were used as input to the Medical Language Extraction and Encoding (MedLEE) NLP tool to create structured output containing standardized medical terms and modifiers for negation, certainty, and temporal status. A random subset stratified by site was analyzed using descriptive quantitative content analysis to confirm identification of TBI findings based on the National Institute of Neurological Disorders and Stroke (NINDS) Common Data Elements project. Findings were coded for presence or absence, weighted by frequency of mentions, and past/future/indication modifiers were filtered. After combining with the manual reference standard, a decision tree classifier was created using data mining tools WEKA 3.7.5 and Salford Predictive Miner 7

  8. Resolution enhancement in medical ultrasound imaging.

    Science.gov (United States)

    Ploquin, Marie; Basarab, Adrian; Kouamé, Denis

    2015-01-01

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

  9. Nuclear imaging in the realm of medical imaging

    International Nuclear Information System (INIS)

    Deconinck, Frank

    2003-01-01

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

  10. Internet of things and automation of imaging: beyond representationalism

    Directory of Open Access Journals (Sweden)

    2016-09-01

    Full Text Available It is no doubt that the production of digital imagery invites for the major update of theoretical apparatus: what up until now was perceived solely or primarily as the stable representation of the world gives way to the image understood in terms of “the continuous actualization of networked data” or “networked terminal.” In my article I would like to argue that analysis of this new visual environment should not be limited to the procedures of data processing. What also invites serious investigation is acknowledging the reliance of contemporary media ecology on wireless communication which according to Adrian Mackenzie functions as “prepositions (‘at,’ ‘in,’ ‘with,’ by’, ‘between,’ ‘near,’ etc in the grammar of contemporary media” It seems especially important in the case of the imagery accompanying some instances of internet of things, where the considerable part of networked imagery is produced in a fully automated and machinic way. This crowdsourced air pollution monitoring platform consists of networked sensors transmitting signals and data which are then visualized as graphs and maps through the IoT service provider, Xively.

  11. Automated counting of bacterial colonies by image analysis.

    Science.gov (United States)

    Chiang, Pei-Ju; Tseng, Min-Jen; He, Zong-Sian; Li, Chia-Hsun

    2015-01-01

    Research on microorganisms often involves culturing as a means to determine the survival and proliferation of bacteria. The number of colonies in a culture is counted to calculate the concentration of bacteria in the original broth; however, manual counting can be time-consuming and imprecise. To save time and prevent inconsistencies, this study proposes a fully automated counting system using image processing methods. To accurately estimate the number of viable bacteria in a known volume of suspension, colonies distributing over the whole surface area of a plate, including the central and rim areas of a Petri dish are taken into account. The performance of the proposed system is compared with verified manual counts, as well as with two freely available counting software programs. Comparisons show that the proposed system is an effective method with excellent accuracy with mean value of absolute percentage error of 3.37%. A user-friendly graphical user interface is also developed and freely available for download, providing researchers in biomedicine with a more convenient instrument for the enumeration of bacterial colonies. Copyright © 2014 Elsevier B.V. All rights reserved.

  12. 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.

  13. 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.

  14. Automated telecommunication-based reminders and adherence with once-daily glaucoma medication dosing: the automated dosing reminder study.

    Science.gov (United States)

    Boland, Michael V; Chang, Dolly S; Frazier, Travis; Plyler, Ryan; Jefferys, Joan L; Friedman, David S

    2014-07-01

    Topical glaucoma medications lower intraocular pressure and alter the course of the disease. Because adherence with glaucoma medications is a known problem, interventions are needed to help those patients who do not take their medications as prescribed. To assess the ability of an automated telecommunication-based intervention to improve adherence with glaucoma medications. We performed a prospective cohort study of medication adherence, followed by a randomized intervention for those found to be nonadherent, of individuals recruited from a university-based glaucoma subspecialty clinic. A total of 491 participants were enrolled in the initial assessment of adherence. Of those, 70 were nonadherent with their medications after 3 months of electronic monitoring and randomized to intervention and control groups. A personal health record was used to store the list of patient medications and reminder preferences. On the basis of those data, participants randomized to the intervention received daily messages, either text or voice, reminding them to take their medication. Participants randomized to the control group received usual care. Difference in adherence before and after initiation of the intervention. Using an intent-to-treat analysis, we found that the median adherence rate in the 38 participants randomized to the intervention increased from 53% to 64% (P telecommunication-based reminders linked to data in a personal health record improved adherence with once-daily glaucoma medications. This is an effective method to improve adherence that could realistically be implemented in ophthalmology practices with a minimum amount of effort on the part of the practice or the patient.

  15. Advanced ultrasound probes for medical imaging

    Science.gov (United States)

    Wildes, Douglas G.; Smith, L. Scott

    2012-05-01

    New medical ultrasound probe architectures and materials build upon established 1D phased array technology and provide improved imaging performance and clinical value. Technologies reviewed include 1.25D and 1.5D arrays for elevation slice thickness control; electro-mechanical and 2D array probes for real-time 3D imaging; catheter probes for imaging during minimally-invasive procedures; single-crystal piezoelectric materials for greater frequency bandwidth; and cMUT arrays using silicon MEMS in place of piezo materials.

  16. Transfer representation learning for medical image analysis.

    Science.gov (United States)

    Chuen-Kai Shie; Chung-Hisang Chuang; Chun-Nan Chou; Meng-Hsi Wu; Chang, Edward Y

    2015-08-01

    There are two major challenges to overcome when developing a classifier to perform automatic disease diagnosis. First, the amount of labeled medical data is typically very limited, and a classifier cannot be effectively trained to attain high disease-detection accuracy. Second, medical domain knowledge is required to identify representative features in data for detecting a target disease. Most computer scientists and statisticians do not have such domain knowledge. In this work, we show that employing transfer learning can remedy both problems. We use Otitis Media (OM) to conduct our case study. Instead of using domain knowledge to extract features from labeled OM images, we construct features based on a dataset entirely OM-irrelevant. More specifically, we first learn a codebook in an unsupervised way from 15 million images collected from ImageNet. The codebook gives us what the encoders consider being the fundamental elements of those 15 million images. We then encode OM images using the codebook and obtain a weighting vector for each OM image. Using the resulting weighting vectors as the feature vectors of the OM images, we employ a traditional supervised learning algorithm to train an OM classifier. The achieved detection accuracy is 88.5% (89.63% in sensitivity and 86.9% in specificity), markedly higher than all previous attempts, which relied on domain experts to help extract features.

  17. A virtual laboratory for medical image analysis

    NARCIS (Netherlands)

    Olabarriaga, Sílvia D.; Glatard, Tristan; de Boer, Piter T.

    2010-01-01

    This paper presents the design, implementation, and usage of a virtual laboratory for medical image analysis. It is fully based on the Dutch grid, which is part of the Enabling Grids for E-sciencE (EGEE) production infrastructure and driven by the gLite middleware. The adopted service-oriented

  18. Medical Imaging with Ultrasound: Some Basic Physics.

    Science.gov (United States)

    Gosling, R.

    1989-01-01

    Discussed are medical applications of ultrasound. The physics of the wave nature of ultrasound including its propagation and production, return by the body, spatial and contrast resolution, attenuation, image formation using pulsed echo ultrasound techniques, measurement of velocity and duplex scanning are described. (YP)

  19. Watermarking patient data in encrypted medical images

    Indian Academy of Sciences (India)

    Information can be sent very quickly by the internet. However, it causes the problems of the information securities and multimedia copyright protections. Therefore, network securi- ties protections have become more important topics. Watermarking is an important technology for these topics. Medical images play a significant ...

  20. 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.

  1. Fast fluid registration of medical images

    DEFF Research Database (Denmark)

    Bro-Nielsen, Morten; Gramkow, Claus

    1996-01-01

    This paper offers a new fast algorithm for non-rigid viscous fluid registration of medical images that is at least an order of magnitude faster than the previous method by (Christensen et al., 1994). The core algorithm in the fluid registration method is based on a linear elastic deformation...

  2. Curve Matching with Applications in Medical Imaging

    DEFF Research Database (Denmark)

    Bauer, Martin; Bruveris, Martins; Harms, Philipp

    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...

  3. The semiotics of medical image Segmentation.

    Science.gov (United States)

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

    2018-02-01

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

  4. 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...

  5. 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.

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

    International Nuclear Information System (INIS)

    Kim, Sun Chil; Kim, Jung Min

    2002-01-01

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

  7. Application of automated image analysis to coal petrography

    Science.gov (United States)

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

    1982-01-01

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

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

    Science.gov (United States)

    Sharp, Gregory; Fritscher, Karl D.; Pekar, Vladimir; Peroni, Marta; Shusharina, Nadya; Veeraraghavan, Harini; Yang, Jinzhong

    2014-01-01

    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. PMID:24784366

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

    International Nuclear Information System (INIS)

    Sharp, Gregory; Fritscher, Karl D.; Shusharina, Nadya; Pekar, Vladimir; Peroni, Marta; Veeraraghavan, Harini; Yang, Jinzhong

    2014-01-01

    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

  10. Neural networks: Application to medical imaging

    Science.gov (United States)

    Clarke, Laurence P.

    1994-01-01

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

  11. Microvascular glycocalyx dimension estimated by automated SDF imaging is not related to cardiovascular disease

    NARCIS (Netherlands)

    Amraoui, Fouad; Olde Engberink, Rik H. G.; van Gorp, Jacqueline; Ramdani, Amal; Vogt, Liffert; van den Born, Bert-Jan H.

    2014-01-01

    The EG regulates vascular homeostasis and has anti-atherogenic properties. SDF imaging allows for noninvasive visualization of microvessels and automated estimation of EG dimensions. We aimed to assess whether microcirculatory EG dimension is related to cardiovascular disease. Sublingual EG

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

    OpenAIRE

    Staley, Tim D.; Anderson, Gemma E.

    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 severa...

  13. Interactive measurement system for medical images

    International Nuclear Information System (INIS)

    Akatsuka, T.; Kubo, T.

    1980-01-01

    The information obtained by quantitative reading of medical pictures is very effective for diagnosis. However, high level tasks such as pattern recognition are difficult to be automated completely, hence an interactive system is a viable and economical alternative. The physician traces the contour of the object of interest using a graphics pen attached to a tablet digitizer. From these digitized contours, the computer calculates the area, length, number of objects, etc., and extracts shape features. The system comprises a mini-computer, a graphic tablet and a graphic display. At present it is possible to perform the following tasks interactively: pelvimetry with the help of radiographs, measurement of the dimensions of microorgans, estimation of cardiac parameters from ECG, etc. (Auth.)

  14. 3-D image pre-processing algorithms for improved automated tracing of neuronal arbors.

    Science.gov (United States)

    Narayanaswamy, Arunachalam; Wang, Yu; Roysam, Badrinath

    2011-09-01

    The accuracy and reliability of automated neurite tracing systems is ultimately limited by image quality as reflected in the signal-to-noise ratio, contrast, and image variability. This paper describes a novel combination of image processing methods that operate on images of neurites captured by confocal and widefield microscopy, and produce synthetic images that are better suited to automated tracing. The algorithms are based on the curvelet transform (for denoising curvilinear structures and local orientation estimation), perceptual grouping by scalar voting (for elimination of non-tubular structures and improvement of neurite continuity while preserving branch points), adaptive focus detection, and depth estimation (for handling widefield images without deconvolution). The proposed methods are fast, and capable of handling large images. Their ability to handle images of unlimited size derives from automated tiling of large images along the lateral dimension, and processing of 3-D images one optical slice at a time. Their speed derives in part from the fact that the core computations are formulated in terms of the Fast Fourier Transform (FFT), and in part from parallel computation on multi-core computers. The methods are simple to apply to new images since they require very few adjustable parameters, all of which are intuitive. Examples of pre-processing DIADEM Challenge images are used to illustrate improved automated tracing resulting from our pre-processing methods.

  15. Medical imaging displays and their use in image interpretation.

    Science.gov (United States)

    Kagadis, George C; Walz-Flannigan, Alisa; Krupinski, Elizabeth A; Nagy, Paul G; Katsanos, Konstantinos; Diamantopoulos, Athanasios; Langer, Steve G

    2013-01-01

    The adequate and repeatable performance of the image display system is a key element of information technology platforms in a modern radiology department. However, despite the wide availability of high-end computing platforms and advanced color and gray-scale monitors, the quality and properties of the final displayed medical image may often be inadequate for diagnostic purposes if the displays are not configured and maintained properly. In this article-an expanded version of the Radiological Society of North America educational module "Image Display"-the authors discuss fundamentals of image display hardware, quality control and quality assurance processes for optimal image interpretation settings, and parameters of the viewing environment that influence reader performance. Radiologists, medical physicists, and other allied professionals should strive to understand the role of display technology and proper usage for a quality radiology practice. The display settings and display quality control and quality assurance processes described in this article can help ensure high standards of perceived image quality and image interpretation accuracy.

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

    Science.gov (United States)

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

    2015-03-01

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

  17. Report on Medical Activities for the Automated AFEES Program

    Science.gov (United States)

    1976-03-10

    review of check-list and protocol of the test and actual examinations under direct observation by the physician. In the third phase, the para - medics... Psoriasis 40.18 Tinea cruris 40. 30 Abnormal color or texture 40. 31 Brownish-yellow spots 40. 33 Yellow 40.35 Pallor 40. 37

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

    Directory of Open Access Journals (Sweden)

    Meng Kuan eLin

    2013-07-01

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

  19. MO-FG-303-04: A Smartphone Application for Automated Mechanical Quality Assurance of Medical Accelerators

    International Nuclear Information System (INIS)

    Kim, H; Lee, H; Choi, K; Ye, S

    2015-01-01

    Purpose: The mechanical quality assurance (QA) of medical accelerators consists of a time consuming series of procedures. Since most of the procedures are done manually – e.g., checking gantry rotation angle with the naked eye using a level attached to the gantry –, it is considered to be a process with high potential for human errors. To remove the possibilities of human errors and reduce the procedure duration, we developed a smartphone application for automated mechanical QA. Methods: The preparation for the automated process was done by attaching a smartphone to the gantry facing upward. For the assessments of gantry and collimator angle indications, motion sensors (gyroscope, accelerator, and magnetic field sensor) embedded in the smartphone were used. For the assessments of jaw position indicator, cross-hair centering, and optical distance indicator (ODI), an optical-image processing module using a picture taken by the high-resolution camera embedded in the smartphone was implemented. The application was developed with the Android software development kit (SDK) and OpenCV library. Results: The system accuracies in terms of angle detection error and length detection error were < 0.1° and < 1 mm, respectively. The mean absolute error for gantry and collimator rotation angles were 0.03° and 0.041°, respectively. The mean absolute error for the measured light field size was 0.067 cm. Conclusion: The automated system we developed can be used for the mechanical QA of medical accelerators with proven accuracy. For more convenient use of this application, the wireless communication module is under development. This system has a strong potential for the automation of the other QA procedures such as light/radiation field coincidence and couch translation/rotations

  20. A special designed library for medical imaging applications

    International Nuclear Information System (INIS)

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

    1994-01-01

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

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

    Science.gov (United States)

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

    1996-01-01

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

  2. Data Analysis Strategies in Medical Imaging.

    Science.gov (United States)

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

    2018-03-26

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

  3. 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

  4. HEP technologies to address medical imaging challenges

    CERN Multimedia

    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.

  5. The effect of JPEG compression on automated detection of microaneurysms in retinal images

    Science.gov (United States)

    Cree, M. J.; Jelinek, H. F.

    2008-02-01

    As JPEG compression at source is ubiquitous in retinal imaging, and the block artefacts introduced are known to be of similar size to microaneurysms (an important indicator of diabetic retinopathy) it is prudent to evaluate the effect of JPEG compression on automated detection of retinal pathology. Retinal images were acquired at high quality and then compressed to various lower qualities. An automated microaneurysm detector was run on the retinal images of various qualities of JPEG compression and the ability to predict the presence of diabetic retinopathy based on the detected presence of microaneurysms was evaluated with receiver operating characteristic (ROC) methodology. The negative effect of JPEG compression on automated detection was observed even at levels of compression sometimes used in retinal eye-screening programmes and these may have important clinical implications for deciding on acceptable levels of compression for a fully automated eye-screening programme.

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

    Science.gov (United States)

    Ayache, N

    2016-05-20

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

  7. 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.

  8. 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.

  9. An Automated Self-Learning Quantification System to Identify Visible Areas in Capsule Endoscopy Images.

    Science.gov (United States)

    Hashimoto, Shinichi; Ogihara, Hiroyuki; Suenaga, Masato; Fujita, Yusuke; Terai, Shuji; Hamamoto, Yoshihiko; Sakaida, Isao

    2017-08-01

    Visibility in capsule endoscopic images is presently evaluated through intermittent analysis of frames selected by a physician. It is thus subjective and not quantitative. A method to automatically quantify the visibility on capsule endoscopic images has not been reported. Generally, when designing automated image recognition programs, physicians must provide a training image; this process is called supervised learning. We aimed to develop a novel automated self-learning quantification system to identify visible areas on capsule endoscopic images. The technique was developed using 200 capsule endoscopic images retrospectively selected from each of three patients. The rate of detection of visible areas on capsule endoscopic images between a supervised learning program, using training images labeled by a physician, and our novel automated self-learning program, using unlabeled training images without intervention by a physician, was compared. The rate of detection of visible areas was equivalent for the supervised learning program and for our automatic self-learning program. The visible areas automatically identified by self-learning program correlated to the areas identified by an experienced physician. We developed a novel self-learning automated program to identify visible areas in capsule endoscopic images.

  10. 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...

  11. Deep Learning in Medical Imaging: General Overview

    Science.gov (United States)

    Lee, June-Goo; Jun, Sanghoon; Cho, Young-Won; Lee, Hyunna; Kim, Guk Bae

    2017-01-01

    The artificial neural network (ANN)–a machine learning technique inspired by the human neuronal synapse system–was introduced in the 1950s. However, the ANN was previously limited in its ability to solve actual problems, due to the vanishing gradient and overfitting problems with training of deep architecture, lack of computing power, and primarily the absence of sufficient data to train the computer system. Interest in this concept has lately resurfaced, due to the availability of big data, enhanced computing power with the current graphics processing units, and novel algorithms to train the deep neural network. Recent studies on this technology suggest its potentially to perform better than humans in some visual and auditory recognition tasks, which may portend its applications in medicine and healthcare, especially in medical imaging, in the foreseeable future. This review article offers perspectives on the history, development, and applications of deep learning technology, particularly regarding its applications in medical imaging. PMID:28670152

  12. Deep Learning in Medical Imaging: General Overview.

    Science.gov (United States)

    Lee, June-Goo; Jun, Sanghoon; Cho, Young-Won; Lee, Hyunna; Kim, Guk Bae; Seo, Joon Beom; Kim, Namkug

    2017-01-01

    The artificial neural network (ANN)-a machine learning technique inspired by the human neuronal synapse system-was introduced in the 1950s. However, the ANN was previously limited in its ability to solve actual problems, due to the vanishing gradient and overfitting problems with training of deep architecture, lack of computing power, and primarily the absence of sufficient data to train the computer system. Interest in this concept has lately resurfaced, due to the availability of big data, enhanced computing power with the current graphics processing units, and novel algorithms to train the deep neural network. Recent studies on this technology suggest its potentially to perform better than humans in some visual and auditory recognition tasks, which may portend its applications in medicine and healthcare, especially in medical imaging, in the foreseeable future. This review article offers perspectives on the history, development, and applications of deep learning technology, particularly regarding its applications in medical imaging.

