WorldWideScience

Sample records for medical image transfer

  1. Deep Learning- and Transfer Learning-Based Super Resolution Reconstruction from Single Medical Image

    Directory of Open Access Journals (Sweden)

    YiNan Zhang

    2017-01-01

    Full Text Available Medical images play an important role in medical diagnosis and research. In this paper, a transfer learning- and deep learning-based super resolution reconstruction method is introduced. The proposed method contains one bicubic interpolation template layer and two convolutional layers. The bicubic interpolation template layer is prefixed by mathematics deduction, and two convolutional layers learn from training samples. For saving training medical images, a SIFT feature-based transfer learning method is proposed. Not only can medical images be used to train the proposed method, but also other types of images can be added into training dataset selectively. In empirical experiments, results of eight distinctive medical images show improvement of image quality and time reduction. Further, the proposed method also produces slightly sharper edges than other deep learning approaches in less time and it is projected that the hybrid architecture of prefixed template layer and unfixed hidden layers has potentials in other applications.

  2. Image quality transfer and applications in diffusion MRI

    DEFF Research Database (Denmark)

    Alexander, Daniel C.; Zikic, Darko; Ghosh, Aurobrata

    2017-01-01

    This paper introduces a new computational imaging technique called image quality transfer (IQT). IQT uses machine learning to transfer the rich information available from one-off experimental medical imaging devices to the abundant but lower-quality data from routine acquisitions. The procedure u...

  3. Transfer function analysis of radiographic imaging systems

    International Nuclear Information System (INIS)

    Metz, C.E.; Doi, K.

    1979-01-01

    The theoretical and experimental aspects of the techniques of transfer function analysis used in radiographic imaging systems are reviewed. The mathematical principles of transfer function analysis are developed for linear, shift-invariant imaging systems, for the relation between object and image and for the image due to a sinusoidal plane wave object. The other basic mathematical principle discussed is 'Fourier analysis' and its application to an input function. Other aspects of transfer function analysis included are alternative expressions for the 'optical transfer function' of imaging systems and expressions are derived for both serial and parallel transfer image sub-systems. The applications of transfer function analysis to radiographic imaging systems are discussed in relation to the linearisation of the radiographic imaging system, the object, the geometrical unsharpness, the screen-film system unsharpness, other unsharpness effects and finally noise analysis. It is concluded that extensive theoretical, computer simulation and experimental studies have demonstrated that the techniques of transfer function analysis provide an accurate and reliable means for predicting and understanding the effects of various radiographic imaging system components in most practical diagnostic medical imaging situations. (U.K.)

  4. 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.

  5. Luminescence in medical image science

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

    2016-01-15

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

  6. Stereoscopic medical imaging collaboration system

    Science.gov (United States)

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

    2007-02-01

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

  7. Image quality evaluation of medical color and monochrome displays using an imaging colorimeter

    Science.gov (United States)

    Roehrig, Hans; Gu, Xiliang; Fan, Jiahua

    2012-10-01

    The purpose of this presentation is to demonstrate the means which permit examining the accuracy of Image Quality with respect to MTF (Modulation Transfer Function) and NPS (Noise Power Spectrum) of Color Displays and Monochrome Displays. Indications were in the past that color displays could affect the clinical performance of color displays negatively compared to monochrome displays. Now colorimeters like the PM-1423 are available which have higher sensitivity and color accuracy than the traditional cameras like CCD cameras. Reference (1) was not based on measurements made with a colorimeter. This paper focuses on the measurements of physical characteristics of the spatial resolution and noise performance of color and monochrome medical displays which were made with a colorimeter and we will after this meeting submit the data to an ROC study so we have again a paper to present at a future SPIE Conference.Specifically, Modulation Transfer Function (MTF) and Noise Power Spectrum (NPS) were evaluated and compared at different digital driving levels (DDL) between the two medical displays. This paper focuses on the measurements of physical characteristics of the spatial resolution and noise performance of color and monochrome medical displays which were made with a colorimeter and we will after this meeting submit the data to an ROC study so we have again a paper to present at a future Annual SPIE Conference. Specifically, Modulation Transfer Function (MTF) and Noise Power Spectrum (NPS) were evaluated and compared at different digital driving levels (DDL) between the two medical displays. The Imaging Colorimeter. Measurement of color image quality needs were done with an imaging colorimeter as it is shown below. Imaging colorimetry is ideally suited to FPD measurement because imaging systems capture spatial data generating millions of data points in a single measurement operation. The imaging colorimeter which was used was the PM-1423 from Radiant Imaging. It uses

  8. Acquiring skill at medical image inspection: learning localized in early visual processes

    Science.gov (United States)

    Sowden, Paul T.; Davies, Ian R. L.; Roling, Penny; Watt, Simon J.

    1997-04-01

    Acquisition of the skill of medical image inspection could be due to changes in visual search processes, 'low-level' sensory learning, and higher level 'conceptual learning.' Here, we report two studies that investigate the extent to which learning in medical image inspection involves low- level learning. Early in the visual processing pathway cells are selective for direction of luminance contrast. We exploit this in the present studies by using transfer across direction of contrast as a 'marker' to indicate the level of processing at which learning occurs. In both studies twelve observers trained for four days at detecting features in x- ray images (experiment one equals discs in the Nijmegen phantom, experiment two equals micro-calcification clusters in digitized mammograms). Half the observers examined negative luminance contrast versions of the images and the remainder examined positive contrast versions. On the fifth day, observers swapped to inspect their respective opposite contrast images. In both experiments leaning occurred across sessions. In experiment one, learning did not transfer across direction of luminance contrast, while in experiment two there was only partial transfer. These findings are consistent with the contention that some of the leaning was localized early in the visual processing pathway. The implications of these results for current medical image inspection training schedules are discussed.

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

    Science.gov (United States)

    Perera, Chandrashan Mahendra; Chakrabarti, Rahul

    2015-02-01

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

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

    Science.gov (United States)

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

    2018-05-01

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

  11. 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.

  12. An open architecture for medical image workstation

    Science.gov (United States)

    Liang, Liang; Hu, Zhiqiang; Wang, Xiangyun

    2005-04-01

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

  13. Remote transfer of PET images by internet

    International Nuclear Information System (INIS)

    Zuo Chuantao; Lin Xiangtong; Guan Yihui; Zhao Jun

    2003-01-01

    The methodology of PET image remote transfer by Internet has been explored. The original images were got with ECAT EXACT HR + PET, and then converted to Dicom format by Mview software. The Dicom images were transferred via Internet. Thus the PET images were transferred via Internet successfully. The ideal images were obtained away from 8 km. The transfer time of brain and whole body image was (37±3)s and (245±10)s respectively, while the transfer rate was (34.7±2.8) kbyte/s and (34.4±1.5)kbyte/s, respectively. The results showed that the remote transfer via Internet was feasible and practical

  14. From calorimetry to medical imaging: a shining example of successful transfer!

    CERN Multimedia

    Caroline Duc

    2012-01-01

    A team at CERN has drawn inspiration from calorimetry methods developed for high-energy physics to create a new positron-emission tomography system for use in medical imaging, which they’ve dubbed AX-PET. With support from European and American laboratories*, the project is reaching fruition, as initial tests confirm its promise.   Snapshot of a “phantom”, a test object, surrounded by the AX-PET photon detectors. Positron-emission tomography (PET) is a medical imaging technique based on the matter-antimatter interaction that can provide a three-dimensional representation of the metabolic activity of an organ. To do so, radioactive marker molecules are first injected into the subject. As the marker decays, it emits positrons (antimatter particles), which are annihilated upon encountering electrons in the surrounding environment. The resulting flash, consisting of two photons, is detected by the PET machine. In conventional PET systems, it is impossible to improv...

  15. Resonance Energy Transfer Molecular Imaging Application in Biomedicine

    Directory of Open Access Journals (Sweden)

    NIE Da-hong1,2;TANG Gang-hua1,3

    2016-11-01

    Full Text Available Resonance energy transfer molecular imaging (RETI can markedly improve signal intensity and tissue penetrating capacity of optical imaging, and have huge potential application in the deep-tissue optical imaging in vivo. Resonance energy transfer (RET is an energy transition from the donor to an acceptor that is in close proximity, including non-radiative resonance energy transfer and radiative resonance energy transfer. RETI is an optical imaging technology that is based on RET. RETI mainly contains fluorescence resonance energy transfer imaging (FRETI, bioluminescence resonance energy transfer imaging (BRETI, chemiluminescence resonance energy transfer imaging (CRETI, and radiative resonance energy transfer imaging (RRETI. RETI is the hot field of molecular imaging research and has been widely used in the fields of biology and medicine. This review mainly focuses on RETI principle and application in biomedicine.

  16. Performance of asynchronous transfer mode (ATM) local area and wide area networks for medical imaging transmission in clinical environment.

    Science.gov (United States)

    Huang, H K; Wong, A W; Zhu, X

    1997-01-01

    Asynchronous transfer mode (ATM) technology emerges as a leading candidate for medical image transmission in both local area network (LAN) and wide area network (WAN) applications. This paper describes the performance of an ATM LAN and WAN network at the University of California, San Francisco. The measurements were obtained using an intensive care unit (ICU) server connecting to four image workstations (WS) at four different locations of a hospital-integrated picture archiving and communication system (HI-PACS) in a daily regular clinical environment. Four types of performance were evaluated: magnetic disk-to-disk, disk-to-redundant array of inexpensive disks (RAID), RAID-to-memory, and memory-to-memory. Results demonstrate that the transmission rate between two workstations can reach 5-6 Mbytes/s from RAID-to-memory, and 8-10 Mbytes/s from memory-to-memory. When the server has to send images to all four workstations simultaneously, the transmission rate to each WS is about 4 Mbytes/s. Both situations are adequate for radiologic image communications for picture archiving and communication systems (PACS) and teleradiology applications.

  17. 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...

  18. 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.

  19. Learning from incident reports in the Australian medical imaging setting: handover and communication errors.

    Science.gov (United States)

    Hannaford, N; Mandel, C; Crock, C; Buckley, K; Magrabi, F; Ong, M; Allen, S; Schultz, T

    2013-02-01

    To determine the type and nature of incidents occurring within medical imaging settings in Australia and identify strategies that could be engaged to reduce the risk of their re-occurrence. 71 search terms, related to clinical handover and communication, were applied to 3976 incidents in the Radiology Events Register. Detailed classification and thematic analysis of a subset of incidents that involved handover or communication (n=298) were undertaken to identify the most prevalent types of error and to make recommendations about patient safety initiatives in medical imaging. Incidents occurred most frequently during patient preparation (34%), when requesting imaging (27%) and when communicating a diagnosis (23%). Frequent problems within each of these stages of the imaging cycle included: inadequate handover of patients (41%) or unsafe or inappropriate transfer of the patient to or from medical imaging (35%); incorrect information on the request form (52%); and delayed communication of a diagnosis (36%) or communication of a wrong diagnosis (36%). The handover of patients and clinical information to and from medical imaging is fraught with error, often compromising patient safety and resulting in communication of delayed or wrong diagnoses, unnecessary radiation exposure and a waste of limited resources. Corrective strategies to address safety concerns related to new information technologies, patient transfer and inadequate test result notification policies are relevant to all healthcare settings. Handover and communication errors are prevalent in medical imaging. System-wide changes that facilitate effective communication are required.

  20. 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

  1. Development of a system for transferring images via a network: supporting a regional liaison.

    Science.gov (United States)

    Mihara, Naoki; Manabe, Shiro; Takeda, Toshihiro; Shinichirou, Kitamura; Junichi, Murakami; Kouji, Kiso; Matsumura, Yasushi

    2013-01-01

    We developed a system that transfers images via network and started using them in our hospital's PACS (Picture Archiving and Communication Systems) in 2006. We are pleased to report that the system has been re-developed and has been running so that there will be a regional liaison in the future. It has become possible to automatically transfer images simply by selecting the destination hospital that is registered in advance at the relay server. The gateway of this system can send images to a multi-center, relay management server, which receives the images and resends them. This system has the potential to be useful for image exchange, and to serve as a regional medical liaison.

  2. A Total Information Management System For All Medical Images

    Science.gov (United States)

    Ouimette, Donald; Nudelman, Sol; Ramsby, Gale; Spackman, Thomas

    1985-09-01

    A PACS has been designed for the University of Connecticut Health Center to serve all departments acquiring images for diagnosis, surgery and therapy. It incorporates a multiple community communications architecture to provide complete information management for medical images, medical data and departmental administrative matter. The system is modular and expandable. It permits an initial installation for radiology and subsequent expansion to include other departments at the Health Center, beginning with internal medicine, surgery, ophthalmology and dentistry. The design permits sufficient expansion to offer the potential for accepting the additional burden of a hospital information system. Primary parameters that led to this system design were based on the anticipation that departments in time could achieve generating 60 to 90% of their images suited to insertion in a PACS, that a high network throughput for large block image transfers would be essen-tial and that total system reliability was fundamental to success.

  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. Interactive visualization and analysis of 3D medical images for neurosurgery

    International Nuclear Information System (INIS)

    Miyazawa, Tatsuo; Otsuki, Taisuke.

    1994-01-01

    We propose a method that makes it possible to interactively rotate and zoom a volume-rendered object and to interactively manipulate a function for transferring data values to color and opacity. The method ray-traces a Value-Intensity-Strength volume (VIS volume) instead of a color-opacity volume, and uses an adaptive refinement technique in generating images. The VIS volume tracing method can reduce by 20-90 percent the computational time of re-calculation necessitated by changing the function for transferring data values to color and opacity, and can reduce the computational time of pre-processing by 20 percent. It can also reduce the required memory space by 40 percent. The combination of VIS volume tracing and adaptive refinement method makes it possible to interactively visualize and analyze 3D medical image data. Once we can see detailed image of 3D objects to determine their orientation, we can easily manipulate the viewing and rendering parameters even while viewing rough, blurred images. The increase in the computation time for generating full-resolution images by using the adaptive refinement technique is approximately five to ten percent. Its effectiveness is evaluated by using the results of visualization for some 3D medical image data. (author)

  5. 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.)

  6. Efficient medical image access in diagnostic environments with limited resources

    Directory of Open Access Journals (Sweden)

    José Eduardo Venson

    Full Text Available Abstract Introduction A medical application running outside the workstation environment has to deal with several constraints, such as reduced available memory and low network bandwidth. The aim of this paper is to present an approach to optimize the data flow for fast image transfer and visualization on mobile devices and remote stationary devices. Methods We use a combination of client- and server-side procedures to reduce the amount of information transferred by the application. Our approach was implemented on top of a commercial PACS and evaluated through user experiments with specialists in typical diagnosis tasks. The quality of the system outcome was measured in relation to the accumulated amount of network data transference and the amount of memory used in the host device. Besides, the system's quality of use (usability was measured through participants’ feedback. Results Contrarily to previous approaches, ours keeps the application within the memory constraints, minimizing data transferring whenever possible, allowing the application to run on a variety of devices. Moreover, it does that without sacrificing the user experience. Experimental data point that over 90% of the users did not notice any delays or degraded image quality, and when they did, they did not impact on the clinical decisions. Conclusion The combined activities and orchestration of our methods allow the image viewer to run on resource-constrained environments, such as those with low network bandwidth or little available memory. These results demonstrate the ability to explore the use of mobile devices as a support tool in the medical workflow.

  7. 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...

  8. 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

  9. Transfer learning improves supervised image segmentation across imaging protocols.

    Science.gov (United States)

    van Opbroek, Annegreet; Ikram, M Arfan; Vernooij, Meike W; de Bruijne, Marleen

    2015-05-01

    The variation between images obtained with different scanners or different imaging protocols presents a major challenge in automatic segmentation of biomedical images. This variation especially hampers the application of otherwise successful supervised-learning techniques which, in order to perform well, often require a large amount of labeled training data that is exactly representative of the target data. We therefore propose to use transfer learning for image segmentation. Transfer-learning techniques can cope with differences in distributions between training and target data, and therefore may improve performance over supervised learning for segmentation across scanners and scan protocols. We present four transfer classifiers that can train a classification scheme with only a small amount of representative training data, in addition to a larger amount of other training data with slightly different characteristics. The performance of the four transfer classifiers was compared to that of standard supervised classification on two magnetic resonance imaging brain-segmentation tasks with multi-site data: white matter, gray matter, and cerebrospinal fluid segmentation; and white-matter-/MS-lesion segmentation. The experiments showed that when there is only a small amount of representative training data available, transfer learning can greatly outperform common supervised-learning approaches, minimizing classification errors by up to 60%.

  10. Advances in medical image computing.

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

    2009-01-01

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

  11. Transfer learning improves supervised image segmentation across imaging protocols

    DEFF Research Database (Denmark)

    van Opbroek, Annegreet; Ikram, M. Arfan; Vernooij, Meike W.

    2015-01-01

    with slightly different characteristics. The performance of the four transfer classifiers was compared to that of standard supervised classification on two MRI brain-segmentation tasks with multi-site data: white matter, gray matter, and CSF segmentation; and white-matter- /MS-lesion segmentation......The variation between images obtained with different scanners or different imaging protocols presents a major challenge in automatic segmentation of biomedical images. This variation especially hampers the application of otherwise successful supervised-learning techniques which, in order to perform...... well, often require a large amount of labeled training data that is exactly representative of the target data. We therefore propose to use transfer learning for image segmentation. Transfer-learning techniques can cope with differences in distributions between training and target data, and therefore...

  12. A specialized plug-in software module for computer-aided quantitative measurement of medical images.

    Science.gov (United States)

    Wang, Q; Zeng, Y J; Huo, P; Hu, J L; Zhang, J H

    2003-12-01

    This paper presents a specialized system for quantitative measurement of medical images. Using Visual C++, we developed a computer-aided software based on Image-Pro Plus (IPP), a software development platform. When transferred to the hard disk of a computer by an MVPCI-V3A frame grabber, medical images can be automatically processed by our own IPP plug-in for immunohistochemical analysis, cytomorphological measurement and blood vessel segmentation. In 34 clinical studies, the system has shown its high stability, reliability and ease of utility.

  13. 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)

  14. 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.

  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. 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)

  17. Medical imaging

    International Nuclear Information System (INIS)

    Elliott, Alex

    2005-01-01

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

  18. 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 ...

  19. Not-so-supervised: a survey of semi-supervised, multi-instance, and transfer learning in medical image analysis

    NARCIS (Netherlands)

    Cheplygina, Veronika; de Bruijne, Marleen; Pluim, Josien P. W.

    2018-01-01

    Machine learning (ML) algorithms have made a tremendous impact in the field of medical imaging. While medical imaging datasets have been growing in size, a challenge for supervised ML algorithms that is frequently mentioned is the lack of annotated data. As a result, various methods which can learn

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

    Directory of Open Access Journals (Sweden)

    Tomi Kauppi

    2013-01-01

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

  1. Image processing in medical ultrasound

    DEFF Research Database (Denmark)

    Hemmsen, Martin Christian

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

  2. Structure of the medical digital image

    International Nuclear Information System (INIS)

    Baltadzhiev, D.

    1997-01-01

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

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

    Science.gov (United States)

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

    2008-12-01

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

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

    Science.gov (United States)

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

    2014-03-01

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

  5. Image Quality Characteristics of Handheld Display Devices for Medical Imaging

    Science.gov (United States)

    Yamazaki, Asumi; Liu, Peter; Cheng, Wei-Chung; Badano, Aldo

    2013-01-01

    Handheld devices such as mobile phones and tablet computers have become widespread with thousands of available software applications. Recently, handhelds are being proposed as part of medical imaging solutions, especially in emergency medicine, where immediate consultation is required. However, handheld devices differ significantly from medical workstation displays in terms of display characteristics. Moreover, the characteristics vary significantly among device types. We investigate the image quality characteristics of various handheld devices with respect to luminance response, spatial resolution, spatial noise, and reflectance. We show that the luminance characteristics of the handheld displays are different from those of workstation displays complying with grayscale standard target response suggesting that luminance calibration might be needed. Our results also demonstrate that the spatial characteristics of handhelds can surpass those of medical workstation displays particularly for recent generation devices. While a 5 mega-pixel monochrome workstation display has horizontal and vertical modulation transfer factors of 0.52 and 0.47 at the Nyquist frequency, the handheld displays released after 2011 can have values higher than 0.63 at the respective Nyquist frequencies. The noise power spectra for workstation displays are higher than 1.2×10−5 mm2 at 1 mm−1, while handheld displays have values lower than 3.7×10−6 mm2. Reflectance measurements on some of the handheld displays are consistent with measurements for workstation displays with, in some cases, low specular and diffuse reflectance coefficients. The variability of the characterization results among devices due to the different technological features indicates that image quality varies greatly among handheld display devices. PMID:24236113

  6. 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

  7. A service protocol for post-processing of medical images on the mobile device

    Science.gov (United States)

    He, Longjun; Ming, Xing; Xu, Lang; Liu, Qian

    2014-03-01

    With computing capability and display size growing, the mobile device has been used as a tool to help clinicians view patient information and medical images anywhere and anytime. It is uneasy and time-consuming for transferring medical images with large data size from picture archiving and communication system to mobile client, since the wireless network is unstable and limited by bandwidth. Besides, limited by computing capability, memory and power endurance, it is hard to provide a satisfactory quality of experience for radiologists to handle some complex post-processing of medical images on the mobile device, such as real-time direct interactive three-dimensional visualization. In this work, remote rendering technology is employed to implement the post-processing of medical images instead of local rendering, and a service protocol is developed to standardize the communication between the render server and mobile client. In order to make mobile devices with different platforms be able to access post-processing of medical images, the Extensible Markup Language is taken to describe this protocol, which contains four main parts: user authentication, medical image query/ retrieval, 2D post-processing (e.g. window leveling, pixel values obtained) and 3D post-processing (e.g. maximum intensity projection, multi-planar reconstruction, curved planar reformation and direct volume rendering). And then an instance is implemented to verify the protocol. This instance can support the mobile device access post-processing of medical image services on the render server via a client application or on the web page.

  8. Magnetic resonance imaging findings after rectus femoris transfer surgery

    International Nuclear Information System (INIS)

    Gold, Garry E.; Asakawa, Deanna S.; Blemker, Silvia S.; Delp, Scott L.

    2004-01-01

    We describe the magnetic resonance (MR) imaging appearance of the knee flexor and extensor tendons after bilateral rectus femoris transfer and hamstring lengthening surgery in five patients (10 limbs) with cerebral palsy. Three-dimensional models of the path of the transferred tendon were constructed in all cases. MR images of the transferred and lengthened tendons were examined and compared with images from ten non-surgical subjects. The models showed that the path of the transferred rectus femoris tendon had a marked angular deviation near the transfer site in all cases. MR imaging demonstrated irregular areas of low signal intensity near the transferred rectus femoris and around the hamstrings in all subjects. Eight of the ten post-surgical limbs showed evidence of fluid near or around the transferred or lengthened tendons. This was not observed in the non-surgical subjects. Thus, MR imaging of patients with cerebral palsy after rectus femoris transfer and hamstring-lengthening surgery shows evidence of signal intensity and contour changes, even several years after surgery. (orig.)

  9. 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

  10. Real-time transfer and display of radiography image

    International Nuclear Information System (INIS)

    Liu Ximing; Wu Zhifang; Miao Jicheng

    2000-01-01

    The information process network of cobalt-60 container inspection system is a local area network based on PC. The system requires reliable transfer of radiography image between collection station and process station and the real-time display of radiography image on process station. Due to the very high data acquisition rate, in order to realize the real-time transfer and display of radiography image, 100 M Ethernet technology and network process communication technology are adopted in the system. Windows Sockets is the most common process communication technology up to now. Several kinds of process communication way under Windows Sockets technology are compared and tested. Finally the author realized 1 Mbyte/s' inerrant image transfer and real-time display with blocked datagram transfer technology

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2002-09-15

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

  12. Medical imaging

    International Nuclear Information System (INIS)

    Loshkajian, A.

    2000-01-01

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

  13. Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning?

    OpenAIRE

    Tajbakhsh, Nima; Shin, Jae Y.; Gurudu, Suryakanth R.; Hurst, R. Todd; Kendall, Christopher B.; Gotway, Michael B.; Liang, Jianming

    2017-01-01

    Training a deep convolutional neural network (CNN) from scratch is difficult because it requires a large amount of labeled training data and a great deal of expertise to ensure proper convergence. A promising alternative is to fine-tune a CNN that has been pre-trained using, for instance, a large set of labeled natural images. However, the substantial differences between natural and medical images may advise against such knowledge transfer. In this paper, we seek to answer the following centr...

  14. 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

  15. 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.

  16. Medical Imaging Informatics in Nuclear Medicine

    NARCIS (Netherlands)

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

    2016-01-01

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

  17. 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

  18. 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.

  19. 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.

  20. Medical consultations and the sharing of medical images involving spinal injury over mobile phone networks.

    Science.gov (United States)

    Filip, Michal; Linzer, Petr; Šámal, Filip; Tesař, Jiří; Herzig, Roman; Školoudík, David

    2012-07-01

    The transmission of medical images and other data over mobile phone networks may facilitate remote medical consultations between neurosurgeons and regional hospitals treating spinal injury patients. The aim of this study was to compare the efficacy of mobile phone consultations with standard hospital workstation consultations in spinal injury patients. The images were exported over the Internet from surrounding local hospitals through the Picture Archiving and Communication System, in DICOM III format, to the central hospital server. The xVision browser was used to view the acquired images on a standard workstation. The data were also exported to the secured hospital Web server IIS60 and converted to JPEG format to enable remote physician access and consultation. The remote consulting physician connected to this server by mobile phone using the phone's Internet browser. A second physician, blind to the mobile phone results, evaluated the same images at a workstation in the hospital. The results of the mobile phone consultations were compared with the results from standard workstation consultations. There was no difference in the quality of spinal computed tomographic/magnetic resonance images viewed on the phone screen compared with on the workstation. More importantly, the final diagnoses made by mobile phone did not differ from those made by workstation consultations. A transfer to the department of neurosurgery was required after consultation in 11 patients. Mobile phone consultations for patients with spinal injuries was as effective as workstation consultations. Mobile phone consultations can increase the expertise available to regional hospitals, which are often the first responders to medical emergencies. Copyright © 2012 Elsevier Inc. All rights reserved.

  1. 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.)

  2. 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.)

  3. 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.

  4. Physical evaluation of color and monochrome medical displays using an imaging colorimeter

    Science.gov (United States)

    Roehrig, Hans; Gu, Xiliang; Fan, Jiahua

    2013-03-01

    This paper presents an approach to physical evaluation of color and monochrome medical grade displays using an imaging colorimeter. The purpose of this study was to examine the influence of medical display types, monochrome or color at the same maximum luminance settings, on diagnostic performance. The focus was on the measurements of physical characteristics including spatial resolution and noise performance, which we believed could affect the clinical performance. Specifically, Modulation Transfer Function (MTF) and Noise Power Spectrum (NPS) were evaluated and compared at different digital driving levels (DDL) between two EIZO displays.

  5. 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)

  6. The Physics of Imaging with Remote Sensors : Photon State Space & Radiative Transfer

    Science.gov (United States)

    Davis, Anthony B.

    2012-01-01

    Standard (mono-pixel/steady-source) retrieval methodology is reaching its fundamental limit with access to multi-angle/multi-spectral photo- polarimetry. Next... Two emerging new classes of retrieval algorithm worth nurturing: multi-pixel time-domain Wave-radiometry transition regimes, and more... Cross-fertilization with bio-medical imaging. Physics-based remote sensing: - What is "photon state space?" - What is "radiative transfer?" - Is "the end" in sight? Two wide-open frontiers! center dot Examples (with variations.

  7. 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.)

  8. Medical imaging and augmented reality. Proceedings

    Energy Technology Data Exchange (ETDEWEB)

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

    2008-07-01

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

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

    Science.gov (United States)

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

    1998-09-01

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

  10. [Medical image compression: a review].

    Science.gov (United States)

    Noreña, Tatiana; Romero, Eduardo

    2013-01-01

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

  11. Generative Interpretation of Medical Images

    DEFF Research Database (Denmark)

    Stegmann, Mikkel Bille

    2004-01-01

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

  12. Towards an ultra-thin medical endoscope: multimode fibre as a wide-field image transferring medium

    Science.gov (United States)

    Duriš, Miroslav; Bradu, Adrian; Podoleanu, Adrian; Hughes, Michael

    2018-03-01

    Multimode optical fibres are attractive for biomedical and industrial applications such as endoscopes because of the small cross section and imaging resolution they can provide in comparison to widely-used fibre bundles. However, the image is randomly scrambled by propagation through a multimode fibre. Even though the scrambling is unpredictable, it is deterministic, and therefore the scrambling can be reversed. To unscramble the image, we treat the multimode fibre as a linear, disordered scattering medium. To calibrate, we scan a focused beam of coherent light over thousands of different beam positions at the distal end and record complex fields at the proximal end of the fibre. This way, the inputoutput response of the system is determined, which then allows computational reconstruction of reflection-mode images. However, there remains the problem of illuminating the tissue via the fibre while avoiding back reflections from the proximal face. To avoid this drawback, we provide here the first preliminary confirmation that an image can be transferred through a 2x2 fibre coupler, with the sample at its distal port interrogated in reflection. Light is injected into one port for illumination and then collected from a second port for imaging.

