Medical Image Databases

PubMed Central

Tagare, Hemant D.; Jaffe, C. Carl; Duncan, James

1997-01-01

Abstract Information contained in medical images differs considerably from that residing in alphanumeric format. The difference can be attributed to four characteristics: (1) the semantics of medical knowledge extractable from images is imprecise; (2) image information contains form and spatial data, which are not expressible in conventional language; (3) a large part of image information is geometric; (4) diagnostic inferences derived from images rest on an incomplete, continuously evolving model of normality. This paper explores the differentiating characteristics of text versus images and their impact on design of a medical image database intended to allow content-based indexing and retrieval. One strategy for implementing medical image databases is presented, which employs object-oriented iconic queries, semantics by association with prototypes, and a generic schema. PMID:9147338

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

PubMed

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.

Teaching procedural skills to medical students: A pilot procedural skills lab.

PubMed

Katz, Laurence M; Finch, Alexander; McKinnish, Tyler; Gilliland, Kurt; Tolleson-Rinehart, Sue; Marks, Bonita L

2017-01-01

Medical students have limited confidence in performing procedural skills. A pilot study was conducted to evaluate the effect of a multifaceted Procedural Skills Lab (PSL) on the confidence of medical students to perform procedural skills. Twelve 2nd year medical students were randomly selected to participate in a pilot PSL. The PSL students met with an instructor for 2 h once a week for 4 weeks. Students participated in a flipped classroom and spaced education program before laboratory sessions that included a cadaver laboratory. Procedural skills included a focused assessment with sonography in trauma (FAST) scan, cardiac echocardiogram, lumbar puncture, arthrocentesis, and insertion of intraosseous and intravenous catheters. Students in the PSL were asked to rank their confidence in performing procedural skills before and after completion of the laboratory sessions (Wilcoxon ranked-sum test). A web-based questionnaire was also emailed to all 2nd year medical students to establish a baseline frequency for observing, performing, and confidence performing procedural skills (Mann-Whitney U-test). Fifty-nine percent (n = 106) of 180 2nd year medical students (n = 12 PSL students [treatment group], n = 94 [control group]) completed the survey. Frequency of observation, performance, and confidence in performing procedural skills was similar between the control and treatment groups at baseline. There was an increased confidence level (p < 0.001) for performing all procedural skills for the treatment group after completion of the PSL. An innovative PSL may increase students' confidence to perform procedural skills. Future studies will examine competency after a PSL.

Fusion Imaging for Procedural Guidance.

PubMed

Wiley, Brandon M; Eleid, Mackram F; Thaden, Jeremy J

2018-05-01

The field of percutaneous structural heart interventions has grown tremendously in recent years. This growth has fueled the development of new imaging protocols and technologies in parallel to help facilitate these minimally-invasive procedures. Fusion imaging is an exciting new technology that combines the strength of 2 imaging modalities and has the potential to improve procedural planning and the safety of many commonly performed transcatheter procedures. In this review we discuss the basic concepts of fusion imaging along with the relative strengths and weaknesses of static vs dynamic fusion imaging modalities. This review will focus primarily on echocardiographic-fluoroscopic fusion imaging and its application in commonly performed transcatheter structural heart procedures. Copyright © 2017 Sociedad Española de Cardiología. Published by Elsevier España, S.L.U. All rights reserved.

Slice-to-volume medical image registration: A survey.

PubMed

Ferrante, Enzo; Paragios, Nikos

2017-07-01

During the last decades, the research community of medical imaging has witnessed continuous advances in image registration methods, which pushed the limits of the state-of-the-art and enabled the development of novel medical procedures. A particular type of image registration problem, known as slice-to-volume registration, played a fundamental role in areas like image guided surgeries and volumetric image reconstruction. However, to date, and despite the extensive literature available on this topic, no survey has been written to discuss this challenging problem. This paper introduces the first comprehensive survey of the literature about slice-to-volume registration, presenting a categorical study of the algorithms according to an ad-hoc taxonomy and analyzing advantages and disadvantages of every category. We draw some general conclusions from this analysis and present our perspectives on the future of the field. Copyright © 2017 Elsevier B.V. All rights reserved.

Ultrasound: medical imaging and beyond (an invited review).

PubMed

Azhari, Haim

2012-09-01

Medical applications of ultrasound were first investigated about seventy years ago. It has rapidly evolved since then, becoming an essential tool in medical imaging. Ultrasound ability to provide real time images with frame rates exceeding several hundred frames per second allows one to view rapid anatomical changes as well as to guide minimal invasive procedures. By, combining Doppler techniques with anatomical images ultrasound provides real time quantitative flow information as well. It is portable, versatile, cost effective and considered sufficiently hazardless to monitor pregnancy. Moreover, ultrasound has the unique capacity to offer therapeutic capabilities in addition to its outstanding imaging abilities. It can be used for physiotherapy, lithotripsy, and thermal ablation, and recent studies have demonstrated its usefulness in drug delivery, gene therapy and molecular imaging. The purpose of this article is to provide an introductory review of the field covering briefly topics from basic physics through current imaging methods to therapeutic applications.

Improving Performance During Image-Guided Procedures

PubMed Central

Duncan, James R.; Tabriz, David

2015-01-01

Objective Image-guided procedures have become a mainstay of modern health care. This article reviews how human operators process imaging data and use it to plan procedures and make intraprocedural decisions. Methods A series of models from human factors research, communication theory, and organizational learning were applied to the human-machine interface that occupies the center stage during image-guided procedures. Results Together, these models suggest several opportunities for improving performance as follows: 1. Performance will depend not only on the operator’s skill but also on the knowledge embedded in the imaging technology, available tools, and existing protocols. 2. Voluntary movements consist of planning and execution phases. Performance subscores should be developed that assess quality and efficiency during each phase. For procedures involving ionizing radiation (fluoroscopy and computed tomography), radiation metrics can be used to assess performance. 3. At a basic level, these procedures consist of advancing a tool to a specific location within a patient and using the tool. Paradigms from mapping and navigation should be applied to image-guided procedures. 4. Recording the content of the imaging system allows one to reconstruct the stimulus/response cycles that occur during image-guided procedures. Conclusions When compared with traditional “open” procedures, the technology used during image-guided procedures places an imaging system and long thin tools between the operator and the patient. Taking a step back and reexamining how information flows through an imaging system and how actions are conveyed through human-machine interfaces suggest that much can be learned from studying system failures. In the same way that flight data recorders revolutionized accident investigations in aviation, much could be learned from recording video data during image-guided procedures. PMID:24921628

Radiology Physician Extenders: A Literature Review of the History and Current Roles of Physician Extenders in Medical Imaging.

PubMed

Sanders, Vicki L; Flanagan, Jennifer

2015-01-01

The purpose of the literature review was to assess the origins of radiology physician extenders and examine the current roles found in the literature of advanced practice physician extenders within medical imaging. Twenty-six articles relating to physician assistants (PAs), nurse practitioners (NPs), radiologist assistants (RAs), and nuclear medicine advanced associates (NMAAs) were reviewed to discern similarities and differences in history, scope of practice, and roles in the medical imaging field. The literature showed PAs and NPs are working mostly in interventional radiology. PAs, NPs, and RAs perform similar tasks in radiology, including history and physicals, evaluation and management, preprocedure work-up, obtaining informed consent, initial observations/reports, and post-procedure follow-up. NPs and PAs perform a variety of procedures but most commonly vascular access, paracentesis, and thoracentesis. RAs perform gastrointestinal, genitourinary, nonvascular invasive fluoroscopy procedures, and vascular access procedures. The review revealed NMAAs are working in an advanced role, but no specific performances of procedures was found in the literature, only suggested tasks and clinical competencies. PAs, NPs, and RAs are currently the three main midlevel providers used in medical imaging. These midlevel providers are being used in a variety of ways to increase the efficiency of the radiologist and provide diagnostic and therapeutic radiologic procedures to patients. NMAAs are being used in medical imaging but little literature is available on current roles in clinical practice. More research is needed to assess the exact procedures and duties being performed by these medical imaging physician extenders.

Digital diagnosis of medical images

NASA Astrophysics Data System (ADS)

Heinonen, Tomi; Kuismin, Raimo; Jormalainen, Raimo; Dastidar, Prasun; Frey, Harry; Eskola, Hannu

2001-08-01

The popularity of digital imaging devices and PACS installations has increased during the last years. Still, images are analyzed and diagnosed using conventional techniques. Our research group begun to study the requirements for digital image diagnostic methods to be applied together with PACS systems. The research was focused on various image analysis procedures (e.g., segmentation, volumetry, 3D visualization, image fusion, anatomic atlas, etc.) that could be useful in medical diagnosis. We have developed Image Analysis software (www.medimag.net) to enable several image-processing applications in medical diagnosis, such as volumetry, multimodal visualization, and 3D visualizations. We have also developed a commercial scalable image archive system (ActaServer, supports DICOM) based on component technology (www.acta.fi), and several telemedicine applications. All the software and systems operate in NT environment and are in clinical use in several hospitals. The analysis software have been applied in clinical work and utilized in numerous patient cases (500 patients). This method has been used in the diagnosis, therapy and follow-up in various diseases of the central nervous system (CNS), respiratory system (RS) and human reproductive system (HRS). In many of these diseases e.g. Systemic Lupus Erythematosus (CNS), nasal airways diseases (RS) and ovarian tumors (HRS), these methods have been used for the first time in clinical work. According to our results, digital diagnosis improves diagnostic capabilities, and together with PACS installations it will become standard tool during the next decade by enabling more accurate diagnosis and patient follow-up.

The child's perspective on discomfort during medical research procedures: a descriptive study.

PubMed

Staphorst, Mira S; Benninga, Marc A; Bisschoff, Margriet; Bon, Irma; Busschbach, Jan J V; Diederen, Kay; van Goudoever, Johannes B; Haarman, Eric G; Hunfeld, Joke A M; Jaddoe, Vincent V W; de Jong, Karin J M; de Jongste, Johan C; Kindermann, Angelika; Königs, Marsh; Oosterlaan, Jaap; Passchier, Jan; Pijnenburg, Mariëlle W; Reneman, Liesbeth; Ridder, Lissy de; Tamminga, Hyke G; Tiemeier, Henning W; Timman, Reinier; van de Vathorst, Suzanne

2017-08-01

The evaluation of discomfort in paediatric research is scarcely evidence-based. In this study, we make a start in describing children's self-reported discomfort during common medical research procedures and compare this with discomfort during dental check-ups which can be considered as a reference level of a 'minimal discomfort' medical procedure. We exploratory study whether there are associations between age, anxiety-proneness, gender, medical condition, previous experiences and discomfort. We also describe children's suggestions for reducing discomfort. Cross-sectional descriptive study. Paediatric research at three academic hospitals. 357 children with and without illnesses (8-18 years, mean=10.6 years) were enrolled: 307 from paediatric research studies and 50 from dental care. We measured various generic forms of discomfort (nervousness, annoyance, pain, fright, boredom, tiredness) due to six common research procedures: buccal swabs, MRI scans, pulmonary function tests, skin prick tests, ultrasound imaging and venepunctures. Most children reported limited discomfort during the research procedures (means: 1-2.6 on a scale from 1 to 5). Compared with dental check-ups, buccal swab tests, skin prick tests and ultrasound imaging were less discomforting, while MRI scans, venepunctures and pulmonary function tests caused a similar degree of discomfort. 60.3% of the children suggested providing distraction by showing movies to reduce discomfort. The exploratory analyses suggested a positive association between anxiety-proneness and discomfort. The findings of this study support the acceptability of participation of children in the studied research procedures, which stimulates evidence-based research practice. Furthermore, the present study can be considered as a first step in providing benchmarks for discomfort of procedures in paediatric research. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved

The child's perspective on discomfort during medical research procedures: a descriptive study

PubMed Central

Staphorst, Mira S; Benninga, Marc A; Bisschoff, Margriet; Bon, Irma; Busschbach, Jan J V; Diederen, Kay; van Goudoever, Johannes B; Haarman, Eric G; Hunfeld, Joke A M; Jaddoe, Vincent V W; de Jong, Karin J M; de Jongste, Johan C; Kindermann, Angelika; Königs, Marsh; Oosterlaan, Jaap; Passchier, Jan; Pijnenburg, Mariëlle W; Reneman, Liesbeth; de Ridder, Lissy; Tamminga, Hyke G; Tiemeier, Henning W; Timman, Reinier; van de Vathorst, Suzanne

2017-01-01

Objective The evaluation of discomfort in paediatric research is scarcely evidence-based. In this study, we make a start in describing children's self-reported discomfort during common medical research procedures and compare this with discomfort during dental check-ups which can be considered as a reference level of a ‘minimal discomfort’ medical procedure. We exploratory study whether there are associations between age, anxiety-proneness, gender, medical condition, previous experiences and discomfort. We also describe children's suggestions for reducing discomfort. Design Cross-sectional descriptive study. Setting Paediatric research at three academic hospitals. Patients 357 children with and without illnesses (8–18 years, mean=10.6 years) were enrolled: 307 from paediatric research studies and 50 from dental care. Main outcome measures We measured various generic forms of discomfort (nervousness, annoyance, pain, fright, boredom, tiredness) due to six common research procedures: buccal swabs, MRI scans, pulmonary function tests, skin prick tests, ultrasound imaging and venepunctures. Results Most children reported limited discomfort during the research procedures (means: 1–2.6 on a scale from 1 to 5). Compared with dental check-ups, buccal swab tests, skin prick tests and ultrasound imaging were less discomforting, while MRI scans, venepunctures and pulmonary function tests caused a similar degree of discomfort. 60.3% of the children suggested providing distraction by showing movies to reduce discomfort. The exploratory analyses suggested a positive association between anxiety-proneness and discomfort. Conclusions The findings of this study support the acceptability of participation of children in the studied research procedures, which stimulates evidence-based research practice. Furthermore, the present study can be considered as a first step in providing benchmarks for discomfort of procedures in paediatric research. PMID:28765130

MATHEMATICAL METHODS IN MEDICAL IMAGE PROCESSING

PubMed Central

ANGENENT, SIGURD; PICHON, ERIC; TANNENBAUM, ALLEN

2013-01-01

In this paper, we describe some central mathematical problems in medical imaging. The subject has been undergoing rapid changes driven by better hardware and software. Much of the software is based on novel methods utilizing geometric partial differential equations in conjunction with standard signal/image processing techniques as well as computer graphics facilitating man/machine interactions. As part of this enterprise, researchers have been trying to base biomedical engineering principles on rigorous mathematical foundations for the development of software methods to be integrated into complete therapy delivery systems. These systems support the more effective delivery of many image-guided procedures such as radiation therapy, biopsy, and minimally invasive surgery. We will show how mathematics may impact some of the main problems in this area, including image enhancement, registration, and segmentation. PMID:23645963

37 CFR 102.26 - Special procedures: Medical records.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 37 Patents, Trademarks, and Copyrights 1 2014-07-01 2014-07-01 false Special procedures: Medical... Special procedures: Medical records. (a) No response to any request for access to medical records by an... routine use, for all systems of records containing medical records, consultations with an individual's...