  13. Deep learning in medical imaging: General overview

    Energy Technology Data Exchange (ETDEWEB)

    Lee, June Goo; Jun, Sang Hoon; Cho, Young Won; Lee, Hyun Na; KIm, Guk Bae; Seo, Joon Beom; Kim, Nam Kug [University of Ulsan College of Medicine, Asan Medical Center, Seoul (Korea, Republic of)

    2017-08-01

    The artificial neural network (ANN)–a machine learning technique inspired by the human neuronal synapse system–was introduced in the 1950s. However, the ANN was previously limited in its ability to solve actual problems, due to the vanishing gradient and overfitting problems with training of deep architecture, lack of computing power, and primarily the absence of sufficient data to train the computer system. Interest in this concept has lately resurfaced, due to the availability of big data, enhanced computing power with the current graphics processing units, and novel algorithms to train the deep neural network. Recent studies on this technology suggest its potentially to perform better than humans in some visual and auditory recognition tasks, which may portend its applications in medicine and health care, especially in medical imaging, in the foreseeable future. This review article offers perspectives on the history, development, and applications of deep learning technology, particularly regarding its applications in medical imaging.

  14. Deep learning in medical imaging: General overview

    International Nuclear Information System (INIS)

    Lee, June Goo; Jun, Sang Hoon; Cho, Young Won; Lee, Hyun Na; KIm, Guk Bae; Seo, Joon Beom; Kim, Nam Kug

    2017-01-01

    The artificial neural network (ANN)–a machine learning technique inspired by the human neuronal synapse system–was introduced in the 1950s. However, the ANN was previously limited in its ability to solve actual problems, due to the vanishing gradient and overfitting problems with training of deep architecture, lack of computing power, and primarily the absence of sufficient data to train the computer system. Interest in this concept has lately resurfaced, due to the availability of big data, enhanced computing power with the current graphics processing units, and novel algorithms to train the deep neural network. Recent studies on this technology suggest its potentially to perform better than humans in some visual and auditory recognition tasks, which may portend its applications in medicine and health care, especially in medical imaging, in the foreseeable future. This review article offers perspectives on the history, development, and applications of deep learning technology, particularly regarding its applications in medical imaging

  15. Active learning: a step towards automating medical concept extraction.

    Science.gov (United States)

    Kholghi, Mahnoosh; Sitbon, Laurianne; Zuccon, Guido; Nguyen, Anthony

    2016-03-01

    This paper presents an automatic, active learning-based system for the extraction of medical concepts from clinical free-text reports. Specifically, (1) the contribution of active learning in reducing the annotation effort and (2) the robustness of incremental active learning framework across different selection criteria and data sets are determined. The comparative performance of an active learning framework and a fully supervised approach were investigated to study how active learning reduces the annotation effort while achieving the same effectiveness as a supervised approach. Conditional random fields as the supervised method, and least confidence and information density as 2 selection criteria for active learning framework were used. The effect of incremental learning vs standard learning on the robustness of the models within the active learning framework with different selection criteria was also investigated. The following 2 clinical data sets were used for evaluation: the Informatics for Integrating Biology and the Bedside/Veteran Affairs (i2b2/VA) 2010 natural language processing challenge and the Shared Annotated Resources/Conference and Labs of the Evaluation Forum (ShARe/CLEF) 2013 eHealth Evaluation Lab. The annotation effort saved by active learning to achieve the same effectiveness as supervised learning is up to 77%, 57%, and 46% of the total number of sequences, tokens, and concepts, respectively. Compared with the random sampling baseline, the saving is at least doubled. Incremental active learning is a promising approach for building effective and robust medical concept extraction models while significantly reducing the burden of manual annotation. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  16. 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.

  17. A recommender system for medical imaging diagnostic.

    Science.gov (United States)

    Monteiro, Eriksson; Valente, Frederico; Costa, Carlos; Oliveira, José Luís

    2015-01-01

    The large volume of data captured daily in healthcare institutions is opening new and great perspectives about the best ways to use it towards improving clinical practice. In this paper we present a context-based recommender system to support medical imaging diagnostic. The system relies on data mining and context-based retrieval techniques to automatically lookup for relevant information that may help physicians in the diagnostic decision.

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

    DEFF Research Database (Denmark)

    Gutte, Henrik; Jakobsson, David; Olofsson, Fredrik

    2007-01-01

    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...... cancer. METHODS: A total of 87 patients who underwent PET/CT examinations due to suspected lung cancer comprised the training group. The test group consisted of PET/CT images from 49 patients suspected with lung cancer. The consensus interpretations by two experienced physicians were used as the 'gold......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...

  19. 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

    2015-11-23

    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.

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

    DEFF Research Database (Denmark)

    Larsen, Anna Bira; Haugbølle, Lotte Stig

    2007-01-01

    BACKGROUND: It has been assumed that a new health technology, automated dose-dispensing (ADD), would result in benefits for medication users, including increased compliance, enhanced medication understanding, and improved safety. However, it was legislators and health professionals who pinpointed...... the assumed user benefits. Neither Danish nor international studies dealt with users' perspective on ADD in general or with respect to the pinpointed benefits, and thus exploration was needed. OBJECTIVES: The objective of this article is to respond to the following research question: How does ADD affect users...

  1. Interactive segmentation framework of the Medical Imaging Interaction Toolkit.

    Science.gov (United States)

    Maleike, D; Nolden, M; Meinzer, H-P; Wolf, I

    2009-10-01

    Interactive methods are indispensable for real world applications of segmentation in medicine, at least to allow for convenient and fast verification and correction of automated techniques. Besides traditional interactive tasks such as adding or removing parts of a segmentation, adjustment of contours or the placement of seed points, the relatively recent Graph Cut and Random Walker segmentation methods demonstrate an interest in advanced interactive strategies for segmentation. Though the value of toolkits and extensible applications is generally accepted for the development of new segmentation algorithms, the topic of interactive segmentation applications is rarely addressed by current toolkits and applications. In this paper, we present the extension of the Medical Imaging Interaction Toolkit (MITK) with a framework for the development of interactive applications for image segmentation. The framework provides a clear structure for the development of new applications and offers a plugin mechanism to easily extend existing applications with additional segmentation tools. In addition, the framework supports shape-based interpolation and multi-level undo/redo of modifications to binary images. To demonstrate the value of the framework, we also present a free, open-source application named InteractiveSegmentation for manual segmentation of medical images (including 3D+t), which is built based on the extended MITK framework. The application includes several features to effectively support manual segmentation, which are not found in comparable freely available applications. InteractiveSegmentation is fully developed and successfully and regularly used in several projects. Using the plugin mechanism, the application enables developers of new algorithms to begin algorithmic work more quickly.

  2. Medical Imaging for the Tracking of Micromotors.

    Science.gov (United States)

    Vilela, Diana; Cossío, Unai; Parmar, Jemish; Martínez-Villacorta, Angel M; Gómez-Vallejo, Vanessa; Llop, Jordi; Sánchez, Samuel

    2018-02-27

    Micro/nanomotors are useful tools for several biomedical applications, including targeted drug delivery and minimally invasive microsurgeries. However, major challenges such as in vivo imaging need to be addressed before they can be safely applied on a living body. Here, we show that positron emission tomography (PET), a molecular imaging technique widely used in medical imaging, can also be used to track a large population of tubular Au/PEDOT/Pt micromotors. Chemisorption of an iodine isotope onto the micromotor's Au surface rendered them detectable by PET, and we could track their movements in a tubular phantom over time frames of up to 15 min. In a second set of experiments, micromotors and the bubbles released during self-propulsion were optically tracked by video imaging and bright-field microscopy. The results from direct optical tracking agreed with those from PET tracking, demonstrating that PET is a suitable technique for the imaging of large populations of active micromotors in opaque environments, thus opening opportunities for the use of this mature imaging technology for the in vivo localization of artificial swimmers.

  3. 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.

  4. Development of technology for medical image fusion

    International Nuclear Information System (INIS)

    Yamaguchi, Takashi; Amano, Daizou

    2012-01-01

    With entry into a field of medical diagnosis in mind, we have developed positron emission tomography (PET) ''MIP-100'' system, of which spatial resolution is far higher than the conventional one, using semiconductor detectors for preclinical imaging for small animals. In response to the recently increasing market demand to fuse functional images by PET and anatomical ones by CT or MRI, we have been developing software to implement image fusion function that enhances marketability of the PET Camera. This paper describes the method of fusing with high accuracy the PET images and anatomical ones by CT system. It also explains that a computer simulation proved the image overlay accuracy to be ±0.3 mm as a result of the development, and that effectiveness of the developed software is confirmed in case of experiment to obtain measured data. Achieving such high accuracy as ±0.3 mm by the software allows us to present fusion images with high resolution (<0.6 mm) without degrading the spatial resolution (<0.5 mm) of the PET system using semiconductor detectors. (author)

  5. Distributed deep learning networks among institutions for medical imaging.

    Science.gov (United States)

    Chang, Ken; Balachandar, Niranjan; Lam, Carson; Yi, Darvin; Brown, James; Beers, Andrew; Rosen, Bruce; Rubin, Daniel L; Kalpathy-Cramer, Jayashree

    2018-03-29

    Deep learning has become a promising approach for automated support for clinical diagnosis. When medical data samples are limited, collaboration among multiple institutions is necessary to achieve high algorithm performance. However, sharing patient data often has limitations due to technical, legal, or ethical concerns. In this study, we propose methods of distributing deep learning models as an attractive alternative to sharing patient data. We simulate the distribution of deep learning models across 4 institutions using various training heuristics and compare the results with a deep learning model trained on centrally hosted patient data. The training heuristics investigated include ensembling single institution models, single weight transfer, and cyclical weight transfer. We evaluated these approaches for image classification in 3 independent image collections (retinal fundus photos, mammography, and ImageNet). We find that cyclical weight transfer resulted in a performance that was comparable to that of centrally hosted patient data. We also found that there is an improvement in the performance of cyclical weight transfer heuristic with a high frequency of weight transfer. We show that distributing deep learning models is an effective alternative to sharing patient data. This finding has implications for any collaborative deep learning study.

  6. Medical imaging informatics simulators: a tutorial.

    Science.gov (United States)

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

    2014-05-01

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

  7. Medical imaging and alternative health care organizations

    International Nuclear Information System (INIS)

    Levy, E.

    1987-01-01

    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 [fr

  8. The quest for standards in medical imaging

    International Nuclear Information System (INIS)

    Gibaud, Bernard

    2011-01-01

    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.

  9. Radically Reducing Radiation Exposure during Routine Medical Imaging

    Science.gov (United States)

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

  10. [Impact of an automated dispensing system for medical devices in cardiac surgery department].

    Science.gov (United States)

    Clou, E; Dompnier, M; Kably, B; Leplay, C; Poupon, E; Archer, V; Paul, M

    2018-01-01

    To secure medical devices' management, the implementation of automated dispensing system in surgical service has been realized. The objective of this study was to evaluate security, organizational and economic impact of installing automated dispensing system for medical devices (ASDM). The implementation took place in a cardiac surgery department. Security impact was assessed by comparing traceability rate of implantable medical devices one year before and one year after installation. Questionnaire on nurses' perception and satisfaction completed this survey. Resupplying costs, stocks' evolution and investments for the implementation of ASDM were the subject of cost-benefit study. After one year, traceability rate is excellent (100%). Nursing staffs were satisfied with 87.5% by this new system. The introduction of ASDM allowed a qualitative and quantitative decrease in stocks, with a reduction of 30% for purchased medical devices and 15% for implantable medical devices in deposit-consignment. Cost-benefit analysis shows a rapid return on investment. Real stock decrease (purchased medical devices) is equivalent to 46.6% of investment. Implementation of ASDM allows to secure storage and dispensing of medical devices. This system has also an important economic impact and appreciated by users. Copyright © 2017 Académie Nationale de Pharmacie. Published by Elsevier Masson SAS. All rights reserved.

  11. CNN-based Segmentation of Medical Imaging Data

    OpenAIRE

    Kayalibay, Baris; Jensen, Grady; van der Smagt, Patrick

    2017-01-01

    Convolutional neural networks have been applied to a wide variety of computer vision tasks. Recent advances in semantic segmentation have enabled their application to medical image segmentation. While most CNNs use two-dimensional kernels, recent CNN-based publications on medical image segmentation featured three-dimensional kernels, allowing full access to the three-dimensional structure of medical images. Though closely related to semantic segmentation, medical image segmentation includes s...

  12. A study for watermark methods appropriate to medical images.

    Science.gov (United States)

    Cho, Y; Ahn, B; Kim, J S; Kim, I Y; Kim, S I

    2001-06-01

    The network system, including the picture archiving and communication system (PACS), is essential in hospital and medical imaging fields these days. Many medical images are accessed and processed on the web, as well as in PACS. Therefore, any possible accidents caused by the illegal modification of medical images must be prevented. Digital image watermark techniques have been proposed as a method to protect against illegal copying or modification of copyrighted material. Invisible signatures made by a digital image watermarking technique can be a solution to these problems. However, medical images have some different characteristics from normal digital images in that one must not corrupt the information contained in the original medical images. In this study, we suggest modified watermark methods appropriate for medical image processing and communication system that prevent clinically important data contained in original images from being corrupted.

  13. Lossy image compression for digital medical imaging systems

    Science.gov (United States)

    Wilhelm, Paul S.; Haynor, David R.; Kim, Yongmin; Nelson, Alan C.; Riskin, Eve A.

    1990-07-01

    Image compression at rates of 10:1 or greater could make PACS much more responsive and economically attractive. This paper describes a protocol for subjective and objective evaluation of the fidelity of compressed/decompressed images to the originals and presents the results ofits application to four representative and promising compression methods. The methods examined are predictive pruned tree-structured vector quantization, fractal compression, the discrete cosine transform with equal weighting of block bit allocation, and the discrete cosine transform with human visual system weighting of block bit allocation. Vector quantization is theoretically capable of producing the best compressed images, but has proven to be difficult to effectively implement. It has the advantage that it can reconstruct images quickly through a simple lookup table. Disadvantages are that codebook training is required, the method is computationally intensive, and achieving the optimum performance would require prohibitively long vector dimensions. Fractal compression is a relatively new compression technique, but has produced satisfactory results while being computationally simple. It is fast at both image compression and image reconstruction. Discrete cosine iransform techniques reproduce images well, but have traditionally been hampered by the need for intensive computing to compress and decompress images. A protocol was developed for side-by-side observer comparison of reconstructed images with originals. Three 1024 X 1024 CR (Computed Radiography) images and two 512 X 512 X-ray CT images were viewed at six bit rates (0.2, 0.4, 0.6, 0.9, 1.2, and 1.5 bpp for CR, and 1.0, 1.3, 1.6, 1.9, 2.2, 2.5 bpp for X-ray CT) by nine radiologists at the University of Washington Medical Center. The CR images were viewed on a Pixar II Megascan (2560 X 2048) monitor and the CT images on a Sony (1280 X 1024) monitor. The radiologists' subjective evaluations of image fidelity were compared to

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

    Science.gov (United States)

    Clement, Alain; Vigouroux, Bertnand

    2003-04-01

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

  15. Fluorescence In Situ Hybridization (FISH Signal Analysis Using Automated Generated Projection Images

    Directory of Open Access Journals (Sweden)

    Xingwei Wang

    2012-01-01

    Full Text Available Fluorescence in situ hybridization (FISH tests provide promising molecular imaging biomarkers to more accurately and reliably detect and diagnose cancers and genetic disorders. Since current manual FISH signal analysis is low-efficient and inconsistent, which limits its clinical utility, developing automated FISH image scanning systems and computer-aided detection (CAD schemes has been attracting research interests. To acquire high-resolution FISH images in a multi-spectral scanning mode, a huge amount of image data with the stack of the multiple three-dimensional (3-D image slices is generated from a single specimen. Automated preprocessing these scanned images to eliminate the non-useful and redundant data is important to make the automated FISH tests acceptable in clinical applications. In this study, a dual-detector fluorescence image scanning system was applied to scan four specimen slides with FISH-probed chromosome X. A CAD scheme was developed to detect analyzable interphase cells and map the multiple imaging slices recorded FISH-probed signals into the 2-D projection images. CAD scheme was then applied to each projection image to detect analyzable interphase cells using an adaptive multiple-threshold algorithm, identify FISH-probed signals using a top-hat transform, and compute the ratios between the normal and abnormal cells. To assess CAD performance, the FISH-probed signals were also independently visually detected by an observer. The Kappa coefficients for agreement between CAD and observer ranged from 0.69 to 1.0 in detecting/counting FISH signal spots in four testing samples. The study demonstrated the feasibility of automated FISH signal analysis that applying a CAD scheme to the automated generated 2-D projection images.

  16. Automated Segmentation of Kidneys from MR Images in Patients with Autosomal Dominant Polycystic Kidney Disease.

    Science.gov (United States)

    Kim, Youngwoo; Ge, Yinghui; Tao, Cheng; Zhu, Jianbing; Chapman, Arlene B; Torres, Vicente E; Yu, Alan S L; Mrug, Michal; Bennett, William M; Flessner, Michael F; Landsittel, Doug P; Bae, Kyongtae T

    2016-04-07

    Our study developed a fully automated method for segmentation and volumetric measurements of kidneys from magnetic resonance images in patients with autosomal dominant polycystic kidney disease and assessed the performance of the automated method with the reference manual segmentation method. Study patients were selected from the Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease. At the enrollment of the Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease Study in 2000, patients with autosomal dominant polycystic kidney disease were between 15 and 46 years of age with relatively preserved GFRs. Our fully automated segmentation method was on the basis of a spatial prior probability map of the location of kidneys in abdominal magnetic resonance images and regional mapping with total variation regularization and propagated shape constraints that were formulated into a level set framework. T2-weighted magnetic resonance image sets of 120 kidneys were selected from 60 patients with autosomal dominant polycystic kidney disease and divided into the training and test datasets. The performance of the automated method in reference to the manual method was assessed by means of two metrics: Dice similarity coefficient and intraclass correlation coefficient of segmented kidney volume. The training and test sets were swapped for crossvalidation and reanalyzed. Successful segmentation of kidneys was performed with the automated method in all test patients. The segmented kidney volumes ranged from 177.2 to 2634 ml (mean, 885.4±569.7 ml). The mean Dice similarity coefficient ±SD between the automated and manual methods was 0.88±0.08. The mean correlation coefficient between the two segmentation methods for the segmented volume measurements was 0.97 (Pkidneys from abdominal magnetic resonance images in patients with autosomal dominant polycystic kidney disease with varying kidney volumes. The performance of the automated method was in good

  17. 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

  18. Cerenkov luminescence imaging of medical isotopes.

    Science.gov (United States)

    Ruggiero, Alessandro; Holland, Jason P; Lewis, Jason S; Grimm, Jan

    2010-07-01

    The development of novel multimodality imaging agents and techniques represents the current frontier of research in the field of medical imaging science. However, the combination of nuclear tomography with optical techniques has yet to be established. Here, we report the use of the inherent optical emissions from the decay of radiopharmaceuticals for Cerenkov luminescence imaging (CLI) of tumors in vivo and correlate the results with those obtained from concordant immuno-PET studies. In vitro phantom studies were used to validate the visible light emission observed from a range of radionuclides including the positron emitters (18)F, (64)Cu, (89)Zr, and (124)I; beta-emitter (131)I; and alpha-particle emitter (225)Ac for potential use in CLI. The novel radiolabeled monoclonal antibody (89)Zr-desferrioxamine B [DFO]-J591 for immuno-PET of prostate-specific membrane antigen (PSMA) expression was used to coregister and correlate the CLI signal observed with the immuno-PET images and biodistribution studies. Phantom studies confirmed that Cerenkov radiation can be observed from a range of positron-, beta-, and alpha-emitting radionuclides using standard optical imaging devices. The change in light emission intensity versus time was concordant with radionuclide decay and was also found to correlate linearly with both the activity concentration and the measured PET signal (percentage injected dose per gram). In vivo studies conducted in male severe combined immune deficient mice bearing PSMA-positive, subcutaneous LNCaP tumors demonstrated that tumor-specific uptake of (89)Zr-DFO-J591 could be visualized by both immuno-PET and CLI. Optical and immuno-PET signal intensities were found to increase over time from 24 to 96 h, and biodistribution studies were found to correlate well with both imaging modalities. These studies represent the first, to our knowledge, quantitative assessment of CLI for measuring radiotracer uptake in vivo. Many radionuclides common to both nuclear

  19. X-ray detectors in medical imaging

    International Nuclear Information System (INIS)

    Spahn, Martin

    2013-01-01

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

  20. Integrating two spectral imaging systems in an automated mineralogy application

    CSIR Research Space (South Africa)

    Harris, D

    2009-11-01

    Full Text Available A system for the automated analysis and sorting of mineral samples has been developed to assist in the concentration of heavy mineral samples in the diamond exploration process. These samples consist of irregularly shaped mineral grains ranging from...