  13. Medical Imaging with Neural Networks

    Energy Technology Data Exchange (ETDEWEB)

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

    1994-12-31

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

  14. 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

  15. Quantitative information in medical imaging

    International Nuclear Information System (INIS)

    Deconinck, F.

    1985-01-01

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

  16. 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

  17. Evidence based medical imaging (EBMI)

    International Nuclear Information System (INIS)

    Smith, Tony

    2008-01-01

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

  18. 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...

  19. Efficient nonlinear registration of 3D images using high order co-ordinate transfer functions.

    Science.gov (United States)

    Barber, D C

    1999-01-01

    There is an increasing interest in image registration for a variety of medical imaging applications. Image registration is achieved through the use of a co-ordinate transfer function (CTF) which maps voxels in one image to voxels in the other image, including in the general case changes in mapped voxel intensity. If images of the same subject are to be registered the co-ordinate transfer function needs to implement a spatial transformation consisting of a displacement and a rigid rotation. In order to achieve registration a common approach is to choose a suitable quality-of-registration measure and devise a method for the efficient generation of the parameters of the CTF which minimize this measure. For registration of images from different subjects more complex transforms are required. In general function minimization is too slow to allow the use of CTFs with more than a small number of parameters. However, provided the images are from the same modality and the CTF can be expanded in terms of an appropriate set of basis functions this paper will show how relatively complex CTFs can be used for registration. The use of increasingly complex CTFs to minimize the within group standard deviation of a set of normal single photon emission tomography brain images is used to demonstrate the improved registration of images from different subjects using CTFs of increasing complexity.

  20. 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

  1. 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

  2. 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.)

  3. Transfer and conversion of images based on EIT in atom vapor.

    Science.gov (United States)

    Cao, Mingtao; Zhang, Liyun; Yu, Ya; Ye, Fengjuan; Wei, Dong; Guo, Wenge; Zhang, Shougang; Gao, Hong; Li, Fuli

    2014-05-01

    Transfer and conversion of images between different wavelengths or polarization has significant applications in optical communication and quantum information processing. We demonstrated the transfer of images based on electromagnetically induced transparency (EIT) in a rubidium vapor cell. In experiments, a 2D image generated by a spatial light modulator is used as a coupling field, and a plane wave served as a signal field. We found that the image carried by coupling field could be transferred to that carried by signal field, and the spatial patterns of transferred image are much better than that of the initial image. It also could be much smaller than that determined by the diffraction limit of the optical system. We also studied the subdiffraction propagation for the transferred image. Our results may have applications in quantum interference lithography and coherent Raman spectroscopy.

  4. HVS-based medical image compression

    Energy Technology Data Exchange (ETDEWEB)

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

    2005-07-01

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

  5. 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

  6. 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.

  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. 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...

  9. Discriminative Transfer Learning for General Image Restoration

    KAUST Repository

    Xiao, Lei; Heide, Felix; Heidrich, Wolfgang; Schö lkopf, Bernhard; Hirsch, Michael

    2018-01-01

    Recently, several discriminative learning approaches have been proposed for effective image restoration, achieving convincing trade-off between image quality and computational efficiency. However, these methods require separate training for each restoration task (e.g., denoising, deblurring, demosaicing) and problem condition (e.g., noise level of input images). This makes it time-consuming and difficult to encompass all tasks and conditions during training. In this paper, we propose a discriminative transfer learning method that incorporates formal proximal optimization and discriminative learning for general image restoration. The method requires a single-pass discriminative training and allows for reuse across various problems and conditions while achieving an efficiency comparable to previous discriminative approaches. Furthermore, after being trained, our model can be easily transferred to new likelihood terms to solve untrained tasks, or be combined with existing priors to further improve image restoration quality.

  10. Discriminative Transfer Learning for General Image Restoration

    KAUST Repository

    Xiao, Lei

    2018-04-30

    Recently, several discriminative learning approaches have been proposed for effective image restoration, achieving convincing trade-off between image quality and computational efficiency. However, these methods require separate training for each restoration task (e.g., denoising, deblurring, demosaicing) and problem condition (e.g., noise level of input images). This makes it time-consuming and difficult to encompass all tasks and conditions during training. In this paper, we propose a discriminative transfer learning method that incorporates formal proximal optimization and discriminative learning for general image restoration. The method requires a single-pass discriminative training and allows for reuse across various problems and conditions while achieving an efficiency comparable to previous discriminative approaches. Furthermore, after being trained, our model can be easily transferred to new likelihood terms to solve untrained tasks, or be combined with existing priors to further improve image restoration quality.

  11. 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.

  12. Classification in Medical Imaging

    DEFF Research Database (Denmark)

    Chen, Chen

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

  13. Reducing noise component on medical images

    Science.gov (United States)

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

    2018-04-01

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

  14. Medical Imaging and Infertility.

    Science.gov (United States)

    Peterson, Rebecca

    2016-11-01

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

  15. Digital Signal Processing for Medical Imaging Using Matlab

    CERN Document Server

    Gopi, E S

    2013-01-01

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

  16. 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.

  17. A survey of medical diagnostic imaging technologies

    Energy Technology Data Exchange (ETDEWEB)

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

    1991-10-01

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

  18. A survey of medical diagnostic imaging technologies

    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

  19. Patient-directed Internet-based Medical Image Exchange: Experience from an Initial Multicenter Implementation.

    Science.gov (United States)

    Greco, Giampaolo; Patel, Anand S; Lewis, Sara C; Shi, Wei; Rasul, Rehana; Torosyan, Mary; Erickson, Bradley J; Hiremath, Atheeth; Moskowitz, Alan J; Tellis, Wyatt M; Siegel, Eliot L; Arenson, Ronald L; Mendelson, David S

    2016-02-01

    Inefficient transfer of personal health records among providers negatively impacts quality of health care and increases cost. This multicenter study evaluates the implementation of the first Internet-based image-sharing system that gives patients ownership and control of their imaging exams, including assessment of patient satisfaction. Patients receiving any medical imaging exams in four academic centers were eligible to have images uploaded into an online, Internet-based personal health record. Satisfaction surveys were provided during recruitment with questions on ease of use, privacy and security, and timeliness of access to images. Responses were rated on a five-point scale and compared using logistic regression and McNemar's test. A total of 2562 patients enrolled from July 2012 to August 2013. The median number of imaging exams uploaded per patient was 5. Most commonly, exams were plain X-rays (34.7%), computed tomography (25.7%), and magnetic resonance imaging (16.1%). Of 502 (19.6%) patient surveys returned, 448 indicated the method of image sharing (Internet, compact discs [CDs], both, other). Nearly all patients (96.5%) responded favorably to having direct access to images, and 78% reported viewing their medical images independently. There was no difference between Internet and CD users in satisfaction with privacy and security and timeliness of access to medical images. A greater percentage of Internet users compared to CD users reported access without difficulty (88.3% vs. 77.5%, P Internet-based image-sharing system is feasible and surpasses the use of CDs with respect to accessibility of imaging exams while generating similar satisfaction with respect to privacy. Copyright © 2015 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

  20. 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

  1. 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

  2. Paul Lecoq assembles a read head made with special crystals for a PET (positron emission tomography) scanner. He is the initiator of the Crystal Clear collaboration, which aims to transfer crystals developed at CERN to applications in medical imaging.

    CERN Multimedia

    Maximilien Brice

    2004-01-01

    Paul Lecoq assembles a read head made with special crystals for a PET (positron emission tomography) scanner. He is the initiator of the Crystal Clear collaboration, which aims to transfer crystals developed at CERN to applications in medical imaging.

  3. Medical image segmentation using genetic algorithms.

    Science.gov (United States)

    Maulik, Ujjwal

    2009-03-01

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

  4. Medical physics 2013. Abstracts

    International Nuclear Information System (INIS)

    Treuer, Harald

    2013-01-01

    The proceedings of the medical physics conference 2013 include abstract of lectures and poster sessions concerning the following issues: Tele-therapy - application systems, nuclear medicine and molecular imaging, neuromodulation, hearing and technical support, basic dosimetry, NMR imaging -CEST (chemical exchange saturation transfer), medical robotics, magnetic particle imaging, audiology, radiation protection, phase contrast - innovative concepts, particle therapy, brachytherapy, computerized tomography, quantity assurance, hybrid imaging techniques, diffusion and lung NMR imaging, image processing - visualization, cardiac and abdominal NMR imaging.

  5. A framework for secure and decentralized sharing of medical imaging data via blockchain consensus.

    Science.gov (United States)

    Patel, Vishal

    2018-04-01

    The electronic sharing of medical imaging data is an important element of modern healthcare systems, but current infrastructure for cross-site image transfer depends on trust in third-party intermediaries. In this work, we examine the blockchain concept, which enables parties to establish consensus without relying on a central authority. We develop a framework for cross-domain image sharing that uses a blockchain as a distributed data store to establish a ledger of radiological studies and patient-defined access permissions. The blockchain framework is shown to eliminate third-party access to protected health information, satisfy many criteria of an interoperable health system, and readily generalize to domains beyond medical imaging. Relative drawbacks of the framework include the complexity of the privacy and security models and an unclear regulatory environment. Ultimately, the large-scale feasibility of such an approach remains to be demonstrated and will depend on a number of factors which we discuss in detail.

  6. A survey of medical diagnostic imaging technologies

    Energy Technology Data Exchange (ETDEWEB)

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

    1991-10-01

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

  7. Medical image segmentation using improved FCM

    Institute of Scientific and Technical Information of China (English)

    ZHANG XiaoFeng; ZHANG CaiMing; TANG WenJing; WEI ZhenWen

    2012-01-01

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

  8. Past, present, and future of sublimation transfer imaging

    Science.gov (United States)

    Akada, Masanori

    1990-07-01

    SONY's announcement of tlavica system shaked the world in 1981. In the new nonphotographic imaging system, image is acquired with CCD to be converted into electric image-signal, stored in magnetic recording media,displayed on a CR1 and printed on a special sheet. To get a hard copy, Sublimation Transfer technology was developed. That announcement brought about world-wide R&D of competitive color imaging systems: Ink-jet, Wax transfer,. Sublimation Transfer(ST) and Electrophotography. In spite of much effort,most of those were insufficient for getting a good hard copy. Developing sufficient ST recording media, Dai Nippon Printing started ST recording media business in 1986. It was the first manufacturing scale production and sale of ST recording media in the world. Nowadays ST technology is known for its advantages: high image quality, consistency from copy to copy, smooth tone-reproduction from high-light to maximum density, and easiness to use. In the following paper progress of ST recording media and the present situation and future markets of the media will be presented.

  9. 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

  10. 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

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

    Science.gov (United States)

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

    2013-01-01

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

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

    Science.gov (United States)

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

    2013-05-01

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

  13. Amide Proton Transfer (APT) MR imaging and Magnetization Transfer (MT) MR imaging of pediatric brain development

    International Nuclear Information System (INIS)

    Zhang, Hong; Kang, Huiying; Peng, Yun; Zhao, Xuna; Jiang, Shanshan; Zhang, Yi; Zhou, Jinyuan

    2016-01-01

    To quantify the brain maturation process during childhood using combined amide proton transfer (APT) and conventional magnetization transfer (MT) imaging at 3 Tesla. Eighty-two neurodevelopmentally normal children (44 males and 38 females; age range, 2-190 months) were imaged using an APT/MT imaging protocol with multiple saturation frequency offsets. The APT-weighted (APTW) and MT ratio (MTR) signals were quantitatively analyzed in multiple brain areas. Age-related changes in MTR and APTW were evaluated with a non-linear regression analysis. The APTW signals followed a decreasing exponential curve with age in all brain regions measured (R"2 = 0.7-0.8 for the corpus callosum, frontal and occipital white matter, and centrum semiovale). The most significant changes appeared within the first year. At maturation, larger decreases in APTW and lower APTW values were found in the white matter. On the contrary, the MTR signals followed an increasing exponential curve with age in the same brain regions measured, with the most significant changes appearing within the initial 2 years. There was an inverse correlation between the MTR and APTW signal intensities during brain maturation. Together with MT imaging, protein-based APT imaging can provide additional information in assessing brain myelination in the paediatric population. (orig.)

  14. Amide Proton Transfer (APT) MR imaging and Magnetization Transfer (MT) MR imaging of pediatric brain development

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Hong; Kang, Huiying; Peng, Yun [Beijing Children' s Hospital, Capital Medical University, Imaging Center, Department of Radiology, Beijing (China); Zhao, Xuna [Philips Healthcare, Beijing (China); Jiang, Shanshan; Zhang, Yi; Zhou, Jinyuan [Johns Hopkins University, Division of MR Research, Department of Radiology, Baltimore, MD (United States)

    2016-10-15

    To quantify the brain maturation process during childhood using combined amide proton transfer (APT) and conventional magnetization transfer (MT) imaging at 3 Tesla. Eighty-two neurodevelopmentally normal children (44 males and 38 females; age range, 2-190 months) were imaged using an APT/MT imaging protocol with multiple saturation frequency offsets. The APT-weighted (APTW) and MT ratio (MTR) signals were quantitatively analyzed in multiple brain areas. Age-related changes in MTR and APTW were evaluated with a non-linear regression analysis. The APTW signals followed a decreasing exponential curve with age in all brain regions measured (R{sup 2} = 0.7-0.8 for the corpus callosum, frontal and occipital white matter, and centrum semiovale). The most significant changes appeared within the first year. At maturation, larger decreases in APTW and lower APTW values were found in the white matter. On the contrary, the MTR signals followed an increasing exponential curve with age in the same brain regions measured, with the most significant changes appearing within the initial 2 years. There was an inverse correlation between the MTR and APTW signal intensities during brain maturation. Together with MT imaging, protein-based APT imaging can provide additional information in assessing brain myelination in the paediatric population. (orig.)

  15. Magnetization transfer MR of cerebrovascular disorders using calculated images

    Energy Technology Data Exchange (ETDEWEB)

    Enomoto, Kyoko; Watabe, Tsuneya; Amanuma, Makoto; Heshiki, Atsuko [Saitama Medical School, Moroyama, Saitama (Japan)

    1997-06-01

    This study applied a magnetization transfer contrast method to patients with cerebrovascular disorders. A 1.5 T superconducting MR unit was used, and magnetization transfer ratio (MTR) images were calculated by evaluating two paired images before and after off-resonance gradient echo pulse sequences. The normal white matter showed the highest MTRs, CSF the lowest, and gray matter, intermediate. Cerebral ischemic patients showed two patterns according to the chronological stage of the affected area. Lesions in the acute and subacute stages revealed higher transfer rates than those in the chronic stage. Patients with cerebral hemorrhage were divided into three groups: the hyperacute group showed a low transfer pattern; the acute group presented inhomogeneous high transfer rates; and the subacute group showed remarkably low transfer rates. In the acute and subacute ischemic stages, increased macromolecules caused higher MTRs than in the chronic stage. In hemorrhagic groups, low MTRs in subacute hemorrhage reflected the transfer of methemoglobin. High MTRs in acute hemorrhage with rich deoxyhemoglobin suggested increased fibrin, plasma, and serum components of macromolecules. The MTC method provided new chronological information on cerebral hemorrhage, adding to that provided by routine MR images. (author)

  16. 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)

  17. 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

  18. Applications of VLSI circuits to medical imaging

    International Nuclear Information System (INIS)

    O'Donnell, M.

    1988-01-01

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

  19. 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

  20. Lossless medical image compression with a hybrid coder

    Science.gov (United States)

    Way, Jing-Dar; Cheng, Po-Yuen

    1998-10-01

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

  1. Transferability of economic evaluations of medical technologies: a new technology for orthopedic surgery.

    Science.gov (United States)

    Steuten, Lotte; Vallejo-Torres, Laura; Young, Terry; Buxton, Martin

    2008-05-01

    Transferring results of economic evaluations across countries or jurisdictions can potentially save scarce evaluation resources while helping to make market access and reimbursement decisions in a timely fashion. This article points out why transferring results of economic evaluations is particularly important in the field of medical technologies. It then provides an overview of factors that are previously identified in the literature as affecting transferability of economic evaluations, as well as methods for transferring results in a scientifically sound way. As the current literature almost exclusively relates to transferability of pharmacoeconomic evaluations, this article highlights those factors and methodologies that are of particular relevance to transferring medical technology assessments. Considering the state-of-the-art literature and a worked, real life, example of transferring an economic evaluation of a product used in orthopedic surgery, we provide recommendations for future work in this important area of medical technology assessment.

  2. A special designed library for medical imaging applications

    International Nuclear Information System (INIS)

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

    1994-01-01

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

  3. 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...

  4. Attitudes towards transferable skills in medical undergraduates.

    Science.gov (United States)

    Whittle, S R; Eaton, D G

    2001-02-01

    Changes to the style of medical teaching will place a greater responsibility on individual medical students to manage their own learning, highlighting the need for students to develop good so-called 'transferable' skills at an early stage in their undergraduate career. To assess the attitudes of first year undergraduates towards transferable skills, and investigate the gender difference in these attitudes. To assess the contribution of their first year course to skills development. First year students, enrolled on a traditional-style course. A questionnaire asking the students to consider: (a) the importance of named transferable skills for medicine; (b) their own ability in these areas; and (c) the influence of their first year course. All students, irrespective of gender, regarded transferable skills as very important to medicine, rating organizational skills and self-learning skills as most important. Overall, students have a high level of confidence in their own skills. Male students rated their overall level of skills more highly than women. In particular they rated their information handling, managing self-learning and technical skills more highly. Students feel that their first year course has enhanced their skills in most areas. Our results suggest that students will feel equipped to succeed in a learning system which places the onus on them to take responsibility for their own learning. They clearly believe that they have the necessary skills for independent learning. The study highlights the need to enhance students' self-evaluation skills.

  5. Electronic photography: a new age of medical imaging?

    Science.gov (United States)

    Tübergen, D; Manegold, B C

    1993-07-01

    This is a critical overview of present conceptions of the introduction of electronic photography in medicine. It is not a complete list of products, rather it is a description of how the requirements of the physician have influenced medical illustration in the past and will continue to do so in the future. Video systems are widely used in medicine. Besides the learning and teaching of effects of television, minimal invasive surgery (MIS) has become reality through endoscopy, rapidly accepted worldwide. Documentation of endoscopic procedures and their effects is becoming routine. Therefore, the conversion of complex optical information into binary units is a logical development to save space for storage. The reproduction, storage and transfer of detailed images is already realized by digital camera systems, photo CD, scanners and picture archiving and communicating system (PACS). Now electronic imaging in medicine has to be regarded as a matter of routine. The real impact of accelerated editing will be shown in the future.

  6. Medical image informatics infrastructure design and applications.

    Science.gov (United States)

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

    1997-01-01

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

  7. A special designed library for medical imaging applications

    Energy Technology Data Exchange (ETDEWEB)

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

    1994-12-31

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

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

    Science.gov (United States)

    Denslow, S

    1994-08-01

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

  9. The Orthanc Ecosystem for Medical Imaging.

    Science.gov (United States)

    Jodogne, Sébastien

    2018-05-03

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

  10. 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.

  11. 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.

  12. 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

  13. Hybrid Imaging: A New Frontier in Medical Imaging

    OpenAIRE

    Bijan Bijan

    2010-01-01

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

  14. Performance assessment of imaging plates for the JHR transfer Neutron Imaging System

    Science.gov (United States)

    Simon, E.; Guimbal, P. AB(; )

    2018-01-01

    The underwater Neutron Imaging System to be installed in the Jules Horowitz Reactor (JHR-NIS) is based on a transfer method using a neutron activated beta-emitter like Dysprosium. The information stored in the converter is to be offline transferred on a specific imaging system, still to be defined. Solutions are currently under investigation for the JHR-NIS in order to anticipate the disappearance of radiographic films commonly used in these applications. We report here the performance assessment of Computed Radiography imagers (Imaging Plates) performed at LLB/Orphée (CEA Saclay). Several imaging plate types are studied, in one hand in the configuration involving an intimate contact with an activated dysprosium foil converter: Fuji BAS-TR, Fuji UR-1 and Carestream Flex XL Blue imaging plates, and in the other hand by using a prototypal imaging plate doped with dysprosium and thus not needing any contact with a separate converter foil. The results for these imaging plates are compared with those obtained with gadolinium doped imaging plate used in direct neutron imaging (Fuji BAS-ND). The detection performances of the different imagers are compared regarding resolution and noise. The many advantages of using imaging plates over radiographic films (high sensitivity, linear response, high dynamic range) could palliate its lower intrinsic resolution.

  15. Feasibility study of P2P-type system architecture with 3D medical image data support for medical integrated network systems

    International Nuclear Information System (INIS)

    Noji, Tamotsu; Arino, Masashi; Suto, Yasuzo

    2010-01-01

    We are investigating an integrated medical network system with an electronic letter of introduction function and a 3D image support function operating in the Internet environment. However, the problems with current C/S (client/server)-type systems are inadequate security countermeasures and insufficient transmission availability. In this report, we propose a medical information cooperation system architecture that employs a P2P (peer-to-peer)-type communication method rather than a C/S-type method, which helps to prevent a reduction in processing speed when large amounts of data (such as 3D images) are transferred. In addition, a virtual clinic was created and a feasibility study was conducted to evaluate the P2P-type system. The results showed that efficiency was improved by about 77% in real-time transmission, suggesting that this system may be suitable for practical application. (author)

  16. 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...

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

    Science.gov (United States)

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

    2012-08-01

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

  18. Imaging techniques for medical diagnosis

    International Nuclear Information System (INIS)

    Gudden, F.

    1982-01-01

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

  19. Pocket Size Solid State FLASH and iPOD Drives for gigabyte storage, display and transfer of digital medical images: an introduction

    International Nuclear Information System (INIS)

    Sankaran, A.

    2008-01-01

    The transition of radiological imaging from analog to digital was closely followed by the development of the Picture Archiving and Communication (PACS) system. Concomitantly, multidimensional imaging ( 4D and 5D, for motion and functional studies on 3D images) have presented new challenges, particularly in handling gigabyte size images from CT, MRI and PET scanners, which generate thousands of images. The storage and analysis of these images necessitate expensive image workstations. This paper highlights the recent innovations in mass storage, display and transfer of images, using miniature/pocket size solid state FLASH and iPOD drives

  20. Pediatric Trauma Transfer Imaging Inefficiencies-Opportunities for Improvement with Cloud Technology.

    Science.gov (United States)

    Puckett, Yana; To, Alvin

    2016-01-01

    This study examines the inefficiencies of radiologic imaging transfers from one hospital to the other during pediatric trauma transfers in an era of cloud based information sharing. Retrospective review of all patients transferred to a pediatric trauma center from 2008-2014 was performed. Imaging was reviewed for whether imaging accompanied the patient, whether imaging was able to be uploaded onto computer for records, whether imaging had to be repeated, and whether imaging obtained at outside hospitals (OSH) was done per universal pediatric trauma guidelines. Of the 1761 patients retrospectively reviewed, 559 met our inclusion criteria. Imaging was sent with the patient 87.7% of the time. Imaging was unable to be uploaded 31.9% of the time. CT imaging had to be repeated 1.8% of the time. CT scan was not done per universal pediatric trauma guidelines 1.2% of the time. Our study demonstrated that current imaging transfer is inefficient, leads to excess ionizing radiation, and increased healthcare costs. Universal implementation of cloud based radiology has the potential to eliminate excess ionizing radiation to children, improve patient care, and save cost to healthcare system.

  1. Pediatric Trauma Transfer Imaging Inefficiencies—Opportunities for Improvement with Cloud Technology

    Directory of Open Access Journals (Sweden)

    Yana Puckett

    2016-02-01

    Full Text Available BACKGROUND: This study examines the inefficiencies of radiologic imaging transfers from one hospital to the other during pediatric trauma transfers in an era of cloud based information sharing. METHODS: Retrospective review of all patients transferred to a pediatric trauma center from 2008–2014 was performed. Imaging was reviewed for whether imaging accompanied the patient, whether imaging was able to be uploaded onto computer for records, whether imaging had to be repeated, and whether imaging obtained at outside hospitals (OSH was done per universal pediatric trauma guidelines. RESULTS: Of the 1761 patients retrospectively reviewed, 559 met our inclusion criteria. Imaging was sent with the patient 87.7% of the time. Imaging was unable to be uploaded 31.9% of the time. CT imaging had to be repeated 1.8% of the time. CT scan was not done per universal pediatric trauma guidelines 1.2% of the time. CONCLUSION: Our study demonstrated that current imaging transfer is inefficient, leads to excess ionizing radiation, and increased healthcare costs. Universal implementation of cloud based radiology has the potential to eliminate excess ionizing radiation to children, improve patient care, and save cost to healthcare system.

  2. 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.

  3. 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

  4. 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.

  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. GIFT-Cloud: A data sharing and collaboration platform for medical imaging research.

    Science.gov (United States)

    Doel, Tom; Shakir, Dzhoshkun I; Pratt, Rosalind; Aertsen, Michael; Moggridge, James; Bellon, Erwin; David, Anna L; Deprest, Jan; Vercauteren, Tom; Ourselin, Sébastien

    2017-02-01

    Clinical imaging data are essential for developing research software for computer-aided diagnosis, treatment planning and image-guided surgery, yet existing systems are poorly suited for data sharing between healthcare and academia: research systems rarely provide an integrated approach for data exchange with clinicians; hospital systems are focused towards clinical patient care with limited access for external researchers; and safe haven environments are not well suited to algorithm development. We have established GIFT-Cloud, a data and medical image sharing platform, to meet the needs of GIFT-Surg, an international research collaboration that is developing novel imaging methods for fetal surgery. GIFT-Cloud also has general applicability to other areas of imaging research. GIFT-Cloud builds upon well-established cross-platform technologies. The Server provides secure anonymised data storage, direct web-based data access and a REST API for integrating external software. The Uploader provides automated on-site anonymisation, encryption and data upload. Gateways provide a seamless process for uploading medical data from clinical systems to the research server. GIFT-Cloud has been implemented in a multi-centre study for fetal medicine research. We present a case study of placental segmentation for pre-operative surgical planning, showing how GIFT-Cloud underpins the research and integrates with the clinical workflow. GIFT-Cloud simplifies the transfer of imaging data from clinical to research institutions, facilitating the development and validation of medical research software and the sharing of results back to the clinical partners. GIFT-Cloud supports collaboration between multiple healthcare and research institutions while satisfying the demands of patient confidentiality, data security and data ownership. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

  7. 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.

  8. 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

  9. A digital library for medical imaging activities

    Science.gov (United States)

    dos Santos, Marcelo; Furuie, Sérgio S.

    2007-03-01

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

  10. [Medical tele-imaging: a good chance for the future].

    Science.gov (United States)

    Bonnin, A

    1999-01-01

    Tele-imaging is an important part of telemedicine: it includes the transmission of medical digital images and plays a role in all fields of telemedicine, such as expertise, consultation, teaching and research. Tele-imaging has been made possible through the digitalization of medical imaging. There are two possibilities: either digitalization of conventional radiological film or direct acquisition of digital images. The transmission of medical imaging requires a high data rate so as to obtain a good quality transmission of the initial images in a reasonable delay. In order to deal with the great amount of information to be stocked and transmitted, a compression of the data, without loss of information, is usually necessary. Interactivity is very important in all these types of transmissions. These tele-transmission techniques are already used world wide, especially in Japan and in the United States, to help in therapeutic or diagnostic decisions. In France, we have been performing real time interactive tele-imaging sessions between radiology and endocrinology departments of Hotel Dieu in Montréal and Hôpital Cochin in Paris. This experimental device includes a visual-conference link between the medical teams and a real time link between two CT scanners. The CT scanner slices appear simultaneously both CT scanner screens; it is even possible to guide a CT scanner examination using remote control from the other hospital. We have successfully repeated the experiment between Cochin and a private hospital in Paris. In the case of the "Prison de la Santé", we have been using telemedicine in order to reduce problematic transfers of prison inmates. Moreover, access to doctors in the prison is sometimes difficult. The system ensures the daily transmission of X-rays, which are immediately read by radiologists at Cochin. In the past, 50 to 70 X-rays had to be read during one weekly visit. Medical tele-imaging raises certain legal, ethical and economic issues, such as

  11. 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.