37 CFR 102.26 - Special procedures: Medical records.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 37 Patents, Trademarks, and Copyrights 1 2012-07-01 2012-07-01 false Special procedures: Medical... Special procedures: Medical records. (a) No response to any request for access to medical records by an... routine use, for all systems of records containing medical records, consultations with an individual's...

Medical Imaging System

NASA Technical Reports Server (NTRS)

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.

12 CFR 310.6 - Special procedures: Medical records.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 12 Banks and Banking 5 2012-01-01 2012-01-01 false Special procedures: Medical records. 310.6... PRIVACY ACT REGULATIONS § 310.6 Special procedures: Medical records. Medical records shall be disclosed on... transmission of the medical information directly to the requesting individual could have an adverse effect upon...

12 CFR 310.6 - Special procedures: Medical records.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 12 Banks and Banking 5 2014-01-01 2014-01-01 false Special procedures: Medical records. 310.6... PRIVACY ACT REGULATIONS § 310.6 Special procedures: Medical records. Medical records shall be disclosed on... transmission of the medical information directly to the requesting individual could have an adverse effect upon...

12 CFR 310.6 - Special procedures: Medical records.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 12 Banks and Banking 4 2010-01-01 2010-01-01 false Special procedures: Medical records. 310.6... PRIVACY ACT REGULATIONS § 310.6 Special procedures: Medical records. Medical records shall be disclosed on... transmission of the medical information directly to the requesting individual could have an adverse effect upon...

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

PubMed

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.

Scientific evaluation and pricing of medical devices and associated procedures in France.

PubMed

Gilard, Martine; Debroucker, Frederique; Dubray, Claude; Allioux, Yves; Aper, Eliane; Barat-Leonhardt, Valérie; Brami, Michèle; Carbonneil, Cédric; Chartier-Kastler, Emmanuel; Coqueblin, Claire; Fare, Sandrine; Giri, Isabelle; Goehrs, Jean-Marie; Levesque, Karine; Maugendre, Philippe; Parquin, François; Sales, Jean-Patrick; Szwarcensztein, Karine

2013-01-01

Medical devices are many and various, ranging from tongue spatulas to implantable or invasive devices and imaging machines; their lifetimes are short, between 18 months and 5 years, due to incessant incremental innovation; and they are operator-dependent: in general, the clinical user performs a fitting procedure (hip implant or pacemaker), a therapeutic procedure using a non-implantable invasive device (arrhythmic site ablation probe, angioplasty balloon, extension spondyloplasty system, etc.) or follow-up of an active implanted device (long-term follow-up of an implanted cardiac defibrillator or of a deep brain stimulator in Parkinson's patients). A round-table held during the XXVIII(th) Giens Workshops meeting focused on the methodology of scientific evaluation of medical devices and the associated procedures with a view to their pricing and financing by the French National Health Insurance system. The working hypothesis was that the available data-set was sufficient for and compatible with scientific evaluation with clinical benefit. Post-registration studies, although contributing to the continuity of assessment, were not dealt with. Moreover, the focus was restricted to devices used in health establishments, where the association between devices and technical medical procedures is optimally representative. An update of the multiple regulatory protocols governing medical devices and procedures is provided. Issues more specifically related to procedures as such, to non-implantable devices and to innovative devices are then dealt with, and the proposals and discussion points raised at the round-table for each of these three areas are presented. © 2013 Société Française de Pharmacologie et de Thérapeutique.

An interventional multispectral photoacoustic imaging platform for the guidance of minimally invasive procedures

NASA Astrophysics Data System (ADS)

Xia, Wenfeng; Nikitichev, Daniil I.; Mari, Jean Martial; West, Simeon J.; Ourselin, Sebastien; Beard, Paul C.; Desjardins, Adrien E.

2015-07-01

Precise and efficient guidance of medical devices is of paramount importance for many minimally invasive procedures. These procedures include fetal interventions, tumor biopsies and treatments, central venous catheterisations and peripheral nerve blocks. Ultrasound imaging is commonly used for guidance, but it often provides insufficient contrast with which to identify soft tissue structures such as vessels, tumors, and nerves. In this study, a hybrid interventional imaging system that combines ultrasound imaging and multispectral photoacoustic imaging for guiding minimally invasive procedures was developed and characterized. The system provides both structural information from ultrasound imaging and molecular information from multispectral photoacoustic imaging. It uses a commercial linear-array ultrasound imaging probe as the ultrasound receiver, with a multimode optical fiber embedded in a needle to deliver pulsed excitation light to tissue. Co-registration of ultrasound and photoacoustic images is achieved with the use of the same ultrasound receiver for both modalities. Using tissue ex vivo, the system successfully discriminated deep-located fat tissue from the surrounding muscle tissue. The measured photoacoustic spectrum of the fat tissue had good agreement with the lipid spectrum in literature.

TU-C-218-01: Effective Medical Imaging Physics Education.

PubMed

Sprawls, P

2012-06-01

A practical and applied knowledge of physics and the associated technology is required for the clinically effective and safe use of the various medical imaging modalities. This is needed by all involved in the imaging process, including radiologists, especially residents in training, technologists, and physicists who provide consultation on optimum and safe procedures and as educators for the other imaging professionals. This area of education is undergoing considerable change and evolution for three reasons: 1. Increasing capabilities and complexity of medical imaging technology and procedures, 2.Expanding scope and availability of educational resources, especially on the internet, and 3. A significant increase in our knowledge of the mental learning process and the design of learning activities to optimize effectiveness and efficiency, especially for clinically applied physics. This course will address those three issues by providing guidance on establishing appropriate clinically focused learning outcomes, a review of the brain function for enhancing clinically applied physics, and the design and delivery of effective learning activities beginning with the classroom and continuing through learning physics during the clinical practice of radiology. Characteristics of each type of learning activity will be considered with respect to effectiveness and efficiency in achieving appropriate learning outcomes. A variety of available resources will be identified and demonstrated for use in the different phases of learning process. A major focus is on enhancing the role of the medical physicist in clinical radiology both as a resource and educator with contemporary technology being the tool, but not the teacher. 1. Develop physics learning objectives that will support effective and safe medical imaging procedures. 2. Understand specific brain functions that are involved in learning and applying physics. 3. Describe the characteristics and development of mental knowledge

5 CFR 2412.7 - Special procedures; medical records.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 5 Administrative Personnel 3 2014-01-01 2014-01-01 false Special procedures; medical records. 2412.7 Section 2412.7 Administrative Personnel FEDERAL LABOR RELATIONS AUTHORITY, GENERAL COUNSEL OF THE... Special procedures; medical records. (a) If medical records are requested for inspection which, in the...

5 CFR 2412.7 - Special procedures; medical records.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 5 Administrative Personnel 3 2012-01-01 2012-01-01 false Special procedures; medical records. 2412.7 Section 2412.7 Administrative Personnel FEDERAL LABOR RELATIONS AUTHORITY, GENERAL COUNSEL OF THE... Special procedures; medical records. (a) If medical records are requested for inspection which, in the...

5 CFR 2412.7 - Special procedures; medical records.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 5 Administrative Personnel 3 2010-01-01 2010-01-01 false Special procedures; medical records. 2412.7 Section 2412.7 Administrative Personnel FEDERAL LABOR RELATIONS AUTHORITY, GENERAL COUNSEL OF THE... Special procedures; medical records. (a) If medical records are requested for inspection which, in the...

Advances in medical image computing.

PubMed

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.

Interactive MR image guidance for neurosurgical and minimally invasive procedures

NASA Astrophysics Data System (ADS)

Wong, Terence Z.; Schwartz, Richard B.; Pergolizzi, Richard S., Jr.; Black, Peter M.; Kacher, Daniel F.; Morrison, Paul R.; Jolesz, Ferenc A.

1999-05-01

Advantages of MR imaging for guidance of minimally invasive procedures include exceptional soft tissue contrast, intrinsic multiplanar imaging capability, and absence of exposure to ionizing radiation. Specialized imaging sequences are available and under development which can further enhance diagnosis and therapy. Flow-sensitive imaging techniques can be used to identify vascular structures. Temperature-sensitive imaging is possible which can provide interactive feedback prior to, during, and following the delivery of thermal energy. Functional MR imaging and dynamic contrast-enhanced MRI sequences can provide additional information for guidance in neurosurgical applications. Functional MR allows mapping of eloquent areas in the brain, so that these areas may be avoided during therapy. Dynamic contrast enhancement techniques can be useful for distinguishing active tumor from tumor necrosis caused by previous radiation therapy. An open-configuration 0.5T MRI system (GE Signa SP) developed at Brigham and Women's Hospital in collaboration with General Electric Medical Systems is described. Interactive navigation systems have been integrated into the MRI system. The imaging system is sited in an operating room environment, and used for image guided neurosurgical procedures (biopsies and tumor excision), as well as minimally invasive thermal therapies. Examples of MR imaging guidance, navigational techniques, and clinical applications are presented.

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

PubMed

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.

29 CFR 1410.5 - Special procedures: Medical records.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 29 Labor 4 2014-07-01 2014-07-01 false Special procedures: Medical records. 1410.5 Section 1410.5 Labor Regulations Relating to Labor (Continued) FEDERAL MEDIATION AND CONCILIATION SERVICE PRIVACY § 1410.5 Special procedures: Medical records. (a) If medical records are requested for inspection which...

29 CFR 1410.5 - Special procedures: Medical records.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 29 Labor 4 2010-07-01 2010-07-01 false Special procedures: Medical records. 1410.5 Section 1410.5 Labor Regulations Relating to Labor (Continued) FEDERAL MEDIATION AND CONCILIATION SERVICE PRIVACY § 1410.5 Special procedures: Medical records. (a) If medical records are requested for inspection which...

29 CFR 1410.5 - Special procedures: Medical records.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 29 Labor 4 2011-07-01 2011-07-01 false Special procedures: Medical records. 1410.5 Section 1410.5 Labor Regulations Relating to Labor (Continued) FEDERAL MEDIATION AND CONCILIATION SERVICE PRIVACY § 1410.5 Special procedures: Medical records. (a) If medical records are requested for inspection which...

Cloud computing in medical imaging.

PubMed

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.

22 CFR 215.6 - Special procedures: Medical records.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 22 Foreign Relations 1 2014-04-01 2014-04-01 false Special procedures: Medical records. 215.6... PRIVACY ACT OF 1974 § 215.6 Special procedures: Medical records. If the Assistant Director for Administration or the Privacy Liaison Officer, determines that the release directly to the individual of medical...

22 CFR 215.6 - Special procedures: Medical records.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 22 Foreign Relations 1 2013-04-01 2013-04-01 false Special procedures: Medical records. 215.6... PRIVACY ACT OF 1974 § 215.6 Special procedures: Medical records. If the Assistant Director for Administration or the Privacy Liaison Officer, determines that the release directly to the individual of medical...

32 CFR 319.7 - Special procedures: Medical records.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 32 National Defense 2 2013-07-01 2013-07-01 false Special procedures: Medical records. 319.7... (CONTINUED) PRIVACY PROGRAM DEFENSE INTELLIGENCE AGENCY PRIVACY PROGRAM § 319.7 Special procedures: Medical records. Medical records, requested pursuant to § 319.5 of this part, will be disclosed to the requester...

32 CFR 319.7 - Special procedures: Medical records.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 32 National Defense 2 2011-07-01 2011-07-01 false Special procedures: Medical records. 319.7... (CONTINUED) PRIVACY PROGRAM DEFENSE INTELLIGENCE AGENCY PRIVACY PROGRAM § 319.7 Special procedures: Medical records. Medical records, requested pursuant to § 319.5 of this part, will be disclosed to the requester...

Medical Imaging.

ERIC Educational Resources Information Center

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)

Medical Image Tamper Detection Based on Passive Image Authentication.

PubMed

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.

7 CFR 1.115 - Special procedures: Medical records.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 1 2013-01-01 2013-01-01 false Special procedures: Medical records. 1.115 Section 1... Regulations § 1.115 Special procedures: Medical records. In the event an agency receives a request pursuant to § 1.112 for access to medical records (including psychological records) whose disclosure it determines...

40 CFR 16.8 - Special procedures: Medical Records.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 1 2014-07-01 2014-07-01 false Special procedures: Medical Records. 16... PRIVACY ACT OF 1974 § 16.8 Special procedures: Medical Records. Should EPA receive a request for access to medical records (including psychological records) disclosure of which the system manager decides would be...

19 CFR 201.27 - Special procedures: Medical records.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 19 Customs Duties 3 2014-04-01 2014-04-01 false Special procedures: Medical records. 201.27... APPLICATION Safeguarding Individual Privacy Pursuant to 5 U.S.C. 552a § 201.27 Special procedures: Medical... maintained by the Commission which pertain to him or her, medical and psychological records merit special...

7 CFR 1.115 - Special procedures: Medical records.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 1 2014-01-01 2014-01-01 false Special procedures: Medical records. 1.115 Section 1... Regulations § 1.115 Special procedures: Medical records. In the event an agency receives a request pursuant to § 1.112 for access to medical records (including psychological records) whose disclosure it determines...

40 CFR 16.8 - Special procedures: Medical Records.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 1 2013-07-01 2013-07-01 false Special procedures: Medical Records. 16... PRIVACY ACT OF 1974 § 16.8 Special procedures: Medical Records. Should EPA receive a request for access to medical records (including psychological records) disclosure of which the system manager decides would be...

29 CFR 1611.6 - Special procedures: Medical records.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 29 Labor 4 2014-07-01 2014-07-01 false Special procedures: Medical records. 1611.6 Section 1611.6... REGULATIONS § 1611.6 Special procedures: Medical records. In the event the Commission receives a request pursuant to § 1611.3 for access to medical records (including psychological records) whose disclosure of...

29 CFR 1611.6 - Special procedures: Medical records.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 29 Labor 4 2011-07-01 2011-07-01 false Special procedures: Medical records. 1611.6 Section 1611.6... REGULATIONS § 1611.6 Special procedures: Medical records. In the event the Commission receives a request pursuant to § 1611.3 for access to medical records (including psychological records) whose disclosure of...

29 CFR 1611.6 - Special procedures: Medical records.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 29 Labor 4 2010-07-01 2010-07-01 false Special procedures: Medical records. 1611.6 Section 1611.6... REGULATIONS § 1611.6 Special procedures: Medical records. In the event the Commission receives a request pursuant to § 1611.3 for access to medical records (including psychological records) whose disclosure of...

15 CFR 4.26 - Special procedures: Medical records.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 15 Commerce and Foreign Trade 1 2014-01-01 2014-01-01 false Special procedures: Medical records. 4... GOVERNMENT INFORMATION Privacy Act § 4.26 Special procedures: Medical records. (a) No response to any request for access to medical records from an individual will be issued by the Privacy Officer for a period of...

15 CFR 4.26 - Special procedures: Medical records.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 15 Commerce and Foreign Trade 1 2013-01-01 2013-01-01 false Special procedures: Medical records. 4... GOVERNMENT INFORMATION Privacy Act § 4.26 Special procedures: Medical records. (a) No response to any request for access to medical records from an individual will be issued by the Privacy Officer for a period of...

Intelligent distributed medical image management

NASA Astrophysics Data System (ADS)

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.