  1. 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

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

    International Nuclear Information System (INIS)

    Karaçalı, Bilge; Vamvakidou, Alexandra P; Tözeren, Aydın

    2007-01-01

    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

  3. Software for medical image based phantom modelling

    International Nuclear Information System (INIS)

    Possani, R.G.; Massicano, F.; Coelho, T.S.; Yoriyaz, H.

    2011-01-01

    Latest treatment planning systems depends strongly on CT images, so the tendency is that the dosimetry procedures in nuclear medicine therapy be also based on images, such as magnetic resonance imaging (MRI) or computed tomography (CT), to extract anatomical and histological information, as well as, functional imaging or activities map as PET or SPECT. This information associated with the simulation of radiation transport software is used to estimate internal dose in patients undergoing treatment in nuclear medicine. This work aims to re-engineer the software SCMS, which is an interface software between the Monte Carlo code MCNP, and the medical images, that carry information from the patient in treatment. In other words, the necessary information contained in the images are interpreted and presented in a specific format to the Monte Carlo MCNP code to perform the simulation of radiation transport. Therefore, the user does not need to understand complex process of inputting data on MCNP, as the SCMS is responsible for automatically constructing anatomical data from the patient, as well as the radioactive source data. The SCMS was originally developed in Fortran- 77. In this work it was rewritten in an object-oriented language (JAVA). New features and data options have also been incorporated into the software. Thus, the new software has a number of improvements, such as intuitive GUI and a menu for the selection of the energy spectra correspondent to a specific radioisotope stored in a XML data bank. The new version also supports new materials and the user can specify an image region of interest for the calculation of absorbed dose. (author)

  4. How automated image analysis techniques help scientists in species identification and classification?

    Science.gov (United States)

    Yousef Kalafi, Elham; Town, Christopher; Kaur Dhillon, Sarinder

    2017-09-04

    Identification of taxonomy at a specific level is time consuming and reliant upon expert ecologists. Hence the demand for automated species identification increased over the last two decades. Automation of data classification is primarily focussed on images, incorporating and analysing image data has recently become easier due to developments in computational technology. Research efforts in identification of species include specimens' image processing, extraction of identical features, followed by classifying them into correct categories. In this paper, we discuss recent automated species identification systems, categorizing and evaluating their methods. We reviewed and compared different methods in step by step scheme of automated identification and classification systems of species images. The selection of methods is influenced by many variables such as level of classification, number of training data and complexity of images. The aim of writing this paper is to provide researchers and scientists an extensive background study on work related to automated species identification, focusing on pattern recognition techniques in building such systems for biodiversity studies.

  5. Development of 3-D Medical Image VIsualization System

    African Journals Online (AJOL)

    User

    available in adequate numbers to hospitals. KEYWORDS: Synthetic holography, 3-D Imaging, Holographic Video, Video Signal Processing,. Stream Processing, FPGA. 1. INTRODUCTION. 1.1 3-D Medical Imaging. The visualization of medical image models such as MRI, CAT, PET and X-ray images usually requires an ...

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

    International Nuclear Information System (INIS)

    Chang Icheng; Lue Kunhan; Hsieh Hungjen; Liu Shuhsin; Kao, Chinhao K.

    2011-01-01

    6-[ 18 F]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)

  7. A semi-automated image analysis procedure for in situ plankton imaging systems.

    Directory of Open Access Journals (Sweden)

    Hongsheng Bi

    Full Text Available Plankton imaging systems are capable of providing fine-scale observations that enhance our understanding of key physical and biological processes. However, processing the large volumes of data collected by imaging systems remains a major obstacle for their employment, and existing approaches are designed either for images acquired under laboratory controlled conditions or within clear waters. In the present study, we developed a semi-automated approach to analyze plankton taxa from images acquired by the ZOOplankton VISualization (ZOOVIS system within turbid estuarine waters, in Chesapeake Bay. When compared to images under laboratory controlled conditions or clear waters, images from highly turbid waters are often of relatively low quality and more variable, due to the large amount of objects and nonlinear illumination within each image. We first customized a segmentation procedure to locate objects within each image and extracted them for classification. A maximally stable extremal regions algorithm was applied to segment large gelatinous zooplankton and an adaptive threshold approach was developed to segment small organisms, such as copepods. Unlike the existing approaches for images acquired from laboratory, controlled conditions or clear waters, the target objects are often the majority class, and the classification can be treated as a multi-class classification problem. We customized a two-level hierarchical classification procedure using support vector machines to classify the target objects ( 95%. First, histograms of oriented gradients feature descriptors were constructed for the segmented objects. In the first step all non-target and target objects were classified into different groups: arrow-like, copepod-like, and gelatinous zooplankton. Each object was passed to a group-specific classifier to remove most non-target objects. After the object was classified, an expert or non-expert then manually removed the non-target objects that

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

    DEFF Research Database (Denmark)

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

    2016-01-01

    An algorithm for image matching of multi-sensor and multi-temporal satellite images is developed. The method is based on the SIFT feature detector proposed by Lowe in (Lowe, 1999). First, SIFT feature points are detected independently in two images (reference and sensed image). The features...

  9. Using the electronic medical record to identify community-acquired pneumonia: toward a replicable automated strategy.

    Directory of Open Access Journals (Sweden)

    Sylvain DeLisle

    Full Text Available Timely information about disease severity can be central to the detection and management of outbreaks of acute respiratory infections (ARI, including influenza. We asked if two resources: 1 free text, and 2 structured data from an electronic medical record (EMR could complement each other to identify patients with pneumonia, an ARI severity landmark.A manual EMR review of 2747 outpatient ARI visits with associated chest imaging identified x-ray reports that could support the diagnosis of pneumonia (kappa score  = 0.88 (95% CI 0.82∶0.93, along with attendant cases with Possible Pneumonia (adds either cough, sputum, fever/chills/night sweats, dyspnea or pleuritic chest pain or with Pneumonia-in-Plan (adds pneumonia stated as a likely diagnosis by the provider. The x-ray reports served as a reference to develop a text classifier using machine-learning software that did not require custom coding. To identify pneumonia cases, the classifier was combined with EMR-based structured data and with text analyses aimed at ARI symptoms in clinical notes.370 reference cases with Possible Pneumonia and 250 with Pneumonia-in-Plan were identified. The x-ray report text classifier increased the positive predictive value of otherwise identical EMR-based case-detection algorithms by 20-70%, while retaining sensitivities of 58-75%. These performance gains were independent of the case definitions and of whether patients were admitted to the hospital or sent home. Text analyses seeking ARI symptoms in clinical notes did not add further value.Specialized software development is not required for automated text analyses to help identify pneumonia patients. These results begin to map an efficient, replicable strategy through which EMR data can be used to stratify ARI severity.

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

    International Nuclear Information System (INIS)

    Kuranishi, Makoto; Kumagai, Michitomo; Shintani, Mitsuo

    2000-01-01

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

  11. 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.)

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

    Directory of Open Access Journals (Sweden)

    Mohendra Roy

    2016-05-01

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

  13. Gestalt descriptions embodiments and medical image interpretation

    DEFF Research Database (Denmark)

    Friis, Jan Kyrre Berg Olsen

    2017-01-01

    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 visual perception. My argument is that biology, society and instruments constitute unique individual ontologies influencing specialist readings of the technological output, in other words, putting limits on the “truth-to-nature” relation, which is so much sought for in science....

  14. Fast histogram equalization for medical image enhancement.

    Science.gov (United States)

    Wang, Qian; Chen, Liya; Shen, Dinggang

    2008-01-01

    To overcome the problem that the histogram equalization can fail for discrete images, a local-mean based strict pixel ordering method has been proposed recently, although it is unpractical for 3D medical image enhancement due to its complex computation. In this paper, a novel histogram mapping method is proposed. It uses a fast local feature generation technique to establish a combined histogram that represents voxels' local means as well as grey levels. Different sections of the combined histogram, separated by individual peaks, are independently mapped into the target histogram scale under the constraint that the final overall histogram should be as uniform as possible. By using this method, the speed of histogram equalization is dramatically improved, and the satisfactory enhancement results are also achieved.

  15. Medical imaging projects meet at CERN

    CERN Multimedia

    CERN Bulletin

    2013-01-01

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

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

    Science.gov (United States)

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

    2013-01-01

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

  17. Automated Melanoma Recognition in Dermoscopy Images via Very Deep Residual Networks.

    Science.gov (United States)

    Yu, Lequan; Chen, Hao; Dou, Qi; Qin, Jing; Heng, Pheng-Ann

    2017-04-01

    Automated melanoma recognition in dermoscopy images is a very challenging task due to the low contrast of skin lesions, the huge intraclass variation of melanomas, the high degree of visual similarity between melanoma and non-melanoma lesions, and the existence of many artifacts in the image. In order to meet these challenges, we propose a novel method for melanoma recognition by leveraging very deep convolutional neural networks (CNNs). Compared with existing methods employing either low-level hand-crafted features or CNNs with shallower architectures, our substantially deeper networks (more than 50 layers) can acquire richer and more discriminative features for more accurate recognition. To take full advantage of very deep networks, we propose a set of schemes to ensure effective training and learning under limited training data. First, we apply the residual learning to cope with the degradation and overfitting problems when a network goes deeper. This technique can ensure that our networks benefit from the performance gains achieved by increasing network depth. Then, we construct a fully convolutional residual network (FCRN) for accurate skin lesion segmentation, and further enhance its capability by incorporating a multi-scale contextual information integration scheme. Finally, we seamlessly integrate the proposed FCRN (for segmentation) and other very deep residual networks (for classification) to form a two-stage framework. This framework enables the classification network to extract more representative and specific features based on segmented results instead of the whole dermoscopy images, further alleviating the insufficiency of training data. The proposed framework is extensively evaluated on ISBI 2016 Skin Lesion Analysis Towards Melanoma Detection Challenge dataset. Experimental results demonstrate the significant performance gains of the proposed framework, ranking the first in classification and the second in segmentation among 25 teams and 28 teams

  18. Identification and red blood cell automated counting from blood smear images using computer-aided system.

    Science.gov (United States)

    Acharya, Vasundhara; Kumar, Preetham

    2018-03-01

    Red blood cell count plays a vital role in identifying the overall health of the patient. Hospitals use the hemocytometer to count the blood cells. Conventional method of placing the smear under microscope and counting the cells manually lead to erroneous results, and medical laboratory technicians are put under stress. A computer-aided system will help to attain precise results in less amount of time. This research work proposes an image-processing technique for counting the number of red blood cells. It aims to examine and process the blood smear image, in order to support the counting of red blood cells and identify the number of normal and abnormal cells in the image automatically. K-medoids algorithm which is robust to external noise is used to extract the WBCs from the image. Granulometric analysis is used to separate the red blood cells from the white blood cells. The red blood cells obtained are counted using the labeling algorithm and circular Hough transform. The radius range for the circle-drawing algorithm is estimated by computing the distance of the pixels from the boundary which automates the entire algorithm. A comparison is done between the counts obtained using the labeling algorithm and circular Hough transform. Results of the work showed that circular Hough transform was more accurate in counting the red blood cells than the labeling algorithm as it was successful in identifying even the overlapping cells. The work also intends to compare the results of cell count done using the proposed methodology and manual approach. The work is designed to address all the drawbacks of the previous research work. The research work can be extended to extract various texture and shape features of abnormal cells identified so that diseases like anemia of inflammation and chronic disease can be detected at the earliest.

  19. Comparison of the automated evaluation of phantom mama in digital and digitalized images

    International Nuclear Information System (INIS)

    Santana, Priscila do Carmo

    2011-01-01

    Mammography is an essential tool for diagnosis and early detection of breast cancer if it is provided as a very good quality service. The process of evaluating the quality of radiographic images in general, and mammography in particular, can be much more accurate, practical and fast with the help of computer analysis tools. This work compare the automated methodology for the evaluation of scanned digital images the phantom mama. By applied the DIP method techniques was possible determine geometrical and radiometric images evaluated. The evaluated parameters include circular details of low contrast, contrast ratio, spatial resolution, tumor masses, optical density and background in Phantom Mama scanned and digitized images. The both results of images were evaluated. Through this comparison was possible to demonstrate that this automated methodology is presented as a promising alternative for the reduction or elimination of subjectivity in both types of images, but the Phantom Mama present insufficient parameters for spatial resolution evaluation. (author)

  20. 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.

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

    International Nuclear Information System (INIS)

    Miles, K.A.

    2005-01-01

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

  2. Medical image diagnosis of liver cancer using artificial intelligence

    International Nuclear Information System (INIS)

    Kondo, Tadashi; Ueno, Junji; Takao, Shoichiro

    2010-01-01

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

  3. 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. Copyright © 2013 Elsevier Ltd. All rights reserved.

  4. 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.

  5. 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. Copyright © 2016 Elsevier Ltd. All rights reserved.

  6. Automated three-dimensional analysis of particle measurements using an optical profilometer and image analysis software.

    Science.gov (United States)

    Bullman, V

    2003-07-01

    The automated collection of topographic images from an optical profilometer coupled with existing image analysis software offers the unique ability to quantify three-dimensional particle morphology. Optional software available with most optical profilers permits automated collection of adjacent topographic images of particles dispersed onto a suitable substrate. Particles are recognized in the image as a set of continuous pixels with grey-level values above the grey level assigned to the substrate, whereas particle height or thickness is represented in the numerical differences between these grey levels. These images are loaded into remote image analysis software where macros automate image processing, and then distinguish particles for feature analysis, including standard two-dimensional measurements (e.g. projected area, length, width, aspect ratios) and third-dimensional measurements (e.g. maximum height, mean height). Feature measurements from each calibrated image are automatically added to cumulative databases and exported to a commercial spreadsheet or statistical program for further data processing and presentation. An example is given that demonstrates the superiority of quantitative three-dimensional measurements by optical profilometry and image analysis in comparison with conventional two-dimensional measurements for the characterization of pharmaceutical powders with plate-like particles.

  7. Diagnostic reference levels in medical imaging

    International Nuclear Information System (INIS)

    Rosenstein, M.

    2001-01-01

    The paper proposes additional advice to national or local authorities and the clinical community on the application of diagnostic reference levels as a practical tool to manage radiation doses to patients in diagnostic radiology and nuclear medicine. A survey was made of the various approaches that have been taken by authoritative bodies to establish diagnostic reference levels for medical imaging tasks. There are a variety of ways to implement the idea of diagnostic reference levels, depending on the medical imaging task of interest, the national or local state of practice and the national or local preferences for technical implementation. The existing International Commission on Radiological Protection (ICRP) guidance is reviewed, the survey information is summarized, a set of unifying principles is espoused and a statement of additional advice that has been proposed to ICRP Committee 3 is presented. The proposed advice would meet a need for a unifying set of principles to provide a framework for diagnostic reference levels but would allow flexibility in their selection and use. While some illustrative examples are given, the proposed advice does not specify the specific quantities to be used, the numerical values to be set for the quantities or the technical details of how national or local authorities should implement diagnostic reference levels. (author)

  8. Computational Intelligence for Medical Imaging Simulations.

    Science.gov (United States)

    Chang, Victor

    2017-11-25

    This paper describes how to simulate medical imaging by computational intelligence to explore areas that cannot be easily achieved by traditional ways, including genes and proteins simulations related to cancer development and immunity. This paper has presented simulations and virtual inspections of BIRC3, BIRC6, CCL4, KLKB1 and CYP2A6 with their outputs and explanations, as well as brain segment intensity due to dancing. Our proposed MapReduce framework with the fusion algorithm can simulate medical imaging. The concept is very similar to the digital surface theories to simulate how biological units can get together to form bigger units, until the formation of the entire unit of biological subject. The M-Fusion and M-Update function by the fusion algorithm can achieve a good performance evaluation which can process and visualize up to 40 GB of data within 600 s. We conclude that computational intelligence can provide effective and efficient healthcare research offered by simulations and visualization.

  9. Contributions to HEVC Prediction for Medical Image Compression

    OpenAIRE

    Guarda, André Filipe Rodrigues

    2016-01-01

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

  10. Microscopic images dataset for automation of RBCs counting

    Directory of Open Access Journals (Sweden)

    Sherif Abbas

    2015-12-01

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

  11. The present and future of medical imaging physics

    International Nuclear Information System (INIS)

    Bao Shanglian; Zhang Huailing; Huang Feizeng

    2004-01-01

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

  12. Machine Learning Interface for Medical Image Analysis.

    Science.gov (United States)

    Zhang, Yi C; Kagen, Alexander C

    2017-10-01

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

  13. [Clinical application of automated digital image analysis for morphology review of peripheral blood leukocyte].

    Science.gov (United States)

    Xing, Ying; Yan, Xiaohua; Pu, Chengwei; Shang, Ke; Dong, Ning; Wang, Run; Wang, Jianzhong

    2016-03-01

    To explore the clinical application of automated digital image analysis in leukocyte morphology examination when review criteria of hematology analyzer are triggered. The reference range of leukocyte differentiation by automated digital image analysis was established by analyzing 304 healthy blood samples from Peking University First Hospital. Six hundred and ninty-seven blood samples from Peking University First Hospital were randomly collected from November 2013 to April 2014, complete blood cells were counted on hematology analyzer, blood smears were made and stained at the same time. Blood smears were detected by automated digital image analyzer and the results were checked (reclassification) by a staff with abundant morphology experience. The same smear was examined manually by microscope. The results by manual microscopic differentiation were used as"golden standard", and diagnostic efficiency of abnormal specimens by automated digital image analysis was calculated, including sensitivity, specificity and accuracy. The difference of abnormal leukocytes detected by two different methods was analyzed in 30 samples of hematological and infectious diseases. Specificity of identifying abnormalities of white blood cells by automated digital image analysis was more than 90% except monocyte. Sensitivity of neutrophil toxic abnormities (including Döhle body, toxic granulate and vacuolization) was 100%; sensitivity of blast cells, immature granulates and atypical lymphocytes were 91.7%, 60% to 81.5% and 61.5%, respectively. Sensitivity of leukocyte differential count was 91.8% for neutrophils, 88.5% for lymphocytes, 69.1% for monocytes, 78.9% for eosinophils and 36.3 for basophils. The positive rate of recognizing abnormal cells (blast, immature granulocyte and atypical lymphocyte) by manual microscopic method was 46.7%, 53.3% and 10%, respectively. The positive rate of automated digital image analysis was 43.3%, 60% and 10%, respectively. There was no statistic

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

    International Nuclear Information System (INIS)

    Gratama van Andel, Hugo A.F.; Meijering, Erik; Vrooman, Henri A.; Stokking, Rik; Lugt, Aad van der; Monye, Cecile de

    2006-01-01

    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.)

  15. Computational Modeling of Medical Images of Brain Tumor Patients for Optimized Radiation Therapy Planning

    DEFF Research Database (Denmark)

    Agn, Mikael

    In brain tumor radiation therapy, the aim is to maximize the delivered radiation dose to the targeted tumor and at the same time minimize the dose to sensitive healthy structures – so-called organs-at-risk (OARs). When planning a radiation therapy session, the tumor and the OARs therefore need......, a need for automated methods that can segment both brain tumors and OARs. However, there is a noticeable lack in the literature of methods that simultaneously segment both types of structures. To automatically segment medical images of brain tumor patients is difficult because brain tumors vary greatly...... in size, shape, appearance and location within the brain. Furthermore, healthy structures surrounding a tumor are pushed and deformed by the so-called mass effect of the tumor. Moreover, medical imaging techniques often result in imaging artifacts and varying intensity across imaging centers. The goal...