  12. 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.

  13. 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.

  14. 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...

  15. 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.

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

    International Nuclear Information System (INIS)

    Momose, Atsushi

    2007-01-01

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

  17. Physics and engineering of medical imaging

    International Nuclear Information System (INIS)

    Guzzardi, R.

    1987-01-01

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

  18. 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.

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

    Directory of Open Access Journals (Sweden)

    Swarnambiga AYYACHAMY

    2013-09-01

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

  20. 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.

  1. 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.

  2. 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.

  3. 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

  4. 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...

  5. 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

  6. Imaging and modeling of collagen architecture in living tissue with polarized light transfer (Conference Presentation)

    Science.gov (United States)

    Ramella-Roman, Jessica C.; Stoff, Susan; Chue-Sang, Joseph; Bai, Yuqiang

    2016-03-01

    The extra-cellular space in connective tissue of animals and humans alike is comprised in large part of collagen. Monitoring of collagen arrangement and cross-linking has been utilized to diagnose a variety of medical conditions and guide surgical intervention. For example, collagen monitoring is useful in the assessment and treatment of cervical cancer, skin cancer, myocardial infarction, and non-arteritic anterior ischemic optic neuropathy. We have developed a suite of tools and models based on polarized light transfer for the assessment of collagen presence, cross-linking, and orientation in living tissue. Here we will present some example of such approach applied to the human cervix. We will illustrate a novel Mueller Matrix (MM) imaging system for the study of cervical tissue; furthermore we will show how our model of polarized light transfer through cervical tissue compares to the experimental findings. Finally we will show validation of the methodology through histological results and Second Harmonic imaging microscopy.

  7. The future of three-dimensional medical imaging

    International Nuclear Information System (INIS)

    Peter, T.M.

    1996-01-01

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

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

    Science.gov (United States)

    Scatliff, James H; Morris, Peter J

    2014-01-01

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

  9. 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

  10. Physics instrumentation for medical imaging

    Energy Technology Data Exchange (ETDEWEB)

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

    1993-04-15

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

  11. 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...

  12. 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.

  13. 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.

  14. 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.

  15. Identifying Medical Diagnoses and Treatable Diseases by Image-Based Deep Learning.

    Science.gov (United States)

    Kermany, Daniel S; Goldbaum, Michael; Cai, Wenjia; Valentim, Carolina C S; Liang, Huiying; Baxter, Sally L; McKeown, Alex; Yang, Ge; Wu, Xiaokang; Yan, Fangbing; Dong, Justin; Prasadha, Made K; Pei, Jacqueline; Ting, Magdalene Y L; Zhu, Jie; Li, Christina; Hewett, Sierra; Dong, Jason; Ziyar, Ian; Shi, Alexander; Zhang, Runze; Zheng, Lianghong; Hou, Rui; Shi, William; Fu, Xin; Duan, Yaou; Huu, Viet A N; Wen, Cindy; Zhang, Edward D; Zhang, Charlotte L; Li, Oulan; Wang, Xiaobo; Singer, Michael A; Sun, Xiaodong; Xu, Jie; Tafreshi, Ali; Lewis, M Anthony; Xia, Huimin; Zhang, Kang

    2018-02-22

    The implementation of clinical-decision support algorithms for medical imaging faces challenges with reliability and interpretability. Here, we establish a diagnostic tool based on a deep-learning framework for the screening of patients with common treatable blinding retinal diseases. Our framework utilizes transfer learning, which trains a neural network with a fraction of the data of conventional approaches. Applying this approach to a dataset of optical coherence tomography images, we demonstrate performance comparable to that of human experts in classifying age-related macular degeneration and diabetic macular edema. We also provide a more transparent and interpretable diagnosis by highlighting the regions recognized by the neural network. We further demonstrate the general applicability of our AI system for diagnosis of pediatric pneumonia using chest X-ray images. This tool may ultimately aid in expediting the diagnosis and referral of these treatable conditions, thereby facilitating earlier treatment, resulting in improved clinical outcomes. VIDEO ABSTRACT. Copyright © 2018 Elsevier Inc. All rights reserved.

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

    Science.gov (United States)

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

    2018-01-01

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

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

    Science.gov (United States)

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

    2013-01-01

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

  18. Tissues segmentation based on multi spectral medical images

    Science.gov (United States)

    Li, Ya; Wang, Ying

    2017-11-01

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

  19. 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.)

  20. OpenID Connect as a security service in cloud-based medical imaging systems.

    Science.gov (United States)

    Ma, Weina; Sartipi, Kamran; Sharghigoorabi, Hassan; Koff, David; Bak, Peter

    2016-04-01

    The evolution of cloud computing is driving the next generation of medical imaging systems. However, privacy and security concerns have been consistently regarded as the major obstacles for adoption of cloud computing by healthcare domains. OpenID Connect, combining OpenID and OAuth together, is an emerging representational state transfer-based federated identity solution. It is one of the most adopted open standards to potentially become the de facto standard for securing cloud computing and mobile applications, which is also regarded as "Kerberos of cloud." We introduce OpenID Connect as an authentication and authorization service in cloud-based diagnostic imaging (DI) systems, and propose enhancements that allow for incorporating this technology within distributed enterprise environments. The objective of this study is to offer solutions for secure sharing of medical images among diagnostic imaging repository (DI-r) and heterogeneous picture archiving and communication systems (PACS) as well as Web-based and mobile clients in the cloud ecosystem. The main objective is to use OpenID Connect open-source single sign-on and authorization service and in a user-centric manner, while deploying DI-r and PACS to private or community clouds should provide equivalent security levels to traditional computing model.

  1. Patients radiation protection in medical imaging. Conference proceedings

    International Nuclear Information System (INIS)

    2011-12-01

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

  2. Segmentation of medical images using explicit anatomical knowledge

    Science.gov (United States)

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

    1999-07-01

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

  3. 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....

  4. Practical guide to quality assurance in medical imaging

    International Nuclear Information System (INIS)

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

    1987-01-01

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

  5. Image transfer by cascaded stack of photonic crystal and air layers

    NARCIS (Netherlands)

    Shen, C.; Michielsen, K.; Raedt, H. De

    2006-01-01

    We demonstrate image transfer by a cascaded stack consisting of two and three triangular-lattice photonic crystal slabs separated by air. The quality of the image transfered by the stack is sensitive to the air/photonic crystal interface termination and the frequency. Depending on the frequency and

  6. Study on the standardization of hospital information system for medical image information sharing

    International Nuclear Information System (INIS)

    Kim, Seon Chil; Kwon, Su Ja

    2001-01-01

    As the adoption of PACS and hospital information system among university hospitals and hospital level institutions grows bigger, the need of sharing and transferring medical information among medical institutions is rising. For the medical information, which is saved in the hospital medical system, to be transferred within the same hospital, domestic, or foreign medical institutions, a standard protocol is necessary. But realistically, most of the domestic hospitals do not abide by H7L which is the HIS standard and so, information transferring is not possible as of present. As such, the purpose of this research is to implement the information between HIS and PACS to an international standard by constructing HL7 messages through HL7 Interface, which will eventually make possible information transferring between different hospitals. Our research team has developed a method which will make the PACS equip hospitals that do not follow HL7 standard which will make possible to transfer information between HIS and PACS through HL7 Message. By constructing message files, which follow the form of HL7 Message in the HL7 Interface, they can be transferred to PACS through the ftp protocol. The realization of the HIS/OCS Interface through HL7 enables data transferring between domestic and foreign medical institutions possible by implementing the international standard in the PACS and HIS data transferring process. The HL7 that our research team has developed made patient data transfer between medical institutions possible. The Interface is for a specific system model and in order for the data transfer between different systems to be realized, interfaces that are fit for each system must be needed. If the Interface is improvised and implemented to each hospital's information system, the data sharing among medical institutions can be broadened

  7. Introduction to Medical Image Analysis

    DEFF Research Database (Denmark)

    Paulsen, Rasmus Reinhold; Moeslund, Thomas B.

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

  8. Task transfer: another pressure for evolution of the medical profession.

    Science.gov (United States)

    Van Der Weyden, Martin B

    2006-07-03

    Since the 1960s, Australian society and the medical profession have undergone enormous change. Our society has moved from a relatively homogeneous and conservative community, supported by limited government services, to one that is multicultural, focused on the individual and consumerism, and supported by extensive government programs, with health care a top public and political priority. A defining feature of contemporary society is its mistrust of institutions, professionals, public servants and politicians. The medical profession has changed from a cohesive entity, valuing generalism and with limited specialisation, to one splintered by ultra-specialisation and competing professional agendas. The medical workforce shortage and efforts to maintain the safety and quality of health services are putting acute pressure on the profession. Task transfer or role substitution of medical services is mooted as a potential solution to this pressure. This has the potential to drastically transform the profession. How task transfer will evolve and change medicine depends on the vision and leadership of the profession and a flexible pragmatism that safeguards quality and safety and places patient priorities above those of the profession.

  9. Advanced data visualization and sensor fusion: Conversion of techniques from medical imaging to Earth science

    Science.gov (United States)

    Savage, Richard C.; Chen, Chin-Tu; Pelizzari, Charles; Ramanathan, Veerabhadran

    1993-01-01

    Hughes Aircraft Company and the University of Chicago propose to transfer existing medical imaging registration algorithms to the area of multi-sensor data fusion. The University of Chicago's algorithms have been successfully demonstrated to provide pixel by pixel comparison capability for medical sensors with different characteristics. The research will attempt to fuse GOES (Geostationary Operational Environmental Satellite), AVHRR (Advanced Very High Resolution Radiometer), and SSM/I (Special Sensor Microwave Imager) sensor data which will benefit a wide range of researchers. The algorithms will utilize data visualization and algorithm development tools created by Hughes in its EOSDIS (Earth Observation SystemData/Information System) prototyping. This will maximize the work on the fusion algorithms since support software (e.g. input/output routines) will already exist. The research will produce a portable software library with documentation for use by other researchers.

  10. Evaluation Of Medical Fluoroscopy Imaging

    International Nuclear Information System (INIS)

    Hartana, Budi; Santoso

    2000-01-01

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

  11. 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.

  12. 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

  13. Ontology modularization to improve semantic medical image annotation.

    Science.gov (United States)

    Wennerberg, Pinar; Schulz, Klaus; Buitelaar, Paul

    2011-02-01

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

  14. Development of 3-D Medical Image VIsualization System

    African Journals Online (AJOL)

    User

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

  15. Leadership and power in medical imaging

    Energy Technology Data Exchange (ETDEWEB)

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

    2006-11-15

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

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

    Directory of Open Access Journals (Sweden)

    Yair Granot

    2008-04-01

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

  18. Hello World Deep Learning in Medical Imaging.

    Science.gov (United States)

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

    2018-05-03

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

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

    Science.gov (United States)

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

    2017-03-01

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

  20. 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.

  1. 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.

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

    Science.gov (United States)

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

    2018-05-01

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

  3. Physics and engineering of medical imaging

    International Nuclear Information System (INIS)

    Guzzardi, R.

    1987-01-01

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

  4. 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.

  5. 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.

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

    OpenAIRE

    McIntosh, Christopher

    2011-01-01

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

  7. Novel medical image enhancement algorithms

    Science.gov (United States)

    Agaian, Sos; McClendon, Stephen A.

    2010-01-01

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

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

    DEFF Research Database (Denmark)

    Hansen, Michael Schacht; Sørensen, Thomas Sangild

    2013-01-01

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

  9. 47 CFR 15.513 - Technical requirements for medical imaging systems.

    Science.gov (United States)

    2010-10-01

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

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

    Science.gov (United States)

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

    2015-03-01

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

  11. 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

  12. Facilitating medical information search using Google Glass connected to a content-based medical image retrieval system.

    Science.gov (United States)

    Widmer, Antoine; Schaer, Roger; Markonis, Dimitrios; Muller, Henning

    2014-01-01

    Wearable computing devices are starting to change the way users interact with computers and the Internet. Among them, Google Glass includes a small screen located in front of the right eye, a camera filming in front of the user and a small computing unit. Google Glass has the advantage to provide online services while allowing the user to perform tasks with his/her hands. These augmented glasses uncover many useful applications, also in the medical domain. For example, Google Glass can easily provide video conference between medical doctors to discuss a live case. Using these glasses can also facilitate medical information search by allowing the access of a large amount of annotated medical cases during a consultation in a non-disruptive fashion for medical staff. In this paper, we developed a Google Glass application able to take a photo and send it to a medical image retrieval system along with keywords in order to retrieve similar cases. As a preliminary assessment of the usability of the application, we tested the application under three conditions (images of the skin; printed CT scans and MRI images; and CT and MRI images acquired directly from an LCD screen) to explore whether using Google Glass affects the accuracy of the results returned by the medical image retrieval system. The preliminary results show that despite minor problems due to the relative stability of the Google Glass, images can be sent to and processed by the medical image retrieval system and similar images are returned to the user, potentially helping in the decision making process.

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

    Directory of Open Access Journals (Sweden)

    Guanqiu Qi

    2017-10-01

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

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

    Science.gov (United States)

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

    2017-01-01

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

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

    Science.gov (United States)

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

    2017-04-01

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

  16. Medical physics 2013. Abstracts; Medizinische Physik 2013. Abstractband

    Energy Technology Data Exchange (ETDEWEB)

    Treuer, Harald (ed.) [Koeln Univ. (Germany). Klinik fuer Stereotaxie und Funktionelle Neurochirurgie

    2013-07-01

    The proceedings of the medical physics conference 2013 include abstract of lectures and poster sessions concerning the following issues: Tele-therapy - application systems, nuclear medicine and molecular imaging, neuromodulation, hearing and technical support, basic dosimetry, NMR imaging -CEST (chemical exchange saturation transfer), medical robotics, magnetic particle imaging, audiology, radiation protection, phase contrast - innovative concepts, particle therapy, brachytherapy, computerized tomography, quantity assurance, hybrid imaging techniques, diffusion and lung NMR imaging, image processing - visualization, cardiac and abdominal NMR imaging.

  17. 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.

  18. Wireless energy transfer platform for medical sensors and implantable devices.

    Science.gov (United States)

    Zhang, Fei; Hackworth, Steven A; Liu, Xiaoyu; Chen, Haiyan; Sclabassi, Robert J; Sun, Mingui

    2009-01-01

    Witricity is a newly developed technique for wireless energy transfer. This paper presents a frequency adjustable witricity system to power medical sensors and implantable devices. New witricity resonators are designed for both energy transmission and reception. A prototype platform is described, including an RF power source, two resonators with new structures, and inductively coupled input and output stages. In vitro experiments, both in open air and using a human head phantom consisting of simulated tissues, are employed to verify the feasibility of this platform. An animal model is utilized to evaluate in vivo energy transfer within the body of a laboratory pig. Our experiments indicate that witricity is an effective new tool for providing a variety of medical sensors and devices with power.

  19. Real-time image mosaicing for medical applications.

    Science.gov (United States)

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

    2007-01-01

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

  20. Nonresearch Industry Payments to Radiologists: Characteristics and Associations With Regional Medical Imaging Utilization.

    Science.gov (United States)

    Kokabi, Nima; Junn, Jacqueline C; Xing, Minzhi; Hemingway, Jennifer; Hughes, Danny R; Duszak, Richard

    2017-03-01

    To evaluate characteristics of nonresearch industry payments to radiologists and associations with regional diagnostic imaging utilization. Using 2014 CMS Open Payment data, all disclosed nonresearch-related industry payments to radiologists were identified. Health Resources and Services Administration Area Health Resources Files were used to identify actual and population-weighted numbers of radiologists by state. Utilizing the 5% random beneficiary sample CMS Research Identifiable Files from 2014, average Medicare imaging spending per beneficiary in each state was calculated. Average frequency and dollar amounts of nonresearch nonroyalty payments to radiologists were calculated at the state level. Using the Pearson correlation coefficient, the relationship between frequency and amounts of nonresearch payments to radiologists versus per-beneficiary Medicare imaging spending was evaluated at the state level. Overall, 2,008 radiologists (1,670 diagnostic, 338 interventional) received nonresearch nonroyalty payments from industry, representing 5.2% of all 38,857 radiologists nationwide. A total of 4,975 individual transfers translated to 2.5 ± 1.3 discrete payments per receiving radiologist with a mean of $432 ± $1,976 (median $26; range $1-$34,050). Food and beverage expenses constituted the vast majority of disclosed transfers (4,111; 83%), followed by travel and lodging (444; 9%), consulting fees (279; 6%), and educational expenses (51; 1%). Considerable geographic variation in payments was observed, ranging from 0% of radiologists in Vermont to 12.9% in the District of Columbia. No correlation was identified between average per-beneficiary Medicare imaging spending and the proportion of nonresearch-funded radiologists in each state (r = 0.06). Similarly, no correlation was identified between average per-beneficiary Medicare imaging spending and the average nonresearch transfer amount to radiologists in each state (r = -0.08). In 2014, only a small minority of

  1. 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)

  2. 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

  3. 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.

  4. Image transfer with spatial coherence for aberration corrected transmission electron microscopes

    International Nuclear Information System (INIS)

    Hosokawa, Fumio; Sawada, Hidetaka; Shinkawa, Takao; Sannomiya, Takumi

    2016-01-01

    The formula of spatial coherence involving an aberration up to six-fold astigmatism is derived for aberration-corrected transmission electron microscopy. Transfer functions for linear imaging are calculated using the newly derived formula with several residual aberrations. Depending on the symmetry and origin of an aberration, the calculated transfer function shows characteristic symmetries. The aberrations that originate from the field’s components, having uniformity along the z direction, namely, the n-fold astigmatism, show rotational symmetric damping of the coherence. The aberrations that originate from the field’s derivatives with respect to z, such as coma, star, and three lobe, show non-rotational symmetric damping. It is confirmed that the odd-symmetric wave aberrations have influences on the attenuation of an image via spatial coherence. Examples of image simulations of haemoglobin and Si [211] are shown by using the spatial coherence for an aberration-corrected electron microscope. - Highlights: • The formula of partial coherence for aberration corrected TEM is derived. • Transfer functions are calculated with several residual aberrations. • The calculated transfer function shows the characteristic damping. • The odd-symmetric wave aberrations can cause the attenuation of image via coherence. • The examples of aberration corrected TEM image simulations are shown.

  5. Image transfer with spatial coherence for aberration corrected transmission electron microscopes

    Energy Technology Data Exchange (ETDEWEB)

    Hosokawa, Fumio, E-mail: hosokawa@bio-net.co.jp [BioNet Ltd., 2-3-28 Nishikityo, Tachikwa, Tokyo (Japan); Tokyo Institute of Technology, 4259 Nagatsuta, Midoriku, Yokohama 226-8503 (Japan); Sawada, Hidetaka [JEOL (UK) Ltd., JEOL House, Silver Court, Watchmead, Welwyn Garden City, Herts AL7 1LT (United Kingdom); Shinkawa, Takao [BioNet Ltd., 2-3-28 Nishikityo, Tachikwa, Tokyo (Japan); Sannomiya, Takumi [Tokyo Institute of Technology, 4259 Nagatsuta, Midoriku, Yokohama 226-8503 (Japan)

    2016-08-15

    The formula of spatial coherence involving an aberration up to six-fold astigmatism is derived for aberration-corrected transmission electron microscopy. Transfer functions for linear imaging are calculated using the newly derived formula with several residual aberrations. Depending on the symmetry and origin of an aberration, the calculated transfer function shows characteristic symmetries. The aberrations that originate from the field’s components, having uniformity along the z direction, namely, the n-fold astigmatism, show rotational symmetric damping of the coherence. The aberrations that originate from the field’s derivatives with respect to z, such as coma, star, and three lobe, show non-rotational symmetric damping. It is confirmed that the odd-symmetric wave aberrations have influences on the attenuation of an image via spatial coherence. Examples of image simulations of haemoglobin and Si [211] are shown by using the spatial coherence for an aberration-corrected electron microscope. - Highlights: • The formula of partial coherence for aberration corrected TEM is derived. • Transfer functions are calculated with several residual aberrations. • The calculated transfer function shows the characteristic damping. • The odd-symmetric wave aberrations can cause the attenuation of image via coherence. • The examples of aberration corrected TEM image simulations are shown.

  6. 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.

  7. Conjugate Image Theory Applied on Capacitive Wireless Power Transfer

    OpenAIRE

    Ben Minnaert; Nobby Stevens

    2017-01-01

    Wireless power transfer using a magnetic field through inductive coupling is steadily entering the market in a broad range of applications. However, for certain applications, capacitive wireless power transfer using electric coupling might be preferable. In order to obtain a maximum power transfer efficiency, an optimal compensation network must be designed at the input and output ports of the capacitive wireless link. In this work, the conjugate image theory is applied to determine this opti...

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

    Science.gov (United States)

    Balan, J A Alex Rajju; Rajan, S Edward

    2014-01-01

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

  9. 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.

  10. Aliphatic polyesters for medical imaging and theranostic applications.

    Science.gov (United States)

    Nottelet, Benjamin; Darcos, Vincent; Coudane, Jean

    2015-11-01

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

  11. Transfer function analysis of positron-emitting tracer imaging system (PETIS) data

    International Nuclear Information System (INIS)

    Keutgen, N.; Matsuhashi, S.; Mizuniwa, C.; Ito, T.; Fujimura, T.; Ishioka, N.S.; Watanabe, S.; Sekine, T.; Uchida, H.; Hashimoto, S.

    2002-01-01

    Quantitative analysis of the two-dimensional image data obtained with the positron-emitting tracer imaging system (PETIS) for plant physiology has been carried out using a transfer function analysis method. While a cut leaf base of Chinese chive (Allium tuberosum Rottler) or a cut stem of soybean (Glycine max L.) was immersed in an aqueous solution containing the [ 18 F] F - ion or [ 13 N]NO 3 - ion, tracer images of the leaf of Chinese chive and the trifoliate of soybean were recorded with PETIS. From the time sequence of images, the tracer transfer function was estimated from which the speed of tracer transport and the fraction moved between specified image positions were deduced

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

    Science.gov (United States)

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

    2017-11-21

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

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

    Science.gov (United States)

    Zhang, Shaoting; Metaxas, Dimitris

    2016-10-01

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

  14. Visualization index for image-enabled medical records

    Science.gov (United States)

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

    2011-03-01

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

  15. 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.

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

    Directory of Open Access Journals (Sweden)

    Ningning Zhou

    2014-01-01

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

  17. 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)

  18. Platform for Automated Real-Time High Performance Analytics on Medical Image Data.

    Science.gov (United States)

    Allen, William J; Gabr, Refaat E; Tefera, Getaneh B; Pednekar, Amol S; Vaughn, Matthew W; Narayana, Ponnada A

    2018-03-01

    Biomedical data are quickly growing in volume and in variety, providing clinicians an opportunity for better clinical decision support. Here, we demonstrate a robust platform that uses software automation and high performance computing (HPC) resources to achieve real-time analytics of clinical data, specifically magnetic resonance imaging (MRI) data. We used the Agave application programming interface to facilitate communication, data transfer, and job control between an MRI scanner and an off-site HPC resource. In this use case, Agave executed the graphical pipeline tool GRAphical Pipeline Environment (GRAPE) to perform automated, real-time, quantitative analysis of MRI scans. Same-session image processing will open the door for adaptive scanning and real-time quality control, potentially accelerating the discovery of pathologies and minimizing patient callbacks. We envision this platform can be adapted to other medical instruments, HPC resources, and analytics tools.

  19. Academic profile of students who transferred to Zagreb School of Medicine from other medical schools in Croatia.

    Science.gov (United States)

    Dusek, Davorka; Dolovcak, Svjetlana; Kljaković-Gaspić, Marko

    2004-02-01

    To assess the academic performance of students who transferred to the Zagreb School of Medicine from other three medical schools in Croatia. Academic performance of medical students who moved from Rijeka, Osijek, or Split University Medical Schools to the Zagreb University School of Medicine at the second or third year was compared with academic performance of students enrolled at the Zagreb University School of Medicine. Using the Zagreb Medical School's registry, we made a list of 57 transfer students to Zagreb Medical School in the 1985-1994 period. Control group was formed of students enrolled at the Zagreb School of Medicine in the same period, whose names followed in alphabetical order after the names of transfer students. Students' performance was analyzed according to their grade average before transfer, grade average in the first year after transfer, total grade average after transfer, overall grade average, and duration of studies. We also analyzed the proportion of students in each group who did not pass the admission test at the Zagreb School of Medicine in the year before the enrollment in Zagreb, Osijek, Rijeka, and Split Medical Schools. Nineteen transfer students, transferred between 1985 and 1988, and their controls were excluded from the analysis because of incomplete data. Transfer students had significantly lower grade average before transfer (3.2-/+0.6 vs 3.5-/+0.7, p=0.03, Student t-test), lower grade average in the first year after transfer (3.2-/+0.6 vs 3.5-/+0.7, p=0.03), lower total grade average after transfer (3.6-/+0.5 vs 4.0-/+0.6, pZagreb School of Medicine in the year before the final enrollment than their controls (15/38 vs 4/38, p=0.009, chi-square test). Transfer students had poorer academic performance than students who passed the admission test and were enrolled at the Zagreb School of Medicine from the first year of studies.

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

    International Nuclear Information System (INIS)

    Gaudeau, Y.

    2006-12-01

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

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

    Directory of Open Access Journals (Sweden)

    K. Vidhya

    2011-02-01

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

  2. The Handbook of Medical Image Perception and Techniques

    Science.gov (United States)

    Samei, Ehsan; Krupinski, Elizabeth

    2014-07-01

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

  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. 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.)

  5. 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...

  6. [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.

  7. MR venography using the 3D-MEDIC (multi echo data imaging combination) sequence for lower extremities

    International Nuclear Information System (INIS)

    Kitagawa, Hisashi; Kishi, Takayuki; Saito, Ryo; Shohji, Tomokazu; Noguchi, Keiji; Sunohara, Nobuo

    2008-01-01

    It is possible to diagnose varicose vein from medical history and physical examinations including inspection and palpation. Non-contrast enhanced MRV (magnetic resonance venography) is becoming popular because it can be easily performed without being affected by the radiographer's skill. We thought that the use of MEDIC (multi echo data imaging combination) would enable us to delineate varicose veins within a short acquisition time and without need for synchronization or contrast enhancement. We used the SIEMENS MAGNETOM Avanto 1.5-Tesla unit to acquire images. Our subjects were five healthy volunteers and five patients with varicose vein. The signal strength of deep veins and muscles were measured. The SNR (signal-to-nose ratio) of deep veins and the CNR (contrast-to-noise ratio) between deep veins and muscles were also measured. Flip angle, fat suppression methods, MTC (magnetic transfer contrast) pulse, and combined echo. Using the optimum image acquisition protocol following our preliminary study with varicose vein patients, the ability of the 3D-MEDIC method to delineate varicose veins was compared with that of the electrocardiogram (ECG)-synchronized two-dimensional time of flight (2D-TOF) method. We found that the following settings would enable us to acquire images from a wide range=coronal, within short acquisition time and needless ECG-triggering. Flip angle=20 degrees, fat suppression method=water excitation, MTC pulse=ON, combined echo=2. 3D-MEDIC was better than the 2D-TOF method in delineating the varicose vein itself and the connection between the varicose vein and deep veins. It is expected that 3D-MEDIC may be useful in the clinical diagnosis of varicose veins. (author)

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

    Energy Technology Data Exchange (ETDEWEB)

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

    1985-04-01

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

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

    International Nuclear Information System (INIS)

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

    1985-01-01

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

  10. 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)

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

    Science.gov (United States)

    Teng, Wei-Guang; Chang, Ping-Lin

    2012-10-01

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

  12. 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....

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

    Science.gov (United States)

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

    2010-04-01

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

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

    Directory of Open Access Journals (Sweden)

    Laszlo Papp

    2018-06-01

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

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

    Directory of Open Access Journals (Sweden)

    Yamada T

    2004-10-01

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

  16. Hard copies for digital medical images: an overview

    Science.gov (United States)

    Blume, Hartwig R.; Muka, Edward

    1995-04-01

    This paper is a condensed version of an invited overview on the technology of film hard-copies used in radiology. Because the overview was given to an essentially nonmedical audience, the reliance on film hard-copies in radiology is outlined in greater detail. The overview is concerned with laser image recorders generating monochrome prints on silver-halide films. The basic components of laser image recorders are sketched. The paper concentrates on the physical parameters - characteristic function, dynamic range, digitization resolution, modulation transfer function, and noise power spectrum - which define image quality and information transfer capability of the printed image. A preliminary approach is presented to compare the printed image quality with noise in the acquired image as well as with the noise of state-of- the-art cathode-ray-tube display systems. High-performance laser-image- recorder/silver-halide-film/light-box systems are well capable of reproducing acquired radiologic information. Most recently development was begun toward a display function standard for soft-copy display systems to facilitate similarity of image presentation between different soft-copy displays as well as between soft- and hard-copy displays. The standard display function is based on perceptional linearization. The standard is briefly reviewed to encourage the printer industry to adopt it, too.