Meta-analysis of the technical performance of an imaging procedure: guidelines and statistical methodology.

PubMed

Huang, Erich P; Wang, Xiao-Feng; Choudhury, Kingshuk Roy; McShane, Lisa M; Gönen, Mithat; Ye, Jingjing; Buckler, Andrew J; Kinahan, Paul E; Reeves, Anthony P; Jackson, Edward F; Guimaraes, Alexander R; Zahlmann, Gudrun

2015-02-01

Medical imaging serves many roles in patient care and the drug approval process, including assessing treatment response and guiding treatment decisions. These roles often involve a quantitative imaging biomarker, an objectively measured characteristic of the underlying anatomic structure or biochemical process derived from medical images. Before a quantitative imaging biomarker is accepted for use in such roles, the imaging procedure to acquire it must undergo evaluation of its technical performance, which entails assessment of performance metrics such as repeatability and reproducibility of the quantitative imaging biomarker. Ideally, this evaluation will involve quantitative summaries of results from multiple studies to overcome limitations due to the typically small sample sizes of technical performance studies and/or to include a broader range of clinical settings and patient populations. This paper is a review of meta-analysis procedures for such an evaluation, including identification of suitable studies, statistical methodology to evaluate and summarize the performance metrics, and complete and transparent reporting of the results. This review addresses challenges typical of meta-analyses of technical performance, particularly small study sizes, which often causes violations of assumptions underlying standard meta-analysis techniques. Alternative approaches to address these difficulties are also presented; simulation studies indicate that they outperform standard techniques when some studies are small. The meta-analysis procedures presented are also applied to actual [18F]-fluorodeoxyglucose positron emission tomography (FDG-PET) test-retest repeatability data for illustrative purposes. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Meta-analysis of the technical performance of an imaging procedure: Guidelines and statistical methodology

PubMed Central

Huang, Erich P; Wang, Xiao-Feng; Choudhury, Kingshuk Roy; McShane, Lisa M; Gönen, Mithat; Ye, Jingjing; Buckler, Andrew J; Kinahan, Paul E; Reeves, Anthony P; Jackson, Edward F; Guimaraes, Alexander R; Zahlmann, Gudrun

2017-01-01

Medical imaging serves many roles in patient care and the drug approval process, including assessing treatment response and guiding treatment decisions. These roles often involve a quantitative imaging biomarker, an objectively measured characteristic of the underlying anatomic structure or biochemical process derived from medical images. Before a quantitative imaging biomarker is accepted for use in such roles, the imaging procedure to acquire it must undergo evaluation of its technical performance, which entails assessment of performance metrics such as repeatability and reproducibility of the quantitative imaging biomarker. Ideally, this evaluation will involve quantitative summaries of results from multiple studies to overcome limitations due to the typically small sample sizes of technical performance studies and/or to include a broader range of clinical settings and patient populations. This paper is a review of meta-analysis procedures for such an evaluation, including identification of suitable studies, statistical methodology to evaluate and summarize the performance metrics, and complete and transparent reporting of the results. This review addresses challenges typical of meta-analyses of technical performance, particularly small study sizes, which often causes violations of assumptions underlying standard meta-analysis techniques. Alternative approaches to address these difficulties are also presented; simulation studies indicate that they outperform standard techniques when some studies are small. The meta-analysis procedures presented are also applied to actual [18F]-fluorodeoxyglucose positron emission tomography (FDG-PET) test–retest repeatability data for illustrative purposes. PMID:24872353

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

PubMed

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.

Clinical evaluation of watermarked medical images.

PubMed

Zain, Jasni M; Fauzi, Abdul M; Aziz, Azian A

2006-01-01

Digital watermarking medical images provides security to the images. The purpose of this study was to see whether digitally watermarked images changed clinical diagnoses when assessed by radiologists. We embedded 256 bits watermark to various medical images in the region of non-interest (RONI) and 480K bits in both region of interest (ROI) and RONI. Our results showed that watermarking medical images did not alter clinical diagnoses. In addition, there was no difference in image quality when visually assessed by the medical radiologists. We therefore concluded that digital watermarking medical images were safe in terms of preserving image quality for clinical purposes.

Medical Image Retrieval: A Multimodal Approach

PubMed Central

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

2014-01-01

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

Imaging and Analytics: The changing face of Medical Imaging

NASA Astrophysics Data System (ADS)

Foo, Thomas

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

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

PubMed

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

2014-09-01

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

Trends in the utilization of medical procedures that use ionizing radiation.

PubMed

Bhargavan, Mythreyi

2008-11-01

Medical procedures that use ionizing radiation have grown rapidly in volume over the last two decades and constitute a substantial portion of the collective radiation doses to the U.S. population. The purpose of this study is to describe the components of this growth. Summarized claims data from Medicare are used to describe trends for the period 1986-2005; supplemental data from other payers and surveys are used for verification and to describe age distributions of those who have these procedures. A notable trend is the rapid growth of CT and nuclear medicine, with CT volume per fee-for-service Medicare enrollee growing, on average, at 8% per y and nuclear medicine at 7% per y during the period 1986-2005. Cardiac procedures-nuclear medicine and interventional radiology-grew at over 15% per y per fee-for-service enrollee during the same period. The share of nuclear medicine procedures performed in physician offices increased from 10% in 1986 to 55% in 2005; the share of CT in the emergency room increased from 3% in 1992 to 17% in 2005. With this expansion in imaging volumes across practice settings, there is an increased need for radiation safety education of ordering physicians, imaging physicians, and patients, so that adequate consideration is given to radiation risk when determining the appropriateness of a prescribed procedure.

32 CFR 319.7 - Special procedures: Medical records.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 32 National Defense 2 2012-07-01 2012-07-01 false Special procedures: Medical records. 319.7 Section 319.7 National Defense Department of Defense (Continued) OFFICE OF THE SECRETARY OF DEFENSE (CONTINUED) PRIVACY PROGRAM DEFENSE INTELLIGENCE AGENCY PRIVACY PROGRAM § 319.7 Special procedures: Medical...

32 CFR 319.7 - Special procedures: Medical records.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 32 National Defense 2 2014-07-01 2014-07-01 false Special procedures: Medical records. 319.7 Section 319.7 National Defense Department of Defense (Continued) OFFICE OF THE SECRETARY OF DEFENSE (CONTINUED) PRIVACY PROGRAM DEFENSE INTELLIGENCE AGENCY PRIVACY PROGRAM § 319.7 Special procedures: Medical...

32 CFR 319.7 - Special procedures: Medical records.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 32 National Defense 2 2010-07-01 2010-07-01 false Special procedures: Medical records. 319.7 Section 319.7 National Defense Department of Defense (Continued) OFFICE OF THE SECRETARY OF DEFENSE (CONTINUED) PRIVACY PROGRAM DEFENSE INTELLIGENCE AGENCY PRIVACY PROGRAM § 319.7 Special procedures: Medical...

Hyperspectral imaging applied to medical diagnoses and food safety

NASA Astrophysics Data System (ADS)

Carrasco, Oscar; Gomez, Richard B.; Chainani, Arun; Roper, William E.

2003-08-01

This paper analyzes the feasibility and performance of HSI systems for medical diagnosis as well as for food safety. Illness prevention and early disease detection are key elements for maintaining good health. Health care practitioners worldwide rely on innovative electronic devices to accurately identify disease. Hyperspectral imaging (HSI) is an emerging technique that may provide a less invasive procedure than conventional diagnostic imaging. By analyzing reflected and fluorescent light applied to the human body, a HSI system serves as a diagnostic tool as well as a method for evaluating the effectiveness of applied therapies. The safe supply and production of food is also of paramount importance to public health illness prevention. Although this paper will focus on imaging and spectroscopy in food inspection procedures -- the detection of contaminated food sources -- to ensure food quality, HSI also shows promise in detecting pesticide levels in food production (agriculture.)

18 CFR 701.306 - Special procedure: Medical records.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 18 Conservation of Power and Water Resources 2 2012-04-01 2012-04-01 false Special procedure: Medical records. 701.306 Section 701.306 Conservation of Power and Water Resources WATER RESOURCES COUNCIL COUNCIL ORGANIZATION Protection of Privacy § 701.306 Special procedure: Medical records. (a) An individual...

18 CFR 701.306 - Special procedure: Medical records.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 18 Conservation of Power and Water Resources 2 2013-04-01 2012-04-01 true Special procedure: Medical records. 701.306 Section 701.306 Conservation of Power and Water Resources WATER RESOURCES COUNCIL COUNCIL ORGANIZATION Protection of Privacy § 701.306 Special procedure: Medical records. (a) An individual...

18 CFR 701.306 - Special procedure: Medical records.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 18 Conservation of Power and Water Resources 2 2010-04-01 2010-04-01 false Special procedure: Medical records. 701.306 Section 701.306 Conservation of Power and Water Resources WATER RESOURCES COUNCIL COUNCIL ORGANIZATION Protection of Privacy § 701.306 Special procedure: Medical records. (a) An individual...

18 CFR 701.306 - Special procedure: Medical records.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 18 Conservation of Power and Water Resources 2 2011-04-01 2011-04-01 false Special procedure: Medical records. 701.306 Section 701.306 Conservation of Power and Water Resources WATER RESOURCES COUNCIL COUNCIL ORGANIZATION Protection of Privacy § 701.306 Special procedure: Medical records. (a) An individual...

18 CFR 701.306 - Special procedure: Medical records.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 18 Conservation of Power and Water Resources 2 2014-04-01 2014-04-01 false Special procedure: Medical records. 701.306 Section 701.306 Conservation of Power and Water Resources WATER RESOURCES COUNCIL COUNCIL ORGANIZATION Protection of Privacy § 701.306 Special procedure: Medical records. (a) An individual...

22 CFR 215.6 - Special procedures: Medical records.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 22 Foreign Relations 1 2010-04-01 2010-04-01 false Special procedures: Medical records. 215.6... PRIVACY ACT OF 1974 § 215.6 Special procedures: Medical records. If the Assistant Director for... records maintained by the Agency could have an adverse effect upon such individual, the Director/Officer...

An Intelligent Cloud Storage Gateway for Medical Imaging.

PubMed

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.

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

NASA Technical Reports Server (NTRS)

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

2011-01-01

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

Content-Based Medical Image Retrieval

NASA Astrophysics Data System (ADS)

Müller, Henning; Deserno, Thomas M.

This chapter details the necessity for alternative access concepts to the currently mainly text-based methods in medical information retrieval. This need is partly due to the large amount of visual data produced, the increasing variety of medical imaging data and changing user patterns. The stored visual data contain large amounts of unused information that, if well exploited, can help diagnosis, teaching and research. The chapter briefly reviews the history of image retrieval and its general methods before technologies that have been developed in the medical domain are focussed. We also discuss evaluation of medical content-based image retrieval (CBIR) systems and conclude with pointing out their strengths, gaps, and further developments. As examples, the MedGIFT project and the Image Retrieval in Medical Applications (IRMA) framework are presented.

21 CFR 892.2030 - Medical image digitizer.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 8 2011-04-01 2011-04-01 false Medical image digitizer. 892.2030 Section 892.2030...) MEDICAL DEVICES RADIOLOGY DEVICES Diagnostic Devices § 892.2030 Medical image digitizer. (a) Identification. A medical image digitizer is a device intended to convert an analog medical image into a digital...

21 CFR 892.2030 - Medical image digitizer.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 21 Food and Drugs 8 2013-04-01 2013-04-01 false Medical image digitizer. 892.2030 Section 892.2030...) MEDICAL DEVICES RADIOLOGY DEVICES Diagnostic Devices § 892.2030 Medical image digitizer. (a) Identification. A medical image digitizer is a device intended to convert an analog medical image into a digital...

21 CFR 892.2030 - Medical image digitizer.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 21 Food and Drugs 8 2012-04-01 2012-04-01 false Medical image digitizer. 892.2030 Section 892.2030...) MEDICAL DEVICES RADIOLOGY DEVICES Diagnostic Devices § 892.2030 Medical image digitizer. (a) Identification. A medical image digitizer is a device intended to convert an analog medical image into a digital...

21 CFR 892.2030 - Medical image digitizer.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 21 Food and Drugs 8 2014-04-01 2014-04-01 false Medical image digitizer. 892.2030 Section 892.2030...) MEDICAL DEVICES RADIOLOGY DEVICES Diagnostic Devices § 892.2030 Medical image digitizer. (a) Identification. A medical image digitizer is a device intended to convert an analog medical image into a digital...

MR imaging guidance for minimally invasive procedures

NASA Astrophysics Data System (ADS)

Wong, Terence Z.; Kettenbach, Joachim; Silverman, Stuart G.; Schwartz, Richard B.; Morrison, Paul R.; Kacher, Daniel F.; Jolesz, Ferenc A.

1998-04-01

Image guidance is one of the major challenges common to all minimally invasive procedures including biopsy, thermal ablation, endoscopy, and laparoscopy. This is essential for (1) identifying the target lesion, (2) planning the minimally invasive approach, and (3) monitoring the therapy as it progresses. MRI is an ideal imaging modality for this purpose, providing high soft tissue contrast and multiplanar imaging, capability with no ionizing radiation. An interventional/surgical MRI suite has been developed at Brigham and Women's Hospital which provides multiplanar imaging guidance during surgery, biopsy, and thermal ablation procedures. The 0.5T MRI system (General Electric Signa SP) features open vertical access, allowing intraoperative imaging to be performed. An integrated navigational system permits near real-time control of imaging planes, and provides interactive guidance for positioning various diagnostic and therapeutic probes. MR imaging can also be used to monitor cryotherapy as well as high temperature thermal ablation procedures sing RF, laser, microwave, or focused ultrasound. Design features of the interventional MRI system will be discussed, and techniques will be described for interactive image acquisition and tracking of interventional instruments. Applications for interactive and near-real-time imaging will be presented as well as examples of specific procedures performed using MRI guidance.

Body Image and Body Contouring Procedures.

PubMed

Sarwer, David B; Polonsky, Heather M

2016-10-01

Dissatisfaction with physical appearance and body image is a common psychological phenomena in Western society. Body image dissatisfaction is frequently reported by those who have excess body weight, but also is seen in those of normal body weight. For both groups of individuals, this dissatisfaction impacts self-esteem and quality of life. Furthermore, it is believed to be the motivational catalyst to a range of appearance-enhancing behaviors, including weight loss efforts and physical activity. Body image dissatisfaction is also believed to play a role in the decision to seek the wide range of body contouring procedures offered by aesthetic physicians. Individuals who seek these procedures typically report increased body image dissatisfaction, focus on the feature they wish to alter with treatment, and often experience improvement in body image following treatment. At the same time, extreme body image dissatisfaction is a symptom of a number of recognized psychiatric disorders. These include anorexia nervosa, bulimia nervosa, and body dysmorphic disorder (BDD), all of which can contraindicate aesthetic treatment. This special topic review paper provides an overview of the relationship between body image dissatisfaction and aesthetic procedures designed to improve body contouring. The review specifically focuses on the relationship of body image and body weight, as well as the presentation of body image psychopathology that would contraindicate aesthetic surgery. The overall goal of the paper is to highlight the clinical implications of the existing research and provide suggestions for future research on the psychological aspects of body contouring procedures. © 2016 The American Society for Aesthetic Plastic Surgery, Inc. Reprints and permission: journals.permissions@oup.com.