  16. Effects of a direct refill program for automated dispensing cabinets on medication-refill errors.

    Science.gov (United States)

    Helmons, Pieter J; Dalton, Ashley J; Daniels, Charles E

    2012-10-01

    The effects of a direct refill program for automated dispensing cabinets (ADCs) on medication-refill errors were studied. This study was conducted in designated acute care areas of a 386-bed academic medical center. A wholesaler-to-ADC direct refill program, consisting of prepackaged delivery of medications and bar-code-assisted ADC refilling, was implemented in the inpatient pharmacy of the medical center in September 2009. Medication-refill errors in 26 ADCs from the general medicine units, the infant special care unit, the surgical and burn intensive care units, and intermediate units were assessed before and after the implementation of this program. Medication-refill errors were defined as an ADC pocket containing the wrong drug, wrong strength, or wrong dosage form. ADC refill errors decreased by 77%, from 62 errors per 6829 refilled pockets (0.91%) to 8 errors per 3855 refilled pockets (0.21%) (p error type detected before the intervention was the incorrect medication (wrong drug, wrong strength, or wrong dosage form) in the ADC pocket. Of the 54 incorrect medications found before the intervention, 38 (70%) were loaded in a multiple-drug drawer. After the implementation of the new refill process, 3 of the 5 incorrect medications were loaded in a multiple-drug drawer. There were 3 instances of expired medications before and only 1 expired medication after implementation of the program. A redesign of the ADC refill process using a wholesaler-to-ADC direct refill program that included delivery of prepackaged medication and bar-code-assisted refill significantly decreased the occurrence of ADC refill errors.

  17. 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.

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

    Science.gov (United States)

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

    2013-06-01

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

  19. 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.

  20. New developments in medical imaging to detect breast cancer

    African Journals Online (AJOL)

    medical imaging modalities are used to detect breast cancer, the most common being X-rays (mammography), ultrasound, magnetic resonance imaging (MRI) and various radionuclide techniques.2. The purpose of this article is to review these and other novel medical imaging modalities. The American College of Radiology ...

  1. Three dimensional image presentation techniques in medical imaging

    International Nuclear Information System (INIS)

    Pizer, S.M.; Fuchs, H.

    1987-01-01

    Medical images can be presented three-dimensionally by techniques that either calculate the effect of reflections from surfaces predefined from slices or project a three-space of luminosities computed from voxel intensities onto the visual receptors. Sliced-based reflective displays are the most common type. Means of producing surface descriptions both via voxel sets and via slice contours are reviewed. Advantages of and means of transparent display to allow the appreciation of the 3D relationships among objects are set forth. Ways to produce additional depth cues by stereoscopy and the kinetic depth effect are discussed, and the importance of interactive modification of viewpoint, clipping plane, displayed objects, etc. are explained. A new device, UNC's Pixel-planes, for accomplishing this in real time are illustrated. Voxel intensity based display methods avoid the need for time-consuming predefinition of object surfaces and thus can allow exploration of 3D image data. Varifocal mirror hardware and fast computation of one or more projections based on object probabilities are two of the more important approaches. While 3D display provides important information about 3D relationships, it cannot provide the kind of appreciation of subtle grey-scale changes that 2D display can. Methods that can combine these two kinds of information by superimposing 2D grey-scale slices on or in the context of 3D displays are discussed. Applications of these techniques for both diagnosis and radiotherapy planning are used as illustrations and guides to the usefulness of these techniques with CT, MRI, and other 3D medical imaging modalities. 24 refs.; 5 figs

  2. Automated recognition of the pericardium contour on processed CT images using genetic algorithms.

    Science.gov (United States)

    Rodrigues, É O; Rodrigues, L O; Oliveira, L S N; Conci, A; Liatsis, P

    2017-08-01

    This work proposes the use of Genetic Algorithms (GA) in tracing and recognizing the pericardium contour of the human heart using Computed Tomography (CT) images. We assume that each slice of the pericardium can be modelled by an ellipse, the parameters of which need to be optimally determined. An optimal ellipse would be one that closely follows the pericardium contour and, consequently, separates appropriately the epicardial and mediastinal fats of the human heart. Tracing and automatically identifying the pericardium contour aids in medical diagnosis. Usually, this process is done manually or not done at all due to the effort required. Besides, detecting the pericardium may improve previously proposed automated methodologies that separate the two types of fat associated to the human heart. Quantification of these fats provides important health risk marker information, as they are associated with the development of certain cardiovascular pathologies. Finally, we conclude that GA offers satisfiable solutions in a feasible amount of processing time. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

    NARCIS (Netherlands)

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

    2013-01-01

    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 applicability

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

    NARCIS (Netherlands)

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

    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

  5. The Medical Image Perception Society Update on Key Issues for Image Perception Research1

    OpenAIRE

    Krupinski, Elizabeth A.; Berbaum, Kevin S.

    2009-01-01

    To guide future investigations, the 2007 Medical Image Perception Society meeting held panel discussions to consider the current state of our knowledge of medical image perception and identify important questions to advance our understanding.

  6. Automated measurement of pressure injury through image processing.

    Science.gov (United States)

    Li, Dan; Mathews, Carol

    2017-11-01

    To develop an image processing algorithm to automatically measure pressure injuries using electronic pressure injury images stored in nursing documentation. Photographing pressure injuries and storing the images in the electronic health record is standard practice in many hospitals. However, the manual measurement of pressure injury is time-consuming, challenging and subject to intra/inter-reader variability with complexities of the pressure injury and the clinical environment. A cross-sectional algorithm development study. A set of 32 pressure injury images were obtained from a western Pennsylvania hospital. First, we transformed the images from an RGB (i.e. red, green and blue) colour space to a YC b C r colour space to eliminate inferences from varying light conditions and skin colours. Second, a probability map, generated by a skin colour Gaussian model, guided the pressure injury segmentation process using the Support Vector Machine classifier. Third, after segmentation, the reference ruler - included in each of the images - enabled perspective transformation and determination of pressure injury size. Finally, two nurses independently measured those 32 pressure injury images, and intraclass correlation coefficient was calculated. An image processing algorithm was developed to automatically measure the size of pressure injuries. Both inter- and intra-rater analysis achieved good level reliability. Validation of the size measurement of the pressure injury (1) demonstrates that our image processing algorithm is a reliable approach to monitoring pressure injury progress through clinical pressure injury images and (2) offers new insight to pressure injury evaluation and documentation. Once our algorithm is further developed, clinicians can be provided with an objective, reliable and efficient computational tool for segmentation and measurement of pressure injuries. With this, clinicians will be able to more effectively monitor the healing process of pressure

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

    Science.gov (United States)

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

    2012-09-01

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

  8. Automated spine and vertebrae detection in CT images using object-based image analysis.

    Science.gov (United States)

    Schwier, M; Chitiboi, T; Hülnhagen, T; Hahn, H K

    2013-09-01

    Although computer assistance has become common in medical practice, some of the most challenging tasks that remain unsolved are in the area of automatic detection and recognition. The human visual perception is in general far superior to computer vision algorithms. Object-based image analysis is a relatively new approach that aims to lift image analysis from a pixel-based processing to a semantic region-based processing of images. It allows effective integration of reasoning processes and contextual concepts into the recognition method. In this paper, we present an approach that applies object-based image analysis to the task of detecting the spine in computed tomography images. A spine detection would be of great benefit in several contexts, from the automatic labeling of vertebrae to the assessment of spinal pathologies. We show with our approach how region-based features, contextual information and domain knowledge, especially concerning the typical shape and structure of the spine and its components, can be used effectively in the analysis process. The results of our approach are promising with a detection rate for vertebral bodies of 96% and a precision of 99%. We also gain a good two-dimensional segmentation of the spine along the more central slices and a coarse three-dimensional segmentation. Copyright © 2013 John Wiley & Sons, Ltd.

  9. Automated whole animal bio-imaging assay for human cancer dissemination.

    Directory of Open Access Journals (Sweden)

    Veerander P S Ghotra

    Full Text Available A quantitative bio-imaging platform is developed for analysis of human cancer dissemination in a short-term vertebrate xenotransplantation assay. Six days after implantation of cancer cells in zebrafish embryos, automated imaging in 96 well plates coupled to image analysis algorithms quantifies spreading throughout the host. Findings in this model correlate with behavior in long-term rodent xenograft models for panels of poorly- versus highly malignant cell lines derived from breast, colorectal, and prostate cancer. In addition, cancer cells with scattered mesenchymal characteristics show higher dissemination capacity than cell types with epithelial appearance. Moreover, RNA interference establishes the metastasis-suppressor role for E-cadherin in this model. This automated quantitative whole animal bio-imaging assay can serve as a first-line in vivo screening step in the anti-cancer drug target discovery pipeline.

  10. Automated Segmentability Index for Layer Segmentation of Macular SD-OCT Images

    NARCIS (Netherlands)

    Lee, K.; Buitendijk, G.H.; Bogunovic, H.; Springelkamp, H.; Hofman, A.; Wahle, A.; Sonka, M.; Vingerling, J.R.; Klaver, C.C.W.; Abramoff, M.D.

    2016-01-01

    PURPOSE: To automatically identify which spectral-domain optical coherence tomography (SD-OCT) scans will provide reliable automated layer segmentations for more accurate layer thickness analyses in population studies. METHODS: Six hundred ninety macular SD-OCT image volumes (6.0 x 6.0 x 2.3 mm3)

  11. An Automated Method for Semantic Classification of Regions in Coastal Images

    NARCIS (Netherlands)

    Hoonhout, B.M.; Radermacher, M.; Baart, F.; Van der Maaten, L.J.P.

    2015-01-01

    Large, long-term coastal imagery datasets are nowadays a low-cost source of information for various coastal research disciplines. However, the applicability of many existing algorithms for coastal image analysis is limited for these large datasets due to a lack of automation and robustness.

  12. 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...

  13. Automated image mosaics by non-automated light microscopes: the MicroMos software tool.

    Science.gov (United States)

    Piccinini, F; Bevilacqua, A; Lucarelli, E

    2013-12-01

    Light widefield microscopes and digital imaging are the basis for most of the analyses performed in every biological laboratory. In particular, the microscope's user is typically interested in acquiring high-detailed images for analysing observed cells and tissues, meanwhile being representative of a wide area to have reliable statistics. The microscopist has to choose between higher magnification factor and extension of the observed area, due to the finite size of the camera's field of view. To overcome the need of arrangement, mosaicing techniques have been developed in the past decades for increasing the camera's field of view by stitching together more images. Nevertheless, these approaches typically work in batch mode and rely on motorized microscopes. Or alternatively, the methods are conceived just to provide visually pleasant mosaics not suitable for quantitative analyses. This work presents a tool for building mosaics of images acquired with nonautomated light microscopes. The method proposed is based on visual information only and the mosaics are built by incrementally stitching couples of images, making the approach available also for online applications. Seams in the stitching regions as well as tonal inhomogeneities are corrected by compensating the vignetting effect. In the experiments performed, we tested different registration approaches, confirming that the translation model is not always the best, despite the fact that the motion of the sample holder of the microscope is apparently translational and typically considered as such. The method's implementation is freely distributed as an open source tool called MicroMos. Its usability makes building mosaics of microscope images at subpixel accuracy easier. Furthermore, optional parameters for building mosaics according to different strategies make MicroMos an easy and reliable tool to compare different registration approaches, warping models and tonal corrections. © 2013 The Authors Journal of

  14. Use of automated medication adherence monitoring in bipolar disorder research: pitfalls, pragmatics, and possibilities.

    Science.gov (United States)

    Levin, Jennifer B; Sams, Johnny; Tatsuoka, Curtis; Cassidy, Kristin A; Sajatovic, Martha

    2015-04-01

    Medication nonadherence occurs in 20-60% of persons with bipolar disorder (BD) and is associated with serious negative outcomes, including relapse, hospitalization, incarceration, suicide and high healthcare costs. Various strategies have been developed to measure adherence in BD. This descriptive paper summarizes challenges and workable strategies using electronic medication monitoring in a randomized clinical trial (RCT) in patients with BD. Descriptive data from 57 nonadherent individuals with BD enrolled in a prospective RCT evaluating a novel customized adherence intervention versus control were analyzed. Analyses focused on whole group data and did not assess intervention effects. Adherence was assessed with the self-reported Tablets Routine Questionnaire and the Medication Event Monitoring System (MEMS). The majority of participants were women (74%), African American (69%), with type I BD (77%). Practical limitations of MEMS included misuse in conjunction with pill minders, polypharmacy, cost, failure to bring to research visits, losing the device, and the device impacting baseline measurement. The advantages were more precise measurement, less biased recall, and collecting data from past time periods for missed interim visits. Automated devices such as MEMS can assist investigators in evaluating adherence in patients with BD. Knowing the anticipated pitfalls allows study teams to implement preemptive procedures for successful implementation in BD adherence studies and can help pave the way for future refinements as automated adherence assessment technologies become more sophisticated and readily available.

  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. 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

  17. 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...

  18. An image-processing program for automated counting

    Science.gov (United States)

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

    1996-01-01

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

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

    Directory of Open Access Journals (Sweden)

    François Mallard

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

  20. Automated Analysis of Microscopic Images of Isolated Pancreatic Islets

    Czech Academy of Sciences Publication Activity Database

    Habart, D.; Švihlík, J.; Schier, Jan; Cahová, M.; Girman, P.; Zacharovová, K.; Berková, Z.; Kříž, J.; Fabryová, E.; Kosinová, L.; Papáčková, Z.; Kybic, J.; Saudek, F.

    2016-01-01

    Roč. 25, č. 12 (2016), s. 2145-2156 ISSN 0963-6897 Grant - others:GA ČR(CZ) GA14-10440S Institutional support: RVO:67985556 Keywords : enumeration of islets * image processing * image segmentation * islet transplantation * machine-learning * quality control Subject RIV: IN - Informatics, Computer Science Impact factor: 3.006, year: 2016 http://library.utia.cas.cz/separaty/2016/ZOI/schier-0465945.pdf

  1. A high performance parallel approach to medical imaging

    International Nuclear Information System (INIS)

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

    1988-01-01

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

  2. 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...

  3. An object localization optimization technique in medical images using plant growth simulation algorithm.

    Science.gov (United States)

    Bhattacharjee, Deblina; Paul, Anand; Kim, Jeong Hong; Kim, Mucheol

    2016-01-01

    The analysis of leukocyte images has drawn interest from fields of both medicine and computer vision for quite some time where different techniques have been applied to automate the process of manual analysis and classification of such images. Manual analysis of blood samples to identify leukocytes is time-consuming and susceptible to error due to the different morphological features of the cells. In this article, the nature-inspired plant growth simulation algorithm has been applied to optimize the image processing technique of object localization of medical images of leukocytes. This paper presents a random bionic algorithm for the automated detection of white blood cells embedded in cluttered smear and stained images of blood samples that uses a fitness function that matches the resemblances of the generated candidate solution to an actual leukocyte. The set of candidate solutions evolves via successive iterations as the proposed algorithm proceeds, guaranteeing their fit with the actual leukocytes outlined in the edge map of the image. The higher precision and sensitivity of the proposed scheme from the existing methods is validated with the experimental results of blood cell images. The proposed method reduces the feasible sets of growth points in each iteration, thereby reducing the required run time of load flow, objective function evaluation, thus reaching the goal state in minimum time and within the desired constraints.

  4. Digital fluoroscopy: a new development in medical imaging

    International Nuclear Information System (INIS)

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

    1986-01-01

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

  5. MIRACLE’s Naive Approach to Medical Images Annotation

    OpenAIRE

    Villena Román, Julio; González Cristóbal, José Carlos; Goñi Menoyo, José Miguel; Martínez Fernández, José Luis

    2005-01-01

    One of the proposed tasks of the ImageCLEF 2005 campaign has been an Automatic Annotation Task. The objective is to provide the classification of a given set of 1,000 previously unseen medical (radiological) images according to 57 predefined categories covering different medical pathologies. 9,000 classified training images are given which can be used in any way to train a classifier. The Automatic Annotation task uses no textual information, but image-content information only. This paper des...

  6. Normalized gradient fields cross-correlation for automated detection of prostate in magnetic resonance images

    Science.gov (United States)

    Fotin, Sergei V.; Yin, Yin; Periaswamy, Senthil; Kunz, Justin; Haldankar, Hrishikesh; Muradyan, Naira; Cornud, François; Turkbey, Baris; Choyke, Peter L.

    2012-02-01

    Fully automated prostate segmentation helps to address several problems in prostate cancer diagnosis and treatment: it can assist in objective evaluation of multiparametric MR imagery, provides a prostate contour for MR-ultrasound (or CT) image fusion for computer-assisted image-guided biopsy or therapy planning, may facilitate reporting and enables direct prostate volume calculation. Among the challenges in automated analysis of MR images of the prostate are the variations of overall image intensities across scanners, the presence of nonuniform multiplicative bias field within scans and differences in acquisition setup. Furthermore, images acquired with the presence of an endorectal coil suffer from localized high-intensity artifacts at the posterior part of the prostate. In this work, a three-dimensional method for fast automated prostate detection based on normalized gradient fields cross-correlation, insensitive to intensity variations and coil-induced artifacts, is presented and evaluated. The components of the method, offline template learning and the localization algorithm, are described in detail. The method was validated on a dataset of 522 T2-weighted MR images acquired at the National Cancer Institute, USA that was split in two halves for development and testing. In addition, second dataset of 29 MR exams from Centre d'Imagerie Médicale Tourville, France were used to test the algorithm. The 95% confidence intervals for the mean Euclidean distance between automatically and manually identified prostate centroids were 4.06 +/- 0.33 mm and 3.10 +/- 0.43 mm for the first and second test datasets respectively. Moreover, the algorithm provided the centroid within the true prostate volume in 100% of images from both datasets. Obtained results demonstrate high utility of the detection method for a fully automated prostate segmentation.

  7. Automated tissue segmentation of MR brain images in the presence of white matter lesions.

    Science.gov (United States)

    Valverde, Sergi; Oliver, Arnau; Roura, Eloy; González-Villà, Sandra; Pareto, Deborah; Vilanova, Joan C; Ramió-Torrentà, Lluís; Rovira, Àlex; Lladó, Xavier

    2017-01-01

    Over the last few years, the increasing interest in brain tissue volume measurements on clinical settings has led to the development of a wide number of automated tissue segmentation methods. However, white matter lesions are known to reduce the performance of automated tissue segmentation methods, which requires manual annotation of the lesions and refilling them before segmentation, which is tedious and time-consuming. Here, we propose a new, fully automated T1-w/FLAIR tissue segmentation approach designed to deal with images in the presence of WM lesions. This approach integrates a robust partial volume tissue segmentation with WM outlier rejection and filling, combining intensity and probabilistic and morphological prior maps. We evaluate the performance of this method on the MRBrainS13 tissue segmentation challenge database, which contains images with vascular WM lesions, and also on a set of Multiple Sclerosis (MS) patient images. On both databases, we validate the performance of our method with other state-of-the-art techniques. On the MRBrainS13 data, the presented approach was at the time of submission the best ranked unsupervised intensity model method of the challenge (7th position) and clearly outperformed the other unsupervised pipelines such as FAST and SPM12. On MS data, the differences in tissue segmentation between the images segmented with our method and the same images where manual expert annotations were used to refill lesions on T1-w images before segmentation were lower or similar to the best state-of-the-art pipeline incorporating automated lesion segmentation and filling. Our results show that the proposed pipeline achieved very competitive results on both vascular and MS lesions. A public version of this approach is available to download for the neuro-imaging community. Copyright © 2016 Elsevier B.V. All rights reserved.

  8. Signal Processing in Medical Ultrasound B-mode Imaging

    International Nuclear Information System (INIS)

    Song, Tai Kyong

    2000-01-01

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

  9. Near-infrared spectroscopic tissue imaging for medical applications

    Science.gov (United States)

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

    2006-12-12

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

  10. Method for Surface Scanning in Medical Imaging and Related Apparatus

    DEFF Research Database (Denmark)

    2015-01-01

    A method and apparatus for surface scanning in medical imaging is provided. The surface scanning apparatus comprises an image source, a first optical fiber bundle comprising first optical fibers having proximal ends and distal ends, and a first optical coupler for coupling an image from the image...