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

    Science.gov (United States)

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

    2017-07-01

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

  18. Gene transfer strategies for improving radiolabeled peptide imaging and therapy

    International Nuclear Information System (INIS)

    Rogers, B.E.; Buchsbaum, D.J.; Zinn, K.R.

    2000-01-01

    Utilization of molecular biology techniques offers attractive options in nuclear medicine for improving cancer imaging and therapy with radiolabeled peptides. Two of these options include utilization of phage-panning to identify novel tumor specific peptides or single chain antibodies and gene transfer techniques to increase the antibodies and gene transfer techniques to increase the number of antigen/receptor sites expressed on malignant cells. The group has focused on the latter approach for improving radiolabeled peptide imaging and therapy. The most widely used gene transfer vectors in clinical gene therapy trials include retrovirus, cationic lipids and adenovirus. It has been utilized adenovirus vectors for gene transfer because of their ability to accomplish efficient in vivo gene transfer. Adenovirus vectors encoding the genes for a variety of antigens/receptors (carcinoembryonic antigen, gastrin-releasing peptide receptor, somatostatin receptor subtype 2 (SSTr2) have all shown that their expression is increased on cancer cells both in vitro and in vivo following adenovirus infection. Of particular interest has been the adenovirus encoding for SSTr2 (AdCMVSSTr2). Various radioisotopes have been attached to somatostatin analogues for imaging and therapy of SSTr2-positive tumors both clinically and in animal models. The use of these analogues in combination with AdCMVSSTr2 is a promising approach for improving the detection sensitivity and therapeutic efficacy of these radiolabeled peptides against solid tumors. In addition, it has been proposed the use of SSTr2 as a marker for imaging the expression of another cancer therapeutic transgene (e.g. cytosine deaminase, thymidine kinase) encoded within the same vector. This would allow for non-invasive monitoring of gene delivery to tumor sites

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

    Science.gov (United States)

    Smistad, Erik; Bozorgi, Mohammadmehdi; Lindseth, Frank

    2015-11-01

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

  20. 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...

  1. A Survey on Deep Learning in Medical Image Analysis

    NARCIS (Netherlands)

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

    2017-01-01

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

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

    International Nuclear Information System (INIS)

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

    2006-01-01

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

  3. 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...

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

    Science.gov (United States)

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

    2010-01-01

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

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

    Science.gov (United States)

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

    2007-11-01

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

  6. Generalized double-humped logistic map-based medical image encryption

    Directory of Open Access Journals (Sweden)

    Samar M. Ismail

    2018-03-01

    Full Text Available This paper presents the design of the generalized Double Humped (DH logistic map, used for pseudo-random number key generation (PRNG. The generalized parameter added to the map provides more control on the map chaotic range. A new special map with a zooming effect of the bifurcation diagram is obtained by manipulating the generalization parameter value. The dynamic behavior of the generalized map is analyzed, including the study of the fixed points and stability ranges, Lyapunov exponent, and the complete bifurcation diagram. The option of designing any specific map is made possible through changing the general parameter increasing the randomness and controllability of the map. An image encryption algorithm is introduced based on pseudo-random sequence generation using the proposed generalized DH map offering secure communication transfer of medical MRI and X-ray images. Security analyses are carried out to consolidate system efficiency including: key sensitivity and key-space analyses, histogram analysis, correlation coefficients, MAE, NPCR and UACI calculations. System robustness against noise attacks has been proved along with the NIST test ensuring the system efficiency. A comparison between the proposed system with respect to previous works is presented.

  7. 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

  8. 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.

  9. Soil transference patterns on bras: Image processing and laboratory dragging experiments.

    Science.gov (United States)

    Murray, Kathleen R; Fitzpatrick, Robert W; Bottrill, Ralph S; Berry, Ron; Kobus, Hilton

    2016-01-01

    In a recent Australian homicide, trace soil on the victim's clothing suggested she was initially attacked in her front yard and not the park where her body was buried. However the important issue that emerged during the trial was how soil was transferred to her clothing. This became the catalyst for designing a range of soil transference experiments (STEs) to study, recognise and classify soil patterns transferred onto fabric when a body is dragged across a soil surface. Soil deposits of interest in this murder were on the victim's bra and this paper reports the results of anthropogenic soil transfer to bra-cups and straps caused by dragging. Transfer patterns were recorded by digital photography and photomicroscopy. Eight soil transfer patterns on fabric, specific to dragging as the transfer method, appeared consistently throughout the STEs. The distinctive soil patterns were largely dependent on a wide range of soil features that were measured and identified for each soil tested using X-ray Diffraction and Non-Dispersive Infra-Red analysis. Digital photographs of soil transfer patterns on fabric were analysed using image processing software to provide a soil object-oriented classification of all soil objects with a diameter of 2 pixels and above transferred. Although soil transfer patterns were easily identifiable by naked-eye alone, image processing software provided objective numerical data to support this traditional (but subjective) interpretation. Image software soil colour analysis assigned a range of Munsell colours to identify and compare trace soil on fabric to other trace soil evidence from the same location; without requiring a spectrophotometer. Trace soil from the same location was identified by linking soils with similar dominant and sub-dominant Munsell colour peaks. Image processing numerical data on the quantity of soil transferred to fabric, enabled a relationship to be discovered between soil type, clay mineralogy (smectite), particle size and

  10. Object-oriented design of medical imaging software.

    Science.gov (United States)

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

    1994-01-01

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

  11. 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)

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

    Science.gov (United States)

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

    2016-11-01

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

  13. 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.

  14. 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...

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

    OpenAIRE

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

    2010-01-01

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

  16. 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...

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

    NARCIS (Netherlands)

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

    2010-01-01

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

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

    International Nuclear Information System (INIS)

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

    2015-01-01

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

  19. Imaging requirements for medical applications of additive manufacturing.

    Science.gov (United States)

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

    2014-02-01

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

  20. Segmentation of elongated structures in medical images

    NARCIS (Netherlands)

    Staal, Jozef Johannes

    2004-01-01

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

  1. Challenges for data storage in medical imaging research.

    Science.gov (United States)

    Langer, Steve G

    2011-04-01

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

  2. 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)

  3. Medical image reconstruction. A conceptual tutorial

    International Nuclear Information System (INIS)

    Zeng, Gengsheng Lawrence

    2010-01-01

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

  4. 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.

  5. Statistical physics of medical ultrasonic images

    International Nuclear Information System (INIS)

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

    1987-01-01

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

  6. Bayesian image restoration for medical images using radon transform

    International Nuclear Information System (INIS)

    Shouno, Hayaru; Okada, Masato

    2010-01-01

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

  7. 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.

  8. 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...

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

    Science.gov (United States)

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

    2015-04-01

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

  10. Superconductors and medical imaging

    International Nuclear Information System (INIS)

    Aubert, Guy

    2011-01-01

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

  11. Modulation transfer function cascade model for a sampled IR imaging system.

    Science.gov (United States)

    de Luca, L; Cardone, G

    1991-05-01

    The performance of the infrared scanning radiometer (IRSR) is strongly stressed in convective heat transfer applications where high spatial frequencies in the signal that describes the thermal image are present. The need to characterize more deeply the system spatial resolution has led to the formulation of a cascade model for the evaluation of the actual modulation transfer function of a sampled IR imaging system. The model can yield both the aliasing band and the averaged modulation response for a general sampling subsystem. For a line scan imaging system, which is the case of a typical IRSR, a rule of thumb that states whether the combined sampling-imaging system is either imaging-dependent or sampling-dependent is proposed. The model is tested by comparing it with other noncascade models as well as by ad hoc measurements performed on a commercial digitized IRSR.

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

    Science.gov (United States)

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

    2017-11-01

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

  14. Multispectral system for medical fluorescence imaging

    International Nuclear Information System (INIS)

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

    1987-01-01

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

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

    Science.gov (United States)

    Handels, H; Ehrhardt, J

    2009-01-01

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

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

    Science.gov (United States)

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

    2013-10-01

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

  17. Synchrotrons and their applications in medical imaging and therapy

    International Nuclear Information System (INIS)

    Lewis, R.

    2004-01-01

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

  18. 76 FR 45402 - Advisory Committee; Medical Imaging Drugs Advisory Committee; Re-Establishment

    Science.gov (United States)

    2011-07-29

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

  19. High-performance method of morphological medical image processing

    Directory of Open Access Journals (Sweden)

    Ryabykh M. S.

    2016-07-01

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

  20. 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)

  1. 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.

  2. Fluorescence resonance energy transfer imaging of CFP/YFP labeled NDH in cyanobacterium cell

    International Nuclear Information System (INIS)

    Ji Dongmei; Lv Wei; Huang Zhengxi; Xia Andong; Xu Min; Ma Weimin; Mi Hualing; Ogawa Teruo

    2007-01-01

    The laser confocal scanning microscopy combined with time-correlated single photon counting imaging technique to obtain fluorescence intensity and fluorescence lifetime images for fluorescence resonance energy transfer measurement is reported. Both the fluorescence lifetime imaging microscopy (FLIM) and intensity images show inhomogeneous cyan fluorescent protein and yellow fluorescent protein (CFP /YFP) expression or inhomogeneous energy transfer between CFP and YFP over whole cell. The results presented in this work show that FLIM could be a potential method to reveal the structure-function behavior of NAD(P)H dehydrogenase complexes in living cell

  3. Spatio-Temporal Encoding in Medical Ultrasound Imaging

    DEFF Research Database (Denmark)

    Gran, Fredrik

    2005-01-01

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

  4. 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.

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

    Directory of Open Access Journals (Sweden)

    Xingxing Zhu

    2018-05-01

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

  6. [Study of Image Quality Comparison Based on the MTF Method Between Different Medical Rigid Endoscopes in an In Vitro Model].

    Science.gov (United States)

    Wang, Yunlong; Ji, Jun; Jiang, Changsong; Huang, Zengyue

    2015-04-01

    This study was aimed to use the method of modulation transfer function (MTF) to compare image quality among three different Olympus medical rigid cystoscopes in an in vitro model. During the experimental processes, we firstly used three different types of cystoscopes (i. e. OLYMPUS cystourethroscopy with FOV of 12 degrees, OLYMPUS Germany A22003A and OLYMPUS A2013A) to collect raster images at different brightness with industrial camera and computer from the resolution target which is with different spatial frequency, and then we processed the collected images using MALAB software with the optical transfer function MTF to obtain the values of MTF at different brightness and different spatial frequency. We then did data mathematical statistics and compared imaging quality. The statistical data showed that all three MTF values were smaller than 1. MTF values with the spatial frequency gradually increasing would decrease approaching 0 at the same brightness. When the brightness enhanced in the same process at the same spatial frequency, MTF values showed a slowly increasing trend. The three endoscopes' MTF values were completely different. In some cases the MTF values had a large difference, and the maximum difference could reach 0.7. Conclusion can be derived from analysis of experimental data that three Olympus medical rigid cystoscopes have completely different imaging quality abilities. The No. 3 endoscope OLYMPUS A2013A has low resolution but high contrast. The No. 1 endoscope OLYMPUS cystourethroscopy with FOV of 12 degrees, on the contrary, had high resolution and lower contrast. The No. 2 endoscope OLYMPUS Germany A22003A had high contrast and high resolution, and its image quality was the best.

  7. Characterisation of a CMOS charge transfer device for TDI imaging

    International Nuclear Information System (INIS)

    Rushton, J.; Holland, A.; Stefanov, K.; Mayer, F.

    2015-01-01

    The performance of a prototype true charge transfer imaging sensor in CMOS is investigated. The finished device is destined for use in TDI applications, especially Earth-observation, and to this end radiation tolerance must be investigated. Before this, complete characterisation is required. This work starts by looking at charge transfer inefficiency and then investigates responsivity using mean-variance techniques

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

    Science.gov (United States)

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

    2015-01-01

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

  9. Quantification of heterogeneity observed in medical images

    OpenAIRE

    Brooks, Frank J; Grigsby, Perry W

    2013-01-01

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

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

    Science.gov (United States)

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

    2018-02-01

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

  11. Automatic transfer function design for medical visualization using visibility distributions and projective color mapping.

    Science.gov (United States)

    Cai, Lile; Tay, Wei-Liang; Nguyen, Binh P; Chui, Chee-Kong; Ong, Sim-Heng

    2013-01-01

    Transfer functions play a key role in volume rendering of medical data, but transfer function manipulation is unintuitive and can be time-consuming; achieving an optimal visualization of patient anatomy or pathology is difficult. To overcome this problem, we present a system for automatic transfer function design based on visibility distribution and projective color mapping. Instead of assigning opacity directly based on voxel intensity and gradient magnitude, the opacity transfer function is automatically derived by matching the observed visibility distribution to a target visibility distribution. An automatic color assignment scheme based on projective mapping is proposed to assign colors that allow for the visual discrimination of different structures, while also reflecting the degree of similarity between them. When our method was tested on several medical volumetric datasets, the key structures within the volume were clearly visualized with minimal user intervention. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

    Directory of Open Access Journals (Sweden)

    Baoru Han

    2015-09-01

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

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

    Science.gov (United States)

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

    2014-10-01

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

  14. Intrasubject registration for change analysis in medical imaging

    NARCIS (Netherlands)

    Staring, M.

    2008-01-01

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

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

    Science.gov (United States)

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

    2017-02-01

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

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

    Science.gov (United States)

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

    2015-11-01

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

  17. Medical Imaging Image Quality Assessment with Monte Carlo Methods

    International Nuclear Information System (INIS)

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

    2015-01-01

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

  18. Multi-task transfer learning deep convolutional neural network: application to computer-aided diagnosis of breast cancer on mammograms

    Science.gov (United States)

    Samala, Ravi K.; Chan, Heang-Ping; Hadjiiski, Lubomir M.; Helvie, Mark A.; Cha, Kenny H.; Richter, Caleb D.

    2017-12-01

    Transfer learning in deep convolutional neural networks (DCNNs) is an important step in its application to medical imaging tasks. We propose a multi-task transfer learning DCNN with the aim of translating the ‘knowledge’ learned from non-medical images to medical diagnostic tasks through supervised training and increasing the generalization capabilities of DCNNs by simultaneously learning auxiliary tasks. We studied this approach in an important application: classification of malignant and benign breast masses. With Institutional Review Board (IRB) approval, digitized screen-film mammograms (SFMs) and digital mammograms (DMs) were collected from our patient files and additional SFMs were obtained from the Digital Database for Screening Mammography. The data set consisted of 2242 views with 2454 masses (1057 malignant, 1397 benign). In single-task transfer learning, the DCNN was trained and tested on SFMs. In multi-task transfer learning, SFMs and DMs were used to train the DCNN, which was then tested on SFMs. N-fold cross-validation with the training set was used for training and parameter optimization. On the independent test set, the multi-task transfer learning DCNN was found to have significantly (p  =  0.007) higher performance compared to the single-task transfer learning DCNN. This study demonstrates that multi-task transfer learning may be an effective approach for training DCNN in medical imaging applications when training samples from a single modality are limited.

  19. 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

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

    Science.gov (United States)

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

    2016-10-01

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

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

    Institute of Scientific and Technical Information of China (English)

    L(U) Qingwen; CHEN Wufan

    2006-01-01

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

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

    Science.gov (United States)

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

    2016-09-01

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

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

    International Nuclear Information System (INIS)

    Duncan, J.S.; Gerig, G.

    2005-01-01

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

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

    International Nuclear Information System (INIS)

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

    2005-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2005-07-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2005-07-01

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

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

    Science.gov (United States)

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

    2015-05-01

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

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

    DEFF Research Database (Denmark)

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

    2008-01-01

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

  9. Imaging systems for medical diagnostics

    International Nuclear Information System (INIS)

    Krestel, E.

    1990-01-01

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

  10. 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

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

    Science.gov (United States)

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

    2017-11-03

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

  12. 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

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

    Science.gov (United States)

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

    2007-01-01

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

  14. View interpolation for medical images on autostereoscopic displays

    NARCIS (Netherlands)

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

    2012-01-01

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

  15. 41 CFR 102-36.465 - May we transfer or exchange excess medical shelf-life items with other federal agencies?

    Science.gov (United States)

    2010-07-01

    ... exchange excess medical shelf-life items with other federal agencies? 102-36.465 Section 102-36.465 Public... Disposal Requires Special Handling Shelf-Life Items § 102-36.465 May we transfer or exchange excess medical shelf-life items with other federal agencies? Yes, you may transfer or exchange excess medical shelf...

  16. Conjugate Image Theory Applied on Capacitive Wireless Power Transfer

    Directory of Open Access Journals (Sweden)

    Ben Minnaert

    2017-01-01

    Full Text Available Wireless power transfer using a magnetic field through inductive coupling is steadily entering the market in a broad range of applications. However, for certain applications, capacitive wireless power transfer using electric coupling might be preferable. In order to obtain a maximum power transfer efficiency, an optimal compensation network must be designed at the input and output ports of the capacitive wireless link. In this work, the conjugate image theory is applied to determine this optimal network as a function of the characteristics of the capacitive wireless link, as well for the series as for the parallel topology. The results are compared with the inductive power transfer system. Introduction of a new concept, the coupling function, enables the description of the compensation network of both an inductive and a capacitive system in two elegant equations, valid for the series and the parallel topology. This approach allows better understanding of the fundamentals of the wireless power transfer link, necessary for the design of an efficient system.

  17. SemVisM: semantic visualizer for medical image

    Science.gov (United States)

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

    2015-01-01

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

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

    International Nuclear Information System (INIS)

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

    2009-01-01

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

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

    Science.gov (United States)

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

    2016-04-01

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

  20. Are Clinical Trial Experiences Utilized?: A Differentiated Model of Medical Sites’ Information Transfer Ability

    DEFF Research Database (Denmark)

    Smed, Marie; Schultz, Carsten; Getz, Kenneth A.

    2015-01-01

    The collaboration with medical professionals in pharmaceutical clinical trials facilitates opportunities to gain valuable market information concerning product functionality issues, as well as issues related to market implementation and adoption. However, previous research on trial management lacks......’ information transfer ability, their methods of communicating, are included. The model is studied on a unique dataset of 395 medical site representatives by applying Rasch scale modeling to differentiate the stickiness of the heterogenic information issues. The results reveal that economic measures...... a differentiated perspective on the potential for information transfer from site to producer. An exploration of the variation in stickiness of information, and therefore the complexity of information transfer in clinical trials, is the main aim of this study. To further enrich the model of the dispersed sites...

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

    Science.gov (United States)

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

    1993-10-01

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

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

    Science.gov (United States)

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

    2017-11-01

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

  3. Plane Wave Medical Ultrasound Imaging Using Adaptive Beamforming

    DEFF Research Database (Denmark)

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

    2008-01-01

    In this paper, the adaptive, minimum variance (MV) beamformer is applied to medical ultrasound imaging. The Significant resolution and contrast gain provided by the adaptive, minimum variance (MV) beamformer, introduces the possibility of plane wave (PW) ultrasound imaging. Data is obtained using...

  4. From medical imaging data to 3D printed anatomical models.

    Directory of Open Access Journals (Sweden)

    Thore M Bücking

    Full Text Available Anatomical models are important training and teaching tools in the clinical environment and are routinely used in medical imaging research. Advances in segmentation algorithms and increased availability of three-dimensional (3D printers have made it possible to create cost-efficient patient-specific models without expert knowledge. We introduce a general workflow that can be used to convert volumetric medical imaging data (as generated by Computer Tomography (CT to 3D printed physical models. This process is broken up into three steps: image segmentation, mesh refinement and 3D printing. To lower the barrier to entry and provide the best options when aiming to 3D print an anatomical model from medical images, we provide an overview of relevant free and open-source image segmentation tools as well as 3D printing technologies. We demonstrate the utility of this streamlined workflow by creating models of ribs, liver, and lung using a Fused Deposition Modelling 3D printer.

  5. 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)

  6. Robotic 3D scanner as an alternative to standard modalities of medical imaging.

    Science.gov (United States)

    Chromy, Adam; Zalud, Ludek

    2014-01-01

    There are special medical cases, where standard medical imaging modalities are able to offer sufficient results, but not in the optimal way. It means, that desired results are produced with unnecessarily high expenses, with redundant informations or with needless demands on patient. This paper deals with one special case, where information useful for examination is the body surface only, inner sight into the body is needless. New specialized medical imaging device is developed for this situation. In the Introduction section, analysis of presently used medical imaging modalities is presented, which declares, that no available imaging device is best fitting for mentioned purposes. In the next section, development of the new specialized medical imaging device is presented, and its principles and functions are described. Then, the parameters of new device are compared with present ones. It brings significant advantages comparing to present imaging systems.

  7. Multi-provider architecture for cloud outsourcing of medical imaging repositories.

    Science.gov (United States)

    Godinho, Tiago Marques; Bastião Silva, Luís A; Costa, Carlos; Oliveira, José Luís

    2014-01-01

    Over the last few years, the extended usage of medical imaging procedures has raised the medical community attention towards the optimization of their workflows. More recently, the federation of multiple institutions into a seamless distribution network has brought hope of increased quality healthcare services along with more efficient resource management. As a result, medical institutions are constantly looking for the best infrastructure to deploy their imaging archives. In this scenario, public cloud infrastructures arise as major candidates, as they offer elastic storage space, optimal data availability without great requirements of maintenance costs or IT personnel, in a pay-as-you-go model. However, standard methodologies still do not take full advantage of outsourced archives, namely because their integration with other in-house solutions is troublesome. This document proposes a multi-provider architecture for integration of outsourced archives with in-house PACS resources, taking advantage of foreign providers to store medical imaging studies, without disregarding security. It enables the retrieval of images from multiple archives simultaneously, improving performance, data availability and avoiding the vendor-locking problem. Moreover it enables load balancing and cache techniques.

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

    Science.gov (United States)

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

    2016-02-12

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

  9. 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.

  10. Real-Time Implementation of Medical Ultrasound Strain Imaging System

    International Nuclear Information System (INIS)

    Jeong, Mok Kun; Kwon, Sung Jae; Bae, Moo Ho

    2008-01-01

    Strain imaging in a medical ultrasound imaging system can differentiate the cancer or tumor in a lesion that is stiffer than the surrounding tissue. In this paper, a strain imaging technique using quasistatic compression is implemented that estimates the displacement between pre- and postcompression ultrasound echoes and obtains strain by differentiating it in the spatial direction. Displacements are computed from the phase difference of complex baseband signals obtained using their autocorrelation, and errors associated with converting the phase difference into time or distance are compensated for by taking into the center frequency variation. Also, to reduce the effect of operator's hand motion, the displacements of all scanlines are normalized with the result that satisfactory strain image quality has been obtained. These techniques have been incorporated into implementing a medical ultrasound strain imaging system that operates in real time.

  11. The masked educator-innovative simulation in an Australian undergraduate Medical Sonography and Medical Imaging program.

    Science.gov (United States)

    Reid-Searl, Kerry; Bowman, Anita; McAllister, Margaret; Cowling, Cynthia; Spuur, Kelly

    2014-12-01

    Clinical learning experiences for sonography and medical imaging students can sometimes involve the practice of technical procedures with less of a focus on developing communication skills with patients. Whilst patient-based simulation scenarios have been widely reported in other health education programmes, there is a paucity of research in sonography and medical imaging. The aim of this study was to explore the effectiveness of Mask-Ed™ (KRS Simulation) in the learning and teaching of clinical communication skills to undergraduate medical sonography and medical imaging students. Mask-Ed™ (KRS Simulation) is a simulation technique where the educator is hidden behind wearable realistic silicone body props including masks. Focus group interviews were conducted with 11 undergraduate medical sonography and medical imaging students at CQUniversity, Australia. The number of participants was limited to the size of the cohort of students enrolled in the course. Prior to these interviews participants were engaged in learning activities that featured the use of the Mask-Ed™ (KRS Simulation) method. Thematic analysis was employed to explore how the introduction of Mask-Ed™ (KRS Simulation) contributed to students' learning in relation to clinical communication skills. Key themes included: benefits of interacting with someone real rather than another student, learning made fun, awareness of empathy, therapeutic communication skills, engaged problem solving and purposeful reflection. Mask-Ed™ (KRS Simulation) combined with interactive sessions with an expert facilitator, contributed positively to students' learning in relation to clinical communication skills. Participants believed that interacting with someone real, as in the Mask-Ed characters was beneficial. In addition to the learning being described as fun, participants gained an awareness of empathy, therapeutic communication skills, engaged problem solving and purposeful reflection.

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

    Science.gov (United States)

    Shen, Hualei; Tao, Dacheng; Ma, Dianfu

    2013-01-01

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

  13. An analytical look at the effects of compression on medical images

    OpenAIRE

    Persons, Kenneth; Palisson, Patrice; Manduca, Armando; Erickson, Bradley J.; Savcenko, Vladimir

    1997-01-01

    This article will take an analytical look at how lossy Joint Photographic Experts Group (JPEG) and wavelet image compression techniques affect medical image content. It begins with a brief explanation of how the JPEG and wavelet algorithms work, and describes in general terms what effect they can have on image quality (removal of noise, blurring, and artifacts). It then focuses more specifically on medical image diagnostic content and explains why subtle pathologies, that may be difficult for...

  14. Telemedicine using an image transfer system in the treatment of neurosurgical emergent cases

    International Nuclear Information System (INIS)

    Saito, Atsushi; Numagami, Yoshihiro; Kamiyama, Hironaga; Furuno, Yuuichi; Nishimura, Shinjitsu; Nishijima, Michiharu

    2007-01-01

    Our department is located in the Tsugaru district, which is famous for heavy snow fall, and the small number of neurosurgeon centers in the urban areas leads to an inadequate distribution of neurosurgeons for patients in this region. Such geographical and social constraints have made it difficult to offer sufficient neurosurgical care to all patients in the region. We describe the usefulness of a telemedicine triage system using an image transfer system in the treatment of neurosurgical emergent cases. Image transfer systems have been installed at our hospital and 11 regional hospitals in the Tsugaru district, and have been utilized for teleconsultation regarding neurosurgical patients via transferred computed tomography images since 1989. Consultations regarding 2,858 cases were directed to our department between 1989 and 2006, including 1,615 cases of stroke, 869 cases of head trauma, 97 cases of brain tumor, and 277 cases with other disorders. 84% of subarachnoid hemorrhage cases and 22% of head trauma cases needed emergent transfer. The state of consciousness in intracerebral hemorrhage, and the state of consciousness and time of consultation in head trauma were statistically significant factors for emergent transfer. The presert telemedicine triage system was useful for ensuring correct diagnosis and appropriate primary neurosurgical care in the regional hospitals without neurosurgical units, resulting in a reinforcement of the relationships among the regional hospitals and the efficient transfer of emergent neurosurgical patients. (author)

  15. 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

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

    CERN Document Server

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

    2008-01-01

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

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

    International Nuclear Information System (INIS)

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

    2011-01-01

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

  18. The study of diagnosis status and, transfer time of stroke patients transferred by pre-hospital emergency medical system (EMS to Vali-Asr hospital in Arak City

    Directory of Open Access Journals (Sweden)

    Saiedeh Bahrampouri

    2013-08-01

    Full Text Available Introduction: Stroke is main cause of death and disability in worldwide and emergency care can decrease complications. Emergency Medical System transferred half of stroke patients to hospital, so improve accuracy of diagnosis may accelerated treatment. This study aimed to determine diagnosis status and, transfer time of stroke patients transferred by prehospital Emergency Medical System to hospital in Arak City. Methods: This study was descriptive -analytic study and all 43 patient’s records with a diagnosis of stroke that transferred by Emergency Medical System to hospital in Arak City was selected. The study Checklist was contained information about age, sex, type of accident prehospital, response time, scene time, transfer time and total time from inpatients records and Emergency Center statistics .Regarding data analysis,SPSS19 software and descriptive statistical tests were used. Results: Mean (SD of age all patients were 73/7±3/8 and 51/2% were women. Ambulance paramedics' stroke diagnosis was correct in 15 (34/9%,20(46/5%of false and 8(18/6% not diagnosed for stroke patients who initially presented to them. The most common non stroke conditions were confusion. Mean response time and scene time, transfer time and total time were 6/9,16/9,9/1 and 35/3 minutes, respectively. In patients with correct diagnose stroke, mean response, scene, transfer and total time were 7,17/1,3/9 and 35/7 minutes. The people with the wrong diagnosis or no diagnosis of stroke by emergency medical personnel were taken to hospital, Mean response, scene, transfer and total time were 6/9, 16/8,9/7 and 33/5 minutes. Conclusions: The results of this study showed that, the correct diagnosis by EMS personnel could be resulted faster transferring patient to definite treatment center.It is recommended to develop prehospital diagnosis tool of stroke, which is contextually adapted and appropriate to facilitate diagnose of strokes and improve the quality of care.