A Comparison of Coverage Restrictions for Biopharmaceuticals and Medical Procedures.

PubMed

Chambers, James; Pope, Elle; Bungay, Kathy; Cohen, Joshua; Ciarametaro, Michael; Dubois, Robert; Neumann, Peter J

2018-04-01

Differences in payer evaluation and coverage of pharmaceuticals and medical procedures suggest that coverage may differ for medications and procedures independent of their clinical benefit. We hypothesized that coverage for medications is more restricted than corresponding coverage for nonmedication interventions. We included top-selling medications and highly utilized procedures. For each intervention-indication pair, we classified value in terms of cost-effectiveness (incremental cost per quality-adjusted life-year), as reported by the Tufts Medical Center Cost-Effectiveness Analysis Registry. For each intervention-indication pair and for each of 10 large payers, we classified coverage, when available, as either "more restrictive" or as "not more restrictive," compared with a benchmark. The benchmark reflected the US Food and Drug Administration label information, when available, or pertinent clinical guidelines. We compared coverage policies and the benchmark in terms of step edits and clinical restrictions. Finally, we regressed coverage restrictiveness against intervention type (medication or nonmedication), controlling for value (cost-effectiveness more or less favorable than a designated threshold). We identified 392 medication and 185 procedure coverage decisions. A total of 26.3% of the medication coverage and 38.4% of the procedure coverage decisions were more restrictive than their corresponding benchmarks. After controlling for value, the odds of being more restrictive were 42% lower for medications than for procedures. Including unfavorable tier placement in the definition of "more restrictive" greatly increased the proportion of medication coverage decisions classified as "more restrictive" and reversed our findings. Therapy access depends on factors other than cost and clinical benefit, suggesting potential health care system inefficiency. Copyright © 2018 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by

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

PubMed

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.

A software tool for automatic classification and segmentation of 2D/3D medical images

NASA Astrophysics Data System (ADS)

Strzelecki, Michal; Szczypinski, Piotr; Materka, Andrzej; Klepaczko, Artur

2013-02-01

Modern medical diagnosis utilizes techniques of visualization of human internal organs (CT, MRI) or of its metabolism (PET). However, evaluation of acquired images made by human experts is usually subjective and qualitative only. Quantitative analysis of MR data, including tissue classification and segmentation, is necessary to perform e.g. attenuation compensation, motion detection, and correction of partial volume effect in PET images, acquired with PET/MR scanners. This article presents briefly a MaZda software package, which supports 2D and 3D medical image analysis aiming at quantification of image texture. MaZda implements procedures for evaluation, selection and extraction of highly discriminative texture attributes combined with various classification, visualization and segmentation tools. Examples of MaZda application in medical studies are also provided.

Hierarchical and successive approximate registration of the non-rigid medical image based on thin-plate splines

NASA Astrophysics Data System (ADS)

Hu, Jinyan; Li, Li; Yang, Yunfeng

2017-06-01

The hierarchical and successive approximate registration method of non-rigid medical image based on the thin-plate splines is proposed in the paper. There are two major novelties in the proposed method. First, the hierarchical registration based on Wavelet transform is used. The approximate image of Wavelet transform is selected as the registered object. Second, the successive approximation registration method is used to accomplish the non-rigid medical images registration, i.e. the local regions of the couple images are registered roughly based on the thin-plate splines, then, the current rough registration result is selected as the object to be registered in the following registration procedure. Experiments show that the proposed method is effective in the registration process of the non-rigid medical images.

Compressive sensing in medical imaging

PubMed Central

Graff, Christian G.; Sidky, Emil Y.

2015-01-01

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. PMID:25968400

12 CFR 261a.7 - Special procedures for medical records.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 12 Banks and Banking 3 2010-01-01 2010-01-01 false Special procedures for medical records. 261a.7... Requests by Individual to Whom Record Pertains § 261a.7 Special procedures for medical records. Medical or... physician, have an adverse effect upon the requester. Upon such determination, the information shall be...

18 CFR 1301.16 - Special procedures-medical records.

Code of Federal Regulations, 2010 CFR

2010-04-01

...-medical records. 1301.16 Section 1301.16 Conservation of Power and Water Resources TENNESSEE VALLEY AUTHORITY PROCEDURES Privacy Act § 1301.16 Special procedures—medical records. If, in the judgment of TVA, the transmission of medical records, including psychological records, directly to a requesting...

[PTSD in young children after medical procedure].

PubMed

Sepers, J W; van der Boon, N; Landsmeer-Beker, N E A

2016-01-01

An eight-year-old boy with spastic type bilateral cerebral palsy and a two-year-old girl with biliary atresia were referred to a psycho-trauma centre. Both children developed post-traumatic stress disorder (PTSD) symptoms as a result of the medical procedure. Because of their symptoms, they were resisting further medical treatment. The children were given trauma-focused treatment (eye movement and desensitisation reprocessing and cognitive behavioural therapy). This article argues that hypnosis and distraction can play a role in preventing PTSD symptoms after undergoing a medical procedure. If PTSD is unavoidable, it is important to recognise the symptoms and to treat these children. Furthermore, their parents might also be traumatised. PTSD symptoms in children and their parents can be successfully treated. Also children with sub-threshold PTSD can benefit from trauma treatment.

Machine Learning for Medical Imaging

PubMed Central

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

2017-01-01

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

Machine Learning for Medical Imaging.

PubMed

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.

Novel Algorithm for Classification of Medical Images

NASA Astrophysics Data System (ADS)

Bhushan, Bharat; Juneja, Monika

2010-11-01

Content-based image retrieval (CBIR) methods in medical image databases have been designed to support specific tasks, such as retrieval of medical images. These methods cannot be transferred to other medical applications since different imaging modalities require different types of processing. To enable content-based queries in diverse collections of medical images, the retrieval system must be familiar with the current Image class prior to the query processing. Further, almost all of them deal with the DICOM imaging format. In this paper a novel algorithm based on energy information obtained from wavelet transform for the classification of medical images according to their modalities is described. For this two types of wavelets have been used and have been shown that energy obtained in either case is quite distinct for each of the body part. This technique can be successfully applied to different image formats. The results are shown for JPEG imaging format.

Policies and Procedures for Reviewing Medical Images From Portable Media: Survey of Radiology Departments

PubMed Central

Kalia, Vivek; Carrino, John A.; Macura, Katarzyna J.

2015-01-01

Purpose The purpose of this study was to survey current practices for portable media (CDs and DVDs) use for medical imaging in both academic and nonacademic radiology departments in the United States. Methods This survey was a stratified, nonrandom sample, 22-question electronic survey, using SurveyMonkey, of members of the Association of Administrators in Academic Radiology, the Association for Medical Imaging Management, and the University HealthSystem Consortium, conducted in November 2009. Questions were grouped by media production and media viewing practices. Results One hundred and two individual responses to the survey were received. Ninety-eight percent of respondents said that their institutions produced Digital Imaging and Communications in Medicine (DICOM)-compliant media, with only 2.0% uncertain. Only 22.2% of respondents claimed that their institutions produced Integrating the Healthcare Enterprise (IHE) Portable Data for Imaging (PDI)-compliant media, while 71.6% were uncertain. Rates of DICOM and IHE PDI compliance did not differ between academic and nonacademic centers. As for testing digital media produced at the institutions for DICOM and IHE PDI compliance, only 16.0% of respondents’ institutions routinely did so. Conclusions Three main problem areas regarding portable media became evident from this study: (1) access, (2) importability, and (3) viewing issues, and problems with any of the 3 can delay patient care. Noncompliance and a lack of knowledge about compliance were found to be major issues in the present study, more so for IHE PDI than for DICOM, and there is much room for improvement. Recommendations include that radiology practices should routinely generate only media compliant with DICOM and IHE PDI and should test for compliance. PMID:21211763

The impact of a medical procedure service on patient safety, procedure quality and resident training opportunities.

PubMed

Tukey, Melissa H; Wiener, Renda Soylemez

2014-03-01

At some academic hospitals, medical procedure services are being developed to provide supervision for residents performing bedside procedures in hopes of improving patient safety and resident education. There is limited knowledge of the impact of such services on procedural complication rates and resident procedural training opportunities. To determine the impact of a medical procedure service (MPS) on patient safety and resident procedural training opportunities. Retrospective cohort analysis comparing characteristics and outcomes of procedures performed by the MPS versus the primary medical service. Consecutive adults admitted to internal medicine services at a large academic hospital who underwent a bedside medical procedure (central venous catheterization, thoracentesis, paracentesis, lumbar puncture) between 1 July 2010 and 31 December 2011. The primary outcome was a composite rate of major complications. Secondary outcomes included resident participation in bedside procedures and use of "best practice" safety process measures. We evaluated 1,707 bedside procedures (548 by the MPS, 1,159 by the primary services). There were no differences in the composite rate of major complications (1.6 % vs. 1.9 %, p = 0.71) or resident participation in bedside procedures (57.0 % vs. 54.3 %, p = 0.31) between the MPS and the primary services. Procedures performed by the MPS were more likely to be successfully completed (95.8 % vs. 92.8 %, p = 0.02) and to use best practice safety process measures, including use of ultrasound guidance when appropriate (96.8 % vs. 90.0 %, p = 0.0004), avoidance of femoral venous catheterization (89.5 vs. 82.7 %, p = 0.02) and involvement of attending physicians (99.3 % vs. 57.0 %, p < 0.0001). Although use of a MPS did not significantly affect the rate of major complications or resident opportunities for training in bedside procedures, it was associated with increased use of best practice safety process measures.

The algorithm stitching for medical imaging

NASA Astrophysics Data System (ADS)

Semenishchev, E.; Marchuk, V.; Voronin, V.; Pismenskova, M.; Tolstova, I.; Svirin, I.

2016-05-01

In this paper we propose a stitching algorithm of medical images into one. The algorithm is designed to stitching the medical x-ray imaging, biological particles in microscopic images, medical microscopic images and other. Such image can improve the diagnosis accuracy and quality for minimally invasive studies (e.g., laparoscopy, ophthalmology and other). The proposed algorithm is based on the following steps: the searching and selection areas with overlap boundaries; the keypoint and feature detection; the preliminary stitching images and transformation to reduce the visible distortion; the search a single unified borders in overlap area; brightness, contrast and white balance converting; the superimposition into a one image. Experimental results demonstrate the effectiveness of the proposed method in the task of image stitching.

Medical imaging systems

DOEpatents

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.

Medical Tourism: The Trend toward Outsourcing Medical Procedures to Foreign Countries

ERIC Educational Resources Information Center

York, Diane

2008-01-01

The rising costs of medical treatment in the United States are fueling a movement to outsource medical treatment. Estimates of the number of Americans traveling overseas for treatment range from 50,000 to 500,000. Charges for common procedures such as heart bypass can be $11,000 in Thailand compared to $130,000 in the United States. Knee…

Virtual medicine: Utilization of the advanced cardiac imaging patient avatar for procedural planning and facilitation.

PubMed

Shinbane, Jerold S; Saxon, Leslie A

Advances in imaging technology have led to a paradigm shift from planning of cardiovascular procedures and surgeries requiring the actual patient in a "brick and mortar" hospital to utilization of the digitalized patient in the virtual hospital. Cardiovascular computed tomographic angiography (CCTA) and cardiovascular magnetic resonance (CMR) digitalized 3-D patient representation of individual patient anatomy and physiology serves as an avatar allowing for virtual delineation of the most optimal approaches to cardiovascular procedures and surgeries prior to actual hospitalization. Pre-hospitalization reconstruction and analysis of anatomy and pathophysiology previously only accessible during the actual procedure could potentially limit the intrinsic risks related to time in the operating room, cardiac procedural laboratory and overall hospital environment. Although applications are specific to areas of cardiovascular specialty focus, there are unifying themes related to the utilization of technologies. The virtual patient avatar computer can also be used for procedural planning, computational modeling of anatomy, simulation of predicted therapeutic result, printing of 3-D models, and augmentation of real time procedural performance. Examples of the above techniques are at various stages of development for application to the spectrum of cardiovascular disease processes, including percutaneous, surgical and hybrid minimally invasive interventions. A multidisciplinary approach within medicine and engineering is necessary for creation of robust algorithms for maximal utilization of the virtual patient avatar in the digital medical center. Utilization of the virtual advanced cardiac imaging patient avatar will play an important role in the virtual health care system. Although there has been a rapid proliferation of early data, advanced imaging applications require further assessment and validation of accuracy, reproducibility, standardization, safety, efficacy, quality

32 CFR 1701.13 - Special procedures for medical/psychiatric/psychological records.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 32 National Defense 6 2010-07-01 2010-07-01 false Special procedures for medical/psychiatric... procedures for medical/psychiatric/psychological records. Current and former ODNI employees, including... access to their medical, psychiatric or psychological testing records by writing to: Information and...

Nanotechnology-supported THz medical imaging

PubMed Central

Stylianou, Andreas; Talias, Michael A

2013-01-01

Over the last few decades, the achievements and progress in the field of medical imaging have dramatically enhanced the early detection and treatment of many pathological conditions. The development of new imaging modalities, especially non-ionising ones, which will improve prognosis, is of crucial importance. A number of novel imaging modalities have been developed but they are still in the initial stages of development and serious drawbacks obstruct them from offering their benefits to the medical field. In the 21 st century, it is believed that nanotechnology will highly influence our everyday life and dramatically change the world of medicine, including medical imaging. Here we discuss how nanotechnology, which is still in its infancy, can improve Terahertz (THz) imaging, an emerging imaging modality, and how it may find its way into real clinical applications. THz imaging is characterised by the use of non-ionising radiation and although it has the potential to be used in many biomedical fields, it remains in the field of basic research. An extensive review of the recent available literature shows how the current state of this emerging imaging modality can be transformed by nanotechnology. Innovative scientific concepts that use nanotechnology-based techniques to overcome some of the limitations of the use of THz imaging are discussed. We review a number of drawbacks, such as a low contrast mechanism, poor source performance and bulky THz systems, which characterise present THz medical imaging and suggest how they can be overcome through nanotechnology. Better resolution and higher detection sensitivity can also be achieved using nanotechnology techniques. PMID:24555052

Medical imaging dose optimisation from ground up: expert opinion of an international summit.

PubMed

Samei, Ehsan; Järvinen, Hannu; Kortesniemi, Mika; Simantirakis, George; Goh, Charles; Wallace, Anthony; Vano, Eliseo; Bejan, Adrian; Rehani, Madan; Vassileva, Jenia

2018-05-17

As in any medical intervention, there is either a known or an anticipated benefit to the patient from undergoing a medical imaging procedure. This benefit is generally significant, as demonstrated by the manner in which medical imaging has transformed clinical medicine. At the same time, when it comes to imaging that deploys ionising radiation, there is a potential associated risk from radiation. Radiation risk has been recognised as a key liability in the practice of medical imaging, creating a motivation for radiation dose optimisation. The level of radiation dose and risk in imaging varies but is generally low. Thus, from the epidemiological perspective, this makes the estimation of the precise level of associated risk highly uncertain. However, in spite of the low magnitude and high uncertainty of this risk, its possibility cannot easily be refuted. Therefore, given the moral obligation of healthcare providers, 'first, do no harm,' there is an ethical obligation to mitigate this risk. Precisely how to achieve this goal scientifically and practically within a coherent system has been an open question. To address this need, in 2016, the International Atomic Energy Agency (IAEA) organised a summit to clarify the role of Diagnostic Reference Levels to optimise imaging dose, summarised into an initial report (Järvinen et al 2017 Journal of Medical Imaging 4 031214). Through a consensus building exercise, the summit further concluded that the imaging optimisation goal goes beyond dose alone, and should include image quality as a means to include both the benefit and the safety of the exam. The present, second report details the deliberation of the summit on imaging optimisation.