  11. Fully automated registration of vibrational microspectroscopic images in histologically stained tissue sections.

    Science.gov (United States)

    Yang, Chen; Niedieker, Daniel; Grosserüschkamp, Frederik; Horn, Melanie; Tannapfel, Andrea; Kallenbach-Thieltges, Angela; Gerwert, Klaus; Mosig, Axel

    2015-11-25

    In recent years, hyperspectral microscopy techniques such as infrared or Raman microscopy have been applied successfully for diagnostic purposes. In many of the corresponding studies, it is common practice to measure one and the same sample under different types of microscopes. Any joint analysis of the two image modalities requires to overlay the images, so that identical positions in the sample are located at the same coordinate in both images. This step, commonly referred to as image registration, has typically been performed manually in the lack of established automated computational registration tools. We propose a corresponding registration algorithm that addresses this registration problem, and demonstrate the robustness of our approach in different constellations of microscopes. First, we deal with subregion registration of Fourier Transform Infrared (FTIR) microscopic images in whole-slide histopathological staining images. Second, we register FTIR imaged cores of tissue microarrays in their histopathologically stained counterparts, and finally perform registration of Coherent anti-Stokes Raman spectroscopic (CARS) images within histopathological staining images. Our validation involves a large variety of samples obtained from colon, bladder, and lung tissue on three different types of microscopes, and demonstrates that our proposed method works fully automated and highly robust in different constellations of microscopes involving diverse types of tissue samples.

  12. 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.

  13. Enhanced Automated Guidance System for Horizontal Auger Boring Based on Image Processing.

    Science.gov (United States)

    Wu, Lingling; Wen, Guojun; Wang, Yudan; Huang, Lei; Zhou, Jiang

    2018-02-15

    Horizontal auger boring (HAB) is a widely used trenchless technology for the high-accuracy installation of gravity or pressure pipelines on line and grade. Differing from other pipeline installations, HAB requires a more precise and automated guidance system for use in a practical project. This paper proposes an economic and enhanced automated optical guidance system, based on optimization research of light-emitting diode (LED) light target and five automated image processing bore-path deviation algorithms. An LED light target was optimized for many qualities, including light color, filter plate color, luminous intensity, and LED layout. The image preprocessing algorithm, direction location algorithm, angle measurement algorithm, deflection detection algorithm, and auto-focus algorithm, compiled in MATLAB, are used to automate image processing for deflection computing and judging. After multiple indoor experiments, this guidance system is applied in a project of hot water pipeline installation, with accuracy controlled within 2 mm in 48-m distance, providing accurate line and grade controls and verifying the feasibility and reliability of the guidance system.

  14. Automated Quality Assessment of Structural Magnetic Resonance Brain Images Based on a Supervised Machine Learning Algorithm

    Directory of Open Access Journals (Sweden)

    Ricardo Andres Pizarro

    2016-12-01

    Full Text Available High-resolution three-dimensional magnetic resonance imaging (3D-MRI is being increasingly used to delineate morphological changes underlying neuropsychiatric disorders. Unfortunately, artifacts frequently compromise the utility of 3D-MRI yielding irreproducible results, from both type I and type II errors. It is therefore critical to screen 3D-MRIs for artifacts before use. Currently, quality assessment involves slice-wise visual inspection of 3D-MRI volumes, a procedure that is both subjective and time consuming. Automating the quality rating of 3D-MRI could improve the efficiency and reproducibility of the procedure. The present study is one of the first efforts to apply a support vector machine (SVM algorithm in the quality assessment of structural brain images, using global and region of interest (ROI automated image quality features developed in-house. SVM is a supervised machine-learning algorithm that can predict the category of test datasets based on the knowledge acquired from a learning dataset. The performance (accuracy of the automated SVM approach was assessed, by comparing the SVM-predicted quality labels to investigator-determined quality labels. The accuracy for classifying 1457 3D-MRI volumes from our database using the SVM approach is around 80%. These results are promising and illustrate the possibility of using SVM as an automated quality assessment tool for 3D-MRI.

  15. Automated Quality Assessment of Structural Magnetic Resonance Brain Images Based on a Supervised Machine Learning Algorithm.

    Science.gov (United States)

    Pizarro, Ricardo A; Cheng, Xi; Barnett, Alan; Lemaitre, Herve; Verchinski, Beth A; Goldman, Aaron L; Xiao, Ena; Luo, Qian; Berman, Karen F; Callicott, Joseph H; Weinberger, Daniel R; Mattay, Venkata S

    2016-01-01

    High-resolution three-dimensional magnetic resonance imaging (3D-MRI) is being increasingly used to delineate morphological changes underlying neuropsychiatric disorders. Unfortunately, artifacts frequently compromise the utility of 3D-MRI yielding irreproducible results, from both type I and type II errors. It is therefore critical to screen 3D-MRIs for artifacts before use. Currently, quality assessment involves slice-wise visual inspection of 3D-MRI volumes, a procedure that is both subjective and time consuming. Automating the quality rating of 3D-MRI could improve the efficiency and reproducibility of the procedure. The present study is one of the first efforts to apply a support vector machine (SVM) algorithm in the quality assessment of structural brain images, using global and region of interest (ROI) automated image quality features developed in-house. SVM is a supervised machine-learning algorithm that can predict the category of test datasets based on the knowledge acquired from a learning dataset. The performance (accuracy) of the automated SVM approach was assessed, by comparing the SVM-predicted quality labels to investigator-determined quality labels. The accuracy for classifying 1457 3D-MRI volumes from our database using the SVM approach is around 80%. These results are promising and illustrate the possibility of using SVM as an automated quality assessment tool for 3D-MRI.

  16. Automation of chromosomes analysis. Automatic system for image processing

    International Nuclear Information System (INIS)

    Le Go, R.; Cosnac, B. de; Spiwack, A.

    1975-01-01

    The A.S.T.I. is an automatic system relating to the fast conversational processing of all kinds of images (cells, chromosomes) converted to a numerical data set (120000 points, 16 grey levels stored in a MOS memory) through a fast D.O. analyzer. The system performs automatically the isolation of any individual image, the area and weighted area of which are computed. These results are directly displayed on the command panel and can be transferred to a mini-computer for further computations. A bright spot allows parts of an image to be picked out and the results to be displayed. This study is particularly directed towards automatic karyo-typing [fr

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

    DEFF Research Database (Denmark)

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

    Graphene, as the forefather of 2D-materials, attracts much attention due to its extraordinary properties like transparency, flexibility and outstanding high conductivity, together with a thickness of only one atom. The properties seem to be dependent on the atomic structure of graphene...... of time making it difficult to resolve dynamic processes or unstable structures. Tools that assist to get the maximum of information out of recorded images are therefore greatly appreciated. In order to get the most accurate results out of the structure detection, we have optimized the imaging conditions...

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

  19. Cost-Effectiveness Analysis of an Automated Medication System Implemented in a Danish Hospital Setting

    DEFF Research Database (Denmark)

    Risoer, Bettina Wulff; Lisby, Marianne; Soerensen, Jan

    2017-01-01

    outcome measure was the number of errors in the medication administration process observed prospectively before and after implementation. To determine the difference in proportion of errors after implementation of the AMS, logistic regression was applied with the presence of error(s) as the dependent......Objectives To evaluate the cost-effectiveness of an automated medication system (AMS) implemented in a Danish hospital setting. Methods An economic evaluation was performed alongside a controlled before-and-after effectiveness study with one control ward and one intervention ward. The primary...... of avoided administration errors was related to the incremental costs to obtain the cost-effectiveness ratio expressed as the cost per avoided administration error. Results The AMS resulted in a statistically significant reduction in the proportion of errors in the intervention ward compared with the control...

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

    DEFF Research Database (Denmark)

    Gutte, Henrik; Jakobsson, David; Olofsson, Fredrik

    2007-01-01

    cancer. METHODS: A total of 87 patients who underwent PET/CT examinations due to suspected lung cancer comprised the training group. The test group consisted of PET/CT images from 49 patients suspected with lung cancer. The consensus interpretations by two experienced physicians were used as the 'gold...... method measured as the area under the receiver operating characteristic curve, was 0.97 in the test group, with an accuracy of 92%. The sensitivity was 86% at a specificity of 100%. CONCLUSIONS: A completely automated method using artificial neural networks can be used to detect lung cancer......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...

  1. Automated determination of size and morphology information from soot transmission electron microscope (TEM)-generated images

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Cheng; Chan, Qing N., E-mail: qing.chan@unsw.edu.au; Zhang, Renlin; Kook, Sanghoon; Hawkes, Evatt R.; Yeoh, Guan H. [UNSW, School of Mechanical and Manufacturing Engineering (Australia); Medwell, Paul R. [The University of Adelaide, Centre for Energy Technology (Australia)

    2016-05-15

    The thermophoretic sampling of particulates from hot media, coupled with transmission electron microscope (TEM) imaging, is a combined approach that is widely used to derive morphological information. The identification and the measurement of the particulates, however, can be complex when the TEM images are of low contrast, noisy, and have non-uniform background signal level. The image processing method can also be challenging and time consuming, when the samples collected have large variability in shape and size, or have some degree of overlapping. In this work, a three-stage image processing sequence is presented to facilitate time-efficient automated identification and measurement of particulates from the TEM grids. The proposed processing sequence is first applied to soot samples that were thermophoretically sampled from a laminar non-premixed ethylene-air flame. The parameter values that are required to be set to facilitate the automated process are identified, and sensitivity of the results to these parameters is assessed. The same analysis process is also applied to soot samples that were acquired from an externally irradiated laminar non-premixed ethylene-air flame, which have different geometrical characteristics, to assess the morphological dependence of the proposed image processing sequence. Using the optimized parameter values, statistical assessments of the automated results reveal that the largest discrepancies that are associated with the estimated values of primary particle diameter, fractal dimension, and prefactor values of the aggregates for the tested cases, are approximately 3, 1, and 10 %, respectively, when compared with the manual measurements.

  2. Automated 3-D Detection of Dendritic Spines from In Vivo Two-Photon Image Stacks.

    Science.gov (United States)

    Singh, P K; Hernandez-Herrera, P; Labate, D; Papadakis, M

    2017-10-01

    Despite the significant advances in the development of automated image analysis algorithms for the detection and extraction of neuronal structures, current software tools still have numerous limitations when it comes to the detection and analysis of dendritic spines. The problem is especially challenging in in vivo imaging, where the difficulty of extracting morphometric properties of spines is compounded by lower image resolution and contrast levels native to two-photon laser microscopy. To address this challenge, we introduce a new computational framework for the automated detection and quantitative analysis of dendritic spines in vivo multi-photon imaging. This framework includes: (i) a novel preprocessing algorithm enhancing spines in a way that they are included in the binarized volume produced during the segmentation of foreground from background; (ii) the mathematical foundation of this algorithm, and (iii) an algorithm for the detection of spine locations in reference to centerline trace and separating them from the branches to whom spines are attached to. This framework enables the computation of a wide range of geometric features such as spine length, spatial distribution and spine volume in a high-throughput fashion. We illustrate our approach for the automated extraction of dendritic spine features in time-series multi-photon images of layer 5 cortical excitatory neurons from the mouse visual cortex.

  3. Automated determination of size and morphology information from soot transmission electron microscope (TEM)-generated images

    International Nuclear Information System (INIS)

    Wang, Cheng; Chan, Qing N.; Zhang, Renlin; Kook, Sanghoon; Hawkes, Evatt R.; Yeoh, Guan H.; Medwell, Paul R.

    2016-01-01

    The thermophoretic sampling of particulates from hot media, coupled with transmission electron microscope (TEM) imaging, is a combined approach that is widely used to derive morphological information. The identification and the measurement of the particulates, however, can be complex when the TEM images are of low contrast, noisy, and have non-uniform background signal level. The image processing method can also be challenging and time consuming, when the samples collected have large variability in shape and size, or have some degree of overlapping. In this work, a three-stage image processing sequence is presented to facilitate time-efficient automated identification and measurement of particulates from the TEM grids. The proposed processing sequence is first applied to soot samples that were thermophoretically sampled from a laminar non-premixed ethylene-air flame. The parameter values that are required to be set to facilitate the automated process are identified, and sensitivity of the results to these parameters is assessed. The same analysis process is also applied to soot samples that were acquired from an externally irradiated laminar non-premixed ethylene-air flame, which have different geometrical characteristics, to assess the morphological dependence of the proposed image processing sequence. Using the optimized parameter values, statistical assessments of the automated results reveal that the largest discrepancies that are associated with the estimated values of primary particle diameter, fractal dimension, and prefactor values of the aggregates for the tested cases, are approximately 3, 1, and 10 %, respectively, when compared with the manual measurements.

  4. 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.

  5. Automated identification of retained surgical items in radiological images

    Science.gov (United States)

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

    2015-03-01

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

  6. Transportation informatics : advanced image processing techniques automated pavement distress evaluation.

    Science.gov (United States)

    2010-01-01

    The current project, funded by MIOH-UTC for the period 1/1/2009- 4/30/2010, is concerned : with the development of the framework for a transportation facility inspection system using : advanced image processing techniques. The focus of this study is ...

  7. Automation of the method gamma of comparison dosimetry images

    International Nuclear Information System (INIS)

    Moreno Reyes, J. C.; Macias Jaen, J.; Arrans Lara, R.

    2013-01-01

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

  8. Adaptive Algorithms for Automated Processing of Document Images

    Science.gov (United States)

    2011-01-01

    IEEE Trans. on Pattern Analysis and Machine Intelligence (PAMI), 21(8):761 –768, Aug. 1999. [84] N. Stamatopoulos, B. Gatos , and T. Georgiou. Automatic...2007. [85] N. Stamatopoulos, B. Gatos , and T. Georgiou. Page frame detection for double page document images. In Proc. of the 9th IAPR Int’l

  9. 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.

  10. 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.

  11. Medical image of the week: pneumomediastinum

    Directory of Open Access Journals (Sweden)

    Franco R Jr

    2014-01-01

    Full Text Available No abstract available. Article truncated at 150 words. A 65 year old man presented with mild increase in shortness of breath. He had a past medical history of diabetes mellitus, hypertension, and severe malnutrition with percutaneous endoscopic gastrostomy (PEG placement after a colectomy and end ileostomy for sigmoid volvulus. CXR (Figure 1 suggested a pneumomediastinum with subsequent chest CT (Figure 2 confirming moderate sized pneumomediastinum. He had a chronic cough from chronic obstructive pulmonary disease (COPD as well as aspiration and chest CT also demonstrated emphysema with small blebs. He denied any significant chest pain. He was followed conservatively with imaging and discharged in stable condition. Pneumomediastinum can be caused by trauma, esophageal rupture after vomiting (Boerhaave’s syndrome and can be a spontaneous event if no obvious precipitating cause is identified (1. Valsalva maneuvers such as cough, sneeze, vomiting and childbirth, can all cause pneumomediastinum. Risk factors include asthma, COPD, interstitial lung disease and inhalational recreational drug use. …

  12. Medical image of the week: moyamoya disease

    Directory of Open Access Journals (Sweden)

    Pak S

    2017-11-01

    Full Text Available No abstract available. Article truncated at 150 words. A 52-year-old, right-handed, Caucasian woman with a history of hypertension and morbid obesity presented with acute onset of word-finding difficulty and slurred speech. Her medical and family history was negative for cerebral vascular event, coronary artery disease or smoking. Computed tomography of the patient's brain showed narrow caliber middle cerebral artery vasculature bilaterally. This abnormal finding prompted further investigation with cerebral angiogram. The angiogram showed bilateral high-grade stenosis of the anterior and middle cerebral arteries, worse on the left (Figure 1. Magnetic resonance imaging revealed multiple left sided punctate infarcts in the frontal and parietal lobes (Figure 2. Diagnosis of ischemic stroke secondary to moyamoya disease was established. This patient was not a candidate for fibrinolytic therapy since it had been more than 4 hours from initial presentation. She was treated with aspirin, clopidogrel, and atorvastatin for secondary prevention of ischemic stroke. Two months after her discharge date, the patient …

  13. Medical image of the week: focal myopericaditis

    Directory of Open Access Journals (Sweden)

    Meenakshisundaram C

    2015-07-01

    Full Text Available No abstract available. Article truncated at 150 words. A 44-year-old man with no significant past medical history was admitted with a history of two episodes of substernal chest pain unrelated to exertion which had resolved spontaneously. Admission vital signs were within normal limits and physical examination was unremarkable. Basic lab tests were normal and urine toxicology was negative. Electrocardiogram was unremarkable with no ST/T changes. Troponin I was elevated at 4.19 which trended up to 6.57. An urgent cardiac angiogram was done which revealed normal patent coronaries. His transthoracic echocardiogram was also reported to be normal. He continued to have intermittent episodes of chest pain that was partially relieved by morphine. Erythrocyte sedimentation rate and C-reactive protein were elevated. Work up for autoimmune diseases, vasculitis, myocarditis panel were insignificant. Later, magnetic resonance imaging (MRI with gadolinium enhanced contrast (Figure 1 was obtained which showed abnormal epicardial/subepicardial myocardial enhancement within the inferolateral wall and cardiac apex consistent with focal ...

  14. Navigation in medical Internet image databases.

    Science.gov (United States)

    Frankewitsch, T; Prokosch, U

    2001-01-01

    The world wide web (WWW) changes common ideas of database access. Hypertext Markup Language allows the simultaneous presentation of information from different sources such as static pages, results of queries from) databases or dynamically generated pages. 'Therefore, the metaphor of the WWW itself as a database was proposed by Mendelzon and Nlilo in 1998. Against this background the techniques of navigation within WWW-databases and the semantic types of their queries has e been analysed. Forty eight image repositories of different types and content, but all concerning medical essence, have been found by search-engines. Many different techniques are offered to enable navigation ranging from simple HTML-link-lists to complex applets. The applets in particular promise an improvement for navigation. Within the meta-information for querying, only ACR- and UMLS-encoding were found, but not standardized vocabularies like ICD10 or Terminologia Anatomica. UMLS especially shows that a well defined thesaurus can improve navigation. However, of the analysed databases only the UMLS 'metathesaurus' is currently implemented without providing additional navigation support based on the UMLS 'semantic network'. Including the information about relationships between the concepts of the metathesaurus or using the UMLS semantic network could provide a much easier navigation within a network of concepts pointing to multimedia files stored somewhere in the WWW.