  19. Plane-Wave Imaging Challenge in Medical Ultrasound

    DEFF Research Database (Denmark)

    Liebgott, Herve; Molares, Alfonso Rodriguez; Jensen, Jørgen Arendt

    2016-01-01

    for this effect, but comparing the different methods is difficult due to the lack of appropriate tools. PICMUS, the Plane-Wave Imaging Challenge in Medical Ultrasound aims to provide these tools. This paper describes the PICMUS challenge, its motivation, implementation, and metrics.......Plane-Wave imaging enables very high frame rates, up to several thousand frames per second. Unfortunately the lack of transmit focusing leads to reduced image quality, both in terms of resolution and contrast. Recently, numerous beamforming techniques have been proposed to compensate...

  20. Using photoshop filters to create anatomic line-art medical images.

    Science.gov (United States)

    Kirsch, Jacobo; Geller, Brian S

    2006-08-01

    There are multiple ways to obtain anatomic drawings suitable for publication or presentations. This article demonstrates how to use Photoshop to alter digital radiologic images to create line-art illustrations in a quick and easy way. We present two simple to use methods; however, not every image can adequately be transformed and personal preferences and specific changes need to be applied to each image to obtain the desired result. There are multiple ways to obtain anatomic drawings suitable for publication or to prepare presentations. Medical illustrators have always played a major role in the radiology and medical education process. Whether used to teach a complex surgical or radiologic procedure, to define typical or atypical patterns of the spread of disease, or to illustrate normal or aberrant anatomy, medical illustration significantly affects learning (). However, if you are not an accomplished illustrator, the alternatives can be expensive (contacting a professional medical illustrator or buying an already existing stock of digital images) or simply not necessarily applicable to what you are trying to communicate. The purpose of this article is to demonstrate how using Photoshop (Adobe Systems, San Jose, CA) to alter digital radiologic images we can create line-art illustrations in a quick, inexpensive, and easy way in preparation for electronic presentations and publication.

  1. Log-Gabor Energy Based Multimodal Medical Image Fusion in NSCT Domain

    Directory of Open Access Journals (Sweden)

    Yong Yang

    2014-01-01

    Full Text Available Multimodal medical image fusion is a powerful tool in clinical applications such as noninvasive diagnosis, image-guided radiotherapy, and treatment planning. In this paper, a novel nonsubsampled Contourlet transform (NSCT based method for multimodal medical image fusion is presented, which is approximately shift invariant and can effectively suppress the pseudo-Gibbs phenomena. The source medical images are initially transformed by NSCT followed by fusing low- and high-frequency components. The phase congruency that can provide a contrast and brightness-invariant representation is applied to fuse low-frequency coefficients, whereas the Log-Gabor energy that can efficiently determine the frequency coefficients from the clear and detail parts is employed to fuse the high-frequency coefficients. The proposed fusion method has been compared with the discrete wavelet transform (DWT, the fast discrete curvelet transform (FDCT, and the dual tree complex wavelet transform (DTCWT based image fusion methods and other NSCT-based methods. Visually and quantitatively experimental results indicate that the proposed fusion method can obtain more effective and accurate fusion results of multimodal medical images than other algorithms. Further, the applicability of the proposed method has been testified by carrying out a clinical example on a woman affected with recurrent tumor images.

  2. Image processing for medical diagnosis of human organs

    International Nuclear Information System (INIS)

    Tamura, Shin-ichi

    1989-01-01

    The report first describes expectations and needs for diagnostic imaging in the field of clinical medicine, radiation medicine in particular, viewed by the author as an image processing expert working at a medical institute. Then, medical image processing techniques are discussed in relation to advanced information processing techniques that are currently drawing much attention in the field of engineering. Finally, discussion is also made of practical applications of image processing techniques to diagnosis. In the field of clinical diagnosis, advanced equipment such as PACS (picture archiving and communication system) has come into wider use, and efforts have been made to shift from visual examination to more quantitative and objective diagnosis by means of such advanced systems. In clinical medicine, practical, robust systems are more useful than sophisticated ones. It is difficult, though important, to develop completely automatized diagnostic systems. The urgent, realistic goal, therefore, is to develop effective diagnosis support systems. In particular, operation support systems equipped with three-dimensional displays will be very useful. (N.K.)

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

    Directory of Open Access Journals (Sweden)

    Čabarkapa Slobodan

    2009-01-01

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

  4. Using digital watermarking to enhance security in wireless medical image transmission.

    Science.gov (United States)

    Giakoumaki, Aggeliki; Perakis, Konstantinos; Banitsas, Konstantinos; Giokas, Konstantinos; Tachakra, Sapal; Koutsouris, Dimitris

    2010-04-01

    During the last few years, wireless networks have been increasingly used both inside hospitals and in patients' homes to transmit medical information. In general, wireless networks suffer from decreased security. However, digital watermarking can be used to secure medical information. In this study, we focused on combining wireless transmission and digital watermarking technologies to better secure the transmission of medical images within and outside the hospital. We utilized an integrated system comprising the wireless network and the digital watermarking module to conduct a series of tests. The test results were evaluated by medical consultants. They concluded that the images suffered no visible quality degradation and maintained their diagnostic integrity. The proposed integrated system presented reasonable stability, and its performance was comparable to that of a fixed network. This system can enhance security during the transmission of medical images through a wireless channel.

  5. 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 ...

  6. 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

  7. Advantages of semiconductor CZT for medical imaging

    Science.gov (United States)

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

    2007-09-01

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

  8. 78 FR 734 - Medical Imaging Drugs Advisory Committee; Notice of Meeting

    Science.gov (United States)

    2013-01-04

    ...] Medical Imaging Drugs Advisory Committee; Notice of Meeting AGENCY: Food and Drug Administration, HHS... and Drug Administration (FDA). The meeting will be open to the public. Name of Committee: Medical Imaging Drugs Advisory Committee. General Function of the Committee: To provide advice and recommendations...

  9. Digital mammographic tumor classification using transfer learning from deep convolutional neural networks.

    Science.gov (United States)

    Huynh, Benjamin Q; Li, Hui; Giger, Maryellen L

    2016-07-01

    Convolutional neural networks (CNNs) show potential for computer-aided diagnosis (CADx) by learning features directly from the image data instead of using analytically extracted features. However, CNNs are difficult to train from scratch for medical images due to small sample sizes and variations in tumor presentations. Instead, transfer learning can be used to extract tumor information from medical images via CNNs originally pretrained for nonmedical tasks, alleviating the need for large datasets. Our database includes 219 breast lesions (607 full-field digital mammographic images). We compared support vector machine classifiers based on the CNN-extracted image features and our prior computer-extracted tumor features in the task of distinguishing between benign and malignant breast lesions. Five-fold cross validation (by lesion) was conducted with the area under the receiver operating characteristic (ROC) curve as the performance metric. Results show that classifiers based on CNN-extracted features (with transfer learning) perform comparably to those using analytically extracted features [area under the ROC curve [Formula: see text

  10. Creating New Medical Ontologies for Image Annotation A Case Study

    CERN Document Server

    Stanescu, Liana; Brezovan, Marius; Mihai, Cristian Gabriel

    2012-01-01

    Creating New Medical Ontologies for Image Annotation focuses on the problem of the medical images automatic annotation process, which is solved in an original manner by the authors. All the steps of this process are described in detail with algorithms, experiments and results. The original algorithms proposed by authors are compared with other efficient similar algorithms. In addition, the authors treat the problem of creating ontologies in an automatic way, starting from Medical Subject Headings (MESH). They have presented some efficient and relevant annotation models and also the basics of the annotation model used by the proposed system: Cross Media Relevance Models. Based on a text query the system will retrieve the images that contain objects described by the keywords.

  11. Information Recovery Algorithm for Ground Objects in Thin Cloud Images by Fusing Guide Filter and Transfer Learning

    Directory of Open Access Journals (Sweden)

    HU Gensheng

    2018-03-01

    Full Text Available Ground object information of remote sensing images covered with thin clouds is obscure. An information recovery algorithm for ground objects in thin cloud images is proposed by fusing guide filter and transfer learning. Firstly, multi-resolution decomposition of thin cloud target images and cloud-free guidance images is performed by using multi-directional nonsubsampled dual-tree complex wavelet transform. Then the decomposed low frequency subbands are processed by using support vector guided filter and transfer learning respectively. The decomposed high frequency subbands are enhanced by using modified Laine enhancement function. The low frequency subbands output by guided filter and those predicted by transfer learning model are fused by the method of selection and weighting based on regional energy. Finally, the enhanced high frequency subbands and the fused low frequency subbands are reconstructed by using inverse multi-directional nonsubsampled dual-tree complex wavelet transform to obtain the ground object information recovery images. Experimental results of Landsat-8 OLI multispectral images show that, support vector guided filter can effectively preserve the detail information of the target images, domain adaptive transfer learning can effectively extend the range of available multi-source and multi-temporal remote sensing images, and good effects for ground object information recover are obtained by fusing guide filter and transfer learning to remove thin cloud on the remote sensing images.

  12. Mapping Iterative Medical Imaging Algorithm on Cell Accelerator

    Directory of Open Access Journals (Sweden)

    Meilian Xu

    2011-01-01

    architectures that exploit data parallel applications, medical imaging algorithms such as OS-SART can be studied to produce increased performance. In this paper, we map OS-SART on cell broadband engine (Cell BE. We effectively use the architectural features of Cell BE to provide an efficient mapping. The Cell BE consists of one powerPC processor element (PPE and eight SIMD coprocessors known as synergetic processor elements (SPEs. The limited memory storage on each of the SPEs makes the mapping challenging. Therefore, we present optimization techniques to efficiently map the algorithm on the Cell BE for improved performance over CPU version. We compare the performance of our proposed algorithm on Cell BE to that of Sun Fire ×4600, a shared memory machine. The Cell BE is five times faster than AMD Opteron dual-core processor. The speedup of the algorithm on Cell BE increases with the increase in the number of SPEs. We also experiment with various parameters, such as number of subsets, number of processing elements, and number of DMA transfers between main memory and local memory, that impact the performance of the algorithm.

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

    Science.gov (United States)

    Giglia, E

    2008-09-01

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

  14. Establishing advanced practice for medical imaging in New Zealand

    International Nuclear Information System (INIS)

    Yielder, Jill; Young, Adrienne; Park, Shelley; Coleman, Karen

    2014-01-01

    Introduction: This article presents the outcome and recommendations following the second stage of a role development project conducted on behalf of the New Zealand Institute of Medical Radiation Technology (NZIMRT). The study sought to support the development of profiles and criteria that may be used to formulate Advanced Scopes of Practice for the profession. It commenced in 2011, following on from initial research that occurred between 2005 and 2008 investigating role development and a possible career structure for medical radiation technologists (MRTs) in New Zealand (NZ). Methods: The study sought to support the development of profiles and criteria that could be used to develop Advanced Scopes of Practice for the profession through inviting 12 specialist medical imaging groups in NZ to participate in a survey. Results: Findings showed strong agreement on potential profiles and on generic criteria within them; however, there was less agreement on specific skills criteria within specialist areas. Conclusions: The authors recommend that one Advanced Scope of Practice be developed for Medical Imaging, with the establishment of generic and specialist criteria. Systems for approval of the overall criteria package for any individual Advanced Practitioner (AP) profile, audit and continuing professional development requirements need to be established by the Medical Radiation Technologists Board (MRTB) to meet the local needs of clinical departments. It is further recommended that the NZIMRT and MRTB promote and support the need for an AP pathway for medical imaging in NZ

  15. Establishing advanced practice for medical imaging in New Zealand

    Energy Technology Data Exchange (ETDEWEB)

    Yielder, Jill, E-mail: j.yielder@auckland.ac.nz [University of Auckland, Auckland (New Zealand); Young, Adrienne; Park, Shelley; Coleman, Karen [University of Otago, Wellington (New Zealand); University of Auckland, Auckland (New Zealand)

    2014-02-15

    Introduction: This article presents the outcome and recommendations following the second stage of a role development project conducted on behalf of the New Zealand Institute of Medical Radiation Technology (NZIMRT). The study sought to support the development of profiles and criteria that may be used to formulate Advanced Scopes of Practice for the profession. It commenced in 2011, following on from initial research that occurred between 2005 and 2008 investigating role development and a possible career structure for medical radiation technologists (MRTs) in New Zealand (NZ). Methods: The study sought to support the development of profiles and criteria that could be used to develop Advanced Scopes of Practice for the profession through inviting 12 specialist medical imaging groups in NZ to participate in a survey. Results: Findings showed strong agreement on potential profiles and on generic criteria within them; however, there was less agreement on specific skills criteria within specialist areas. Conclusions: The authors recommend that one Advanced Scope of Practice be developed for Medical Imaging, with the establishment of generic and specialist criteria. Systems for approval of the overall criteria package for any individual Advanced Practitioner (AP) profile, audit and continuing professional development requirements need to be established by the Medical Radiation Technologists Board (MRTB) to meet the local needs of clinical departments. It is further recommended that the NZIMRT and MRTB promote and support the need for an AP pathway for medical imaging in NZ.

  16. Medical Imaging Field of Magnetic Resonance Imaging: Identification of Specialties within the Field

    Science.gov (United States)

    Grey, Michael L.

    2009-01-01

    This study was conducted to determine if specialty areas are emerging in the magnetic resonance imaging (MRI) profession due to advancements made in the medical sciences, imaging technology, and clinical applications used in MRI that would require new developments in education/training programs and national registry examinations. In this…

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

    International Nuclear Information System (INIS)

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

    1999-01-01

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

  18. Placental transfer of antidepressant medications: implications for postnatal adaptation syndrome.

    Science.gov (United States)

    Ewing, Grace; Tatarchuk, Yekaterina; Appleby, Dina; Schwartz, Nadav; Kim, Deborah

    2015-04-01

    Seven to thirteen percent of women are either prescribed or taking (depending on the study) an antidepressant during pregnancy. Because antidepressants freely cross into the intrauterine environment, we aim to summarize the current findings on placental transfer of antidepressants. Although generally low risk, antidepressants have been associated with postnatal adaptation syndrome (PNAS). Specifically, we explore whether the antidepressants most closely associated with PNAS (paroxetine, fluoxetine, venlafaxine) cross the placenta to a greater extent than other antidepressants. We review research on antidepressants in the context of placental anatomy, placental transport mechanisms, placental metabolism, pharmacokinetics, as well as non-placental maternal and fetal factors. This provides insight into the complexity involved in understanding how placental transfer of antidepressants may relate to adverse perinatal outcomes. Ultimately, from this data there is no pattern in which PNAS is related to placental transfer of antidepressant medications. In general, there is large interindividual variability for each type of antidepressant. To make the most clinically informed decisions about the use of antidepressants in pregnancy, studies that link maternal, placental and fetal genetic polymorphisms, placental transfer rates and infant outcomes are needed.

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

    DEFF Research Database (Denmark)

    2015-01-01

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

  20. Medical Imaging in Differentiating the Diabetic Charcot Foot from Osteomyelitis.

    Science.gov (United States)

    Short, Daniel J; Zgonis, Thomas

    2017-01-01

    Diabetic Charcot neuroarthropathy (DCN) poses a great challenge to diagnose in the early stages and when plain radiographs do not depict any initial signs of osseous fragmentation or dislocation in a setting of a high clinical index of suspicion. Medical imaging, including magnetic resonance imaging, computed tomography, and advanced bone scintigraphy, has its own unique clinical indications when treating the DCN with or without concomitant osteomyelitis. This article reviews different clinical case scenarios for choosing the most accurate medical imaging in differentiating DCN from osteomyelitis. Copyright © 2016 Elsevier Inc. All rights reserved.

  1. Investigating Students' Ideas About X-rays While Developing Teaching Materials for a Medical Physics Course

    International Nuclear Information System (INIS)

    Kalita, Spartak; Zollman, Dean

    2007-01-01

    The goal of the Modern Miracle Medical Machines project is to promote pre-med students' interest in physics by using the context of contemporary medical imaging. The X-ray medical imaging learning module will be a central part of this effort. To investigate students' transfer of learning in this context we have conducted a series of clinical and teaching interviews. In the latter interview, some of the proposed learning materials were used. The students brought to our discussion pieces of knowledge transferred from very different sources such as their own X-ray experiences, previous learning and the mass media. This transfer seems to result in more or less firm mental models which often are not always internally consistent or coherent

  2. Fast fluid registration of medical images

    DEFF Research Database (Denmark)

    Bro-Nielsen, Morten; Gramkow, Claus

    1996-01-01

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

  3. Meditate don't medicate: How medical imaging evidence supports the role of meditation in the treatment of depression

    International Nuclear Information System (INIS)

    Annells, S.; Kho, K.; Bridge, P.

    2016-01-01

    Introduction: Depression is a debilitating psychiatric disorder that affects a large proportion of the population. The current treatment for depression involves anti-depressant medication which is associated with side effects and a heightened risk of relapse. Methods: A systematic literature review was performed to determine the value of medical imaging studies in measuring the impact of meditation on depression. Results: Medical imaging studies have successfully demonstrated that meditation may counteract or prevent the physiological cause of depression by decreasing amygdala activity and increasing grey matter volume and activity of the hippocampus, prefrontal cortex and other brain regions associated with attention and emotional self-regulation. Recent advances in functional imaging have enabled visualisation of neural plasticity within the brain. This has shown that for meditators, practice-induced alterations could be due to micro-anatomical processes that may represent an increased functional capacity within the brain regions activated. These changes within brain physiology in association with the skills gained during meditation such as self-regulation, mental processing of negative information and relaxation techniques could potentially lead to a permanent cure for depression and thus prevent relapse. Conclusions: The results of this review suggest that medical imaging has a valuable role to play in evidencing the physiological changes within the brain caused by meditation that counteract those that cause depression. These studies indicate that meditation is a viable alternative to medication for clinical treatment of patients with depression. More rigorous longitudinal imaging studies are proposed to enhance understanding of the neural pathways and mechanisms of meditation. - Highlights: • Medical imaging demonstrates physiological changes that counteract those that cause depression. • Meditation is an alternative to medication for clinical treatment of

  4. The effect of the TIM program (Transfer ICU Medication reconciliation) on medication transfer errors in two Dutch intensive care units : Design of a prospective 8-month observational study with a before and after period

    NARCIS (Netherlands)

    B.E. Bosma (Bertha); E. Meuwese (Edmé); S.S. Tan (Siok Swan); J. van Bommel (Jasper); Melief, P.H.G.J. (Piet Herman Gerard Jan); N.G.M. Hunfeld (Nicola); P.M.L.A. van den Bemt (Patricia)

    2017-01-01

    markdownabstract__Background:__ The transfer of patients to and from the Intensive Care Unit (ICU) is prone to medication errors. The aim of the present study is to determine whether the number of medication errors at ICU admission and discharge and the associated potential harm and costs are

  5. Diagnostic imaging over the last 50 years: research and development in medical imaging science and technology

    International Nuclear Information System (INIS)

    Doi, Kunio

    2006-01-01

    Over the last 50 years, diagnostic imaging has grown from a state of infancy to a high level of maturity. Many new imaging modalities have been developed. However, modern medical imaging includes not only image production but also image processing, computer-aided diagnosis (CAD), image recording and storage, and image transmission, most of which are included in a picture archiving and communication system (PACS). The content of this paper includes a short review of research and development in medical imaging science and technology, which covers (a) diagnostic imaging in the 1950s, (b) the importance of image quality and diagnostic performance, (c) MTF, Wiener spectrum, NEQ and DQE, (d) ROC analysis, (e) analogue imaging systems, (f) digital imaging systems, (g) image processing, (h) computer-aided diagnosis, (i) PACS, (j) 3D imaging and (k) future directions. Although some of the modalities are already very sophisticated, further improvements will be made in image quality for MRI, ultrasound and molecular imaging. The infrastructure of PACS is likely to be improved further in terms of its reliability, speed and capacity. However, CAD is currently still in its infancy, and is likely to be a subject of research for a long time. (review)

  6. Medical Image Fusion Algorithm Based on Nonlinear Approximation of Contourlet Transform and Regional Features

    Directory of Open Access Journals (Sweden)

    Hui Huang

    2017-01-01

    Full Text Available According to the pros and cons of contourlet transform and multimodality medical imaging, here we propose a novel image fusion algorithm that combines nonlinear approximation of contourlet transform with image regional features. The most important coefficient bands of the contourlet sparse matrix are retained by nonlinear approximation. Low-frequency and high-frequency regional features are also elaborated to fuse medical images. The results strongly suggested that the proposed algorithm could improve the visual effects of medical image fusion and image quality, image denoising, and enhancement.

  7. A survey on deep learning in medical image analysis.

    Science.gov (United States)

    Litjens, Geert; Kooi, Thijs; Bejnordi, Babak Ehteshami; Setio, Arnaud Arindra Adiyoso; Ciompi, Francesco; Ghafoorian, Mohsen; van der Laak, Jeroen A W M; van Ginneken, Bram; Sánchez, Clara I

    2017-12-01

    Deep learning algorithms, in particular convolutional networks, have rapidly become a methodology of choice for analyzing medical images. This paper reviews the major deep learning concepts pertinent to medical image analysis and summarizes over 300 contributions to the field, most of which appeared in the last year. We survey the use of deep learning for image classification, object detection, segmentation, registration, and other tasks. Concise overviews are provided of studies per application area: neuro, retinal, pulmonary, digital pathology, breast, cardiac, abdominal, musculoskeletal. We end with a summary of the current state-of-the-art, a critical discussion of open challenges and directions for future research. Copyright © 2017 Elsevier B.V. All rights reserved.

  8. Secure public cloud platform for medical images sharing.

    Science.gov (United States)

    Pan, Wei; Coatrieux, Gouenou; Bouslimi, Dalel; Prigent, Nicolas

    2015-01-01

    Cloud computing promises medical imaging services offering large storage and computing capabilities for limited costs. In this data outsourcing framework, one of the greatest issues to deal with is data security. To do so, we propose to secure a public cloud platform devoted to medical image sharing by defining and deploying a security policy so as to control various security mechanisms. This policy stands on a risk assessment we conducted so as to identify security objectives with a special interest for digital content protection. These objectives are addressed by means of different security mechanisms like access and usage control policy, partial-encryption and watermarking.

  9. Dual-tree complex wavelet for medical image watermarking

    International Nuclear Information System (INIS)

    Mavudila, K.R.; Ndaye, B.M.; Masmoudi, L.; Hassanain, N.; Cherkaoui, M.

    2010-01-01

    In order to transmit medical data between hospitals, we insert the information for each patient in the image and its diagnosis, the watermarking consist to insert a message in the image and try to find it with the maximum possible fidelity. This paper presents a blind watermarking scheme in wavelet transform domain dual tree (DTT), who increasing the robustness and preserves the image quality. This system is transparent to the user and allows image integrity control. In addition, it provides information on the location of potential alterations and an evaluation of image modifications which is of major importance in a medico-legal framework. An example using head magnetic resonance and mammography imaging illustrates the overall method. Wavelet techniques can be successfully applied in various image processing methods, namely in image de noising, segmentation, classification, watermarking and others. In this paper we discussed the application of dual tree complex wavelet transform (D T-CWT), which has significant advantages over classic discrete wavelet transform (DWT), for certain image processing problems. The D T-CWT is a form of discreet wavelet transform which generates complex coefficients by using a dual tree of wavelet filters to obtain their real and imaginary parts. The main part of the paper is devoted to profit the exceptional quality for D T-CWT, compared to classical DWT, for a blind medical image watermarking, our schemes are using for the performance bivariate shrinkage with local variance estimation and are robust of attacks and favourably preserves the visual quality. Experimental results show that embedded watermarks using CWT give good image quality and are robust in comparison with the classical DWT.

  10. An atlas of the (near) future: cognitive computing applications for medical imaging (Conference Presentation)

    Science.gov (United States)

    LeGrand, Anne

    2017-02-01

    The role of medical imaging in global health systems is literally fundamental. Like labs, medical images are used at one point or another in almost every high cost, high value episode of care. CT scans, mammograms, and x-rays, for example, "atlas" the body and help chart a course forward for a patient's care team. Imaging precision has improved as a result of technological advancements and breakthroughs in related medical research. Those advancements also bring with them exponential growth in medical imaging data. As IBM trains Watson to "see" medical images, Ms. Le Grand will discuss recent advances made by Watson Health and explore the potential value of "augmented intelligence" to assist healthcare providers like radiologists and cardiologists, as well as the patients they serve.

  11. Anniversary Paper: Image processing and manipulation through the pages of Medical Physics

    International Nuclear Information System (INIS)

    Armato, Samuel G. III; Ginneken, Bram van

    2008-01-01

    The language of radiology has gradually evolved from ''the film'' (the foundation of radiology since Wilhelm Roentgen's 1895 discovery of x-rays) to ''the image,'' an electronic manifestation of a radiologic examination that exists within the bits and bytes of a computer. Rather than simply storing and displaying radiologic images in a static manner, the computational power of the computer may be used to enhance a radiologist's ability to visually extract information from the image through image processing and image manipulation algorithms. Image processing tools provide a broad spectrum of opportunities for image enhancement. Gray-level manipulations such as histogram equalization, spatial alterations such as geometric distortion correction, preprocessing operations such as edge enhancement, and enhanced radiography techniques such as temporal subtraction provide powerful methods to improve the diagnostic quality of an image or to enhance structures of interest within an image. Furthermore, these image processing algorithms provide the building blocks of more advanced computer vision methods. The prominent role of medical physicists and the AAPM in the advancement of medical image processing methods, and in the establishment of the ''image'' as the fundamental entity in radiology and radiation oncology, has been captured in 35 volumes of Medical Physics.

  12. 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.

  13. High-performance floating-point image computing workstation for medical applications

    Science.gov (United States)

    Mills, Karl S.; Wong, Gilman K.; Kim, Yongmin

    1990-07-01

    The medical imaging field relies increasingly on imaging and graphics techniques in diverse applications with needs similar to (or more stringent than) those of the military, industrial and scientific communities. However, most image processing and graphics systems available for use in medical imaging today are either expensive, specialized, or in most cases both. High performance imaging and graphics workstations which can provide real-time results for a number of applications, while maintaining affordability and flexibility, can facilitate the application of digital image computing techniques in many different areas. This paper describes the hardware and software architecture of a medium-cost floating-point image processing and display subsystem for the NeXT computer, and its applications as a medical imaging workstation. Medical imaging applications of the workstation include use in a Picture Archiving and Communications System (PACS), in multimodal image processing and 3-D graphics workstation for a broad range of imaging modalities, and as an electronic alternator utilizing its multiple monitor display capability and large and fast frame buffer. The subsystem provides a 2048 x 2048 x 32-bit frame buffer (16 Mbytes of image storage) and supports both 8-bit gray scale and 32-bit true color images. When used to display 8-bit gray scale images, up to four different 256-color palettes may be used for each of four 2K x 2K x 8-bit image frames. Three of these image frames can be used simultaneously to provide pixel selectable region of interest display. A 1280 x 1024 pixel screen with 1: 1 aspect ratio can be windowed into the frame buffer for display of any portion of the processed image or images. In addition, the system provides hardware support for integer zoom and an 82-color cursor. This subsystem is implemented on an add-in board occupying a single slot in the NeXT computer. Up to three boards may be added to the NeXT for multiple display capability (e

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

    Directory of Open Access Journals (Sweden)

    Hariton Costin

    2012-07-01

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

  15. Physics-based deformable organisms for medical image analysis

    Science.gov (United States)

    Hamarneh, Ghassan; McIntosh, Chris

    2005-04-01

    Previously, "Deformable organisms" were introduced as a novel paradigm for medical image analysis that uses artificial life modelling concepts. Deformable organisms were designed to complement the classical bottom-up deformable models methodologies (geometrical and physical layers), with top-down intelligent deformation control mechanisms (behavioral and cognitive layers). However, a true physical layer was absent and in order to complete medical image segmentation tasks, deformable organisms relied on pure geometry-based shape deformations guided by sensory data, prior structural knowledge, and expert-generated schedules of behaviors. In this paper we introduce the use of physics-based shape deformations within the deformable organisms framework yielding additional robustness by allowing intuitive real-time user guidance and interaction when necessary. We present the results of applying our physics-based deformable organisms, with an underlying dynamic spring-mass mesh model, to segmenting and labelling the corpus callosum in 2D midsagittal magnetic resonance images.