Medical image archive node simulation and architecture

NASA Astrophysics Data System (ADS)

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

Flat-panel cone-beam CT: a novel imaging technology for image-guided procedures

NASA Astrophysics Data System (ADS)

Siewerdsen, Jeffrey H.; Jaffray, David A.; Edmundson, Gregory K.; Sanders, W. P.; Wong, John W.; Martinez, Alvaro A.

2001-05-01

The use of flat-panel imagers for cone-beam CT signals the emergence of an attractive technology for volumetric imaging. Recent investigations demonstrate volume images with high spatial resolution and soft-tissue visibility and point to a number of logistical characteristics (e.g., open geometry, volume acquisition in a single rotation about the patient, and separation of the imaging and patient support structures) that are attractive to a broad spectrum of applications. Considering application to image-guided (IG) procedures - specifically IG therapies - this paper examines the performance of flat-panel cone-beam CT in relation to numerous constraints and requirements, including time (i.e., speed of image acquisition), dose, and field-of-view. The imaging and guidance performance of a prototype flat panel cone-beam CT system is investigated through the construction of procedure-specific tasks that test the influence of image artifacts (e.g., x-ray scatter and beam-hardening) and volumetric imaging performance (e.g., 3D spatial resolution, noise, and contrast) - taking two specific examples in IG brachytherapy and IG vertebroplasty. For IG brachytherapy, a procedure-specific task is constructed which tests the performance of flat-panel cone-beam CT in measuring the volumetric distribution of Pd-103 permanent implant seeds in relation to neighboring bone and soft-tissue structures in a pelvis phantom. For IG interventional procedures, a procedure-specific task is constructed in the context of vertebroplasty performed on a cadaverized ovine spine, demonstrating the volumetric image quality in pre-, intra-, and post-therapeutic images of the region of interest and testing the performance of the system in measuring the volumetric distribution of bone cement (PMMA) relative to surrounding spinal anatomy. Each of these tasks highlights numerous promising and challenging aspects of flat-panel cone-beam CT applied to IG procedures.

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

PubMed

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

Mobile medical image retrieval

NASA Astrophysics Data System (ADS)

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

21 CFR 892.2020 - Medical image communications device.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 21 Food and Drugs 8 2013-04-01 2013-04-01 false Medical image communications device. 892.2020... (CONTINUED) MEDICAL DEVICES RADIOLOGY DEVICES Diagnostic Devices § 892.2020 Medical image communications device. (a) Identification. A medical image communications device provides electronic transfer of medical...

21 CFR 892.2020 - Medical image communications device.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 8 2011-04-01 2011-04-01 false Medical image communications device. 892.2020... (CONTINUED) MEDICAL DEVICES RADIOLOGY DEVICES Diagnostic Devices § 892.2020 Medical image communications device. (a) Identification. A medical image communications device provides electronic transfer of medical...

21 CFR 892.2020 - Medical image communications device.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 21 Food and Drugs 8 2012-04-01 2012-04-01 false Medical image communications device. 892.2020... (CONTINUED) MEDICAL DEVICES RADIOLOGY DEVICES Diagnostic Devices § 892.2020 Medical image communications device. (a) Identification. A medical image communications device provides electronic transfer of medical...

21 CFR 892.2020 - Medical image communications device.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 21 Food and Drugs 8 2014-04-01 2014-04-01 false Medical image communications device. 892.2020... (CONTINUED) MEDICAL DEVICES RADIOLOGY DEVICES Diagnostic Devices § 892.2020 Medical image communications device. (a) Identification. A medical image communications device provides electronic transfer of medical...

Architecture of distributed picture archiving and communication systems for storing and processing high resolution medical images

NASA Astrophysics Data System (ADS)

Tokareva, Victoria

2018-04-01

New generation medicine demands a better quality of analysis increasing the amount of data collected during checkups, and simultaneously decreasing the invasiveness of a procedure. Thus it becomes urgent not only to develop advanced modern hardware, but also to implement special software infrastructure for using it in everyday clinical practice, so-called Picture Archiving and Communication Systems (PACS). Developing distributed PACS is a challenging task for nowadays medical informatics. The paper discusses the architecture of distributed PACS server for processing large high-quality medical images, with respect to technical specifications of modern medical imaging hardware, as well as international standards in medical imaging software. The MapReduce paradigm is proposed for image reconstruction by server, and the details of utilizing the Hadoop framework for this task are being discussed in order to provide the design of distributed PACS as ergonomic and adapted to the needs of end users as possible.

Medical hyperspectral imaging: a review

PubMed Central

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

Costing imaging procedures.

PubMed

Bretland, P M

1988-01-01

The existing National Health Service financial system makes comprehensive costing of any service very difficult. A method of costing using modern commercial methods has been devised, classifying costs into variable, semi-variable and fixed and using the principle of overhead absorption for expenditure not readily allocated to individual procedures. It proved possible to establish a cost spectrum over the financial year 1984-85. The cheapest examinations were plain radiographs outside normal working hours, followed by plain radiographs, ultrasound, special procedures, fluoroscopy, nuclear medicine, angiography and angiographic interventional procedures in normal working hours. This differs from some published figures, particularly those in the Körner report. There was some overlap between fluoroscopic interventional and the cheaper nuclear medicine procedures, and between some of the more expensive nuclear medicine procedures and the cheaper angiographic ones. Only angiographic and the few more expensive nuclear medicine procedures exceed the cost of the inpatient day. The total cost of the imaging service to the district was about 4% of total hospital expenditure. It is shown that where more procedures are undertaken, the semi-variable and fixed (including capital) elements of the cost decrease (and vice versa) so that careful study is required to assess the value of proposed economies. The method is initially time-consuming and requires a computer system with 512 Kb of memory, but once the basic costing system is established in a department, detailed financial monitoring should become practicable. The necessity for a standard comprehensive costing procedure of this nature, based on sound cost accounting principles, appears inescapable, particularly in view of its potential application to management budgeting.

DICOM: a standard for medical imaging

NASA Astrophysics Data System (ADS)

Horii, Steven C.; Bidgood, W. Dean

1993-01-01

Since 1983, the American College of Radiology (ACR) and the National Electrical Manufacturers Association (NEMA) have been engaged in developing standards related to medical imaging. This alliance of users and manufacturers was formed to meet the needs of the medical imaging community as its use of digital imaging technology increased. The development of electronic picture archiving and communications systems (PACS), which could connect a number of medical imaging devices together in a network, led to the need for a standard interface and data structure for use on imaging equipment. Since medical image files tend to be very large and include much text information along with the image, the need for a fast, flexible, and extensible standard was quickly established. The ACR-NEMA Digital Imaging and Communications Standards Committee developed a standard which met these needs. The standard (ACR-NEMA 300-1988) was first published in 1985 and revised in 1988. It is increasingly available from equipment manufacturers. The current work of the ACR- NEMA Committee has been to extend the standard to incorporate direct network connection features, and build on standards work done by the International Standards Organization in its Open Systems Interconnection series. This new standard, called Digital Imaging and Communication in Medicine (DICOM), follows an object-oriented design methodology and makes use of as many existing internationally accepted standards as possible. This paper gives a brief overview of the requirements for communications standards in medical imaging, a history of the ACR-NEMA effort and what it has produced, and a description of the DICOM standard.

Radiation Exposure from Medical Exams and Procedures

MedlinePlus

Fact Sheet Adopted: January 2010 Health Physics Society Specialists in Radiation Safety Radiation Exposure from Medical Exams and Procedures Ionizing radiation is used daily in hospitals and clinics ...

21 CFR 892.2040 - Medical image hardcopy device.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 8 2011-04-01 2011-04-01 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...

21 CFR 892.2040 - Medical image hardcopy device.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 21 Food and Drugs 8 2014-04-01 2014-04-01 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...

21 CFR 892.2040 - Medical image hardcopy device.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 21 Food and Drugs 8 2012-04-01 2012-04-01 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...

21 CFR 892.2040 - Medical image hardcopy device.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 21 Food and Drugs 8 2013-04-01 2013-04-01 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...

Stereoscopic medical imaging collaboration system

NASA Astrophysics Data System (ADS)

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.

BIRAM: a content-based image retrieval framework for medical images

NASA Astrophysics Data System (ADS)

Moreno, Ramon A.; Furuie, Sergio S.

2006-03-01

In the medical field, digital images are becoming more and more important for diagnostics and therapy of the patients. At the same time, the development of new technologies has increased the amount of image data produced in a hospital. This creates a demand for access methods that offer more than text-based queries for retrieval of the information. In this paper is proposed a framework for the retrieval of medical images that allows the use of different algorithms for the search of medical images by similarity. The framework also enables the search for textual information from an associated medical report and DICOM header information. The proposed system can be used for support of clinical decision making and is intended to be integrated with an open source picture, archiving and communication systems (PACS). The BIRAM has the following advantages: (i) Can receive several types of algorithms for image similarity search; (ii) Allows the codification of the report according to a medical dictionary, improving the indexing of the information and retrieval; (iii) The algorithms can be selectively applied to images with the appropriated characteristics, for instance, only in magnetic resonance images. The framework was implemented in Java language using a MS Access 97 database. The proposed framework can still be improved, by the use of regions of interest (ROI), indexing with slim-trees and integration with a PACS Server.

Reducing noise component on medical images

NASA Astrophysics Data System (ADS)

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.

21 CFR 892.2010 - Medical image storage device.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 21 Food and Drugs 8 2013-04-01 2013-04-01 false Medical image storage device. 892.2010 Section 892...) MEDICAL DEVICES RADIOLOGY DEVICES Diagnostic Devices § 892.2010 Medical image storage device. (a) Identification. A medical image storage device is a device that provides electronic storage and retrieval...

21 CFR 892.2010 - Medical image storage device.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 8 2011-04-01 2011-04-01 false Medical image storage device. 892.2010 Section 892...) MEDICAL DEVICES RADIOLOGY DEVICES Diagnostic Devices § 892.2010 Medical image storage device. (a) Identification. A medical image storage device is a device that provides electronic storage and retrieval...

21 CFR 892.2010 - Medical image storage device.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 21 Food and Drugs 8 2014-04-01 2014-04-01 false Medical image storage device. 892.2010 Section 892...) MEDICAL DEVICES RADIOLOGY DEVICES Diagnostic Devices § 892.2010 Medical image storage device. (a) Identification. A medical image storage device is a device that provides electronic storage and retrieval...

21 CFR 892.2010 - Medical image storage device.

Code of Federal Regulations, 2010 CFR

2010-04-01

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

21 CFR 892.2010 - Medical image storage device.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 21 Food and Drugs 8 2012-04-01 2012-04-01 false Medical image storage device. 892.2010 Section 892...) MEDICAL DEVICES RADIOLOGY DEVICES Diagnostic Devices § 892.2010 Medical image storage device. (a) Identification. A medical image storage device is a device that provides electronic storage and retrieval...

Medical Image Analysis by Cognitive Information Systems - a Review.

PubMed

Ogiela, Lidia; Takizawa, Makoto

2016-10-01

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

Overview of deep learning in medical imaging.

PubMed

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

Medical imaging, PACS, and imaging informatics: retrospective.

PubMed

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

Viewpoints on Medical Image Processing: From Science to Application

PubMed Central

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

Viewpoints on Medical Image Processing: From Science to Application.

PubMed

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.

A study for watermark methods appropriate to medical images.

PubMed

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

2001-06-01

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

Image 100 procedures manual development: Applications system library definition and Image 100 software definition

NASA Technical Reports Server (NTRS)

Guseman, L. F., Jr.; Decell, H. P., Jr.

1975-01-01

An outline for an Image 100 procedures manual for Earth Resources Program image analysis was developed which sets forth guidelines that provide a basis for the preparation and updating of an Image 100 Procedures Manual. The scope of the outline was limited to definition of general features of a procedures manual together with special features of an interactive system. Computer programs were identified which should be implemented as part of an applications oriented library for the system.

Is it possible to eliminate patient identification errors in medical imaging?

PubMed

Danaher, Luke A; Howells, Joan; Holmes, Penny; Scally, Peter

2011-08-01

The aim of this article is to review a system that validates and documents the process of ensuring the correct patient, correct site and side, and correct procedure (commonly referred to as the 3 C's) within medical imaging. A 4-step patient identification and procedure matching process was developed using health care and aviation models. The process was established in medical imaging departments after a successful interventional radiology pilot program. The success of the project was evaluated using compliance audit data, incident reporting data before and after the implementation of the process, and a staff satisfaction survey. There was 95% to 100% verification of site and side and 100% verification of correct patient, procedure, and consent. Correct patient data and side markers were present in 82% to 95% of cases. The number of incidents before and after the implementation of the 3 C's was difficult to assess because of a change in reporting systems and incident underreporting. More incidents are being reported, particularly "near misses." All near misses were related to incorrect patient identification stickers being placed on request forms. The majority of staff members surveyed found the process easy (55.8%), quick (47.7%), relevant (51.7%), and useful (60.9%). Although identification error is difficult to eliminate, practical initiatives can engender significant systems improvement in complex health care environments. Crown Copyright © 2011. Published by Elsevier Inc. All rights reserved.

Awareness of radiation protection and dose levels of imaging procedures among medical students, radiography students, and radiology residents at an academic hospital: Results of a comprehensive survey.

PubMed

Faggioni, Lorenzo; Paolicchi, Fabio; Bastiani, Luca; Guido, Davide; Caramella, Davide

2017-01-01

To evaluate the awareness of radiation protection issues and the knowledge of dose levels of imaging procedures among medical students, radiology residents, and radiography students at an academic hospital. A total of 159 young doctors and students (including 60 radiology residents, 56 medical students, and 43 radiography students) were issued a questionnaire consisting of 16 multiple choice questions divided into three separated sections (i.e., demographic data, awareness about radiation protection issues, and knowledge about radiation dose levels of common radiological examinations). Medical students claimed to have at least a good knowledge of radiation protection issues more frequently than radiology residents and radiography students (94.4% vs 55% and 35.7%, respectively; P<0.05), with no cases of perceived excellent knowledge among radiography students. However, the actual knowledge of essential radiation protection topics such as regulations, patient and tissue susceptibility to radiation damage, professional radiation risk and dose optimisation, as well as of radiation doses delivered by common radiological procedures was significantly worse among medical students than radiology residents and radiography students (P<0.05). Those latter significantly outperformed radiology residents as to knowledge of radiation protection issues (P<0.01). Overall, less than 50% of survey respondents correctly answered all questions of the survey. Radiology residents, radiography students and medical students have a limited awareness about radiation protection, with a specific gap of knowledge concerning real radiation doses of daily radiological examinations. Both undergraduate and postgraduate teaching needs to be effectively implemented with radiation safety courses. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Lossless medical image compression with a hybrid coder

NASA Astrophysics Data System (ADS)

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.