  15. Medical image of the week: purpura fulminans

    Directory of Open Access Journals (Sweden)

    Power EP

    2016-12-01

    Full Text Available No abstract available. Article truncated at 150 words. A 54-year-old man with coronary artery disease, fibromyalgia and chronic sacral ulcers was brought to the emergency department due to acute changes in mentation and hypotension. He suffered a cardiac arrest shortly after arrival to the emergency department during emergent airway management. After successful resuscitation, he was admitted to the medical intensive care unit and treated for septic shock with fluid resuscitation, vasopressors and broad spectrum antibiotics. Laboratory results were significant for disseminated intravascular coagulopathy (DIC- thrombocytopenia, decreased fibrinogen and elevated PT, PTT and D-dimer levels. Profound metabolic acidosis and lactate elevation was also seen. Blood Cultures later revealed a multi-drug resistant E. coli bacteremia. Images of the lower extremities (Figure 1 were obtained at initial assessment and are consistent with purpura fulminans. He did not survive the stay. Purpura fulminans, also referred to as skin mottling, is an evolving skin condition which is characterized by an acutely worsening reticular …

  16. Unsupervised fully automated inline analysis of global left ventricular function in CINE MR imaging.

    Science.gov (United States)

    Theisen, Daniel; Sandner, Torleif A; Bauner, Kerstin; Hayes, Carmel; Rist, Carsten; Reiser, Maximilian F; Wintersperger, Bernd J

    2009-08-01

    To implement and evaluate the accuracy of unsupervised fully automated inline analysis of global ventricular function and myocardial mass (MM). To compare automated with manual segmentation in patients with cardiac disorders. In 50 patients, cine imaging of the left ventricle was performed with an accelerated retrogated steady state free precession sequence (GRAPPA; R = 2) on a 1.5 Tesla whole body scanner (MAGNETOM Avanto, Siemens Healthcare, Germany). A spatial resolution of 1.4 x 1.9 mm was achieved with a slice thickness of 8 mm and a temporal resolution of 42 milliseconds. Ventricular coverage was based on 9 to 12 short axis slices extending from the annulus of the mitral valve to the apex with 2 mm gaps. Fully automated segmentation and contouring was performed instantaneously after image acquisition. In addition to automated processing, cine data sets were also manually segmented using a semi-automated postprocessing software. Results of both methods were compared with regard to end-diastolic volume (EDV), end-systolic volume (ESV), ejection fraction (EF), and MM. A subgroup analysis was performed in patients with normal (> or =55%) and reduced EF (<55%) based on the results of the manual analysis. Thirty-two percent of patients had a reduced left ventricular EF of <55%. Volumetric results of the automated inline analysis for EDV (r = 0.96), ESV (r = 0.95), EF (r = 0.89), and MM (r = 0.96) showed high correlation with the results of manual segmentation (all P < 0.001). Head-to-head comparison did not show significant differences between automated and manual evaluation for EDV (153.6 +/- 52.7 mL vs. 149.1 +/- 48.3 mL; P = 0.05), ESV (61.6 +/- 31.0 mL vs. 64.1 +/- 31.7 mL; P = 0.08), and EF (58.0 +/- 11.6% vs. 58.6 +/- 11.6%; P = 0.5). However, differences were significant for MM (150.0 +/- 61.3 g vs. 142.4 +/- 59.0 g; P < 0.01). The standard error was 15.6 (EDV), 9.7 (ESV), 5.0 (EF), and 17.1 (mass). The mean time for manual analysis was 15 minutes

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

    DEFF Research Database (Denmark)

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

    2001-01-01

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

  18. Automated detection of new impact sites on Martian surface from HiRISE images

    Science.gov (United States)

    Xin, Xin; Di, Kaichang; Wang, Yexin; Wan, Wenhui; Yue, Zongyu

    2017-10-01

    In this study, an automated method for Martian new impact site detection from single images is presented. It first extracts dark areas in full high resolution image, then detects new impact craters within dark areas using a cascade classifier which combines local binary pattern features and Haar-like features trained by an AdaBoost machine learning algorithm. Experimental results using 100 HiRISE images show that the overall detection rate of proposed method is 84.5%, with a true positive rate of 86.9%. The detection rate and true positive rate in the flat regions are 93.0% and 91.5%, respectively.

  19. Automated Dermoscopy Image Analysis of Pigmented Skin Lesions

    Directory of Open Access Journals (Sweden)

    Alfonso Baldi

    2010-03-01

    Full Text Available Dermoscopy (dermatoscopy, epiluminescence microscopy is a non-invasive diagnostic technique for the in vivo observation of pigmented skin lesions (PSLs, allowing a better visualization of surface and subsurface structures (from the epidermis to the papillary dermis. This diagnostic tool permits the recognition of morphologic structures not visible by the naked eye, thus opening a new dimension in the analysis of the clinical morphologic features of PSLs. In order to reduce the learning-curve of non-expert clinicians and to mitigate problems inherent in the reliability and reproducibility of the diagnostic criteria used in pattern analysis, several indicative methods based on diagnostic algorithms have been introduced in the last few years. Recently, numerous systems designed to provide computer-aided analysis of digital images obtained by dermoscopy have been reported in the literature. The goal of this article is to review these systems, focusing on the most recent approaches based on content-based image retrieval systems (CBIR.

  20. Automated segmentation of pigmented skin lesions in multispectral imaging

    International Nuclear Information System (INIS)

    Carrara, Mauro; Tomatis, Stefano; Bono, Aldo; Bartoli, Cesare; Moglia, Daniele; Lualdi, Manuela; Colombo, Ambrogio; Santinami, Mario; Marchesini, Renato

    2005-01-01

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

  1. Supervised variational model with statistical inference and its application in medical image segmentation.

    Science.gov (United States)

    Li, Changyang; Wang, Xiuying; Eberl, Stefan; Fulham, Michael; Yin, Yong; Dagan Feng, David

    2015-01-01

    Automated and general medical image segmentation can be challenging because the foreground and the background may have complicated and overlapping density distributions in medical imaging. Conventional region-based level set algorithms often assume piecewise constant or piecewise smooth for segments, which are implausible for general medical image segmentation. Furthermore, low contrast and noise make identification of the boundaries between foreground and background difficult for edge-based level set algorithms. Thus, to address these problems, we suggest a supervised variational level set segmentation model to harness the statistical region energy functional with a weighted probability approximation. Our approach models the region density distributions by using the mixture-of-mixtures Gaussian model to better approximate real intensity distributions and distinguish statistical intensity differences between foreground and background. The region-based statistical model in our algorithm can intuitively provide better performance on noisy images. We constructed a weighted probability map on graphs to incorporate spatial indications from user input with a contextual constraint based on the minimization of contextual graphs energy functional. We measured the performance of our approach on ten noisy synthetic images and 58 medical datasets with heterogeneous intensities and ill-defined boundaries and compared our technique to the Chan-Vese region-based level set model, the geodesic active contour model with distance regularization, and the random walker model. Our method consistently achieved the highest Dice similarity coefficient when compared to the other methods.

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

    Science.gov (United States)

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

    2018-03-01

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

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

    Science.gov (United States)

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

    2014-01-01

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

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

    DEFF Research Database (Denmark)

    Hansen, Michael Schacht; Sørensen, Thomas Sangild

    2013-01-01

    with a set of dedicated toolboxes in shared libraries for medical image reconstruction. This includes generic toolboxes for data-parallel (e.g., GPU-based) execution of compute-intensive components. The basic framework architecture is independent of medical imaging modality, but this article focuses on its...

  5. Scoring of radiation-induced micronuclei in cytokinesis-blocked human lymphocytes by automated image analysis

    International Nuclear Information System (INIS)

    Verhaegen, F.; Seuntjens, J.; Thierens, H.

    1994-01-01

    The micronucleus assay in human lymphocytes is, at present, frequently used to assess chromosomal damage caused by ionizing radiation or mutagens. Manual scoring of micronuclei (MN) by trained personnel is very time-consuming, tiring work, and the results depend on subjective interpretation of scoring criteria. More objective scoring can be accomplished only if the test can be automated. Furthermore, an automated system allows scoring of large numbers of cells, thereby increasing the statistical significance of the results. This is of special importance for screening programs for low doses of chromosome-damaging agents. In this paper, the first results of our effort to automate the micronucleus assay with an image-analysis system are represented. The method we used is described in detail, and the results are compared to those of other groups. Our system is able to detect 88% of the binucleated lymphocytes on the slides. The procedure consists of a fully automated localization of binucleated cells and counting of the MN within these cells, followed by a simple and fast manual operation in which the false positives are removed. Preliminary measurements for blood samples irradiated with a dose of 1 Gy X-rays indicate that the automated system can find 89% ± 12% of the micronuclei within the binucleated cells compared to a manual screening. 18 refs., 8 figs., 1 tab

  6. AUTOMATED INSPECTION OF POWER LINE CORRIDORS TO MEASURE VEGETATION UNDERCUT USING UAV-BASED IMAGES

    Directory of Open Access Journals (Sweden)

    M. Maurer

    2017-08-01

    Full Text Available Power line corridor inspection is a time consuming task that is performed mostly manually. As the development of UAVs made huge progress in recent years, and photogrammetric computer vision systems became well established, it is time to further automate inspection tasks. In this paper we present an automated processing pipeline to inspect vegetation undercuts of power line corridors. For this, the area of inspection is reconstructed, geo-referenced, semantically segmented and inter class distance measurements are calculated. The presented pipeline performs an automated selection of the proper 3D reconstruction method for on the one hand wiry (power line, and on the other hand solid objects (surrounding. The automated selection is realized by performing pixel-wise semantic segmentation of the input images using a Fully Convolutional Neural Network. Due to the geo-referenced semantic 3D reconstructions a documentation of areas where maintenance work has to be performed is inherently included in the distance measurements and can be extracted easily. We evaluate the influence of the semantic segmentation according to the 3D reconstruction and show that the automated semantic separation in wiry and dense objects of the 3D reconstruction routine improves the quality of the vegetation undercut inspection. We show the generalization of the semantic segmentation to datasets acquired using different acquisition routines and to varied seasons in time.

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

    Science.gov (United States)

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

    2013-12-01

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

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

    Science.gov (United States)

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

    1992-01-01

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

  9. Synthetic Aperture Imaging in Medical Ultrasound

    DEFF Research Database (Denmark)

    Nikolov, Svetoslav; Gammelmark, Kim; Pedersen, Morten

    2004-01-01

    with high precision, and the imaging is easily extended to real-time 3D scanning. This paper presents the work done at the Center for Fast Ultrasound Imaging in the area of SA imaging. Three areas that benefit from SA imaging are described. Firstly a preliminary in-vivo evaluation comparing conventional B...

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

    Science.gov (United States)

    Rojas de la Escalera, D

    2013-01-01

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

  11. Automated gas bubble imaging at sea floor - a new method of in situ gas flux quantification

    Science.gov (United States)

    Thomanek, K.; Zielinski, O.; Sahling, H.; Bohrmann, G.

    2010-06-01

    Photo-optical systems are common in marine sciences and have been extensively used in coastal and deep-sea research. However, due to technical limitations in the past photo images had to be processed manually or semi-automatically. Recent advances in technology have rapidly improved image recording, storage and processing capabilities which are used in a new concept of automated in situ gas quantification by photo-optical detection. The design for an in situ high-speed image acquisition and automated data processing system is reported ("Bubblemeter"). New strategies have been followed with regards to back-light illumination, bubble extraction, automated image processing and data management. This paper presents the design of the novel method, its validation procedures and calibration experiments. The system will be positioned and recovered from the sea floor using a remotely operated vehicle (ROV). It is able to measure bubble flux rates up to 10 L/min with a maximum error of 33% for worst case conditions. The Bubblemeter has been successfully deployed at a water depth of 1023 m at the Makran accretionary prism offshore Pakistan during a research expedition with R/V Meteor in November 2007.

  12. An image processing framework for automated analysis of swimming behavior in tadpoles with vestibular alterations

    Science.gov (United States)

    Zarei, Kasra; Fritzsch, Bernd; Buchholz, James H. J.

    2017-03-01

    Micogravity, as experienced during prolonged space flight, presents a problem for space exploration. Animal models, specifically tadpoles, with altered connections of the vestibular ear allow the examination of the effects of microgravity and can be quantitatively monitored through tadpole swimming behavior. We describe an image analysis framework for performing automated quantification of tadpole swimming behavior. Speckle reducing anisotropic diffusion is used to smooth tadpole image signals by diffusing noise while retaining edges. A narrow band level set approach is used for sharp tracking of the tadpole body. The use of level set method for interface tracking provides an inherent advantage of using level set based image segmentation algorithm (active contouring). Active contour segmentation is followed by two-dimensional skeletonization, which allows the automated quantification of tadpole deflection angles, and subsequently tadpole escape (or C-start) response times. Evaluation of the image analysis methodology was performed by comparing the automated quantifications of deflection angles to manual assessments (obtained using a standard grading scheme), and produced a high correlation (r2 = 0.99) indicating high reliability and accuracy of the proposed method. The methods presented form an important element of objective quantification of the escape response of the tadpole vestibular system to mechanical and biochemical manipulations, and can ultimately contribute to a better understanding of the effects of altered gravity perception on humans.

  13. Automated identification of Monogeneans using digital image processing and K-nearest neighbour approaches.

    Science.gov (United States)

    Yousef Kalafi, Elham; Tan, Wooi Boon; Town, Christopher; Dhillon, Sarinder Kaur

    2016-12-22

    Monogeneans are flatworms (Platyhelminthes) that are primarily found on gills and skin of fishes. Monogenean parasites have attachment appendages at their haptoral regions that help them to move about the body surface and feed on skin and gill debris. Haptoral attachment organs consist of sclerotized hard parts such as hooks, anchors and marginal hooks. Monogenean species are differentiated based on their haptoral bars, anchors, marginal hooks, reproductive parts' (male and female copulatory organs) morphological characters and soft anatomical parts. The complex structure of these diagnostic organs and also their overlapping in microscopic digital images are impediments for developing fully automated identification system for monogeneans (LNCS 7666:256-263, 2012), (ISDA; 457-462, 2011), (J Zoolog Syst Evol Res 52(2): 95-99. 2013;). In this study images of hard parts of the haptoral organs such as bars and anchors are used to develop a fully automated identification technique for monogenean species identification by implementing image processing techniques and machine learning methods. Images of four monogenean species namely Sinodiplectanotrema malayanus, Trianchoratus pahangensis, Metahaliotrema mizellei and Metahaliotrema sp. (undescribed) were used to develop an automated technique for identification. K-nearest neighbour (KNN) was applied to classify the monogenean specimens based on the extracted features. 50% of the dataset was used for training and the other 50% was used as testing for system evaluation. Our approach demonstrated overall classification accuracy of 90%. In this study Leave One Out (LOO) cross validation is used for validation of our system and the accuracy is 91.25%. The methods presented in this study facilitate fast and accurate fully automated classification of monogeneans at the species level. In future studies more classes will be included in the model, the time to capture the monogenean images will be reduced and improvements in

  14. Automated and effective content-based image retrieval for digital mammography.

    Science.gov (United States)

    Singh, Vibhav Prakash; Srivastava, Subodh; Srivastava, Rajeev

    2018-01-01

    Nowadays, huge number of mammograms has been generated in hospitals for the diagnosis of breast cancer. Content-based image retrieval (CBIR) can contribute more reliable diagnosis by classifying the query mammograms and retrieving similar mammograms already annotated by diagnostic descriptions and treatment results. Since labels, artifacts, and pectoral muscles present in mammograms can bias the retrieval procedures, automated detection and exclusion of these image noise patterns and/or non-breast regions is an essential pre-processing step. In this study, an efficient and automated CBIR system of mammograms was developed and tested. First, the pre-processing steps including automatic labelling-artifact suppression, automatic pectoral muscle removal, and image enhancement using the adaptive median filter were applied. Next, pre-processed images were segmented using the co-occurrence thresholds based seeded region growing algorithm. Furthermore, a set of image features including shape, histogram based statistical, Gabor, wavelet, and Gray Level Co-occurrence Matrix (GLCM) features, was computed from the segmented region. In order to select the optimal features, a minimum redundancy maximum relevance (mRMR) feature selection method was then applied. Finally, similar images were retrieved using Euclidean distance similarity measure. The comparative experiments conducted with reference to benchmark mammographic images analysis society (MIAS) database confirmed the effectiveness of the proposed work concerning average precision of 72% and 61.30% for normal & abnormal classes of mammograms, respectively.

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

    International Nuclear Information System (INIS)

    Flaberg, Emilie; Sabelström, Per; Strandh, Christer; Szekely, Laszlo

    2008-01-01

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

  16. Automated detection of diabetic retinopathy in retinal images

    Directory of Open Access Journals (Sweden)

    Carmen Valverde

    2016-01-01

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

  17. Automated extraction of metastatic liver cancer regions from abdominal contrast CT images

    International Nuclear Information System (INIS)

    Yamakawa, Junki; Matsubara, Hiroaki; Kimura, Shouta; Hasegawa, Junichi; Shinozaki, Kenji; Nawano, Shigeru

    2010-01-01

    In this paper, automated extraction of metastatic liver cancer regions from abdominal contrast X-ray CT images is investigated. Because even in Japan, cases of metastatic liver cancers are increased due to recent Europeanization and/or Americanization of Japanese eating habits, development of a system for computer aided diagnosis of them is strongly expected. Our automated extraction procedure consists of following four steps; liver region extraction, density transformation for enhancement of cancer regions, segmentation for obtaining candidate cancer regions, and reduction of false positives by shape feature. Parameter values used in each step of the procedure are decided based on density and shape features of typical metastatic liver cancers. In experiments using practical 20 cases of metastatic liver tumors, it is shown that 56% of true cancers can be detected successfully from CT images by the proposed procedure. (author)

  18. A Fully Automated Method to Detect and Segment a Manufactured Object in an Underwater Color Image

    Directory of Open Access Journals (Sweden)

    Phlypo Ronald

    2010-01-01

    Full Text Available We propose a fully automated active contours-based method for the detection and the segmentation of a moored manufactured object in an underwater image. Detection of objects in underwater images is difficult due to the variable lighting conditions and shadows on the object. The proposed technique is based on the information contained in the color maps and uses the visual attention method, combined with a statistical approach for the detection and an active contour for the segmentation of the object to overcome the above problems. In the classical active contour method the region descriptor is fixed and the convergence of the method depends on the initialization. With our approach, this dependence is overcome with an initialization using the visual attention results and a criterion to select the best region descriptor. This approach improves the convergence and the processing time while providing the advantages of a fully automated method.

  19. Extraction of prostatic lumina and automated recognition for prostatic calculus image using PCA-SVM.

    Science.gov (United States)

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

    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 classifier showed an average time 0.1432 second, an average training accuracy of 100%, an average test accuracy of 93.12%, a sensitivity of 87.74%, and a specificity of 94.82%. We concluded that the algorithm, based on texture features and PCA-SVM, can recognize the concentric structure and visualized features easily. Therefore, this method is effective for the automated recognition of prostatic calculi.

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

    Science.gov (United States)

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

    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 classifier showed an average time 0.1432 second, an average training accuracy of 100%, an average test accuracy of 93.12%, a sensitivity of 87.74%, and a specificity of 94.82%. We concluded that the algorithm, based on texture features and PCA-SVM, can recognize the concentric structure and visualized features easily. Therefore, this method is effective for the automated recognition of prostatic calculi. PMID:21461364

  1. Automated Image-Based Procedures for Adaptive Radiotherapy

    DEFF Research Database (Denmark)

    Bjerre, Troels

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

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

    International Nuclear Information System (INIS)

    Basit, M.A.

    2012-01-01

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

  3. An efficient similarity measure technique for medical image registration

    Indian Academy of Sciences (India)

    In this paper, an efficient similarity measure technique is proposed for medical image registration. The proposed approach is based on the Gerschgorin circles theorem. In this approach, image registration is carried out by considering Gerschgorin bounds of a covariance matrix of two compared images with normalized ...

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

    DEFF Research Database (Denmark)

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

    2012-01-01

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

  5. The impact of air pollution on the level of micronuclei measured by automated image analysis

    Czech Academy of Sciences Publication Activity Database

    Rössnerová, Andrea; Špátová, Milada; Rossner, P.; Solanský, I.; Šrám, Radim

    2009-01-01

    Roč. 669, 1-2 (2009), s. 42-47 ISSN 0027-5107 R&D Projects: GA AV ČR 1QS500390506; GA MŠk 2B06088; GA MŠk 2B08005 Institutional research plan: CEZ:AV0Z50390512 Keywords : micronuclei * binucleated cells * automated image analysis Subject RIV: DN - Health Impact of the Environment Quality Impact factor: 3.556, year: 2009

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

    Directory of Open Access Journals (Sweden)

    Benjamin M. Gyori

    2014-01-01

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

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

    International Nuclear Information System (INIS)

    Santana, Priscila do Carmo

    2010-01-01

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

  8. Automated seed detection and three-dimensional reconstruction. I. Seed localization from fluoroscopic images or radiographs

    International Nuclear Information System (INIS)

    Tubic, Dragan; Zaccarin, Andre; Pouliot, Jean; Beaulieu, Luc

    2001-01-01

    An automated procedure for the detection of the position and the orientation of radioactive seeds on fluoroscopic images or scanned radiographs is presented. The extracted positions of seed centers and the orientations are used for three-dimensional reconstruction of permanent prostate implants. The extraction procedure requires several steps: correction of image intensifier distortions, normalization, background removal, automatic threshold selection, thresholding, and finally, moment analysis and classification of the connected components. The algorithm was tested on 75 fluoroscopic images. The results show that, on average, 92% of the seeds are detected automatically. The orientation is found with an error smaller than 5 deg. for 75% of the seeds. The orientation of overlapping seeds (10%) should be considered as an estimate at best. The image processing procedure can also be used for seed or catheter detection in CT images, with minor modifications

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

    Directory of Open Access Journals (Sweden)

    Petr Kotas

    2012-01-01

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

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

    Science.gov (United States)

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

    2009-09-01

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

  11. Photons-based medical imaging - Radiology, X-ray tomography, gamma and positrons tomography, optical imaging

    International Nuclear Information System (INIS)

    Fanet, H.; Dinten, J.M.; Moy, J.P.; Rinkel, J.; Buvat, I.; Da Silva, A.; Douek, P.; Peyrin, F.; Frija, G.; Trebossen, R.