  16. A framework for interactive visualization of digital medical images.

    Science.gov (United States)

    Koehring, Andrew; Foo, Jung Leng; Miyano, Go; Lobe, Thom; Winer, Eliot

    2008-10-01

    The visualization of medical images obtained from scanning techniques such as computed tomography and magnetic resonance imaging is a well-researched field. However, advanced tools and methods to manipulate these data for surgical planning and other tasks have not seen widespread use among medical professionals. Radiologists have begun using more advanced visualization packages on desktop computer systems, but most physicians continue to work with basic two-dimensional grayscale images or not work directly with the data at all. In addition, new display technologies that are in use in other fields have yet to be fully applied in medicine. It is our estimation that usability is the key aspect in keeping this new technology from being more widely used by the medical community at large. Therefore, we have a software and hardware framework that not only make use of advanced visualization techniques, but also feature powerful, yet simple-to-use, interfaces. A virtual reality system was created to display volume-rendered medical models in three dimensions. It was designed to run in many configurations, from a large cluster of machines powering a multiwalled display down to a single desktop computer. An augmented reality system was also created for, literally, hands-on interaction when viewing models of medical data. Last, a desktop application was designed to provide a simple visualization tool, which can be run on nearly any computer at a user's disposal. This research is directed toward improving the capabilities of medical professionals in the tasks of preoperative planning, surgical training, diagnostic assistance, and patient education.

  17. Pseudo-color processing in nuclear medical image

    International Nuclear Information System (INIS)

    Wang Zhiqian; Jin Yongjie

    1992-01-01

    The application of pseudo-color technology in nuclear medical image processing is discussed. It includes selection of the number of pseudo-colors, method of realizing pseudo-color transformation, function of pseudo-color transformation and operation on the function

  18. Prototype Web-based continuing medical education using FlashPix images.

    Science.gov (United States)

    Landman, A; Yagi, Y; Gilbertson, J; Dawson, R; Marchevsky, A; Becich, M J

    2000-01-01

    Continuing Medical Education (CME) is a requirement among practicing physicians to promote continuous enhancement of clinical knowledge to reflect new developments in medical care. Previous research has harnessed the Web to disseminate complete pathology CME case studies including history, images, diagnoses, and discussions to the medical community. Users submit real-time diagnoses and receive instantaneous feedback, eliminating the need for hard copies of case material and case evaluation forms. This project extends the Web-based CME paradigm with the incorporation of multi-resolution FlashPix images and an intuitive, interactive user interface. The FlashPix file format combines a high-resolution version of an image with a hierarchy of several lower resolution copies, providing real-time magnification via a single image file. The Web interface was designed specifically to simulate microscopic analysis, using the latest Javascript, Java and Common Gateway Interface tools. As the project progresses to the evaluation stage, it is hoped that this active learning format will provide a practical and efficacious environment for continuing medical education with additional application potential in classroom demonstrations, proficiency testing, and telepathology. Using Microsoft Internet Explorer 4.0 and above, the working prototype Web-based CME environment is accessible at http://telepathology.upmc.edu/WebInterface/NewInterface/welcome.html.

  19. 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.

  20. Multi-Modality Medical Image Fusion Based on Wavelet Analysis and Quality Evaluation

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    Multi-modality medical image fusion has more and more important applications in medical image analysisand understanding. In this paper, we develop and apply a multi-resolution method based on wavelet pyramid to fusemedical images from different modalities such as PET-MRI and CT-MRI. In particular, we evaluate the different fusionresults when applying different selection rules and obtain optimum combination of fusion parameters.

  1. What We Do and Do Not Know about Teaching Medical Image Interpretation

    NARCIS (Netherlands)

    Kok, E M; Van Geel, Koos; van Merrienboer, Jeroen J. G.; Robben, S G F

    2017-01-01

    Educators in medical image interpretation have difficulty finding scientific evidence as to how they should design their instruction. We review and comment on 81 papers that investigated instructional design in medical image interpretation. We distinguish between studies that evaluated complete

  2. Application of an internet web-site of medical images in tele-radiology

    International Nuclear Information System (INIS)

    Wang Weizhong; Wang Hua; Xie Jingxia; Wang Songzhang; Li Xiangdong; Qian Min; Cao Huixia

    2000-01-01

    Objective: To build and Internet web-site of medical images for tele-education and tele-consultation. Methods: Collecting medical images of cases that fulfilled diagnostic standards for teaching and were pathologically proved. The images were digitized using digital camera and scanner. Frontpage 98, Homesite 2.5 and text editors were used for programming. Results: The web site encompasses many useful cases and was update every week. With smart and friendly interface, easy used navigation, the site runs reliably in TCP/IP environment. The site's URL is http://imager.163.net. At present, the site has received about 100 visits per week. Conclusion: The well-designed and programmed internet web site of medical images would be easily acceptable and is going to play an important role in tele-education and tele-consultation

  3. Seventh Medical Image Computing and Computer Assisted Intervention Conference (MICCAI 2012)

    CERN Document Server

    Miller, Karol; Nielsen, Poul; Computational Biomechanics for Medicine : Models, Algorithms and Implementation

    2013-01-01

    One of the greatest challenges for mechanical engineers is to extend the success of computational mechanics to fields outside traditional engineering, in particular to biology, biomedical sciences, and medicine. This book is an opportunity for computational biomechanics specialists to present and exchange opinions on the opportunities of applying their techniques to computer-integrated medicine. Computational Biomechanics for Medicine: Models, Algorithms and Implementation collects the papers from the Seventh Computational Biomechanics for Medicine Workshop held in Nice in conjunction with the Medical Image Computing and Computer Assisted Intervention conference. The topics covered include: medical image analysis, image-guided surgery, surgical simulation, surgical intervention planning, disease prognosis and diagnostics, injury mechanism analysis, implant and prostheses design, and medical robotics.

  4. Amide proton transfer imaging for differentiation of benign and atypical meningiomas

    Energy Technology Data Exchange (ETDEWEB)

    Joo, Bio [The Armed Forces Capital Hospital, Department of Radiology, Seongnam, Gyeonggi-do (Korea, Republic of); Han, Kyunghwa; Choi, Yoon Seong; Lee, Seung-Koo [Yonsei University College of Medicine, Department of Radiology and Research Institute of Radiological Science, College of Medicine, Seoul (Korea, Republic of); Ahn, Sung Soo [Yonsei University College of Medicine, Department of Radiology and Research Institute of Radiological Science, College of Medicine, Seoul (Korea, Republic of); Yonsei University, Department of Radiology, College of Medicine, Seoul (Korea, Republic of); Chang, Jong Hee; Kang, Seok-Gu [Yonsei University College of Medicine, Department of Neurosurgery, Seoul (Korea, Republic of); Kim, Se Hoon [Yonsei University College of Medicine, Department of Pathology, Seoul (Korea, Republic of); Zhou, Jinyuan [Johns Hopkins University School of Medicine, Division of MRI Research, Department of Radiology, Baltimore, MD (United States)

    2018-01-15

    To investigate the difference in amide proton transfer (APT)-weighted signals between benign and atypical meningiomas and determine the value of APT imaging for differentiating the two. Fifty-seven patients with pathologically diagnosed meningiomas (benign, 44; atypical, 13), who underwent preoperative MRI with APT imaging between December 2014 and August 2016 were included. We compared normalised magnetisation transfer ratio asymmetry (nMTR{sub asym}) values between benign and atypical meningiomas on APT-weighted images. Conventional MRI features were qualitatively assessed. Both imaging features were evaluated by multivariable logistic regression analysis. The discriminative value of MRI with and without nMTR{sub asym} was evaluated. The nMTR{sub asym} of atypical meningiomas was significantly greater than that of benign meningiomas (2.46% vs. 1.67%; P < 0.001). In conventional MR images, benign and atypical meningiomas exhibited significant differences in maximum tumour diameter, non-skull base location, and heterogeneous enhancement. On multivariable logistic regression analysis, high nMTR{sub asym} was an independent predictor of atypical meningiomas (adjusted OR, 11.227; P = 0.014). The diagnostic performance of MRI improved with nMTR{sub asym} for predicting atypical meningiomas. Atypical meningiomas exhibited significantly higher APT-weighted signal intensities than benign meningiomas. The discriminative value of conventional MRI improved significantly when combined with APT imaging for diagnosis of atypical meningioma. (orig.)

  5. Computer Software Configuration Item-Specific Flight Software Image Transfer Script Generator

    Science.gov (United States)

    Bolen, Kenny; Greenlaw, Ronald

    2010-01-01

    A K-shell UNIX script enables the International Space Station (ISS) Flight Control Team (FCT) operators in NASA s Mission Control Center (MCC) in Houston to transfer an entire or partial computer software configuration item (CSCI) from a flight software compact disk (CD) to the onboard Portable Computer System (PCS). The tool is designed to read the content stored on a flight software CD and generate individual CSCI transfer scripts that are capable of transferring the flight software content in a given subdirectory on the CD to the scratch directory on the PCS. The flight control team can then transfer the flight software from the PCS scratch directory to the Electronically Erasable Programmable Read Only Memory (EEPROM) of an ISS Multiplexer/ Demultiplexer (MDM) via the Indirect File Transfer capability. The individual CSCI scripts and the CSCI Specific Flight Software Image Transfer Script Generator (CFITSG), when executed a second time, will remove all components from their original execution. The tool will identify errors in the transfer process and create logs of the transferred software for the purposes of configuration management.

  6. 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.

  7. WE-H-202-04: Advanced Medical Image Registration Techniques

    International Nuclear Information System (INIS)

    Christensen, G.

    2016-01-01

    Deformable image registration has now been commercially available for several years, with solid performance in a number of sites and for several applications including contour and dose mapping. However, more complex applications have arisen, such as assessing response to radiation therapy over time, registering images pre- and post-surgery, and auto-segmentation from atlases. These applications require innovative registration algorithms to achieve accurate alignment. The goal of this session is to highlight emerging registration technology and these new applications. The state of the art in image registration will be presented from an engineering perspective. Translational clinical applications will also be discussed to tie these new registration approaches together with imaging and radiation therapy applications in specific diseases such as cervical and lung cancers. Learning Objectives: To understand developing techniques and algorithms in deformable image registration that are likely to translate into clinical tools in the near future. To understand emerging imaging and radiation therapy clinical applications that require such new registration algorithms. Research supported in part by the National Institutes of Health under award numbers P01CA059827, R01CA166119, and R01CA166703. Disclosures: Phillips Medical systems (Hugo), Roger Koch (Christensen) support, Varian Medical Systems (Brock), licensing agreements from Raysearch (Brock) and Varian (Hugo).; K. Brock, Licensing Agreement - RaySearch Laboratories. Research Funding - Varian Medical Systems; G. Hugo, Research grant from National Institutes of Health, award number R01CA166119.; G. Christensen, Research support from NIH grants CA166119 and CA166703 and a gift from Roger Koch. There are no conflicts of interest.

  8. WE-H-202-04: Advanced Medical Image Registration Techniques

    Energy Technology Data Exchange (ETDEWEB)

    Christensen, G. [University of Iowa (United States)

    2016-06-15

    Deformable image registration has now been commercially available for several years, with solid performance in a number of sites and for several applications including contour and dose mapping. However, more complex applications have arisen, such as assessing response to radiation therapy over time, registering images pre- and post-surgery, and auto-segmentation from atlases. These applications require innovative registration algorithms to achieve accurate alignment. The goal of this session is to highlight emerging registration technology and these new applications. The state of the art in image registration will be presented from an engineering perspective. Translational clinical applications will also be discussed to tie these new registration approaches together with imaging and radiation therapy applications in specific diseases such as cervical and lung cancers. Learning Objectives: To understand developing techniques and algorithms in deformable image registration that are likely to translate into clinical tools in the near future. To understand emerging imaging and radiation therapy clinical applications that require such new registration algorithms. Research supported in part by the National Institutes of Health under award numbers P01CA059827, R01CA166119, and R01CA166703. Disclosures: Phillips Medical systems (Hugo), Roger Koch (Christensen) support, Varian Medical Systems (Brock), licensing agreements from Raysearch (Brock) and Varian (Hugo).; K. Brock, Licensing Agreement - RaySearch Laboratories. Research Funding - Varian Medical Systems; G. Hugo, Research grant from National Institutes of Health, award number R01CA166119.; G. Christensen, Research support from NIH grants CA166119 and CA166703 and a gift from Roger Koch. There are no conflicts of interest.

  9. Amide proton transfer imaging of high intensity focused ultrasound-treated tumor tissue

    NARCIS (Netherlands)

    Hectors, S.J.C.G.; Jacobs, I.; Strijkers, G.J.; Nicolay, K.

    2014-01-01

    Purpose: In this study, the suitability of amide proton transfer (APT) imaging as a biomarker for the characterization of high intensity focused ultrasound (HIFU)-treated tumor tissue was assessed. Methods: APT imaging was performed on tumor-bearing mice before (n=15), directly after (n=15) and at 3

  10. Amide Proton Transfer Imaging of High Intensity Focused Ultrasound-Treated Tumor Tissue

    NARCIS (Netherlands)

    Hectors, Stefanie J. C. G.; Jacobs, Igor; Strijkers, Gustav J.; Nicolay, Klaas

    2014-01-01

    PurposeIn this study, the suitability of amide proton transfer (APT) imaging as a biomarker for the characterization of high intensity focused ultrasound (HIFU)-treated tumor tissue was assessed. MethodsAPT imaging was performed on tumor-bearing mice before (n=15), directly after (n=15) and at 3

  11. Imaging after vascular gene therapy

    International Nuclear Information System (INIS)

    Manninen, Hannu I.; Yang, Xiaoming

    2005-01-01

    Targets for cardiovascular gene therapy currently include limiting restenosis after balloon angioplasty and stent placement, inhibiting vein bypass graft intimal hyperplasia/stenosis, therapeutic angiogenesis for cardiac and lower-limb ischemia, and prevention of thrombus formation. While catheter angiography is still standard method to follow-up vascular gene transfer, other modern imaging techniques, especially intravascular ultrasound (IVUS), magnetic resonance (MR), and positron emission tomography (PET) imaging provide complementary information about the therapeutic effect of vascular gene transfer in humans. Although molecular imaging of therapeutic gene expression in the vasculatures is still in its technical development phase, it has already offered basic medical science an extremely useful in vivo evaluation tool for non- or minimally invasive imaging of vascular gene therapy

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

    NARCIS (Netherlands)

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

    2004-01-01

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

  13. Novel gaseous detectors for medical imaging

    International Nuclear Information System (INIS)

    Danielsson, M.; Fonte, P.; Francke, T.; Iacobaeus, C.; Ostling, J.; Peskov, V.

    2004-01-01

    We have developed and successfully tested prototypes of two new types of gaseous detectors for medical imaging purposes. The first one is called the Electronic Portal Imaging Device (EPID). It is oriented on monitoring and the precise alignment of the therapeutic cancer treatment beam (pulsed gamma radiation) with respect to the patient's tumor position. The latest will be determined from an X-ray image of the patient obtained in the time intervals between the gamma pulses. The detector is based on a 'sandwich' of hole-type gaseous detectors (GEM and glass microcapillary plates) with metallic gamma and X-ray converters coated with CsI layers. The second detector is an X-ray image scanner oriented on mammography and other radiographic applications. It is based on specially developed by us high rate RPCs that are able to operate at rates of 10 5 Hz/mm 2 with a position resolution better than 50 μm at 1 atm. The quality of the images obtained with the latest version of this device were in most cases more superior than those obtained from commercially available detectors

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

    Science.gov (United States)

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

    2011-01-01

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

  15. Anniversary Paper: Image processing and manipulation through the pages of Medical Physics

    Energy Technology Data Exchange (ETDEWEB)

    Armato, Samuel G. III; Ginneken, Bram van [Department of Radiology, University of Chicago, 5841 South Maryland Avenue, Chicago, Illinois 60637 (United States); Image Sciences Institute, University Medical Center Utrecht, Heidelberglaan 100, Room Q0S.459, 3584 CX Utrecht (Netherlands)

    2008-10-15

    The language of radiology has gradually evolved from ''the film'' (the foundation of radiology since Wilhelm Roentgen's 1895 discovery of x-rays) to ''the image,'' an electronic manifestation of a radiologic examination that exists within the bits and bytes of a computer. Rather than simply storing and displaying radiologic images in a static manner, the computational power of the computer may be used to enhance a radiologist's ability to visually extract information from the image through image processing and image manipulation algorithms. Image processing tools provide a broad spectrum of opportunities for image enhancement. Gray-level manipulations such as histogram equalization, spatial alterations such as geometric distortion correction, preprocessing operations such as edge enhancement, and enhanced radiography techniques such as temporal subtraction provide powerful methods to improve the diagnostic quality of an image or to enhance structures of interest within an image. Furthermore, these image processing algorithms provide the building blocks of more advanced computer vision methods. The prominent role of medical physicists and the AAPM in the advancement of medical image processing methods, and in the establishment of the ''image'' as the fundamental entity in radiology and radiation oncology, has been captured in 35 volumes of Medical Physics.

  16. Cloud computing in medical imaging.

    Science.gov (United States)

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

    2013-07-01

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

  17. Method for estimating modulation transfer function from sample images.

    Science.gov (United States)

    Saiga, Rino; Takeuchi, Akihisa; Uesugi, Kentaro; Terada, Yasuko; Suzuki, Yoshio; Mizutani, Ryuta

    2018-02-01

    The modulation transfer function (MTF) represents the frequency domain response of imaging modalities. Here, we report a method for estimating the MTF from sample images. Test images were generated from a number of images, including those taken with an electron microscope and with an observation satellite. These original images were convolved with point spread functions (PSFs) including those of circular apertures. The resultant test images were subjected to a Fourier transformation. The logarithm of the squared norm of the Fourier transform was plotted against the squared distance from the origin. Linear correlations were observed in the logarithmic plots, indicating that the PSF of the test images can be approximated with a Gaussian. The MTF was then calculated from the Gaussian-approximated PSF. The obtained MTF closely coincided with the MTF predicted from the original PSF. The MTF of an x-ray microtomographic section of a fly brain was also estimated with this method. The obtained MTF showed good agreement with the MTF determined from an edge profile of an aluminum test object. We suggest that this approach is an alternative way of estimating the MTF, independently of the image type. Copyright © 2017 Elsevier Ltd. All rights reserved.

  18. Principles of medical imaging with emphasis on tomography

    Energy Technology Data Exchange (ETDEWEB)

    Kouris, K [Institute of Nuclear Medicine, University College, London Medical School, Mortimer Street, London W1N 8AA (United Kingdom)

    1994-12-31

    Medical imaging with ionizing and non-ionizing radiations belongs to the class of problems known as indirect sensing. This article is concerned with imaging methods known as image reconstruction from projections or computerized tomography. A brief comparative study of the theory is presented. Depending on the nature and modes of propagation of the employed radiation, methods are discussed either under transmission tomography (with gamma rays and X rays) or emission tomography (with gamma rays and positrons). Magnetic resonance Imaging (MRI) is described as resonant absorption and re-emission of radiofrequency energy. (author). 6 refs, 1 fig.

  19. Lead-free piezoelectric materials and ultrasonic transducers for medical imaging

    Directory of Open Access Journals (Sweden)

    Elaheh Taghaddos

    2015-06-01

    Full Text Available Piezoelectric materials have been vastly used in ultrasonic transducers for medical imaging. In this paper, firstly, the most promising lead-free compositions with perovskite structure for medical imaging applications have been reviewed. The electromechanical properties of various lead-free ceramics, composites, and single crystals based on barium titanate, bismuth sodium titanate, potassium sodium niobate, and lithium niobate are presented. Then, fundamental principles and design considerations of ultrasonic transducers are briefly described. Finally, recent developments in lead-free ultrasonic probes are discussed and their acoustic performance is compared to lead-based transducers. Focused transducers with different beam focusing methods such as lens focusing and mechanical shaping are explained. Additionally, acoustic characteristics of lead-free probes including the pulse-echo results as well as their imaging capabilities for various applications such as phantom imaging, in vitro intravascular ultrasound imaging of swine aorta, and in vivo or ex vivo imaging of human eyes and skin are reviewed.

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

    DEFF Research Database (Denmark)

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

    2011-01-01

    This contribution describes and evaluates an experimental combination of a spiral and discipline-oriented curriculum implemented in the bachelor’s and master’s program in Medicine and Technology. The implementation in the master’s program is in the form of a study line in Medical Imaging and Radi......This contribution describes and evaluates an experimental combination of a spiral and discipline-oriented curriculum implemented in the bachelor’s and master’s program in Medicine and Technology. The implementation in the master’s program is in the form of a study line in Medical Imaging...... and Radiation Physics containing three disciplines: Imaging modalities, Radiation therapy and Image processing. The two imaging courses in the bachelor’s program and the first imaging course in the master’s program follow a spiral curriculum in which most disciplines are encountered in all courses......, but in a gradually more advanced manner. The remaining courses in the master’s program follow a discipline-oriented curriculum. From a practical point of view, the spiral course portfolio works well in an undergraduate environment, where the courses involved are to be taken by all students and in the order planned...

  1. A Multimodal Search Engine for Medical Imaging Studies.

    Science.gov (United States)

    Pinho, Eduardo; Godinho, Tiago; Valente, Frederico; Costa, Carlos

    2017-02-01

    The use of digital medical imaging systems in healthcare institutions has increased significantly, and the large amounts of data in these systems have led to the conception of powerful support tools: recent studies on content-based image retrieval (CBIR) and multimodal information retrieval in the field hold great potential in decision support, as well as for addressing multiple challenges in healthcare systems, such as computer-aided diagnosis (CAD). However, the subject is still under heavy research, and very few solutions have become part of Picture Archiving and Communication Systems (PACS) in hospitals and clinics. This paper proposes an extensible platform for multimodal medical image retrieval, integrated in an open-source PACS software with profile-based CBIR capabilities. In this article, we detail a technical approach to the problem by describing its main architecture and each sub-component, as well as the available web interfaces and the multimodal query techniques applied. Finally, we assess our implementation of the engine with computational performance benchmarks.

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

    Science.gov (United States)

    Grignon, Bruno; Oldrini, Guillaume; Walter, Frédéric

    2016-03-01

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

  3. Mediaprocessors in medical imaging for high performance and flexibility

    Science.gov (United States)

    Managuli, Ravi; Kim, Yongmin

    2002-05-01

    New high performance programmable processors, called mediaprocessors, have been emerging since the early 1990s for various digital media applications, such as digital TV, set-top boxes, desktop video conferencing, and digital camcorders. Modern mediaprocessors, e.g., TI's TMS320C64x and Hitachi/Equator Technologies MAP-CA, can offer high performance utilizing both instruction-level and data-level parallelism. During this decade, with continued performance improvement and cost reduction, we believe that the mediaprocessors will become a preferred choice in designing imaging and video systems due to their flexibility in incorporating new algorithms and applications via programming and faster-time-to-market. In this paper, we will evaluate the suitability of these mediaprocessors in medical imaging. We will review the core routines of several medical imaging modalities, such as ultrasound and DR, and present how these routines can be mapped to mediaprocessors and their resultant performance. We will analyze the architecture of several leading mediaprocessors. By carefully mapping key imaging routines, such as 2D convolution, unsharp masking, and 2D FFT, to the mediaprocessor, we have been able to achieve comparable (if not better) performance to that of traditional hardwired approaches. Thus, we believe that future medical imaging systems will benefit greatly from these advanced mediaprocessors, offering significantly increased flexibility and adaptability, reducing the time-to-market, and improving the cost/performance ratio compared to the existing systems while meeting the high computing requirements.

  4. Mapping the different methods adopted for diagnostic imaging instruction at medical schools in Brazil.

    Science.gov (United States)

    Chojniak, Rubens; Carneiro, Dominique Piacenti; Moterani, Gustavo Simonetto Peres; Duarte, Ivone da Silva; Bitencourt, Almir Galvão Vieira; Muglia, Valdair Francisco; D'Ippolito, Giuseppe

    2017-01-01

    To map the different methods for diagnostic imaging instruction at medical schools in Brazil. In this cross-sectional study, a questionnaire was sent to each of the coordinators of 178 Brazilian medical schools. The following characteristics were assessed: teaching model; total course hours; infrastructure; numbers of students and professionals involved; themes addressed; diagnostic imaging modalities covered; and education policies related to diagnostic imaging. Of the 178 questionnaires sent, 45 (25.3%) were completed and returned. Of those 45 responses, 17 (37.8%) were from public medical schools, whereas 28 (62.2%) were from private medical schools. Among the 45 medical schools evaluated, the method of diagnostic imaging instruction was modular at 21 (46.7%), classic (independent discipline) at 13 (28.9%), hybrid (classical and modular) at 9 (20.0%), and none of the preceding at 3 (6.7%). Diagnostic imaging is part of the formal curriculum at 36 (80.0%) of the schools, an elective course at 3 (6.7%), and included within another modality at 6 (13.3%). Professors involved in diagnostic imaging teaching are radiologists at 43 (95.5%) of the institutions. The survey showed that medical courses in Brazil tend to offer diagnostic imaging instruction in courses that include other content and at different time points during the course. Radiologists are extensively involved in undergraduate medical education, regardless of the teaching methodology employed at the institution.

  5. The scheme and implementing of workstation configuration for medical imaging information system

    International Nuclear Information System (INIS)

    Tao Yonghao; Miao Jingtao

    2002-01-01

    Objective: To discuss the scheme and implementing for workstation configuration of medical imaging information system which would be adapted to the practice situation of China. Methods: The workstations were logically divided into PACS workstations and RIS workstations, the former applied to three kinds of diagnostic practice: the small matrix images, large matrix images, and high resolution gray scale display application, and the latter consisted of many different models which depended upon the usage and function process. Results: A dual screen configuration for image diagnostic workstation integrated the image viewing and reporting procedure physically, while the small matrix images as CT or MR were operated on 17 in (1 in = 2.54 cm) color monitors, the conventional X-ray diagnostic procedure was implemented based on 21 in color monitors or portrait format gray scale 2 K by 2.5 K monitors. All other RIS workstations not involved in image process were set up with a common PC configuration. Conclusion: The essential principle for designing a workstation scheme of medical imaging information system should satisfy the basic requirements of medical image diagnosis and fit into the available investment situation

  6. Intelligent Image Recognition System for Marine Fouling Using Softmax Transfer Learning and Deep Convolutional Neural Networks

    Directory of Open Access Journals (Sweden)

    C. S. Chin

    2017-01-01

    Full Text Available The control of biofouling on marine vessels is challenging and costly. Early detection before hull performance is significantly affected is desirable, especially if “grooming” is an option. Here, a system is described to detect marine fouling at an early stage of development. In this study, an image of fouling can be transferred wirelessly via a mobile network for analysis. The proposed system utilizes transfer learning and deep convolutional neural network (CNN to perform image recognition on the fouling image by classifying the detected fouling species and the density of fouling on the surface. Transfer learning using Google’s Inception V3 model with Softmax at last layer was carried out on a fouling database of 10 categories and 1825 images. Experimental results gave acceptable accuracies for fouling detection and recognition.

  7. An Intelligent Cloud Storage Gateway for Medical Imaging.

    Science.gov (United States)

    Viana-Ferreira, Carlos; Guerra, António; Silva, João F; Matos, Sérgio; Costa, Carlos

    2017-09-01

    Historically, medical imaging repositories have been supported by indoor infrastructures. However, the amount of diagnostic imaging procedures has continuously increased over the last decades, imposing several challenges associated with the storage volume, data redundancy and availability. Cloud platforms are focused on delivering hardware and software services over the Internet, becoming an appealing solution for repository outsourcing. Although this option may bring financial and technological benefits, it also presents new challenges. In medical imaging scenarios, communication latency is a critical issue that still hinders the adoption of this paradigm. This paper proposes an intelligent Cloud storage gateway that optimizes data access times. This is achieved through a new cache architecture that combines static rules and pattern recognition for eviction and prefetching. The evaluation results, obtained from experiments over a real-world dataset, show that cache hit ratios can reach around 80%, leading to reductions of image retrieval times by over 60%. The combined use of eviction and prefetching policies proposed can significantly reduce communication latency, even when using a small cache in comparison to the total size of the repository. Apart from the performance gains, the proposed system is capable of adjusting to specific workflows of different institutions.