Crypto-Watermarking of Transmitted Medical Images.

PubMed

Al-Haj, Ali; Mohammad, Ahmad; Amer, Alaa'

2017-02-01

Telemedicine is a booming healthcare practice that has facilitated the exchange of medical data and expertise between healthcare entities. However, the widespread use of telemedicine applications requires a secured scheme to guarantee confidentiality and verify authenticity and integrity of exchanged medical data. In this paper, we describe a region-based, crypto-watermarking algorithm capable of providing confidentiality, authenticity, and integrity for medical images of different modalities. The proposed algorithm provides authenticity by embedding robust watermarks in images' region of non-interest using SVD in the DWT domain. Integrity is provided in two levels: strict integrity implemented by a cryptographic hash watermark, and content-based integrity implemented by a symmetric encryption-based tamper localization scheme. Confidentiality is achieved as a byproduct of hiding patient's data in the image. Performance of the algorithm was evaluated with respect to imperceptibility, robustness, capacity, and tamper localization, using different medical images. The results showed the effectiveness of the algorithm in providing security for telemedicine applications.

Analysis of utilization patterns and associated costs of the breast imaging and diagnostic procedures after screening mammography.

PubMed

Vlahiotis, Anna; Griffin, Brian; Stavros, A Thomas; Margolis, Jay

2018-01-01

Little data exist on real-world patterns and associated costs of downstream breast diagnostic procedures following an abnormal screening mammography or clinical exam. To analyze the utilization patterns in real-world clinical settings for breast imaging and diagnostic procedures, including the frequency and volume of patients and procedures, procedure sequencing, and associated health care expenditures. Using medical claims from 2011 to 2015 MarketScan Commercial and Medicare Databases, adult females with breast imaging/diagnostic procedures (diagnostic mammography, ultrasound, molecular breast imaging, tomosynthesis, magnetic resonance imaging, or biopsy) other than screening mammography were selected. Continuous health plan coverage without breast diagnostic procedures was required for ≥13 months before the first found breast diagnostic procedure (index event), with a 13-month post-index follow-up period. Key outcomes included diagnostic procedure volumes, sequences, and payments. Results reported descriptively were projected to provide US national patient and procedure volumes. The final sample of 875,526 patients was nationally projected to 12,394,432 patients annually receiving 8,732,909 diagnostic mammograms (53.3% of patients), 6,987,399 breast ultrasounds (42.4% of patients), and 1,585,856 biopsies (10.3% of patients). Following initial diagnostic procedures, 49.4% had second procedures, 20.1% followed with third procedures, and 10.0% had a fourth procedure. Mean (SD) costs for diagnostic mammograms of US$349 ($493), ultrasounds US$132 ($134), and biopsies US$1,938 ($2,343) contributed US$3.05 billion, US$0.92 billion, and US$3.07 billion, respectively, to annual diagnostic breast expenditures estimated at US$7.91 billion. The volume and expense of additional breast diagnostic testing, estimated at US$7.91 billion annually, underscores the need for technological improvements in the breast diagnostic landscape.

Medical image informatics infrastructure design and applications.

PubMed

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.

Deep Learning in Medical Image Analysis

PubMed Central

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

2016-01-01

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

Computational medical imaging and hemodynamics framework for functional analysis and assessment of cardiovascular structures.

PubMed

Wong, Kelvin K L; Wang, Defeng; Ko, Jacky K L; Mazumdar, Jagannath; Le, Thu-Thao; Ghista, Dhanjoo

2017-03-21

Cardiac dysfunction constitutes common cardiovascular health issues in the society, and has been an investigation topic of strong focus by researchers in the medical imaging community. Diagnostic modalities based on echocardiography, magnetic resonance imaging, chest radiography and computed tomography are common techniques that provide cardiovascular structural information to diagnose heart defects. However, functional information of cardiovascular flow, which can in fact be used to support the diagnosis of many cardiovascular diseases with a myriad of hemodynamics performance indicators, remains unexplored to its full potential. Some of these indicators constitute important cardiac functional parameters affecting the cardiovascular abnormalities. With the advancement of computer technology that facilitates high speed computational fluid dynamics, the realization of a support diagnostic platform of hemodynamics quantification and analysis can be achieved. This article reviews the state-of-the-art medical imaging and high fidelity multi-physics computational analyses that together enable reconstruction of cardiovascular structures and hemodynamic flow patterns within them, such as of the left ventricle (LV) and carotid bifurcations. The combined medical imaging and hemodynamic analysis enables us to study the mechanisms of cardiovascular disease-causing dysfunctions, such as how (1) cardiomyopathy causes left ventricular remodeling and loss of contractility leading to heart failure, and (2) modeling of LV construction and simulation of intra-LV hemodynamics can enable us to determine the optimum procedure of surgical ventriculation to restore its contractility and health This combined medical imaging and hemodynamics framework can potentially extend medical knowledge of cardiovascular defects and associated hemodynamic behavior and their surgical restoration, by means of an integrated medical image diagnostics and hemodynamic performance analysis framework.

Detection of immune-related adverse events by medical imaging in patients treated with anti-programmed cell death 1.

PubMed

Mekki, Ahmed; Dercle, Laurent; Lichtenstein, Philip; Marabelle, Aurélien; Michot, Jean-Marie; Lambotte, Olivier; Le Pavec, Jérôme; De Martin, Eleonora; Balleyguier, Corinne; Champiat, Stéphane; Ammari, Samy

2018-06-01

Programmed death receptor-1 blocking antibodies (anti-PD1) are a new standard of care in many cancer types. Patients benefit from improved survival but have the risk of immune-related adverse events (irAE). We evaluated if medical imaging procedures, used for anti-tumour response assessment, can detect irAEs. All consecutive patients treated with anti-PD1 and with a medical imaging acquisition performed within 2 weeks with irAEs ≥2 were retrospectively included. Data were gathered from June 2014 to February 2017, and a central review was performed. The primary and secondary end-points were i) to evaluate the overall detection rate of irAEs by medical imaging and ii) to provide a comprehensive radiological description of irAEs. Fifty-three patients (31 women, 22 men; average age: 61 years) were included. The primary tumour was melanoma (n = 32), lung cancer (n = 18) and other (n = 3). Patients were treated with nivolumab (n = 27) or pembrolizumab (n = 26). Of 74 medical imaging procedures analysed (ratio = 1.4 medical imaging per patient), 55 irAE were detected. The detection rate was overall: 74% (95 confidence interval: 63-84%), positron emission tomography with 18F-fludeoxyglucose integrated with computed tomography (18F-FDG PET/CT): 83% (n = 10/12), magnetic resonance imaging: 83% (n = 5/6), computed tomography scan: 79% (n = 19/24), ultrasonography: 70% (n = 19/27), standard X-rays: 40% (n = 2/5), lung/mediastinum: 100% (n = 7/7), enterocolitis: 100% (n = 8/8), hypophysitis: 100% (n = 3/3), thyroiditis: 75% (n = 15/20), hepatitis: 67% (n = 2/3), arthralgia or arthritis: 40% (n = 2/5) and pancreas: 28% (n = 2/7). Medical imaging detected 74% of irAE in patients treated with anti-PD1. Beyond response assessment, medical imaging can detect irAE and guide towards specific management. We described the most frequent sites and patterns of imaging findings. Copyright © 2018 Elsevier Ltd. All rights reserved.

Semi-automatic medical image segmentation with adaptive local statistics in Conditional Random Fields framework.

PubMed

Hu, Yu-Chi J; Grossberg, Michael D; Mageras, Gikas S

2008-01-01

Planning radiotherapy and surgical procedures usually require onerous manual segmentation of anatomical structures from medical images. In this paper we present a semi-automatic and accurate segmentation method to dramatically reduce the time and effort required of expert users. This is accomplished by giving a user an intuitive graphical interface to indicate samples of target and non-target tissue by loosely drawing a few brush strokes on the image. We use these brush strokes to provide the statistical input for a Conditional Random Field (CRF) based segmentation. Since we extract purely statistical information from the user input, we eliminate the need of assumptions on boundary contrast previously used by many other methods, A new feature of our method is that the statistics on one image can be reused on related images without registration. To demonstrate this, we show that boundary statistics provided on a few 2D slices of volumetric medical data, can be propagated through the entire 3D stack of images without using the geometric correspondence between images. In addition, the image segmentation from the CRF can be formulated as a minimum s-t graph cut problem which has a solution that is both globally optimal and fast. The combination of a fast segmentation and minimal user input that is reusable, make this a powerful technique for the segmentation of medical images.

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

PubMed

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.

Deep Learning in Medical Image Analysis.

PubMed

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.

The Orthanc Ecosystem for Medical Imaging.

PubMed

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.

A hierarchical SVG image abstraction layer for medical imaging

NASA Astrophysics Data System (ADS)

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.

Thirty-day emergency room visits and hospital admissions after outpatient non-vascular image-guided procedures.

PubMed

Nguyen, Quang; Mehta, Sahil V; Fang, Jieming; Sheiman, Robert; Kane, Robert; Ahmed, Muneeb; Sarwar, Ammar; Siewert, Bettina; Brook, Olga R

2017-10-01

To evaluate the rate of post-procedure emergency department (ED) visits and hospital admissions following outpatient non-vascular image-guided interventions performed under moderate sedation and to identify common and preventable causes of emergency department visits and hospital admissions. Institutional review board approval was acquired for this HIPAA-compliant retrospective study with waiver of informed consent. 1426 consecutive patients undergoing 1512 outpatient image-guided procedures under moderate sedation from November 2012 to August 2014 were included. The average patient age was 57.2 ± 15.2 years, and 602 (42%) patients were women. Major procedure categories included ultrasound-guided liver biopsies, ultrasound-guided kidney biopsies, and CT-guided lung biopsies/fiducial placement. Procedure details and medical follow-up within and after 30 days of the procedure were analyzed. A total of 168 (11.8%) patients were admitted to the hospital within 30 days of the procedure, with 29 of the admissions (17.3% of total admissions and 1.9% of total procedures) being procedure related. The most common procedure-related complication that required admission was hemorrhage (10/29, 34.5% of procedure-related admissions, 6.0% of total admissions, and 0.7% of total procedures), followed by pneumothorax (9/29, 31%, 5.4%, 0.6%), infection (4/29, 13.8%, 2.4%, 0.3%), and pain (3/29, 10.3%, 1.8%, 0.2%). Eighteen (62.1%) procedure-related admissions were immediately indicated. Thirty patients visited the ED and were subsequently discharged without admission with eight of the visits being procedure related (8/1512, 0.5%). All the procedure-related ED visits were due to pain. There were two deaths (2/1512, 0.1%) related to procedures, one from a thromboembolic event and another from post-biopsy hemorrhage. Outpatient non-vascular image-guided procedures result in a 30-day 1.9% hospital admission, 30-day 0.5% emergency room visit, and 30-day 0.1% mortality rate.

Comparative analysis of Medicare spending for medical imaging: sustained dramatic slowdown compared with other services.

PubMed

Lee, David W; Duszak, Richard; Hughes, Danny R

2013-12-01

The purpose of this study was to assess trends in Medicare spending growth for medical imaging relative to other services and the Deficit Reduction Act (DRA). We calculated per-beneficiary Part B Medicare medical imaging expenditures for three-digit Berenson-Eggers Type of Service (BETOS) categories using Physician Supplier Procedure Summary Master Files for 32 million beneficiaries from 2000 to 2011. We adjusted BETOS categories to address changes in coding and payment policy and excluded categories with 2011 aggregate spending less than $500 million. We computed and ranked compound annual growth rates over three periods: pre-DRA (2000-2005), DRA transition period (2005-2007), and post-DRA (2007-2011). Forty-four modified BETOS categories fulfilled the inclusion criteria. Between 2000 and 2006, Medicare outlays for nonimaging services grew by 6.8% versus 12.0% for imaging services. In the ensuing 5 years, annual growth in spending for nonimaging continued at 3.6% versus a decline of 3.5% for imaging. Spending growth for all services during the pre-DRA, DRA, and post-DRA periods were 7.8%, 3.8%, and 2.9 compared with 15.0%, -3.4%, and -2.2% for advanced imaging services. Advanced imaging was among the fastest growing categories of Medicare services in the early 2000s but was in the bottom 2% of spending categories in 2011. Between 2007 and 2011, the fastest growing service categories were evaluation and management services with other specialists (29.1%), nursing home visits (11.2%), anesthesia (9.1%), and other ambulatory procedures (9.0%). Slowing volume growth and massive Medicare payment cuts have left medical imaging near the bottom of all service categories contributing to growth in Medicare spending.

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

PubMed

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.

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

PubMed

Bi, Hongsheng; Guo, Zhenhua; Benfield, Mark C; Fan, Chunlei; Ford, Michael; Shahrestani, Suzan; Sieracki, Jeffery M

2015-01-01

Plankton imaging systems are capable of providing fine-scale observations that enhance our understanding of key physical and biological processes. However, processing the large volumes of data collected by imaging systems remains a major obstacle for their employment, and existing approaches are designed either for images acquired under laboratory controlled conditions or within clear waters. In the present study, we developed a semi-automated approach to analyze plankton taxa from images acquired by the ZOOplankton VISualization (ZOOVIS) system within turbid estuarine waters, in Chesapeake Bay. When compared to images under laboratory controlled conditions or clear waters, images from highly turbid waters are often of relatively low quality and more variable, due to the large amount of objects and nonlinear illumination within each image. We first customized a segmentation procedure to locate objects within each image and extracted them for classification. A maximally stable extremal regions algorithm was applied to segment large gelatinous zooplankton and an adaptive threshold approach was developed to segment small organisms, such as copepods. Unlike the existing approaches for images acquired from laboratory, controlled conditions or clear waters, the target objects are often the majority class, and the classification can be treated as a multi-class classification problem. We customized a two-level hierarchical classification procedure using support vector machines to classify the target objects (< 5%), and remove the non-target objects (> 95%). First, histograms of oriented gradients feature descriptors were constructed for the segmented objects. In the first step all non-target and target objects were classified into different groups: arrow-like, copepod-like, and gelatinous zooplankton. Each object was passed to a group-specific classifier to remove most non-target objects. After the object was classified, an expert or non-expert then manually removed the

A Semi-Automated Image Analysis Procedure for In Situ Plankton Imaging Systems

PubMed Central

Bi, Hongsheng; Guo, Zhenhua; Benfield, Mark C.; Fan, Chunlei; Ford, Michael; Shahrestani, Suzan; Sieracki, Jeffery M.