    2010-01-01

    This book describes the different principles used in medical imaging. The detection aspects, the processing electronics and algorithms are detailed for the different techniques. This first tome analyses the photons-based techniques (X-rays, gamma rays and visible light). Content: 1 - physical background: radiation-matter interaction, consequences on detection and medical imaging; 2 - detectors for medical imaging; 3 - processing of numerical radiography images for quantization; 4 - X-ray tomography; 5 - positrons emission tomography: principles and applications; 6 - mono-photonic imaging; 7 - optical imaging; Index. (J.S.)

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

    Directory of Open Access Journals (Sweden)

    Sebastian Vetter

    2011-12-01

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

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

    Science.gov (United States)

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

    2015-10-01

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

  14. Automated color classification of urine dipstick image in urine examination

    Science.gov (United States)

    Rahmat, R. F.; Royananda; Muchtar, M. A.; Taqiuddin, R.; Adnan, S.; Anugrahwaty, R.; Budiarto, R.

    2018-03-01

    Urine examination using urine dipstick has long been used to determine the health status of a person. The economical and convenient use of urine dipstick is one of the reasons urine dipstick is still used to check people health status. The real-life implementation of urine dipstick is done manually, in general, that is by comparing it with the reference color visually. This resulted perception differences in the color reading of the examination results. In this research, authors used a scanner to obtain the urine dipstick color image. The use of scanner can be one of the solutions in reading the result of urine dipstick because the light produced is consistent. A method is required to overcome the problems of urine dipstick color matching and the test reference color that have been conducted manually. The method proposed by authors is Euclidean Distance, Otsu along with RGB color feature extraction method to match the colors on the urine dipstick with the standard reference color of urine examination. The result shows that the proposed approach was able to classify the colors on a urine dipstick with an accuracy of 95.45%. The accuracy of color classification on urine dipstick against the standard reference color is influenced by the level of scanner resolution used, the higher the scanner resolution level, the higher the accuracy.

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

    Science.gov (United States)

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

    2015-01-01

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

  16. Automated vehicle counting using image processing and machine learning

    Science.gov (United States)

    Meany, Sean; Eskew, Edward; Martinez-Castro, Rosana; Jang, Shinae

    2017-04-01

    Vehicle counting is used by the government to improve roadways and the flow of traffic, and by private businesses for purposes such as determining the value of locating a new store in an area. A vehicle count can be performed manually or automatically. Manual counting requires an individual to be on-site and tally the traffic electronically or by hand. However, this can lead to miscounts due to factors such as human error A common form of automatic counting involves pneumatic tubes, but pneumatic tubes disrupt traffic during installation and removal, and can be damaged by passing vehicles. Vehicle counting can also be performed via the use of a camera at the count site recording video of the traffic, with counting being performed manually post-recording or using automatic algorithms. This paper presents a low-cost procedure to perform automatic vehicle counting using remote video cameras with an automatic counting algorithm. The procedure would utilize a Raspberry Pi micro-computer to detect when a car is in a lane, and generate an accurate count of vehicle movements. The method utilized in this paper would use background subtraction to process the images and a machine learning algorithm to provide the count. This method avoids fatigue issues that are encountered in manual video counting and prevents the disruption of roadways that occurs when installing pneumatic tubes

  17. Automated anesthesia carts reduce drug recording errors in medication administrations - A single center study in the largest tertiary referral hospital in China.

    Science.gov (United States)

    Wang, Ying; Du, Yingying; Zhao, Yingying; Ren, Yang; Zhang, Wei

    2017-08-01

    To clinically evaluate a type of patented automated anesthesia cart in medication administrations in anesthesia. This was a prospectively randomized open label clinical trial. In 10 designated operating suits in the First Affiliated Hospital of Zhengzhou University, in China. 1066 cases originated from 10,812 medication administrations in anesthesia were randomized. 78 registered anesthesiologists managed the medication. The patients received medication administrations in anesthesia with either an automated or a conventional manual cart. American Society of Anesthesiologists (ASA) score, sex, duration of anesthesia and surgical specialty, errors in administration of medications (incorrect medication given (substitution), medication not given (omission) and drug recordings errors"), compliance and satisfaction were recorded. The total error rate was 7.3% with the automated anesthesia carts (1 in 14 administrations) and 11.9% with conventional manual carts (1 in 8 administrations). Automated anesthesia carts significantly reduced the drug recording error rate compared to conventional manual carts (Perrors omission errors was found between groups of automated anesthesia carts and conventional manual carts. The anesthesiologists' compliance with the automated anesthesia carts was unsatisfactory, and all the errors in medication recordings with the automated anesthesia carts were due to the incorrect use of the carts. Most of the participating anesthesiologists preferred the automated anesthesia carts (Perrors in medication administrations of anesthesia. Copyright © 2017 Elsevier Inc. All rights reserved.

  18. A survey of GPU-based medical image computing techniques

    Science.gov (United States)

    Shi, Lin; Liu, Wen; Zhang, Heye; Xie, Yongming

    2012-01-01

    Medical imaging currently plays a crucial role throughout the entire clinical applications from medical scientific research to diagnostics and treatment planning. However, medical imaging procedures are often computationally demanding due to the large three-dimensional (3D) medical datasets to process in practical clinical applications. With the rapidly enhancing performances of graphics processors, improved programming support, and excellent price-to-performance ratio, the graphics processing unit (GPU) has emerged as a competitive parallel computing platform for computationally expensive and demanding tasks in a wide range of medical image applications. The major purpose of this survey is to provide a comprehensive reference source for the starters or researchers involved in GPU-based medical image processing. Within this survey, the continuous advancement of GPU computing is reviewed and the existing traditional applications in three areas of medical image processing, namely, segmentation, registration and visualization, are surveyed. The potential advantages and associated challenges of current GPU-based medical imaging are also discussed to inspire future applications in medicine. PMID:23256080

  19. 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.

  20. Automated video analysis of non-verbal communication in a medical setting

    Directory of Open Access Journals (Sweden)

    Yuval Hart

    2016-08-01

    Full Text Available Non-verbal communication plays a significant role in establishing good rapport between physicians and patients and influences patient’s health outcomes. Therefore, it is important to measure and 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 of non-verbal interactions in a medical setting. We test the tool using videos of subjects that interact with an actor portraying a doctor performing one of two scripted scenarios of interviewing the subjects: in one scenario the actor was focused on his computer and briefly engaged with the subject. The second scenario included active listening by the doctor and heavy focus on 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 wide range of medical settings.

  1. 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.

  2. Effects of two types of medical contrast media on routine chemistry results by three automated chemistry analyzers.

    Science.gov (United States)

    Park, Yu Jin; Rim, John Hoon; Yim, Jisook; Lee, Sang-Guk; Kim, Jeong-Ho

    2017-08-01

    The use of iodinated contrast media has grown in popularity in the past two decades, but relatively little attention has been paid to the possible interferential effects of contrast media on laboratory test results. Herein, we investigate medical contrast media interference with routine chemistry results obtained by three automated chemistry analyzers. Ten levels of pooled serum were used in the study. Two types of medical contrast media [Iopamiro (iopamidol) and Omnipaque (iohexol)] were evaluated. To evaluate the dose-dependent effects of the contrast media, iopamidol and iohexol were spiked separately into aliquots of serum for final concentrations of 1.8%, 3.6%, 5.5%, 7.3%, and 9.1%. The 28 analytes included in the routine chemistry panel were measured by using Hitachi 7600, AU5800, and Cobas c702 analyzers. We calculated the delta percentage difference (DPD) between the samples and the control, and examined dose-dependent trends. When the mean DPD values were compared with the reference cut-off criteria, the only uniformly interferential effect observed for all analyzers was in total protein with iopamidol. Two additional analytes that showed trends toward interferential effects only in few analyzers and exceeded the limits of the allowable error were the serum iron and the total CO 2 . The other combinations of analyzer and contrast showed no consistent dose-dependent propensity for change in any analyte level. Our study suggests that many of the analytes included in routine chemistry results, except total protein and serum iron, are not significantly affected by iopamidol and iohexol. These results suggest that it would be beneficial to apply a flexible medical evaluation process for patients requiring both laboratory tests and imaging studies, minimizing the need for strict regulations for sequential tests. Copyright © 2017 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

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

    Science.gov (United States)

    Singh, Preetpal

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

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

    Directory of Open Access Journals (Sweden)

    B. Kuhlenkötter

    2006-01-01

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

  5. Automated recognition and characterization of solar active regions based on the SOHO/MDI images

    Science.gov (United States)

    Pap, J. M.; Turmon, M.; Mukhtar, S.; Bogart, R.; Ulrich, R.; Froehlich, C.; Wehrli, C.

    1997-01-01

    The first results of a new method to identify and characterize the various surface structures on the sun, which may contribute to the changes in solar total and spectral irradiance, are shown. The full disk magnetograms (1024 x 1024 pixels) of the Michelson Doppler Imager (MDI) experiment onboard SOHO are analyzed. Use of a Bayesian inference scheme allows objective, uniform, automated processing of a long sequence of images. The main goal is to identify the solar magnetic features causing irradiance changes. The results presented are based on a pilot time interval of August 1996.

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

    Science.gov (United States)

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

    2015-04-01

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

  7. Use of medical imaging as an epidemiologic tracer

    International Nuclear Information System (INIS)

    Dartigues, J.F.

    1987-01-01

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

  8. Real Time Medical Image Consultation System Through Internet

    Directory of Open Access Journals (Sweden)

    D. Durga Prasad

    2010-01-01

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

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

    Science.gov (United States)

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

    2017-02-01

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

  10. 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.

  11. An Automated Reference Frame Selection (ARFS) Algorithm for Cone Imaging with Adaptive Optics Scanning Light Ophthalmoscopy.

    Science.gov (United States)

    Salmon, Alexander E; Cooper, Robert F; Langlo, Christopher S; Baghaie, Ahmadreza; Dubra, Alfredo; Carroll, Joseph

    2017-04-01

    To develop an automated reference frame selection (ARFS) algorithm to replace the subjective approach of manually selecting reference frames for processing adaptive optics scanning light ophthalmoscope (AOSLO) videos of cone photoreceptors. Relative distortion was measured within individual frames before conducting image-based motion tracking and sorting of frames into distinct spatial clusters. AOSLO images from nine healthy subjects were processed using ARFS and human-derived reference frames, then aligned to undistorted AO-flood images by nonlinear registration and the registration transformations were compared. The frequency at which humans selected reference frames that were rejected by ARFS was calculated in 35 datasets from healthy subjects, and subjects with achromatopsia, albinism, or retinitis pigmentosa. The level of distortion in this set of human-derived reference frames was assessed. The average transformation vector magnitude required for registration of AOSLO images to AO-flood images was significantly reduced from 3.33 ± 1.61 pixels when using manual reference frame selection to 2.75 ± 1.60 pixels (mean ± SD) when using ARFS ( P = 0.0016). Between 5.16% and 39.22% of human-derived frames were rejected by ARFS. Only 2.71% to 7.73% of human-derived frames were ranked in the top 5% of least distorted frames. ARFS outperforms expert observers in selecting minimally distorted reference frames in AOSLO image sequences. The low success rate in human frame choice illustrates the difficulty in subjectively assessing image distortion. Manual reference frame selection represented a significant barrier to a fully automated image-processing pipeline (including montaging, cone identification, and metric extraction). The approach presented here will aid in the clinical translation of AOSLO imaging.

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

    OpenAIRE

    Mohammad Madadpour Inallou; Majid Pouladian; Bahman Mehri

    2013-01-01

    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, c...

  13. Quantification of Pulmonary Fibrosis in a Bleomycin Mouse Model Using Automated Histological Image Analysis.

    Directory of Open Access Journals (Sweden)

    Jean-Claude Gilhodes

    Full Text Available Current literature on pulmonary fibrosis induced in animal models highlights the need of an accurate, reliable and reproducible histological quantitative analysis. One of the major limits of histological scoring concerns the fact that it is observer-dependent and consequently subject to variability, which may preclude comparative studies between different laboratories. To achieve a reliable and observer-independent quantification of lung fibrosis we developed an automated software histological image analysis performed from digital image of entire lung sections. This automated analysis was compared to standard evaluation methods with regard to its validation as an end-point measure of fibrosis. Lung fibrosis was induced in mice by intratracheal administration of bleomycin (BLM at 0.25, 0.5, 0.75 and 1 mg/kg. A detailed characterization of BLM-induced fibrosis was performed 14 days after BLM administration using lung function testing, micro-computed tomography and Ashcroft scoring analysis. Quantification of fibrosis by automated analysis was assessed based on pulmonary tissue density measured from thousands of micro-tiles processed from digital images of entire lung sections. Prior to analysis, large bronchi and vessels were manually excluded from the original images. Measurement of fibrosis has been expressed by two indexes: the mean pulmonary tissue density and the high pulmonary tissue density frequency. We showed that tissue density indexes gave access to a very accurate and reliable quantification of morphological changes induced by BLM even for the lowest concentration used (0.25 mg/kg. A reconstructed 2D-image of the entire lung section at high resolution (3.6 μm/pixel has been performed from tissue density values allowing the visualization of their distribution throughout fibrotic and non-fibrotic regions. A significant correlation (p<0.0001 was found between automated analysis and the above standard evaluation methods. This correlation

  14. 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.

  15. Automated low-contrast pattern recognition algorithm for magnetic resonance image quality assessment.

    Science.gov (United States)

    Ehman, Morgan O; Bao, Zhonghao; Stiving, Scott O; Kasam, Mallik; Lanners, Dianna; Peterson, Teresa; Jonsgaard, Renee; Carter, Rickey; McGee, Kiaran P

    2017-08-01

    Low contrast (LC) detectability is a common test criterion for diagnostic radiologic quality control (QC) programs. Automation of this test is desirable in order to reduce human variability and to speed up analysis. However, automation is challenging due to the complexity of the human visual perception system and the ability to create algorithms that mimic this response. This paper describes the development and testing of an automated LC detection algorithm for use in the analysis of magnetic resonance (MR) images of the American College of Radiology (ACR) QC phantom. The detection algorithm includes fuzzy logic decision processes and various edge detection methods to quantify LC detectability. Algorithm performance was first evaluated using a single LC phantom MR image with the addition of incremental zero mean Gaussian noise resulting in a total of 200 images. A c-statistic was calculated to determine the role of CNR to indicate when the algorithm would detect ten spokes. To evaluate inter-rater agreement between experienced observers and the algorithm, a blinded observer study was performed on 196 LC phantom images acquired from nine clinical MR scanners. The nine scanners included two MR manufacturers and two field strengths (1.5 T, 3.0 T). Inter-rater and algorithm-rater agreement was quantified using Krippendorff's alpha. For the Gaussian noise added data, CNR ranged from 0.519 to 11.7 with CNR being considered an excellent discriminator of algorithm performance (c-statistic = 0.9777). Reviewer scoring of the clinical phantom data resulted in an inter-rater agreement of 0.673 with the agreement between observers and algorithm equal to 0.652, both of which indicate significant agreement. This study demonstrates that the detection of LC test patterns for MR imaging QC programs can be successfully developed and that their response can model the human visual detection system of expert MR QC readers. © 2017 American Association of Physicists in Medicine.

  16. Quantification of Pulmonary Fibrosis in a Bleomycin Mouse Model Using Automated Histological Image Analysis.

    Science.gov (United States)

    Gilhodes, Jean-Claude; Julé, Yvon; Kreuz, Sebastian; Stierstorfer, Birgit; Stiller, Detlef; Wollin, Lutz

    2017-01-01

    Current literature on pulmonary fibrosis induced in animal models highlights the need of an accurate, reliable and reproducible histological quantitative analysis. One of the major limits of histological scoring concerns the fact that it is observer-dependent and consequently subject to variability, which may preclude comparative studies between different laboratories. To achieve a reliable and observer-independent quantification of lung fibrosis we developed an automated software histological image analysis performed from digital image of entire lung sections. This automated analysis was compared to standard evaluation methods with regard to its validation as an end-point measure of fibrosis. Lung fibrosis was induced in mice by intratracheal administration of bleomycin (BLM) at 0.25, 0.5, 0.75 and 1 mg/kg. A detailed characterization of BLM-induced fibrosis was performed 14 days after BLM administration using lung function testing, micro-computed tomography and Ashcroft scoring analysis. Quantification of fibrosis by automated analysis was assessed based on pulmonary tissue density measured from thousands of micro-tiles processed from digital images of entire lung sections. Prior to analysis, large bronchi and vessels were manually excluded from the original images. Measurement of fibrosis has been expressed by two indexes: the mean pulmonary tissue density and the high pulmonary tissue density frequency. We showed that tissue density indexes gave access to a very accurate and reliable quantification of morphological changes induced by BLM even for the lowest concentration used (0.25 mg/kg). A reconstructed 2D-image of the entire lung section at high resolution (3.6 μm/pixel) has been performed from tissue density values allowing the visualization of their distribution throughout fibrotic and non-fibrotic regions. A significant correlation (pfibrosis in mice, which will be very valuable for future preclinical drug explorations.

  17. An automated algorithm for photoreceptors counting in adaptive optics retinal images

    Science.gov (United States)

    Liu, Xu; Zhang, Yudong; Yun, Dai

    2012-10-01

    Eyes are important organs of humans that detect light and form spatial and color vision. Knowing the exact number of cones in retinal image has great importance in helping us understand the mechanism of eyes' function and the pathology of some eye disease. In order to analyze data in real time and process large-scale data, an automated algorithm is designed to label cone photoreceptors in adaptive optics (AO) retinal images. Images acquired by the flood-illuminated AO system are taken to test the efficiency of this algorithm. We labeled these images both automatically and manually, and compared the results of the two methods. A 94.1% to 96.5% agreement rate between the two methods is achieved in this experiment, which demonstrated the reliability and efficiency of the algorithm.

  18. SAND: an automated VLBI imaging and analysing pipeline - I. Stripping component trajectories

    Science.gov (United States)

    Zhang, M.; Collioud, A.; Charlot, P.

    2018-02-01

    We present our implementation of an automated very long baseline interferometry (VLBI) data-reduction pipeline that is dedicated to interferometric data imaging and analysis. The pipeline can handle massive VLBI data efficiently, which makes it an appropriate tool to investigate multi-epoch multiband VLBI data. Compared to traditional manual data reduction, our pipeline provides more objective results as less human interference is involved. The source extraction is carried out in the image plane, while deconvolution and model fitting are performed in both the image plane and the uv plane for parallel comparison. The output from the pipeline includes catalogues of CLEANed images and reconstructed models, polarization maps, proper motion estimates, core light curves and multiband spectra. We have developed a regression STRIP algorithm to automatically detect linear or non-linear patterns in the jet component trajectories. This algorithm offers an objective method to match jet components at different epochs and to determine their proper motions.

  19. Medical Image Compression Based on Region of Interest, With Application to Colon CT Images

    National Research Council Canada - National Science Library

    Gokturk, Salih

    2001-01-01

    CT or MRI Medical imaging produce human body pictures in digital form. Since these imaging techniques produce prohibitive amounts of data, compression is necessary for storage and communication purposes...

  20. Ordering of diagnostic information in encoded medical images. Accuracy progression

    Science.gov (United States)

    Przelaskowski, A.; Jóźwiak, R.; Krzyżewski, T.; Wróblewska, A.

    2008-03-01

    A concept of diagnostic accuracy progression for embedded coding of medical images was presented. Implementation of JPEG2000 encoder with a modified PCRD optimization algorithm was realized and initially verified as a tool for accurate medical image streaming. Mean square error as a distortion measure was replaced by other numerical measures to revise quality progression according to diagnostic importance of successively encoded image information. A faster increment of image diagnostic importance during reconstruction of initial packets of code stream was reached. Modified Jasper code was initially tested on a set of mammograms containing clusters of microcalcifications and malignant masses, and other radiograms. Teleradiologic applications were considered as the first area of interests.