  8. Review of medical imaging with emphasis on X-ray detectors

    Science.gov (United States)

    Hoheisel, Martin

    2006-07-01

    Medical imaging can be looked at from two different perspectives, the medical and the physical. The medical point of view is application-driven and involves finding the best way of tackling a medical problem through imaging, i.e. either to answer a diagnostic question, or to facilitate a therapy. For this purpose, industry offers a broad spectrum of radiographic, fluoroscopic, and angiographic equipment. The requirements depend on the medical problem: which organs have to be imaged, which details have to be made visible, how to deal with the problem of motion if any, and so forth. In radiography, for instance, large detector sizes of up to 43 cm×43 cm and relatively high energies are needed to image a whole chest. In mammography, pixel sizes between 25 and 70 μm are favorable for good spatial resolution, which is essential for detecting microcalcifications. In cardiology, 30-60 images per second are required to follow the heart's motion. In computed tomography, marginal contrast differences down to one Hounsfield unit have to be resolved. In all cases, but especially in pediatrics, the required radiation dose must be kept as low as reasonably achievable. Moreover, three-dimensional(3D) reconstruction of image data allows much better orientation in the body, permitting a more accurate diagnosis, precise treatment planning, and image-guided therapy. Additional functional information from different modalities is very helpful, information such as perfusion, flow rate, diffusion, oxygen concentration, metabolism, and receptor affinity for specific molecules. To visualize, functional and anatomical information are fused into one combined image. The physical point of view is technology-driven. A choice of different energies from the electromagnetic spectrum is available for imaging; not only X-rays in the range of 10-150 keV, but also γ rays, which are used in nuclear medicine, X-rays in the MeV range, which are used in portal imaging to monitor radiation therapy

  9. Review of medical imaging with emphasis on X-ray detectors

    Energy Technology Data Exchange (ETDEWEB)

    Hoheisel, Martin [Siemens AG Medical Solutions, Angiography, Fluoroscopic- and Radiographic Systems, Innovations, Siemensstr.1, 91301 Forchheim (Germany)]. E-mail: martin.hoheisel@siemens.com

    2006-07-01

    Medical imaging can be looked at from two different perspectives, the medical and the physical. The medical point of view is application-driven and involves finding the best way of tackling a medical problem through imaging, i.e. either to answer a diagnostic question, or to facilitate a therapy. For this purpose, industry offers a broad spectrum of radiographic, fluoroscopic, and angiographic equipment. The requirements depend on the medical problem: which organs have to be imaged, which details have to be made visible, how to deal with the problem of motion if any, and so forth. In radiography, for instance, large detector sizes of up to 43 cmx43 cm and relatively high energies are needed to image a whole chest. In mammography, pixel sizes between 25 and 70 {mu}m are favorable for good spatial resolution, which is essential for detecting microcalcifications. In cardiology, 30-60 images per second are required to follow the heart's motion. In computed tomography, marginal contrast differences down to one Hounsfield unit have to be resolved. In all cases, but especially in pediatrics, the required radiation dose must be kept as low as reasonably achievable. Moreover, three-dimensional(3D) reconstruction of image data allows much better orientation in the body, permitting a more accurate diagnosis, precise treatment planning, and image-guided therapy. Additional functional information from different modalities is very helpful, information such as perfusion, flow rate, diffusion, oxygen concentration, metabolism, and receptor affinity for specific molecules. To visualize, functional and anatomical information are fused into one combined image. The physical point of view is technology-driven. A choice of different energies from the electromagnetic spectrum is available for imaging; not only X-rays in the range of 10-150 keV, but also {gamma} rays, which are used in nuclear medicine, X-rays in the MeV range, which are used in portal imaging to monitor radiation

  10. Review of medical imaging with emphasis on X-ray detectors

    International Nuclear Information System (INIS)

    Hoheisel, Martin

    2006-01-01

    Medical imaging can be looked at from two different perspectives, the medical and the physical. The medical point of view is application-driven and involves finding the best way of tackling a medical problem through imaging, i.e. either to answer a diagnostic question, or to facilitate a therapy. For this purpose, industry offers a broad spectrum of radiographic, fluoroscopic, and angiographic equipment. The requirements depend on the medical problem: which organs have to be imaged, which details have to be made visible, how to deal with the problem of motion if any, and so forth. In radiography, for instance, large detector sizes of up to 43 cmx43 cm and relatively high energies are needed to image a whole chest. In mammography, pixel sizes between 25 and 70 μm are favorable for good spatial resolution, which is essential for detecting microcalcifications. In cardiology, 30-60 images per second are required to follow the heart's motion. In computed tomography, marginal contrast differences down to one Hounsfield unit have to be resolved. In all cases, but especially in pediatrics, the required radiation dose must be kept as low as reasonably achievable. Moreover, three-dimensional(3D) reconstruction of image data allows much better orientation in the body, permitting a more accurate diagnosis, precise treatment planning, and image-guided therapy. Additional functional information from different modalities is very helpful, information such as perfusion, flow rate, diffusion, oxygen concentration, metabolism, and receptor affinity for specific molecules. To visualize, functional and anatomical information are fused into one combined image. The physical point of view is technology-driven. A choice of different energies from the electromagnetic spectrum is available for imaging; not only X-rays in the range of 10-150 keV, but also γ rays, which are used in nuclear medicine, X-rays in the MeV range, which are used in portal imaging to monitor radiation therapy

  11. Ultrasound introscopic image quantitative characteristics for medical diagnosis

    Science.gov (United States)

    Novoselets, Mikhail K.; Sarkisov, Sergey S.; Gridko, Alexander N.; Tcheban, Anatoliy K.

    1993-09-01

    The results on computer aided extraction of quantitative characteristics (QC) of ultrasound introscopic images for medical diagnosis are presented. Thyroid gland (TG) images of Chernobil Accident sufferers are considered. It is shown that TG diseases can be associated with some values of selected QCs of random echo distribution in the image. The possibility of these QCs usage for TG diseases recognition in accordance with calculated values is analyzed. The role of speckle noise elimination in the solution of the problem on TG diagnosis is considered too.

  12. Diagnostic Imaging in the Medical Support of the Future Missions to the Moon

    Science.gov (United States)

    Sargsyan, Ashot E.; Jones, Jeffrey A.; Hamilton, Douglas R.; Dulchavsky, Scott A.; Duncan, J. Michael

    2007-01-01

    This viewgraph presentation is a course that reviews the diagnostic imaging techniques available for medical support on the future moon missions. The educational objectives of the course are to: 1) Update the audience on the curreultrasound imaging in space flight; 2) Discuss the unique aspects of conducting ultrasound imaging on ISS, interplanetary transit, ultrasound imaging on ISS, interplanetary transit, and lunar surface operations; and 3) Review preliminary data obtained in simulations of medical imaging in lunar surface operations.

  13. The four-dimensional mouse whole-body phantoms and its application in medical imaging research

    International Nuclear Information System (INIS)

    Li Chongguo; Wu Dake

    2012-01-01

    Medical imaging simulation is a powerful tool for characterizing,evaluating,and optimizing medical imaging devices and techniques. A vital aspect of simulation is to have a realistic phantom or model of the subject's anatomy. Four-dimensional mouse whole-body phantoms provide realistic models of the mouse anatomy and physiology for imaging studies. When combined with accurate models for the imaging process,are capable of providing a wealth of realistic imaging data from subjects with various anatomies and motions (cardiac and respiratory) in health and disease. With this ability, the four-dimensional mouse whole-body phantoms have enormous potential to study the effects of anatomical, physiological and physical factors on medical and small animal imaging and to research new instrumentation, image acquisition strategies, image processing, reconstruction methods, image visualization and interpretation techniques. (authors)

  14. Multimodality image registration. A special development in medical imaging has been strongly influenced by a small but highly qualified software think-tank

    International Nuclear Information System (INIS)

    Diemling, M.

    2007-01-01

    The importance of image fusion and registration in the field of medical diagnostics will be shown. After some details and background of image registration, as well as the history of nuclear medicine imaging - given by the example of HERMES Medical Solutions of Stockholm, Sweden - the reader finds seven cases illustrating the clinical importance of this method. These cases were collected from various fields of applications of medical imaging, they are carefully documented and illustrated. (orig.)

  15. Geodesic Flow Kernel Support Vector Machine for Hyperspectral Image Classification by Unsupervised Subspace Feature Transfer

    Directory of Open Access Journals (Sweden)

    Alim Samat

    2016-03-01

    Full Text Available In order to deal with scenarios where the training data, used to deduce a model, and the validation data have different statistical distributions, we study the problem of transformed subspace feature transfer for domain adaptation (DA in the context of hyperspectral image classification via a geodesic Gaussian flow kernel based support vector machine (GFKSVM. To show the superior performance of the proposed approach, conventional support vector machines (SVMs and state-of-the-art DA algorithms, including information-theoretical learning of discriminative cluster for domain adaptation (ITLDC, joint distribution adaptation (JDA, and joint transfer matching (JTM, are also considered. Additionally, unsupervised linear and nonlinear subspace feature transfer techniques including principal component analysis (PCA, randomized nonlinear principal component analysis (rPCA, factor analysis (FA and non-negative matrix factorization (NNMF are investigated and compared. Experiments on two real hyperspectral images show the cross-image classification performances of the GFKSVM, confirming its effectiveness and suitability when applied to hyperspectral images.

  16. Consistency and standardization of color in medical imaging: a consensus report.

    Science.gov (United States)

    Badano, Aldo; Revie, Craig; Casertano, Andrew; Cheng, Wei-Chung; Green, Phil; Kimpe, Tom; Krupinski, Elizabeth; Sisson, Christye; Skrøvseth, Stein; Treanor, Darren; Boynton, Paul; Clunie, David; Flynn, Michael J; Heki, Tatsuo; Hewitt, Stephen; Homma, Hiroyuki; Masia, Andy; Matsui, Takashi; Nagy, Balázs; Nishibori, Masahiro; Penczek, John; Schopf, Thomas; Yagi, Yukako; Yokoi, Hideto

    2015-02-01

    This article summarizes the consensus reached at the Summit on Color in Medical Imaging held at the Food and Drug Administration (FDA) on May 8-9, 2013, co-sponsored by the FDA and ICC (International Color Consortium). The purpose of the meeting was to gather information on how color is currently handled by medical imaging systems to identify areas where there is a need for improvement, to define objective requirements, and to facilitate consensus development of best practices. Participants were asked to identify areas of concern and unmet needs. This summary documents the topics that were discussed at the meeting and recommendations that were made by the participants. Key areas identified where improvements in color would provide immediate tangible benefits were those of digital microscopy, telemedicine, medical photography (particularly ophthalmic and dental photography), and display calibration. Work in these and other related areas has been started within several professional groups, including the creation of the ICC Medical Imaging Working Group.

  17. Educating Globally in Medical Imaging in Latin America and Caribbean via Webinars

    Science.gov (United States)

    Saunders, Carmen Teresa

    2017-01-01

    Professional development courses that focus on increasing knowledge and improving skill sets are an integral part of a medical imager's career. This study was a qualitative formative evaluation with purposeful sampling of participants in a professional development webinar course offered to medical imaging professionals in 35 Latin American and…

  18. Three-dimensional analysis and display of medical images

    International Nuclear Information System (INIS)

    Bajcsy, R.

    1985-01-01

    Until recently, the most common medical images were X-rays on film analyzed by an expert, ususally a radiologist, who used, in addition to his/her visual perceptual abilities, knowledge obtained through medical studies, and experience. Today, however, with the advent of various imaging techniques, X-ray computerized axial tomographs (CAT), positron emission tomographs (PET), ultrasound tomographs, nuclear magnetic resonance tomographs (NMR), just to mention a few, the images are generated by computers and displayed on computer-controlled devices; so it is appropriate to think about more quantitative and perhaps automated ways of data analysis. Furthermore, since the data are generated by computer, it is only natural to take advantage of the computer for analysis purposes. In addition, using the computer, one can analyze more data and relate different modalities from the same subject, such as, for example, comparing the CAT images with PET images from the same subject. In the next section (The PET Scanner) the authors shall only briefly mention with appropriate references the modeling of the positron emission tomographic scanner, since this imaging technique is not as widely described in the literature as the CAT scanner. The modeling of the interpreter is not going to be mentioned, since it is a topic that by itself deserves a full paper; see, for example, Pizer [1981]. The thrust of this chapter is on modeling the organs that are being imaged and the matching techniques between the model and the data. The image data is from CAT and PET scans. Although the authors believe that their techniques are applicable to any organ of the human body, the examples are only from the brain

  19. 3D surface reconstruction using optical flow for medical imaging

    International Nuclear Information System (INIS)

    Weng, Nan; Yang, Yee-Hong; Pierson, R.

    1996-01-01

    The recovery of a 3D model from a sequence of 2D images is very useful in medical image analysis. Image sequences obtained from the relative motion between the object and the camera or the scanner contain more 3D information than a single image. Methods to visualize the computed tomograms can be divided into two approaches: the surface rendering approach and the volume rendering approach. A new surface rendering method using optical flow is proposed. Optical flow is the apparent motion in the image plane produced by the projection of the real 3D motion onto 2D image. In this paper, the object remains stationary while the scanner undergoes translational motion. The 3D motion of an object can be recovered from the optical flow field using additional constraints. By extracting the surface information from 3D motion, it is possible to get an accurate 3D model of the object. Both synthetic and real image sequences have been used to illustrate the feasibility of the proposed method. The experimental results suggest that the proposed method is suitable for the reconstruction of 3D models from ultrasound medical images as well as other computed tomograms

  20. From analogue to apps--developing an app to prepare children for medical imaging procedures.

    Science.gov (United States)

    Williams, Gigi; Greene, Siobhan

    2015-01-01

    The Royal Children's Hospital (RCH) in Melbourne has launched a world-first app for children that will help reduce anxiety and the need for anesthesia during medical imaging procedures. The free, game-based app, "Okee in Medical Imaging", helps children aged from four to eight years to prepare for all medical imaging procedures--X-ray, CT, MRI, ultrasound, nuclear medicine, and fluoroscopy. The app is designed to reduce anticipatory fear of imaging procedures, while helping to ensure that children attend imaging appointments equipped with the skills required for efficient and effective scans to be performed. This paper describes how the app was developed.

  1. Three-Dimensional Printing and Medical Imaging: A Review of the Methods and Applications.

    Science.gov (United States)

    Marro, Alessandro; Bandukwala, Taha; Mak, Walter

    2016-01-01

    The purpose of this article is to review recent innovations on the process and application of 3-dimensional (3D) printed objects from medical imaging data. Data for 3D printed medical models can be obtained from computed tomography, magnetic resonance imaging, and ultrasound using the Data Imaging and Communications in Medicine (DICOM) software. The data images are processed using segmentation and mesh generation tools and converted to a standard tessellation language (STL) file for printing. 3D printing technologies include stereolithography, selective laser sintering, inkjet, and fused-deposition modeling . 3D printed models have been used for preoperative planning of complex surgeries, the creation of custom prosthesis, and in the education and training of physicians. The application of medical imaging and 3D printers has been successful in providing solutions to many complex medical problems. As technology advances, its applications continue to grow in the future. Copyright © 2015 Mosby, Inc. All rights reserved.

  2. Student Perspectives of Imaging Anatomy in Undergraduate Medical Education

    Science.gov (United States)

    Machado, Jorge Americo Dinis; Barbosa, Joselina Maria Pinto; Ferreira, Maria Amelia Duarte

    2013-01-01

    Radiological imaging is gaining relevance in the acquisition of competencies in clinical anatomy. The aim of this study was to evaluate the perceptions of medical students on teaching/learning of imaging anatomy as an integrated part of anatomical education. A questionnaire was designed to evaluate the perceptions of second-year students…

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

    International Nuclear Information System (INIS)

    Li Mei; Xia Xu; Zhang Jiemin; Chen Mingfeng

    1998-01-01

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

  4. Process techniques of charge transfer time reduction for high speed CMOS image sensors

    International Nuclear Information System (INIS)

    Cao Zhongxiang; Li Quanliang; Han Ye; Qin Qi; Feng Peng; Liu Liyuan; Wu Nanjian

    2014-01-01

    This paper proposes pixel process techniques to reduce the charge transfer time in high speed CMOS image sensors. These techniques increase the lateral conductivity of the photo-generated carriers in a pinned photodiode (PPD) and the voltage difference between the PPD and the floating diffusion (FD) node by controlling and optimizing the N doping concentration in the PPD and the threshold voltage of the reset transistor, respectively. The techniques shorten the charge transfer time from the PPD diode to the FD node effectively. The proposed process techniques do not need extra masks and do not cause harm to the fill factor. A sub array of 32 × 64 pixels was designed and implemented in the 0.18 μm CIS process with five implantation conditions splitting the N region in the PPD. The simulation and measured results demonstrate that the charge transfer time can be decreased by using the proposed techniques. Comparing the charge transfer time of the pixel with the different implantation conditions of the N region, the charge transfer time of 0.32 μs is achieved and 31% of image lag was reduced by using the proposed process techniques. (semiconductor devices)

  5. Implementation of Synthetic Aperture Imaging in Medical Ultrasound

    DEFF Research Database (Denmark)

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

    2010-01-01

    The main advantage of medical ultrasound imaging is its real time capability, which makes it possible to visualize dynamic structures in the human body. Real time synthetic aperture imaging puts very high demands on the hardware, which currently cannot be met. A method for reducing the number...... of calculations and still retain the many advantages of SA imaging is described. It consists of a dual stage beamformer, where the first can be a simple fixed focus analog beamformer and the second an ordinary digital ultrasound beamformer. The performance and constrictions of the approach is described....

  6. 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 vis...

  7. 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...

  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...

  9. Preliminary application in teaching of medical imaging with picture archiving and communication systems

    International Nuclear Information System (INIS)

    Wei Yuqing; Hu Jian; Wang Xuejian; Cao Jun; Tong Juan; Shen Guiquan; Luo Min; Luo Song

    2003-01-01

    Objective: To evaluate PACS (picture archiving and communication systems) in the teaching of medical imaging. Methods: Large screen multimedia reading room and electronic study room were built with GE PACS and Angel RIS (radiology information system) and end-term picture-word work-station. Pictures and words of PACS were unloaded directly for teaching and teaching image bank and test image bank. Results: Large screen multimedia reading room, classroom, and electronic study room were built successfully. Valuable information of nearly 5000 patients in the teaching imaging bank of PACS was accumulated. Classic medical imaging teaching mode was changed. Real-time and multi-mode teaching were realized, and teaching effect was greatly improved. The PACS-based teaching model was accepted pleasantly by students. Conclusion: PACS is very useful to improve the teaching quality of medical imaging and it is worth to popularize

  10. The quest for standards in medical imaging

    Energy Technology Data Exchange (ETDEWEB)

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

    2011-05-15

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

  11. 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.

  12. 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.

  13. 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

  14. 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...

  15. 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

  16. 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.

  17. Controlled searching in reversibly de-identified medical imaging archives.

    Science.gov (United States)

    Silva, Jorge Miguel; Pinho, Eduardo; Monteiro, Eriksson; Silva, João Figueira; Costa, Carlos

    2018-01-01

    Nowadays, digital medical imaging in healthcare has become a fundamental tool for medical diagnosis. This growth has been accompanied by the development of technologies and standards, such as the DICOM standard and PACS. This environment led to the creation of collaborative projects where there is a need to share medical data between different institutions for research and educational purposes. In this context, it is necessary to maintain patient data privacy and provide an easy and secure mechanism for authorized personnel access. This paper presents a solution that fully de-identifies standard medical imaging objects, including metadata and pixel data, providing at the same time a reversible de-identifier mechanism that retains search capabilities from the original data. The last feature is important in some scenarios, for instance, in collaborative platforms where data is anonymized when shared with the community but searchable for data custodians or authorized entities. The solution was integrated into an open source PACS archive and validated in a multidisciplinary collaborative scenario. Copyright © 2017 Elsevier Inc. All rights reserved.

  18. NASA technology utilization applications. [transfer of medical sciences

    Science.gov (United States)

    1973-01-01

    The work is reported from September 1972 through August 1973 by the Technology Applications Group of the Science Communication Division (SCD), formerly the Biological Sciences Communication Project (BSCP) in the Department of Medical and Public Affairs of the George Washington University. The work was supportive of many aspects of the NASA Technology Utilization program but in particular those dealing with Biomedical and Technology Application Teams, Applications Engineering projects, new technology reporting and documentation and transfer activities. Of particular interest are detailed reports on the progress of various hardware projects, and suggestions and criteria for the evaluation of candidate hardware projects. Finally some observations about the future expansion of the TU program are offered.

  19. Potential for increasing conspicuity of short-T1 lesions in the brain using magnetisation transfer imaging

    International Nuclear Information System (INIS)

    De Souza, N.M.; Hajnal, J.V.; Baudouin, C.J.

    1995-01-01

    We investigated the feasibility of using T1-weighted magnetisation transfer sequences to generate tissue contrast and increase the conspicuity of short-T1 areas within the brain. We imaged two normal volunteers with and without saturating off-resonance radiofrequency irradiation at a range of repetition times (TR 200-760 ms). T1 values and magnetisation transfer ratios for white matter and deep grey matter were calculated. We studied eight patients with intracranial lesions showing short-T1 areas, using mildly T1-weighted sequences with and without magnetisation transfer contrast. Lesion numbers, areas and signal intensities were measured and lesion-to-background contrast was calculated. Comparison was made with conventional T1-weighted spin-echo images. In the normal volunteers, contrast between the thalamus, caudate and lentiform nuclei and white matter showed striking visual differences, with magnetisation transfer weighting, with decreasing TR. In all patients, short-T1 lesions were seen more clearly on magnetisation transfer-weighted images, with significant increase in lesion number, area and contrast, when compared with conventional T1-weighted scans. (orig.)

  20. Characteristics and determinants of knowledge transfer policies at universities and public institutions in medical research--protocol for a systematic review of the qualitative research literature.

    Science.gov (United States)

    Jahn, Rosa; Müller, Olaf; Bozorgmehr, Kayvan

    2015-08-19

    Universities, public institutions, and the transfer of knowledge to the private sector play a major role in the development of medical technologies. The decisions of universities and public institutions regarding the transfer of knowledge impact the accessibility of the final product, making it easier or more difficult for consumers to access these products. In the case of medical research, these products are pharmaceuticals, diagnostics, or medical procedures. The ethical dimension of access to these potentially lifesaving products is apparent and distinguishes the transfer of medical knowledge from the transfer of knowledge in other areas. While the general field of technology transfer from academic and public to private actors is attracting an increasing amount of scholarly attention, the specifications of knowledge transfer in the medical field are not as well explored. This review seeks to provide a systematic overview and analysis of the qualitative literature on the characteristics and determinants of knowledge transfer in medical research and development. The review systematically searches the literature for qualitative studies that focus on knowledge transfer characteristics and determinants at medical academic and public research institutions. It aims at identifying and analyzing the literature on the content and context of knowledge transfer policies, decision-making processes, and actors at academic and public institutions. The search strategy includes the databases PubMed, Web of Science, ProQuest, and DiVa. These databases will be searched based on pre-specified search terms. The studies selected for inclusion in the review will be critically assessed for their quality utilizing the Qualitative Research Checklist developed by the Clinical Appraisal Skills Programme. Data extraction and synthesis will be based on the meta-ethnographic approach. This review seeks to further the understanding of the kinds of transfer pathways that exist in medical

  1. Implementing Protocols to Improve Patient Safety in the Medical Imaging Department.

    Science.gov (United States)

    Carrizales, Gwen; Clark, Kevin R

    2015-01-01

    Patient safety is a focal point in healthcare because of recent changes issued by CMS. Hospital reimbursement rates have fallen, and these reimbursement rates are governed by CMS mandates regarding patient safety procedures. Reimbursement changes are reflected in the National Patient Safety Goals (NPSGs) administered annually by The Joint Commission. Medical imaging departments have multiple areas of patient safety concerns including effective handoff communication, proper patient identification, and safe medication/contrast administration. This literature review examines those areas of patient safety within the medical imaging department and reveals the need for continued protocol and policy changes to keep patients safe.

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

    Science.gov (United States)

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

    2018-05-01

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

  3. Assessment of neural networks training strategies for histomorphometric analysis of synchrotron radiation medical images

    International Nuclear Information System (INIS)

    Alvarenga de Moura Meneses, Anderson; Gomes Pinheiro, Christiano Jorge; Rancoita, Paola; Schaul, Tom; Gambardella, Luca Maria; Schirru, Roberto; Barroso, Regina Cely; Oliveira, Luis Fernando de

    2010-01-01

    Micro-computed tomography (μCT) obtained by synchrotron radiation (SR) enables magnified images with a high space resolution that might be used as a non-invasive and non-destructive technique for the quantitative analysis of medical images, in particular the histomorphometry (HMM) of bony mass. In the preprocessing of such images, conventional operations such as binarization and morphological filtering are used before calculating the stereological parameters related, for example, to the trabecular bone microarchitecture. However, there is no standardization of methods for HMM based on μCT images, especially the ones obtained with SR X-ray. Notwithstanding the several uses of artificial neural networks (ANNs) in medical imaging, their application to the HMM of SR-μCT medical images is still incipient, despite the potential of both techniques. The contribution of this paper is the assessment and comparison of well-known training algorithms as well as the proposal of training strategies (combinations of training algorithms, sub-image kernel and symmetry information) for feed-forward ANNs in the task of bone pixels recognition in SR-μCT medical images. For a quantitative comparison, the results of a cross validation and a statistical analysis of the results for 36 training strategies are presented. The ANNs demonstrated both very low mean square errors in the validation, and good quality segmentation of the image of interest for application to HMM in SR-μCT medical images.

  4. Assessment of neural networks training strategies for histomorphometric analysis of synchrotron radiation medical images

    Energy Technology Data Exchange (ETDEWEB)

    Alvarenga de Moura Meneses, Anderson, E-mail: ameneses@lmp.ufrj.b [Federal University of Rio de Janeiro, COPPE, Nuclear Engineering Program, CP 68509, CEP 21.941-972, Rio de Janeiro, RJ (Brazil); IDSIA (Dalle Molle Institute for Artificial Intelligence), University of Lugano (Switzerland); Gomes Pinheiro, Christiano Jorge [State University of Rio de Janeiro, RJ (Brazil); Rancoita, Paola [IDSIA (Dalle Molle Institute for Artificial Intelligence), University of Lugano (Switzerland); Mathematics Department, Universita degli Studi di Milano (Italy); Schaul, Tom; Gambardella, Luca Maria [IDSIA (Dalle Molle Institute for Artificial Intelligence), University of Lugano (Switzerland); Schirru, Roberto [Federal University of Rio de Janeiro, COPPE, Nuclear Engineering Program, CP 68509, CEP 21.941-972, Rio de Janeiro, RJ (Brazil); Barroso, Regina Cely; Oliveira, Luis Fernando de [State University of Rio de Janeiro, RJ (Brazil)

    2010-09-21

    Micro-computed tomography ({mu}CT) obtained by synchrotron radiation (SR) enables magnified images with a high space resolution that might be used as a non-invasive and non-destructive technique for the quantitative analysis of medical images, in particular the histomorphometry (HMM) of bony mass. In the preprocessing of such images, conventional operations such as binarization and morphological filtering are used before calculating the stereological parameters related, for example, to the trabecular bone microarchitecture. However, there is no standardization of methods for HMM based on {mu}CT images, especially the ones obtained with SR X-ray. Notwithstanding the several uses of artificial neural networks (ANNs) in medical imaging, their application to the HMM of SR-{mu}CT medical images is still incipient, despite the potential of both techniques. The contribution of this paper is the assessment and comparison of well-known training algorithms as well as the proposal of training strategies (combinations of training algorithms, sub-image kernel and symmetry information) for feed-forward ANNs in the task of bone pixels recognition in SR-{mu}CT medical images. For a quantitative comparison, the results of a cross validation and a statistical analysis of the results for 36 training strategies are presented. The ANNs demonstrated both very low mean square errors in the validation, and good quality segmentation of the image of interest for application to HMM in SR-{mu}CT medical images.

  5. 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

  6. 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.

  7. Open source tools for standardized privacy protection of medical images

    Science.gov (United States)

    Lien, Chung-Yueh; Onken, Michael; Eichelberg, Marco; Kao, Tsair; Hein, Andreas

    2011-03-01

    In addition to the primary care context, medical images are often useful for research projects and community healthcare networks, so-called "secondary use". Patient privacy becomes an issue in such scenarios since the disclosure of personal health information (PHI) has to be prevented in a sharing environment. In general, most PHIs should be completely removed from the images according to the respective privacy regulations, but some basic and alleviated data is usually required for accurate image interpretation. Our objective is to utilize and enhance these specifications in order to provide reliable software implementations for de- and re-identification of medical images suitable for online and offline delivery. DICOM (Digital Imaging and Communications in Medicine) images are de-identified by replacing PHI-specific information with values still being reasonable for imaging diagnosis and patient indexing. In this paper, this approach is evaluated based on a prototype implementation built on top of the open source framework DCMTK (DICOM Toolkit) utilizing standardized de- and re-identification mechanisms. A set of tools has been developed for DICOM de-identification that meets privacy requirements of an offline and online sharing environment and fully relies on standard-based methods.