2015-01-01

Plankton imaging systems are capable of providing fine-scale observations that enhance our understanding of key physical and biological processes. However, processing the large volumes of data collected by imaging systems remains a major obstacle for their employment, and existing approaches are designed either for images acquired under laboratory controlled conditions or within clear waters. In the present study, we developed a semi-automated approach to analyze plankton taxa from images acquired by the ZOOplankton VISualization (ZOOVIS) system within turbid estuarine waters, in Chesapeake Bay. When compared to images under laboratory controlled conditions or clear waters, images from highly turbid waters are often of relatively low quality and more variable, due to the large amount of objects and nonlinear illumination within each image. We first customized a segmentation procedure to locate objects within each image and extracted them for classification. A maximally stable extremal regions algorithm was applied to segment large gelatinous zooplankton and an adaptive threshold approach was developed to segment small organisms, such as copepods. Unlike the existing approaches for images acquired from laboratory, controlled conditions or clear waters, the target objects are often the majority class, and the classification can be treated as a multi-class classification problem. We customized a two-level hierarchical classification procedure using support vector machines to classify the target objects (< 5%), and remove the non-target objects (> 95%). First, histograms of oriented gradients feature descriptors were constructed for the segmented objects. In the first step all non-target and target objects were classified into different groups: arrow-like, copepod-like, and gelatinous zooplankton. Each object was passed to a group-specific classifier to remove most non-target objects. After the object was classified, an expert or non-expert then manually removed the

The semiotics of medical image Segmentation.

PubMed

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.

Cosmetic procedures among youths: a survey of junior college and medical students in Singapore.

PubMed

Ng, Jia Hui; Yeak, Seth; Phoon, Natalie; Lo, Stephen

2014-08-01

Although cosmetic procedures have become increasingly popular among the younger population in recent years, limited research on this subject has been done in the Asian context. We aimed to explore the views and knowledge regarding cosmetic procedures among junior college (JC) and medical students in Singapore. In the first phase of the study, a cross-sectional, self-administered survey of 1,500 JC students aged 16-21 years from six JCs was conducted in 2010. The same survey was then conducted on a random sample of Year 2-5 medical students from an undergraduate medical school in 2011. In total, 1,164 JC and 241 medical students responded to the surveys. There was an overall female to male ratio of 1.3:1. Of all the respondents, 2.5% of the JC students and 3.0% of the medical students admitted to having undergone cosmetic procedures. Among those who claimed to have never had cosmetic procedures done, 9.0% and 44.0% of the JC and medical students, respectively, responded that they would consider such procedures in the future. Those who disapproved of their peers undergoing cosmetic surgery comprised 35.0% of JC students and 56.8% of medical students. Among the JC and medical students, 52.0% and 36.1%, respectively, were unaware of any risks associated with cosmetic procedures. The younger population is increasingly accepting of cosmetic procedures. However, there is a general lack of understanding of the risks associated with such procedures. Education of both the general public and medical students may help prevent potential medicolegal issues.

A digital library for medical imaging activities

NASA Astrophysics Data System (ADS)

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.

A RONI Based Visible Watermarking Approach for Medical Image Authentication.

PubMed

Thanki, Rohit; Borra, Surekha; Dwivedi, Vedvyas; Borisagar, Komal

2017-08-09

Nowadays medical data in terms of image files are often exchanged between different hospitals for use in telemedicine and diagnosis. Visible watermarking being extensively used for Intellectual Property identification of such medical images, leads to serious issues if failed to identify proper regions for watermark insertion. In this paper, the Region of Non-Interest (RONI) based visible watermarking for medical image authentication is proposed. In this technique, to RONI of the cover medical image is first identified using Human Visual System (HVS) model. Later, watermark logo is visibly inserted into RONI of the cover medical image to get watermarked medical image. Finally, the watermarked medical image is compared with the original medical image for measurement of imperceptibility and authenticity of proposed scheme. The experimental results showed that this proposed scheme reduces the computational complexity and improves the PSNR when compared to many existing schemes.

A Framework for Integration of Heterogeneous Medical Imaging Networks

PubMed Central

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. PMID:25279021

A framework for integration of heterogeneous medical imaging networks.

PubMed

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.

NCRP report 160 and what it means for medical imaging and nuclear medicine.

PubMed

Bolus, Norman E

2013-12-01

The purpose of this paper is to briefly explain report 160 of the National Council on Radiation Protection and Measurement and the significance of the report to medical imaging as a whole and nuclear medicine specifically. The implications of the findings of report 160 have had repercussions and will continue to affect all of ionizing radiation medical imaging. The nuclear medicine community should have an understanding of why and how report 160 is important. After reading this article, the nuclear medicine technologist will be familiar with the main focus of report 160, the significant change that has occurred since the 1980s in the ionizing radiation exposure of people in the United States, the primary background source of ionizing radiation in the United States, the primary medical exposure to ionizing radiation in the United States, trends in nuclear medicine procedures and patient exposure, and a comparison of population doses between 2006 and the early 1980s as outlined in report 160.

12 CFR 1403.6 - Special procedures for medical records.

Code of Federal Regulations, 2010 CFR

2010-01-01

... Section 1403.6 Banks and Banking FARM CREDIT SYSTEM INSURANCE CORPORATION PRIVACY ACT REGULATIONS § 1403.6 Special procedures for medical records. Medical records in the custody of the Farm Credit System Insurance... the individual to whom they pertain or that person's authorized or legal representative or to a...

Cosmetic procedures among youths: a survey of junior college and medical students in Singapore

PubMed Central

Ng, Jia Hui; Yeak, Seth; Phoon, Natalie; Lo, Stephen

2014-01-01

INTRODUCTION Although cosmetic procedures have become increasingly popular among the younger population in recent years, limited research on this subject has been done in the Asian context. We aimed to explore the views and knowledge regarding cosmetic procedures among junior college (JC) and medical students in Singapore. METHODS In the first phase of the study, a cross-sectional, self-administered survey of 1,500 JC students aged 16–21 years from six JCs was conducted in 2010. The same survey was then conducted on a random sample of Year 2–5 medical students from an undergraduate medical school in 2011. RESULTS In total, 1,164 JC and 241 medical students responded to the surveys. There was an overall female to male ratio of 1.3:1. Of all the respondents, 2.5% of the JC students and 3.0% of the medical students admitted to having undergone cosmetic procedures. Among those who claimed to have never had cosmetic procedures done, 9.0% and 44.0% of the JC and medical students, respectively, responded that they would consider such procedures in the future. Those who disapproved of their peers undergoing cosmetic surgery comprised 35.0% of JC students and 56.8% of medical students. Among the JC and medical students, 52.0% and 36.1%, respectively, were unaware of any risks associated with cosmetic procedures. CONCLUSION The younger population is increasingly accepting of cosmetic procedures. However, there is a general lack of understanding of the risks associated with such procedures. Education of both the general public and medical students may help prevent potential medicolegal issues. PMID:25189303

An ITK framework for deterministic global optimization for medical image registration

NASA Astrophysics Data System (ADS)

Dru, Florence; Wachowiak, Mark P.; Peters, Terry M.

2006-03-01

Similarity metric optimization is an essential step in intensity-based rigid and nonrigid medical image registration. For clinical applications, such as image guidance of minimally invasive procedures, registration accuracy and efficiency are prime considerations. In addition, clinical utility is enhanced when registration is integrated into image analysis and visualization frameworks, such as the popular Insight Toolkit (ITK). ITK is an open source software environment increasingly used to aid the development, testing, and integration of new imaging algorithms. In this paper, we present a new ITK-based implementation of the DIRECT (Dividing Rectangles) deterministic global optimization algorithm for medical image registration. Previously, it has been shown that DIRECT improves the capture range and accuracy for rigid registration. Our ITK class also contains enhancements over the original DIRECT algorithm by improving stopping criteria, adaptively adjusting a locality parameter, and by incorporating Powell's method for local refinement. 3D-3D registration experiments with ground-truth brain volumes and clinical cardiac volumes show that combining DIRECT with Powell's method improves registration accuracy over Powell's method used alone, is less sensitive to initial misorientation errors, and, with the new stopping criteria, facilitates adequate exploration of the search space without expending expensive iterations on non-improving function evaluations. Finally, in this framework, a new parallel implementation for computing mutual information is presented, resulting in near-linear speedup with two processors.

Medical image registration based on normalized multidimensional mutual information

NASA Astrophysics Data System (ADS)

Li, Qi; Ji, Hongbing; Tong, Ming

2009-10-01

Registration of medical images is an essential research topic in medical image processing and applications, and especially a preliminary and key step for multimodality image fusion. This paper offers a solution to medical image registration based on normalized multi-dimensional mutual information. Firstly, affine transformation with translational and rotational parameters is applied to the floating image. Then ordinal features are extracted by ordinal filters with different orientations to represent spatial information in medical images. Integrating ordinal features with pixel intensities, the normalized multi-dimensional mutual information is defined as similarity criterion to register multimodality images. Finally the immune algorithm is used to search registration parameters. The experimental results demonstrate the effectiveness of the proposed registration scheme.

THz Medical Imaging: in vivo Hydration Sensing

PubMed Central

Taylor, Zachary D.; Singh, Rahul S.; Bennett, David B.; Tewari, Priyamvada; Kealey, Colin P.; Bajwa, Neha; Culjat, Martin O.; Stojadinovic, Alexander; Lee, Hua; Hubschman, Jean-Pierre; Brown, Elliott R.; Grundfest, Warren S.

2015-01-01

The application of THz to medical imaging is experiencing a surge in both interest and federal funding. A brief overview of the field is provided along with promising and emerging applications and ongoing research. THz imaging phenomenology is discussed and tradeoffs are identified. A THz medical imaging system, operating at ~525 GHz center frequency with ~125 GHz of response normalized bandwidth is introduced and details regarding principles of operation are provided. Two promising medical applications of THz imaging are presented: skin burns and cornea. For burns, images of second degree, partial thickness burns were obtained in rat models in vivo over an 8 hour period. These images clearly show the formation and progression of edema in and around the burn wound area. For cornea, experimental data measuring the hydration of ex vivo porcine cornea under drying is presented demonstrating utility in ophthalmologic applications. PMID:26085958

Medical microscopic image matching based on relativity

NASA Astrophysics Data System (ADS)

Xie, Fengying; Zhu, Liangen; Jiang, Zhiguo

2003-12-01

In this paper, an effective medical micro-optical image matching algorithm based on relativity is described. The algorithm includes the following steps: Firstly, selecting a sub-area that has obvious character in one of the two images as standard image; Secondly, finding the right matching position in the other image; Thirdly, applying coordinate transformation to merge the two images together. As a kind of application of image matching in medical micro-optical image, this method overcomes the shortcoming of microscope whose visual field is little and makes it possible to watch a big object or many objects in one view. Simultaneously it implements adaptive selection of standard image, and has a satisfied matching speed and result.

Medical Images Remote Consultation

NASA Astrophysics Data System (ADS)

Ferraris, Maurizio; Frixione, Paolo; Squarcia, Sandro

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

Multiscale Medical Image Fusion in Wavelet Domain

PubMed Central

Khare, Ashish

2013-01-01

Wavelet transforms have emerged as a powerful tool in image fusion. However, the study and analysis of medical image fusion is still a challenging area of research. Therefore, in this paper, we propose a multiscale fusion of multimodal medical images in wavelet domain. Fusion of medical images has been performed at multiple scales varying from minimum to maximum level using maximum selection rule which provides more flexibility and choice to select the relevant fused images. The experimental analysis of the proposed method has been performed with several sets of medical images. Fusion results have been evaluated subjectively and objectively with existing state-of-the-art fusion methods which include several pyramid- and wavelet-transform-based fusion methods and principal component analysis (PCA) fusion method. The comparative analysis of the fusion results has been performed with edge strength (Q), mutual information (MI), entropy (E), standard deviation (SD), blind structural similarity index metric (BSSIM), spatial frequency (SF), and average gradient (AG) metrics. The combined subjective and objective evaluations of the proposed fusion method at multiple scales showed the effectiveness and goodness of the proposed approach. PMID:24453868

A “Cookbook” Cost Analysis Procedure for Medical Information Systems*

PubMed Central

Torrance, Janice L.; Torrance, George W.; Covvey, H. Dominic

1983-01-01

A costing procedure for medical information systems is described. The procedure incorporates state-of-the-art costing methods in an easy to follow “cookbook” format. Application of the procedure consists of filling out a series of Mac-Tor EZ-Cost forms. The procedure and forms have been field tested by application to a cardiovascular database system. This article describes the major features of the costing procedure. The forms and other details are available upon request.

An interactive medical image segmentation framework using iterative refinement.

PubMed

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.

Imaging-related medications: a class overview

PubMed Central

2007-01-01

Imaging-related medications (contrast agents) are commonly utilized to improve visualization of radiographic, computed tomography (CT), and magnetic resonance (MR) images. While traditional medications are used specifically for their pharmacological actions, the ideal imaging agent provides enhanced contrast with little biological interaction. The radiopaque agents, barium sulfate and iodinated contrast agents, confer “contrast” to x-ray films by their physical ability to directly absorb x-rays. Gadolinium-based MR agents enhance visualization of tissues when exposed to a magnetic field. Ferrous-ferric oxide–based paramagnetic agents provide negative contrast for MR liver studies. This article provides an overview of clinically relevant information for the imaging-related medications commonly in use. It reviews the safety improvements in new generations of drugs; risk factors and precautions for the reduction of severe adverse reactions (i.e., extravasation, contrast-induced nephropathy, metformin-induced lactic acidosis, and nephrogenic fibrosing dermopathy/nephrogenic systemic fibrosis); and the significance of diligent patient screening before contrast exposure and appropriate monitoring after exposure. PMID:17948119

Managing complex processing of medical image sequences by program supervision techniques

NASA Astrophysics Data System (ADS)

Crubezy, Monica; Aubry, Florent; Moisan, Sabine; Chameroy, Virginie; Thonnat, Monique; Di Paola, Robert

1997-05-01

Our objective is to offer clinicians wider access to evolving medical image processing (MIP) techniques, crucial to improve assessment and quantification of physiological processes, but difficult to handle for non-specialists in MIP. Based on artificial intelligence techniques, our approach consists in the development of a knowledge-based program supervision system, automating the management of MIP libraries. It comprises a library of programs, a knowledge base capturing the expertise about programs and data and a supervision engine. It selects, organizes and executes the appropriate MIP programs given a goal to achieve and a data set, with dynamic feedback based on the results obtained. It also advises users in the development of new procedures chaining MIP programs.. We have experimented the approach for an application of factor analysis of medical image sequences as a means of predicting the response of osteosarcoma to chemotherapy, with both MRI and NM dynamic image sequences. As a result our program supervision system frees clinical end-users from performing tasks outside their competence, permitting them to concentrate on clinical issues. Therefore our approach enables a better exploitation of possibilities offered by MIP and higher quality results, both in terms of robustness and reliability.

Wavelets in medical imaging

NASA Astrophysics Data System (ADS)

Zahra, Noor e.; Sevindir, Hulya Kodal; Aslan, Zafer; Siddiqi, A. H.

2012-07-01

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.

Electronic photography: a new age of medical imaging?

PubMed

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.

Radiation Risk From Medical Imaging

PubMed Central

Lin, Eugene C.