  1. [Principles of medical liability and practice in medical imaging].

    Science.gov (United States)

    Thibierge, M; Fournier, L; Cabanis, E A

    1999-07-01

    Radiologists are liable for all aspects of their practice, from the indication of an examination to the radiology report and follow-up, as well as for providing information and recommendations. They are liable for their decisions and actions. They are liable for their competence and continuous medical education. They are also liable for their own equipment and staff. In cases of litigation, the liability of a radiologist may be questioned. Four types of procedures must been known: penal, civil, administrative and disciplinary.

  2. Semi-automated camera trap image processing for the detection of ungulate fence crossing events.

    Science.gov (United States)

    Janzen, Michael; Visser, Kaitlyn; Visscher, Darcy; MacLeod, Ian; Vujnovic, Dragomir; Vujnovic, Ksenija

    2017-09-27

    Remote cameras are an increasingly important tool for ecological research. While remote camera traps collect field data with minimal human attention, the images they collect require post-processing and characterization before it can be ecologically and statistically analyzed, requiring the input of substantial time and money from researchers. The need for post-processing is due, in part, to a high incidence of non-target images. We developed a stand-alone semi-automated computer program to aid in image processing, categorization, and data reduction by employing background subtraction and histogram rules. Unlike previous work that uses video as input, our program uses still camera trap images. The program was developed for an ungulate fence crossing project and tested against an image dataset which had been previously processed by a human operator. Our program placed images into categories representing the confidence of a particular sequence of images containing a fence crossing event. This resulted in a reduction of 54.8% of images that required further human operator characterization while retaining 72.6% of the known fence crossing events. This program can provide researchers using remote camera data the ability to reduce the time and cost required for image post-processing and characterization. Further, we discuss how this procedure might be generalized to situations not specifically related to animal use of linear features.

  3. High-resolution imaging optomechatronics for precise liquid crystal display module bonding automated optical inspection

    Science.gov (United States)

    Ni, Guangming; Liu, Lin; Zhang, Jing; Liu, Juanxiu; Liu, Yong

    2018-01-01

    With the development of the liquid crystal display (LCD) module industry, LCD modules become more and more precise with larger sizes, which demands harsh imaging requirements for automated optical inspection (AOI). Here, we report a high-resolution and clearly focused imaging optomechatronics for precise LCD module bonding AOI inspection. It first presents and achieves high-resolution imaging for LCD module bonding AOI inspection using a line scan camera (LSC) triggered by a linear optical encoder, self-adaptive focusing for the whole large imaging region using LSC, and a laser displacement sensor, which reduces the requirements of machining, assembly, and motion control of AOI devices. Results show that this system can directly achieve clearly focused imaging for AOI inspection of large LCD module bonding with 0.8 μm image resolution, 2.65-mm scan imaging width, and no limited imaging width theoretically. All of these are significant for AOI inspection in the LCD module industry and other fields that require imaging large regions with high resolution.

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

    Science.gov (United States)

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

    2017-03-01

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

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

    Science.gov (United States)

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

    2017-04-01

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

  6. Automated data processing architecture for the Gemini Planet Imager Exoplanet Survey

    Science.gov (United States)

    Wang, Jason J.; Perrin, Marshall D.; Savransky, Dmitry; Arriaga, Pauline; Chilcote, Jeffrey K.; De Rosa, Robert J.; Millar-Blanchaer, Maxwell A.; Marois, Christian; Rameau, Julien; Wolff, Schuyler G.; Shapiro, Jacob; Ruffio, Jean-Baptiste; Maire, Jérôme; Marchis, Franck; Graham, James R.; Macintosh, Bruce; Ammons, S. Mark; Bailey, Vanessa P.; Barman, Travis S.; Bruzzone, Sebastian; Bulger, Joanna; Cotten, Tara; Doyon, René; Duchêne, Gaspard; Fitzgerald, Michael P.; Follette, Katherine B.; Goodsell, Stephen; Greenbaum, Alexandra Z.; Hibon, Pascale; Hung, Li-Wei; Ingraham, Patrick; Kalas, Paul; Konopacky, Quinn M.; Larkin, James E.; Marley, Mark S.; Metchev, Stanimir; Nielsen, Eric L.; Oppenheimer, Rebecca; Palmer, David W.; Patience, Jennifer; Poyneer, Lisa A.; Pueyo, Laurent; Rajan, Abhijith; Rantakyrö, Fredrik T.; Schneider, Adam C.; Sivaramakrishnan, Anand; Song, Inseok; Soummer, Remi; Thomas, Sandrine; Wallace, J. Kent; Ward-Duong, Kimberly; Wiktorowicz, Sloane J.

    2018-01-01

    The Gemini Planet Imager Exoplanet Survey (GPIES) is a multiyear direct imaging survey of 600 stars to discover and characterize young Jovian exoplanets and their environments. We have developed an automated data architecture to process and index all data related to the survey uniformly. An automated and flexible data processing framework, which we term the Data Cruncher, combines multiple data reduction pipelines (DRPs) together to process all spectroscopic, polarimetric, and calibration data taken with GPIES. With no human intervention, fully reduced and calibrated data products are available less than an hour after the data are taken to expedite follow up on potential objects of interest. The Data Cruncher can run on a supercomputer to reprocess all GPIES data in a single day as improvements are made to our DRPs. A backend MySQL database indexes all files, which are synced to the cloud, and a front-end web server allows for easy browsing of all files associated with GPIES. To help observers, quicklook displays show reduced data as they are processed in real time, and chatbots on Slack post observing information as well as reduced data products. Together, the GPIES automated data processing architecture reduces our workload, provides real-time data reduction, optimizes our observing strategy, and maintains a homogeneously reduced dataset to study planet occurrence and instrument performance.

  7. Comparative Cost-Effectiveness Analysis of Three Different Automated Medication Systems Implemented in a Danish Hospital Setting.

    Science.gov (United States)

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

    2018-02-01

    Automated medication systems have been found to reduce errors in the medication process, but little is known about the cost-effectiveness of such systems. The objective of this study was to perform a model-based indirect cost-effectiveness comparison of three different, real-world automated medication systems compared with current standard practice. The considered automated medication systems were a patient-specific automated medication system (psAMS), a non-patient-specific automated medication system (npsAMS), and a complex automated medication system (cAMS). The economic evaluation used original effect and cost data from prospective, controlled, before-and-after studies of medication systems implemented at a Danish hematological ward and an acute medical unit. Effectiveness was described as the proportion of clinical and procedural error opportunities that were associated with one or more errors. An error was defined as a deviation from the electronic prescription, from standard hospital policy, or from written procedures. The cost assessment was based on 6-month standardization of observed cost data. The model-based comparative cost-effectiveness analyses were conducted with system-specific assumptions of the effect size and costs in scenarios with consumptions of 15,000, 30,000, and 45,000 doses per 6-month period. With 30,000 doses the cost-effectiveness model showed that the cost-effectiveness ratio expressed as the cost per avoided clinical error was €24 for the psAMS, €26 for the npsAMS, and €386 for the cAMS. Comparison of the cost-effectiveness of the three systems in relation to different valuations of an avoided error showed that the psAMS was the most cost-effective system regardless of error type or valuation. The model-based indirect comparison against the conventional practice showed that psAMS and npsAMS were more cost-effective than the cAMS alternative, and that psAMS was more cost-effective than npsAMS.

  8. FUZZY BASED CONTRAST STRETCHING FOR MEDICAL IMAGE ENHANCEMENT

    Directory of Open Access Journals (Sweden)

    T.C. Raja Kumar

    2011-07-01

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

  9. Methodology for quantitative evaluation of diagnostic medical imaging

    International Nuclear Information System (INIS)

    Metz, C.

    1980-01-01

    This report deals with the evaluation of the performance of diagnostic medical imaging procedures using the Receiver Operating Characteristic or ROC analysis. The development of new tests for the statistical significance of apparent differences between ROC curves is discussed

  10. An Automated MR Image Segmentation System Using Multi-layer Perceptron Neural Network

    Directory of Open Access Journals (Sweden)

    Amiri S

    2013-12-01

    Full Text Available Background: Brain tissue segmentation for delineation of 3D anatomical structures from magnetic resonance (MR images can be used for neuro-degenerative disorders, characterizing morphological differences between subjects based on volumetric analysis of gray matter (GM, white matter (WM and cerebrospinal fluid (CSF, but only if the obtained segmentation results are correct. Due to image artifacts such as noise, low contrast and intensity non-uniformity, there are some classifcation errors in the results of image segmentation. Objective: An automated algorithm based on multi-layer perceptron neural networks (MLPNN is presented for segmenting MR images. The system is to identify two tissues of WM and GM in human brain 2D structural MR images. A given 2D image is processed to enhance image intensity and to remove extra cerebral tissue. Thereafter, each pixel of the image under study is represented using 13 features (8 statistical and 5 non- statistical features and is classifed using a MLPNN into one of the three classes WM and GM or unknown. Results: The developed MR image segmentation algorithm was evaluated using 20 real images. Training using only one image, the system showed robust performance when tested using the remaining 19 images. The average Jaccard similarity index and Dice similarity metric for the GM and WM tissues were estimated to be 75.7 %, 86.0% for GM, and 67.8% and 80.7%for WM, respectively. Conclusion: The obtained performances are encouraging and show that the presented method may assist with segmentation of 2D MR images especially where categorizing WM and GM is of interest.

  11. Automated Adaptive Brightness in Wireless Capsule Endoscopy Using Image Segmentation and Sigmoid Function.

    Science.gov (United States)

    Shrestha, Ravi; Mohammed, Shahed K; Hasan, Md Mehedi; Zhang, Xuechao; Wahid, Khan A

    2016-08-01

    Wireless capsule endoscopy (WCE) plays an important role in the diagnosis of gastrointestinal (GI) diseases by capturing images of human small intestine. Accurate diagnosis of endoscopic images depends heavily on the quality of captured images. Along with image and frame rate, brightness of the image is an important parameter that influences the image quality which leads to the design of an efficient illumination system. Such design involves the choice and placement of proper light source and its ability to illuminate GI surface with proper brightness. Light emitting diodes (LEDs) are normally used as sources where modulated pulses are used to control LED's brightness. In practice, instances like under- and over-illumination are very common in WCE, where the former provides dark images and the later provides bright images with high power consumption. In this paper, we propose a low-power and efficient illumination system that is based on an automated brightness algorithm. The scheme is adaptive in nature, i.e., the brightness level is controlled automatically in real-time while the images are being captured. The captured images are segmented into four equal regions and the brightness level of each region is calculated. Then an adaptive sigmoid function is used to find the optimized brightness level and accordingly a new value of duty cycle of the modulated pulse is generated to capture future images. The algorithm is fully implemented in a capsule prototype and tested with endoscopic images. Commercial capsules like Pillcam and Mirocam were also used in the experiment. The results show that the proposed algorithm works well in controlling the brightness level accordingly to the environmental condition, and as a result, good quality images are captured with an average of 40% brightness level that saves power consumption of the capsule.

  12. An Automated MR Image Segmentation System Using Multi-layer Perceptron Neural Network.

    Science.gov (United States)

    Amiri, S; Movahedi, M M; Kazemi, K; Parsaei, H

    2013-12-01

    Brain tissue segmentation for delineation of 3D anatomical structures from magnetic resonance (MR) images can be used for neuro-degenerative disorders, characterizing morphological differences between subjects based on volumetric analysis of gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF), but only if the obtained segmentation results are correct. Due to image artifacts such as noise, low contrast and intensity non-uniformity, there are some classification errors in the results of image segmentation. An automated algorithm based on multi-layer perceptron neural networks (MLPNN) is presented for segmenting MR images. The system is to identify two tissues of WM and GM in human brain 2D structural MR images. A given 2D image is processed to enhance image intensity and to remove extra cerebral tissue. Thereafter, each pixel of the image under study is represented using 13 features (8 statistical and 5 non- statistical features) and is classified using a MLPNN into one of the three classes WM and GM or unknown. The developed MR image segmentation algorithm was evaluated using 20 real images. Training using only one image, the system showed robust performance when tested using the remaining 19 images. The average Jaccard similarity index and Dice similarity metric for the GM and WM tissues were estimated to be 75.7 %, 86.0% for GM, and 67.8% and 80.7%for WM, respectively. The obtained performances are encouraging and show that the presented method may assist with segmentation of 2D MR images especially where categorizing WM and GM is of interest.

  13. A Kalman filter technique applied for medical image reconstruction

    International Nuclear Information System (INIS)

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

    2011-01-01

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

  14. 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.

  15. SlideJ: An ImageJ plugin for automated processing of whole slide images.

    Directory of Open Access Journals (Sweden)

    Vincenzo Della Mea

    Full Text Available The digital slide, or Whole Slide Image, is a digital image, acquired with specific scanners, that represents a complete tissue sample or cytological specimen at microscopic level. While Whole Slide image analysis is recognized among the most interesting opportunities, the typical size of such images-up to Gpixels- can be very demanding in terms of memory requirements. Thus, while algorithms and tools for processing and analysis of single microscopic field images are available, Whole Slide images size makes the direct use of such tools prohibitive or impossible. In this work a plugin for ImageJ, named SlideJ, is proposed with the objective to seamlessly extend the application of image analysis algorithms implemented in ImageJ for single microscopic field images to a whole digital slide analysis. The plugin has been complemented by examples of macro in the ImageJ scripting language to demonstrate its use in concrete situations.

  16. Microscope image based fully automated stomata detection and pore measurement method for grapevines

    Directory of Open Access Journals (Sweden)

    Hiranya Jayakody

    2017-11-01

    Full Text Available Abstract Background Stomatal behavior in grapevines has been identified as a good indicator of the water stress level and overall health of the plant. Microscope images are often used to analyze stomatal behavior in plants. However, most of the current approaches involve manual measurement of stomatal features. The main aim of this research is to develop a fully automated stomata detection and pore measurement method for grapevines, taking microscope images as the input. The proposed approach, which employs machine learning and image processing techniques, can outperform available manual and semi-automatic methods used to identify and estimate stomatal morphological features. Results First, a cascade object detection learning algorithm is developed to correctly identify multiple stomata in a large microscopic image. Once the regions of interest which contain stomata are identified and extracted, a combination of image processing techniques are applied to estimate the pore dimensions of the stomata. The stomata detection approach was compared with an existing fully automated template matching technique and a semi-automatic maximum stable extremal regions approach, with the proposed method clearly surpassing the performance of the existing techniques with a precision of 91.68% and an F1-score of 0.85. Next, the morphological features of the detected stomata were measured. Contrary to existing approaches, the proposed image segmentation and skeletonization method allows us to estimate the pore dimensions even in cases where the stomatal pore boundary is only partially visible in the microscope image. A test conducted using 1267 images of stomata showed that the segmentation and skeletonization approach was able to correctly identify the stoma opening 86.27% of the time. Further comparisons made with manually traced stoma openings indicated that the proposed method is able to estimate stomata morphological features with accuracies of 89.03% for area

  17. Microscope image based fully automated stomata detection and pore measurement method for grapevines.

    Science.gov (United States)

    Jayakody, Hiranya; Liu, Scarlett; Whitty, Mark; Petrie, Paul

    2017-01-01

    Stomatal behavior in grapevines has been identified as a good indicator of the water stress level and overall health of the plant. Microscope images are often used to analyze stomatal behavior in plants. However, most of the current approaches involve manual measurement of stomatal features. The main aim of this research is to develop a fully automated stomata detection and pore measurement method for grapevines, taking microscope images as the input. The proposed approach, which employs machine learning and image processing techniques, can outperform available manual and semi-automatic methods used to identify and estimate stomatal morphological features. First, a cascade object detection learning algorithm is developed to correctly identify multiple stomata in a large microscopic image. Once the regions of interest which contain stomata are identified and extracted, a combination of image processing techniques are applied to estimate the pore dimensions of the stomata. The stomata detection approach was compared with an existing fully automated template matching technique and a semi-automatic maximum stable extremal regions approach, with the proposed method clearly surpassing the performance of the existing techniques with a precision of 91.68% and an F1-score of 0.85. Next, the morphological features of the detected stomata were measured. Contrary to existing approaches, the proposed image segmentation and skeletonization method allows us to estimate the pore dimensions even in cases where the stomatal pore boundary is only partially visible in the microscope image. A test conducted using 1267 images of stomata showed that the segmentation and skeletonization approach was able to correctly identify the stoma opening 86.27% of the time. Further comparisons made with manually traced stoma openings indicated that the proposed method is able to estimate stomata morphological features with accuracies of 89.03% for area, 94.06% for major axis length, 93.31% for minor

  18. [A novel image processing and analysis system for medical images based on IDL language].

    Science.gov (United States)

    Tang, Min

    2009-08-01

    Medical image processing and analysis system, which is of great value in medical research and clinical diagnosis, has been a focal field in recent years. Interactive data language (IDL) has a vast library of built-in math, statistics, image analysis and information processing routines, therefore, it has become an ideal software for interactive analysis and visualization of two-dimensional and three-dimensional scientific datasets. The methodology is proposed to design a novel image processing and analysis system for medical images based on IDL. There are five functional modules in this system: Image Preprocessing, Image Segmentation, Image Reconstruction, Image Measurement and Image Management. Experimental results demonstrate that this system is effective and efficient, and it has the advantages of extensive applicability, friendly interaction, convenient extension and favorable transplantation.

  19. An Automated Tracking Approach for Extraction of Retinal Vasculature in Fundus Images

    Directory of Open Access Journals (Sweden)

    Alireza Osareh

    2010-01-01

    Full Text Available Purpose: To present a novel automated method for tracking and detection of retinal blood vessels in fundus images. Methods: For every pixel in retinal images, a feature vector was computed utilizing multiscale analysis based on Gabor filters. To classify the pixels based on their extracted features as vascular or non-vascular, various classifiers including Quadratic Gaussian (QG, K-Nearest Neighbors (KNN, and Neural Networks (NN were investigated. The accuracy of classifiers was evaluated using Receiver Operating Characteristic (ROC curve analysis in addition to sensitivity and specificity measurements. We opted for an NN model due to its superior performance in classification of retinal pixels as vascular and non-vascular. Results: The proposed method achieved an overall accuracy of 96.9%, sensitivity of 96.8%, and specificity of 97.3% for identification of retinal blood vessels using a dataset of 40 images. The area under the ROC curve reached a value of 0.967. Conclusion: Automated tracking and identification of retinal blood vessels based on Gabor filters and neural network classifiers seems highly successful. Through a comprehensive optimization process of operational parameters, our proposed scheme does not require any user intervention and has consistent performance for both normal and abnormal images.

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

    Science.gov (United States)

    Jiang, Luan; Ling, Shan; Li, Qiang

    2016-03-01

    Cardiovascular diseases are becoming a leading cause of death all over the world. The cardiac function could be evaluated by global and regional parameters of left ventricle (LV) of the heart. The purpose of this study is to develop and evaluate a fully automated scheme for segmentation of LV in short axis cardiac cine MR images. Our fully automated method consists of three major steps, i.e., LV localization, LV segmentation at end-diastolic phase, and LV segmentation propagation to the other phases. First, the maximum intensity projection image along the time phases of the midventricular slice, located at the center of the image, was calculated to locate the region of interest of LV. Based on the mean intensity of the roughly segmented blood pool in the midventricular slice at each phase, end-diastolic (ED) and end-systolic (ES) phases were determined. Second, the endocardial and epicardial boundaries of LV of each slice at ED phase were synchronously delineated by use of a dual dynamic programming technique. The external costs of the endocardial and epicardial boundaries were defined with the gradient values obtained from the original and enhanced images, respectively. Finally, with the advantages of the continuity of the boundaries of LV across adjacent phases, we propagated the LV segmentation from the ED phase to the other phases by use of dual dynamic programming technique. The preliminary results on 9 clinical cardiac cine MR cases show that the proposed method can obtain accurate segmentation of LV based on subjective evaluation.