  8. 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)

  9. 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.

  10. Contributions in compression of 3D medical images and 2D images; Contributions en compression d'images medicales 3D et d'images naturelles 2D

    Energy Technology Data Exchange (ETDEWEB)

    Gaudeau, Y

    2006-12-15

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

  11. Local gray level S-curve transformation - A generalized contrast enhancement technique for medical images.

    Science.gov (United States)

    Gandhamal, Akash; Talbar, Sanjay; Gajre, Suhas; Hani, Ahmad Fadzil M; Kumar, Dileep

    2017-04-01

    Most medical images suffer from inadequate contrast and brightness, which leads to blurred or weak edges (low contrast) between adjacent tissues resulting in poor segmentation and errors in classification of tissues. Thus, contrast enhancement to improve visual information is extremely important in the development of computational approaches for obtaining quantitative measurements from medical images. In this research, a contrast enhancement algorithm that applies gray-level S-curve transformation technique locally in medical images obtained from various modalities is investigated. The S-curve transformation is an extended gray level transformation technique that results into a curve similar to a sigmoid function through a pixel to pixel transformation. This curve essentially increases the difference between minimum and maximum gray values and the image gradient, locally thereby, strengthening edges between adjacent tissues. The performance of the proposed technique is determined by measuring several parameters namely, edge content (improvement in image gradient), enhancement measure (degree of contrast enhancement), absolute mean brightness error (luminance distortion caused by the enhancement), and feature similarity index measure (preservation of the original image features). Based on medical image datasets comprising 1937 images from various modalities such as ultrasound, mammograms, fluorescent images, fundus, X-ray radiographs and MR images, it is found that the local gray-level S-curve transformation outperforms existing techniques in terms of improved contrast and brightness, resulting in clear and strong edges between adjacent tissues. The proposed technique can be used as a preprocessing tool for effective segmentation and classification of tissue structures in medical images. Copyright © 2017 Elsevier Ltd. All rights reserved.

  12. Rough-fuzzy pattern recognition applications in bioinformatics and medical imaging

    CERN Document Server

    Maji, Pradipta

    2012-01-01

    Learn how to apply rough-fuzzy computing techniques to solve problems in bioinformatics and medical image processing Emphasizing applications in bioinformatics and medical image processing, this text offers a clear framework that enables readers to take advantage of the latest rough-fuzzy computing techniques to build working pattern recognition models. The authors explain step by step how to integrate rough sets with fuzzy sets in order to best manage the uncertainties in mining large data sets. Chapters are logically organized according to the major phases of pattern recognition systems dev

  13. Promises and challenges for the implementation of computational medical imaging (radiomics) in oncology.

    Science.gov (United States)

    Limkin, E J; Sun, R; Dercle, L; Zacharaki, E I; Robert, C; Reuzé, S; Schernberg, A; Paragios, N; Deutsch, E; Ferté, C

    2017-06-01

    Medical image processing and analysis (also known as Radiomics) is a rapidly growing discipline that maps digital medical images into quantitative data, with the end goal of generating imaging biomarkers as decision support tools for clinical practice. The use of imaging data from routine clinical work-up has tremendous potential in improving cancer care by heightening understanding of tumor biology and aiding in the implementation of precision medicine. As a noninvasive method of assessing the tumor and its microenvironment in their entirety, radiomics allows the evaluation and monitoring of tumor characteristics such as temporal and spatial heterogeneity. One can observe a rapid increase in the number of computational medical imaging publications-milestones that have highlighted the utility of imaging biomarkers in oncology. Nevertheless, the use of radiomics as clinical biomarkers still necessitates amelioration and standardization in order to achieve routine clinical adoption. This Review addresses the critical issues to ensure the proper development of radiomics as a biomarker and facilitate its implementation in clinical practice. © The Author 2017. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

  14. High speed display algorithm for 3D medical images using Multi Layer Range Image

    International Nuclear Information System (INIS)

    Ban, Hideyuki; Suzuki, Ryuuichi

    1993-01-01

    We propose high speed algorithm that display 3D voxel images obtained from medical imaging systems such as MRI. This algorithm convert voxel image data to 6 Multi Layer Range Image (MLRI) data, which is an augmentation of the range image data. To avoid the calculation for invisible voxels, the algorithm selects at most 3 MLRI data from 6 in accordance with the view direction. The proposed algorithm displays 256 x 256 x 256 voxel data within 0.6 seconds using 22 MIPS Workstation without a special hardware such as Graphics Engine. Real-time display will be possible on 100 MIPS class Workstation by our algorithm. (author)

  15. Medical imaging in clinical applications algorithmic and computer-based approaches

    CERN Document Server

    Bhateja, Vikrant; Hassanien, Aboul

    2016-01-01

    This volume comprises of 21 selected chapters, including two overview chapters devoted to abdominal imaging in clinical applications supported computer aided diagnosis approaches as well as different techniques for solving the pectoral muscle extraction problem in the preprocessing part of the CAD systems for detecting breast cancer in its early stage using digital mammograms. The aim of this book is to stimulate further research in medical imaging applications based algorithmic and computer based approaches and utilize them in real-world clinical applications. The book is divided into four parts, Part-I: Clinical Applications of Medical Imaging, Part-II: Classification and clustering, Part-III: Computer Aided Diagnosis (CAD) Tools and Case Studies and Part-IV: Bio-inspiring based Computer Aided diagnosis techniques. .

  16. Chemical exchange saturation transfer MR imaging of Parkinson's disease at 3 Tesla

    International Nuclear Information System (INIS)

    Li, Chunmei; Peng, Shuai; Wang, Rui; Chen, Min; Chen, Haibo; Su, Wen; Zhao, Xuna; Zhou, Jinyuan

    2014-01-01

    To demonstrate the feasibility of using chemical exchange saturation transfer (CEST) imaging to detect Parkinson's disease (PD) in patients at 3 Tesla. Twenty-seven PD patients (17 men and 10 women; age range, 54-77 years) and 22 age-matched normal controls (13 men and 9 women; age range, 55-73 years) were examined on a 3-Tesla MRI system. Magnetization transfer spectra with 31 different frequency offsets (-6 to 6 ppm) were acquired at two transverse slices of the head, including the basal ganglia and midbrain. One-way analysis of variance tests was used to compare the differences in CEST imaging signals between PD patients and normal controls. Total CEST signal between the offsets of 0 and 4 ppm in the substantia nigra was significantly lower in PD patients than in normal controls (P = 0.006), which could be associated with the loss of dopaminergic neurons. Protein-based CEST imaging signals at the offset of 3.5 ppm in the globus pallidus, putamen and caudate were significantly increased in PD patients, compared to normal controls (P < 0.001, P = 0.003, P < 0.001, respectively). CEST imaging signals could potentially serve as imaging biomarkers to aid in the non-invasive molecular diagnosis of PD. (orig.)

  17. Evaluation of biolistic gene transfer methods in vivo using non-invasive bioluminescent imaging techniques

    Directory of Open Access Journals (Sweden)

    Daniell Henry

    2011-06-01

    Full Text Available Abstract Background Gene therapy continues to hold great potential for treating many different types of disease and dysfunction. Safe and efficient techniques for gene transfer and expression in vivo are needed to enable gene therapeutic strategies to be effective in patients. Currently, the most commonly used methods employ replication-defective viral vectors for gene transfer, while physical gene transfer methods such as biolistic-mediated ("gene-gun" delivery to target tissues have not been as extensively explored. In the present study, we evaluated the efficacy of biolistic gene transfer techniques in vivo using non-invasive bioluminescent imaging (BLI methods. Results Plasmid DNA carrying the firefly luciferase (LUC reporter gene under the control of the human Cytomegalovirus (CMV promoter/enhancer was transfected into mouse skin and liver using biolistic methods. The plasmids were coupled to gold microspheres (1 μm diameter using different DNA Loading Ratios (DLRs, and "shot" into target tissues using a helium-driven gene gun. The optimal DLR was found to be in the range of 4-10. Bioluminescence was measured using an In Vivo Imaging System (IVIS-50 at various time-points following transfer. Biolistic gene transfer to mouse skin produced peak reporter gene expression one day after transfer. Expression remained detectable through four days, but declined to undetectable levels by six days following gene transfer. Maximum depth of tissue penetration following biolistic transfer to abdominal skin was 200-300 μm. Similarly, biolistic gene transfer to mouse liver in vivo also produced peak early expression followed by a decline over time. In contrast to skin, however, liver expression of the reporter gene was relatively stable 4-8 days post-biolistic gene transfer, and remained detectable for nearly two weeks. Conclusions The use of bioluminescence imaging techniques enabled efficient evaluation of reporter gene expression in vivo. Our results

  18. Interactive data language (IDL) for medical image processing

    International Nuclear Information System (INIS)

    Md Saion Salikin

    2002-01-01

    Interactive Data Language (IDL) is one of many softwares available in the market for medical image processing and analysis. IDL is a complete, structured language that can be used both interactively and to create sophisticated functions, procedures, and applications. It provides a suitable processing routines and display method which include animation, specification of colour table including 24-bit capability, 3-D visualization and many graphic operation. The important features of IDL for medical imaging are segmentation, visualization, quantification and pattern recognition. In visualization IDL is capable of allowing greater precision and flexibility when visualizing data. For example, IDL eliminates the limits on Number of Contour level. In term of data analysis, IDL is capable of handling complicated functions such as Fast Fourier Transform (FFT) function, Hough and Radon Transform function, Legendre Polynomial function, as well as simple functions such as Histogram function. In pattern recognition, pattern description is defined as points rather than pixels. With this functionality, it is easy to re-use the same pattern on more than one destination device (even if the destinations have varying resolution). In other words it have the ability to specify values in points. However there are a few disadvantages of using IDL. Licensing is by dongkel key and limited licences hence limited access to potential IDL users. A few examples are shown to demonstrate the capabilities of IDL in carrying out its function for medical image processing. (Author)

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

    DEFF Research Database (Denmark)

    Nikolov, Svetoslav; Jensen, Jørgen Arendt

    2003-01-01

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

  20. Quantitative Magnetization Transfer Imaging in Human Brain at 3 T via Selective Inversion Recovery

    OpenAIRE

    Dortch, Richard D.; Li, Ke; Gochberg, Daniel F.; Welch, E. Brian; Dula, Adrienne N.; Tamhane, Ashish A.; Gore, John C.; Smith, Seth A.

    2011-01-01

    Quantitative magnetization transfer imaging yields indices describing the interactions between free water protons and immobile, macromolecular protons—including the macromolecular to free pool size ratio (PSR) and the rate of magnetization transfer between pools kmf. This study describes the first implementation of the selective inversion recovery quantitative magnetization transfer method on a clinical 3.0-T scanner in human brain in vivo. Selective inversion recovery data were acquired at 1...

  1. Shared Medical Imaging Repositories.

    Science.gov (United States)

    Lebre, Rui; Bastião, Luís; Costa, Carlos

    2018-01-01

    This article describes the implementation of a solution for the integration of ownership concept and access control over medical imaging resources, making possible the centralization of multiple instances of repositories. The proposed architecture allows the association of permissions to repository resources and delegation of rights to third entities. It includes a programmatic interface for management of proposed services, made available through web services, with the ability to create, read, update and remove all components resulting from the architecture. The resulting work is a role-based access control mechanism that was integrated with Dicoogle Open-Source Project. The solution has several application scenarios like, for instance, collaborative platforms for research and tele-radiology services deployed at Cloud.

  2. Research and Realization of Medical Image Fusion Based on Three-Dimensional Reconstruction

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    A new medical image fusion technique is presented. The method is based on three-dimensional reconstruction. After reconstruction, the three-dimensional volume data is normalized by three-dimensional coordinate conversion in the same way and intercepted through setting up cutting plane including anatomical structure, as a result two images in entire registration on space and geometry are obtained and the images are fused at last.Compared with traditional two-dimensional fusion technique, three-dimensional fusion technique can not only resolve the different problems existed in the two kinds of images, but also avoid the registration error of the two kinds of images when they have different scan and imaging parameter. The research proves this fusion technique is more exact and has no registration, so it is more adapt to arbitrary medical image fusion with different equipments.

  3. Finding the Truth in Medical Imaging: Painting the Picture of Appropriateness for Magnetic Resonance Imaging in Canada.

    Science.gov (United States)

    Vanderby, Sonia; Peña-Sánchez, Juan Nicolás; Kalra, Neil; Babyn, Paul

    2015-11-01

    Questions about the appropriateness of medical imaging exams, particularly related to magnetic resonance exams, have arisen in recent years. However, the prevalence of inappropriate imaging in Canada is unclear as inappropriate exam proportion estimates are often based on studies from other countries. Hence, we sought to compare and summarize Canadian studies related to magnetic resonance imaging appropriateness. We completed a systematic literature search identifying studies related to magnetic resonance appropriateness in Canada published between 2003 and 2013. Two researchers independently searched and evaluated the literature available. Articles that studied or discussed magnetic resonance appropriateness in Canada were selected based on titles, abstracts, and, where necessary, full article review. Articles relating solely to other modalities or countries were excluded, as were imaging appropriateness guidelines and reviews. Fourteen articles were included: 8 quantitative studies and 6 editorials/commentaries. The quantitative studies reported inappropriate proportions of magnetic resonance exams ranging from 2%-28.5%. Our review also revealed substantial variations among study methods and analyses. Common topics identified among editorials/commentaries included reasons for obtaining imaging in general and for selecting a specific modality, consequences of inappropriate imaging, factors contributing to demand, and suggested means of mitigating inappropriate medical imaging use. The available studies do not support the common claim that 30% of medical imaging exams in Canada are inappropriate. The actual proportion of inappropriate magnetic resonance exams has not yet been established conclusively in Canada. Further research, particularly on a widespread national scale, is needed to guide healthcare policies. Copyright © 2015 Canadian Association of Radiologists. Published by Elsevier Inc. All rights reserved.

  4. 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

  5. Dynamic CT perfusion image data compression for efficient parallel processing.

    Science.gov (United States)

    Barros, Renan Sales; Olabarriaga, Silvia Delgado; Borst, Jordi; van Walderveen, Marianne A A; Posthuma, Jorrit S; Streekstra, Geert J; van Herk, Marcel; Majoie, Charles B L M; Marquering, Henk A

    2016-03-01

    The increasing size of medical imaging data, in particular time series such as CT perfusion (CTP), requires new and fast approaches to deliver timely results for acute care. Cloud architectures based on graphics processing units (GPUs) can provide the processing capacity required for delivering fast results. However, the size of CTP datasets makes transfers to cloud infrastructures time-consuming and therefore not suitable in acute situations. To reduce this transfer time, this work proposes a fast and lossless compression algorithm for CTP data. The algorithm exploits redundancies in the temporal dimension and keeps random read-only access to the image elements directly from the compressed data on the GPU. To the best of our knowledge, this is the first work to present a GPU-ready method for medical image compression with random access to the image elements from the compressed data.

  6. The Imaging and Medical Beam Line at the Australian Synchrotron

    Science.gov (United States)

    Hausermann, Daniel; Hall, Chris; Maksimenko, Anton; Campbell, Colin

    2010-07-01

    As a result of the enthusiastic support from the Australian biomedical, medical and clinical communities, the Australian Synchrotron is constructing a world-class facility for medical research, the `Imaging and Medical Beamline'. The IMBL began phased commissioning in late 2008 and is scheduled to commence the first clinical research programs with patients in 2011. It will provide unrivalled x-ray facilities for imaging and radiotherapy for a wide range of research applications in diseases, treatments and understanding of physiological processes. The main clinical research drivers are currently high resolution and sensitivity cardiac and breast imaging, cell tracking applied to regenerative and stem cell medicine and cancer therapies. The beam line has a maximum source to sample distance of 136 m and will deliver a 60 cm by 4 cm x-ray beam1—monochromatic and white—to a three storey satellite building fully equipped for pre-clinical and clinical research. Currently operating with a 1.4 Tesla multi-pole wiggler, it will upgrade to a 4.2 Tesla device which requires the ability to handle up to 21 kW of x-ray power at any point along the beam line. The applications envisaged for this facility include imaging thick objects encompassing materials, humans and animals. Imaging can be performed in the range 15-150 keV. Radiotherapy research typically requires energies between 30 and 120 keV, for both monochromatic and broad beam.

  7. Prototype Web-based continuing medical education using FlashPix images.

    OpenAIRE

    Landman, A.; Yagi, Y.; Gilbertson, J.; Dawson, R.; Marchevsky, A.; Becich, M. J.

    2000-01-01

    Continuing Medical Education (CME) is a requirement among practicing physicians to promote continuous enhancement of clinical knowledge to reflect new developments in medical care. Previous research has harnessed the Web to disseminate complete pathology CME case studies including history, images, diagnoses, and discussions to the medical community. Users submit real-time diagnoses and receive instantaneous feedback, eliminating the need for hard copies of case material and case evaluation fo...

  8. Medical imaging: Material change for X-ray detectors

    Science.gov (United States)

    Rowlands, John A.

    2017-10-01

    The X-ray sensitivity of radiology instruments is limited by the materials used in their detectors. A material from the perovskite family of semiconductors could allow lower doses of X-rays to be used for medical imaging. See Letter p.87

  9. 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)

  10. A QR code based zero-watermarking scheme for authentication of medical images in teleradiology cloud.

    Science.gov (United States)

    Seenivasagam, V; Velumani, R

    2013-01-01

    Healthcare institutions adapt cloud based archiving of medical images and patient records to share them efficiently. Controlled access to these records and authentication of images must be enforced to mitigate fraudulent activities and medical errors. This paper presents a zero-watermarking scheme implemented in the composite Contourlet Transform (CT)-Singular Value Decomposition (SVD) domain for unambiguous authentication of medical images. Further, a framework is proposed for accessing patient records based on the watermarking scheme. The patient identification details and a link to patient data encoded into a Quick Response (QR) code serves as the watermark. In the proposed scheme, the medical image is not subjected to degradations due to watermarking. Patient authentication and authorized access to patient data are realized on combining a Secret Share with the Master Share constructed from invariant features of the medical image. The Hu's invariant image moments are exploited in creating the Master Share. The proposed system is evaluated with Checkmark software and is found to be robust to both geometric and non geometric attacks.

  11. A QR Code Based Zero-Watermarking Scheme for Authentication of Medical Images in Teleradiology Cloud

    Directory of Open Access Journals (Sweden)

    V. Seenivasagam

    2013-01-01

    Full Text Available Healthcare institutions adapt cloud based archiving of medical images and patient records to share them efficiently. Controlled access to these records and authentication of images must be enforced to mitigate fraudulent activities and medical errors. This paper presents a zero-watermarking scheme implemented in the composite Contourlet Transform (CT—Singular Value Decomposition (SVD domain for unambiguous authentication of medical images. Further, a framework is proposed for accessing patient records based on the watermarking scheme. The patient identification details and a link to patient data encoded into a Quick Response (QR code serves as the watermark. In the proposed scheme, the medical image is not subjected to degradations due to watermarking. Patient authentication and authorized access to patient data are realized on combining a Secret Share with the Master Share constructed from invariant features of the medical image. The Hu’s invariant image moments are exploited in creating the Master Share. The proposed system is evaluated with Checkmark software and is found to be robust to both geometric and non geometric attacks.

  12. Image-based electronic patient records for secured collaborative medical applications.

    Science.gov (United States)

    Zhang, Jianguo; Sun, Jianyong; Yang, Yuanyuan; Liang, Chenwen; Yao, Yihong; Cai, Weihua; Jin, Jin; Zhang, Guozhen; Sun, Kun

    2005-01-01

    We developed a Web-based system to interactively display image-based electronic patient records (EPR) for secured intranet and Internet collaborative medical applications. The system consists of four major components: EPR DICOM gateway (EPR-GW), Image-based EPR repository server (EPR-Server), Web Server and EPR DICOM viewer (EPR-Viewer). In the EPR-GW and EPR-Viewer, the security modules of Digital Signature and Authentication are integrated to perform the security processing on the EPR data with integrity and authenticity. The privacy of EPR in data communication and exchanging is provided by SSL/TLS-based secure communication. This presentation gave a new approach to create and manage image-based EPR from actual patient records, and also presented a way to use Web technology and DICOM standard to build an open architecture for collaborative medical applications.

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

    International Nuclear Information System (INIS)

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

    2013-01-01

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

  14. Medical Image Data and Datasets in the Era of Machine Learning-Whitepaper from the 2016 C-MIMI Meeting Dataset Session.

    Science.gov (United States)

    Kohli, Marc D; Summers, Ronald M; Geis, J Raymond

    2017-08-01

    At the first annual Conference on Machine Intelligence in Medical Imaging (C-MIMI), held in September 2016, a conference session on medical image data and datasets for machine learning identified multiple issues. The common theme from attendees was that everyone participating in medical image evaluation with machine learning is data starved. There is an urgent need to find better ways to collect, annotate, and reuse medical imaging data. Unique domain issues with medical image datasets require further study, development, and dissemination of best practices and standards, and a coordinated effort among medical imaging domain experts, medical imaging informaticists, government and industry data scientists, and interested commercial, academic, and government entities. High-level attributes of reusable medical image datasets suitable to train, test, validate, verify, and regulate ML products should be better described. NIH and other government agencies should promote and, where applicable, enforce, access to medical image datasets. We should improve communication among medical imaging domain experts, medical imaging informaticists, academic clinical and basic science researchers, government and industry data scientists, and interested commercial entities.

  15. A quality-refinement process for medical imaging applications.

    Science.gov (United States)

    Neuhaus, J; Maleike, D; Nolden, M; Kenngott, H-G; Meinzer, H-P; Wolf, I

    2009-01-01

    To introduce and evaluate a process for refinement of software quality that is suitable to research groups. In order to avoid constraining researchers too much, the quality improvement process has to be designed carefully. The scope of this paper is to present and evaluate a process to advance quality aspects of existing research prototypes in order to make them ready for initial clinical studies. The proposed process is tailored for research environments and therefore more lightweight than traditional quality management processes. Focus on quality criteria that are important at the given stage of the software life cycle. Usage of tools that automate aspects of the process is emphasized. To evaluate the additional effort that comes along with the process, it was exemplarily applied for eight prototypical software modules for medical image processing. The introduced process has been applied to improve the quality of all prototypes so that they could be successfully used in clinical studies. The quality refinement yielded an average of 13 person days of additional effort per project. Overall, 107 bugs were found and resolved by applying the process. Careful selection of quality criteria and the usage of automated process tools lead to a lightweight quality refinement process suitable for scientific research groups that can be applied to ensure a successful transfer of technical software prototypes into clinical research workflows.

  16. Application of a latent variables model for the medical images analysis

    International Nuclear Information System (INIS)

    Campos S, Y.; Ruiz C, S.

    2008-01-01

    In recent years the technological advance has allowed the significant advance in diverse research fields, the medicine has not been exempt of this technology and the use of this technology has allowed a significant advance in the equipment that are used to obtain medical images. The quantity of information that is generated with this equipment has grown in exponential form and it is a difficult task to carry out a quantitative analysis of the data also the manipulation of big quantities of information makes the medical images analysis a complicated task. It is in fact this complexity what motivates this work where one of the main objectives is the analysis of techniques that allow to work with the complexity of the data generated with medical equipment. Likewise, it is wanted to illustrate an application of the peaceful uses of the nuclear energy to treat a medical problem where the diagnostic it depends essentially on the current medical equipment to give an appropriate treatment to the patients. (Author)

  17. State-of-the-art radiation detectors for medical imaging: Demands and trends

    International Nuclear Information System (INIS)

    Darambara, Dimitra G.

    2006-01-01

    Over the last half-century a variety of significant technical advances in several scientific fields has been pointing to an exploding growth in the field of medical imaging leading to a better interpretation of more specific anatomical, biochemical and molecular pathways. In particular, the development of novel imaging detectors and readout electronics has been critical to the advancement of medical imaging allowing the invention of breakthrough platforms for simultaneous acquisition of multi-modality images at molecular level. The present paper presents a review of the challenges, demands and constraints on radiation imaging detectors imposed by the nature of the modality and the physics of the imaging source. This is followed by a concise review and perspective on various types of state-of-the-art detector technologies that have been developed to meet these requirements. Trends, prospects and new concepts for future imaging detectors are also highlighted

  18. State-of-the-art radiation detectors for medical imaging: Demands and trends

    Energy Technology Data Exchange (ETDEWEB)

    Darambara, Dimitra G. [Joint Department of Physics, Royal Marsden Foundation Trust and Institute of Cancer Research, Fulham Road, London SW3 6JJ (United Kingdom)]. E-mail: dimitra.darambara@icr.ac.uk

    2006-12-20

    Over the last half-century a variety of significant technical advances in several scientific fields has been pointing to an exploding growth in the field of medical imaging leading to a better interpretation of more specific anatomical, biochemical and molecular pathways. In particular, the development of novel imaging detectors and readout electronics has been critical to the advancement of medical imaging allowing the invention of breakthrough platforms for simultaneous acquisition of multi-modality images at molecular level. The present paper presents a review of the challenges, demands and constraints on radiation imaging detectors imposed by the nature of the modality and the physics of the imaging source. This is followed by a concise review and perspective on various types of state-of-the-art detector technologies that have been developed to meet these requirements. Trends, prospects and new concepts for future imaging detectors are also highlighted.

  19. A virtual image chain for perceived image quality of medical display

    Science.gov (United States)

    Marchessoux, Cédric; Jung, Jürgen

    2006-03-01

    This paper describes a virtual image chain for medical display (project VICTOR: granted in the 5th framework program by European commission). The chain starts from raw data of an image digitizer (CR, DR) or synthetic patterns and covers image enhancement (MUSICA by Agfa) and both display possibilities, hardcopy (film on viewing box) and softcopy (monitor). Key feature of the chain is a complete image wise approach. A first prototype is implemented in an object-oriented software platform. The display chain consists of several modules. Raw images are either taken from scanners (CR-DR) or from a pattern generator, in which characteristics of DR- CR systems are introduced by their MTF and their dose-dependent Poisson noise. The image undergoes image enhancement and comes to display. For soft display, color and monochrome monitors are used in the simulation. The image is down-sampled. The non-linear response of a color monitor is taken into account by the GOG or S-curve model, whereas the Standard Gray-Scale-Display-Function (DICOM) is used for monochrome display. The MTF of the monitor is applied on the image in intensity levels. For hardcopy display, the combination of film, printer, lightbox and viewing condition is modeled. The image is up-sampled and the DICOM-GSDF or a Kanamori Look-Up-Table is applied. An anisotropic model for the MTF of the printer is applied on the image in intensity levels. The density-dependent color (XYZ) of the hardcopy film is introduced by Look-Up-tables. Finally a Human Visual System Model is applied to the intensity images (XYZ in terms of cd/m2) in order to eliminate nonvisible differences. Comparison leads to visible differences, which are quantified by higher order image quality metrics. A specific image viewer is used for the visualization of the intensity image and the visual difference maps.

  20. [Computational medical imaging (radiomics) and potential for immuno-oncology].

    Science.gov (United States)

    Sun, R; Limkin, E J; Dercle, L; Reuzé, S; Zacharaki, E I; Chargari, C; Schernberg, A; Dirand, A S; Alexis, A; Paragios, N; Deutsch, É; Ferté, C; Robert, C

    2017-10-01

    The arrival of immunotherapy has profoundly changed the management of multiple cancers, obtaining unexpected tumour responses. However, until now, the majority of patients do not respond to these new treatments. The identification of biomarkers to determine precociously responding patients is a major challenge. Computational medical imaging (also known as radiomics) is a promising and rapidly growing discipline. This new approach consists in the analysis of high-dimensional data extracted from medical imaging, to further describe tumour phenotypes. This approach has the advantages of being non-invasive, capable of evaluating the tumour and its microenvironment in their entirety, thus characterising spatial heterogeneity, and being easily repeatable over time. The end goal of radiomics is to determine imaging biomarkers as decision support tools for clinical practice and to facilitate better understanding of cancer biology, allowing the assessment of the changes throughout the evolution of the disease and the therapeutic sequence. This review will develop the process of computational imaging analysis and present its potential in immuno-oncology. Copyright © 2017 Société française de radiothérapie oncologique (SFRO). Published by Elsevier SAS. All rights reserved.