2010-01-01

This review provides a practical overview of the excess cancer risks related to radiation from medical imaging. Primary care physicians should have a basic understanding of these risks. Because of recent attention to this issue, patients are more likely to express concerns over radiation risk. In addition, physicians can play a role in reducing radiation risk to their patients by considering these risks when making imaging referrals. This review provides a brief overview of the evidence pertaining to low-level radiation and excess cancer risks and addresses the radiation doses and risks from common medical imaging studies. Specific subsets of patients may be at greater risk from radiation exposure, and radiation risk should be considered carefully in these patients. Recent technical innovations have contributed to lowering the radiation dose from computed tomography, and the referring physician should be aware of these innovations in making imaging referrals. PMID:21123642

Medical image classification based on multi-scale non-negative sparse coding.

PubMed

Zhang, Ruijie; Shen, Jian; Wei, Fushan; Li, Xiong; Sangaiah, Arun Kumar

2017-11-01

With the rapid development of modern medical imaging technology, medical image classification has become more and more important in medical diagnosis and clinical practice. Conventional medical image classification algorithms usually neglect the semantic gap problem between low-level features and high-level image semantic, which will largely degrade the classification performance. To solve this problem, we propose a multi-scale non-negative sparse coding based medical image classification algorithm. Firstly, Medical images are decomposed into multiple scale layers, thus diverse visual details can be extracted from different scale layers. Secondly, for each scale layer, the non-negative sparse coding model with fisher discriminative analysis is constructed to obtain the discriminative sparse representation of medical images. Then, the obtained multi-scale non-negative sparse coding features are combined to form a multi-scale feature histogram as the final representation for a medical image. Finally, SVM classifier is combined to conduct medical image classification. The experimental results demonstrate that our proposed algorithm can effectively utilize multi-scale and contextual spatial information of medical images, reduce the semantic gap in a large degree and improve medical image classification performance. Copyright © 2017 Elsevier B.V. All rights reserved.

21 CFR 892.2020 - Medical image communications device.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Medical image communications device. 892.2020 Section 892.2020 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES RADIOLOGY DEVICES Diagnostic Devices § 892.2020 Medical image communications...

Content-independent embedding scheme for multi-modal medical image watermarking.

PubMed

Nyeem, Hussain; Boles, Wageeh; Boyd, Colin

2015-02-04

As the increasing adoption of information technology continues to offer better distant medical services, the distribution of, and remote access to digital medical images over public networks continues to grow significantly. Such use of medical images raises serious concerns for their continuous security protection, which digital watermarking has shown great potential to address. We present a content-independent embedding scheme for medical image watermarking. We observe that the perceptual content of medical images varies widely with their modalities. Recent medical image watermarking schemes are image-content dependent and thus they may suffer from inconsistent embedding capacity and visual artefacts. To attain the image content-independent embedding property, we generalise RONI (region of non-interest, to the medical professionals) selection process and use it for embedding by utilising RONI's least significant bit-planes. The proposed scheme thus avoids the need for RONI segmentation that incurs capacity and computational overheads. Our experimental results demonstrate that the proposed embedding scheme performs consistently over a dataset of 370 medical images including their 7 different modalities. Experimental results also verify how the state-of-the-art reversible schemes can have an inconsistent performance for different modalities of medical images. Our scheme has MSSIM (Mean Structural SIMilarity) larger than 0.999 with a deterministically adaptable embedding capacity. Our proposed image-content independent embedding scheme is modality-wise consistent, and maintains a good image quality of RONI while keeping all other pixels in the image untouched. Thus, with an appropriate watermarking framework (i.e., with the considerations of watermark generation, embedding and detection functions), our proposed scheme can be viable for the multi-modality medical image applications and distant medical services such as teleradiology and eHealth.

Medical Office Laboratory Procedures: Course Proposal. Revised.

ERIC Educational Resources Information Center

Baker, Eleanor

A proposal is presented for a Community College of Philadelphia course, entitled "Medical Office Laboratory Procedures," which provides a laboratory introduction to microscopic and chemical analysis of blood and urine as performed in the physician's office. Following a standard cover form, a statement of the purpose of the course discusses course…

Medical image registration: basic science and clinical implications.

PubMed

Imran, Muhammad Babar; Meo, Sultan Ayoub; Yousuf, Mohammad; Othman, Saleh; Shahid, Abubakar

2010-01-01

Image Registration is a process of aligning two or more images so that corresponding feature can be related objectively. Integration of corresponding and complementary information from various images has become an important area of computation in medical imaging. Merging different images of the same patient taken by different modalities or acquired at different times is quite useful in interpreting lower resolution functional images, such as those provided by nuclear medicine, in determining spatial relationships of structures seen in different modalities. This will help in planning surgery and longitudinal follow up. The aim of this article was to introduce image registration to all those who are working in field of medical sciences in general and medical doctors in particular; and indicate how and where this specialty is moving to provide better health care services.

Supervised restoration of degraded medical images using multiple-point geostatistics.

PubMed

Pham, Tuan D

2012-06-01

Reducing noise in medical images has been an important issue of research and development for medical diagnosis, patient treatment, and validation of biomedical hypotheses. Noise inherently exists in medical and biological images due to the acquisition and transmission in any imaging devices. Being different from image enhancement, the purpose of image restoration is the process of removing noise from a degraded image in order to recover as much as possible its original version. This paper presents a statistically supervised approach for medical image restoration using the concept of multiple-point geostatistics. Experimental results have shown the effectiveness of the proposed technique which has potential as a new methodology for medical and biological image processing. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Image registration: enabling technology for image guided surgery and therapy.

PubMed

Sauer, Frank

2005-01-01

Imaging looks inside the patient's body, exposing the patient's anatomy beyond what is visible on the surface. Medical imaging has a very successful history for medical diagnosis. It also plays an increasingly important role as enabling technology for minimally invasive procedures. Interventional procedures (e.g. catheter based cardiac interventions) are traditionally supported by intra-procedure imaging (X-ray fluoro, ultrasound). There is realtime feedback, but the images provide limited information. Surgical procedures are traditionally supported with pre-operative images (CT, MR). The image quality can be very good; however, the link between images and patient has been lost. For both cases, image registration can play an essential role -augmenting intra-op images with pre-op images, and mapping pre-op images to the patient's body. We will present examples of both approaches from an application oriented perspective, covering electrophysiology, radiation therapy, and neuro-surgery. Ultimately, as the boundaries between interventional radiology and surgery are becoming blurry, also the different methods for image guidance will merge. Image guidance will draw upon a combination of pre-op and intra-op imaging together with magnetic or optical tracking systems, and enable precise minimally invasive procedures. The information is registered into a common coordinate system, and allows advanced methods for visualization such as augmented reality or advanced methods for therapy delivery such as robotics.

Cardiac Imaging System

NASA Technical Reports Server (NTRS)

1990-01-01

Although not available to all patients with narrowed arteries, balloon angioplasty has expanded dramatically since its introduction with an estimated further growth to 562,000 procedures in the U.S. alone by 1992. Growth has fueled demand for higher quality imaging systems that allow the cardiologist to be more accurate and increase the chances of a successful procedure. A major advance is the Digital Cardiac Imaging (DCI) System designed by Philips Medical Systems International, Best, The Netherlands and marketed in the U.S. by Philips Medical Systems North America Company. The key benefit is significantly improved real-time imaging and the ability to employ image enhancement techniques to bring out added details. Using a cordless control unit, the cardiologist can manipulate images to make immediate assessment, compare live x-ray and roadmap images by placing them side-by-side on monitor screens, or compare pre-procedure and post procedure conditions. The Philips DCI improves the cardiologist's precision by expanding the information available to him.

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

PubMed

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.

Radiology and Enterprise Medical Imaging Extensions (REMIX).

PubMed

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.

RayPlus: a Web-Based Platform for Medical Image Processing.

PubMed

Yuan, Rong; Luo, Ming; Sun, Zhi; Shi, Shuyue; Xiao, Peng; Xie, Qingguo

2017-04-01

Medical image can provide valuable information for preclinical research, clinical diagnosis, and treatment. As the widespread use of digital medical imaging, many researchers are currently developing medical image processing algorithms and systems in order to accommodate a better result to clinical community, including accurate clinical parameters or processed images from the original images. In this paper, we propose a web-based platform to present and process medical images. By using Internet and novel database technologies, authorized users can easily access to medical images and facilitate their workflows of processing with server-side powerful computing performance without any installation. We implement a series of algorithms of image processing and visualization in the initial version of Rayplus. Integration of our system allows much flexibility and convenience for both research and clinical communities.

Radically Reducing Radiation Exposure during Routine Medical Imaging

Cancer.gov

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.

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

PubMed

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.

Denoising Medical Images using Calculus of Variations

PubMed Central

Kohan, Mahdi Nakhaie; Behnam, Hamid

2011-01-01

We propose a method for medical image denoising using calculus of variations and local variance estimation by shaped windows. This method reduces any additive noise and preserves small patterns and edges of images. A pyramid structure-texture decomposition of images is used to separate noise and texture components based on local variance measures. The experimental results show that the proposed method has visual improvement as well as a better SNR, RMSE and PSNR than common medical image denoising methods. Experimental results in denoising a sample Magnetic Resonance image show that SNR, PSNR and RMSE have been improved by 19, 9 and 21 percents respectively. PMID:22606674

Tissues segmentation based on multi spectral medical images

NASA Astrophysics Data System (ADS)

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.

[Research Progress of Multi-Model Medical Image Fusion at Feature Level].

PubMed

Zhang, Junjie; Zhou, Tao; Lu, Huiling; Wang, Huiqun

2016-04-01

Medical image fusion realizes advantage integration of functional images and anatomical images.This article discusses the research progress of multi-model medical image fusion at feature level.We firstly describe the principle of medical image fusion at feature level.Then we analyze and summarize fuzzy sets,rough sets,D-S evidence theory,artificial neural network,principal component analysis and other fusion methods’ applications in medical image fusion and get summery.Lastly,we in this article indicate present problems and the research direction of multi-model medical images in the future.

Procedural and interpretive skills of medical students: experiences and attitudes of third-year students.

PubMed

Wu, Edward H; Elnicki, D Michael; Alper, Eric J; Bost, James E; Corbett, Eugene C; Fagan, Mark J; Mechaber, Alex; Ogden, Paul E; Sebastian, James L; Torre, Dario M

2006-10-01

Recent data do not exist on medical students' performance of and attitudes toward procedural and interpretive skills deemed important by medical educators. A total of 171 medical students at seven medical schools were surveyed regarding frequency of performance, self-confidence, and perceived importance of 21 procedural and interpretive skills. Of the 122 responding students (71% response rate), a majority had never performed lumbar puncture, thoracentesis, paracentesis, or blood culture, and students reported lowest self-confidence in these skills. At least one-quarter of students had never performed phlebotomy, peripheral intravenous catheter insertion, or arterial blood sampling. Students perceived all 21 skills as important to learn and perform during medical school. Through the third year of medical school, a majority of students had never performed important procedures, and a substantial minority had not performed basic procedures. Students had low self-confidence in skills they rarely performed, but perceived all skills surveyed as important.

Normalized methodology for medical infrared imaging

NASA Astrophysics Data System (ADS)

Vargas, J. V. C.; Brioschi, M. L.; Dias, F. G.; Parolin, M. B.; Mulinari-Brenner, F. A.; Ordonez, J. C.; Colman, D.

2009-01-01

A normalized procedure for medical infrared imaging is suggested, and illustrated by a leprosy and hepatitis C treatment follow-up, in order to investigate the effect of concurrent treatment which has not been reported before. A 50-year-old man with indeterminate leprosy and a 20-year history of hepatitis C was monitored for 587 days, starting from the day the patient received treatment for leprosy. Standard therapy for hepatitis C started 30 days later. Both visual observations and normalized infrared imaging were conducted periodically to assess the response to leprosy treatment. The primary end points were effectiveness of the method under different boundary conditions over the period, and rapid assessment of the response to leprosy treatment. The patient achieved sustained hepatitis C virological response 6 months after the end of the treatment. The normalized infrared results demonstrate the leprosy treatment success in spite of the concurrent hepatitis C treatment, since day 87, whereas repigmentation was visually assessed only after day 182, and corroborated with a skin biopsy on day 390. The method detected the effectiveness of the leprosy treatment in 87 days, whereas repigmentation started only in 182 days. Hepatitis C and leprosy treatment did not affect each other.

Multiview Locally Linear Embedding for Effective Medical Image Retrieval

PubMed Central

Shen, Hualei; Tao, Dacheng; Ma, Dianfu

2013-01-01

Content-based medical image retrieval continues to gain attention for its potential to assist radiological image interpretation and decision making. Many approaches have been proposed to improve the performance of medical image retrieval system, among which visual features such as SIFT, LBP, and intensity histogram play a critical role. Typically, these features are concatenated into a long vector to represent medical images, and thus traditional dimension reduction techniques such as locally linear embedding (LLE), principal component analysis (PCA), or laplacian eigenmaps (LE) can be employed to reduce the “curse of dimensionality”. Though these approaches show promising performance for medical image retrieval, the feature-concatenating method ignores the fact that different features have distinct physical meanings. In this paper, we propose a new method called multiview locally linear embedding (MLLE) for medical image retrieval. Following the patch alignment framework, MLLE preserves the geometric structure of the local patch in each feature space according to the LLE criterion. To explore complementary properties among a range of features, MLLE assigns different weights to local patches from different feature spaces. Finally, MLLE employs global coordinate alignment and alternating optimization techniques to learn a smooth low-dimensional embedding from different features. To justify the effectiveness of MLLE for medical image retrieval, we compare it with conventional spectral embedding methods. We conduct experiments on a subset of the IRMA medical image data set. Evaluation results show that MLLE outperforms state-of-the-art dimension reduction methods. PMID:24349277

Intelligent retrieval of medical images from the Internet

NASA Astrophysics Data System (ADS)

Tang, Yau-Kuo; Chiang, Ted T.

1996-05-01

The object of this study is using Internet resources to provide a cost-effective, user-friendly method to access the medical image archive system and to provide an easy method for the user to identify the images required. This paper describes the prototype system architecture, the implementation, and results. In the study, we prototype the Intelligent Medical Image Retrieval (IMIR) system as a Hypertext Transport Prototype server and provide Hypertext Markup Language forms for user, as an Internet client, using browser to enter image retrieval criteria for review. We are developing the intelligent retrieval engine, with the capability to map the free text search criteria to the standard terminology used for medical image identification. We evaluate retrieved records based on the number of the free text entries matched and their relevance level to the standard terminology. We are in the integration and testing phase. We have collected only a few different types of images for testing and have trained a few phrases to map the free text to the standard medical terminology. Nevertheless, we are able to demonstrate the IMIR's ability to search, retrieve, and review medical images from the archives using general Internet browser. The prototype also uncovered potential problems in performance, security, and accuracy. Additional studies and enhancements will make the system clinically operational.

Monte Carlo simulations of medical imaging modalities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Estes, G.P.

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

Medical tourism: the trend toward outsourcing medical procedures to foreign countries.

PubMed

York, Diane

2008-01-01

The rising costs of medical treatment in the United States are fueling a movement to outsource medical treatment. Estimates of the number of Americans traveling overseas for treatment range from 50,000 to 500,000. Charges for common procedures such as heart bypass can be $11,000 in Thailand compared to $130,000 in the United States. Knee replacement in the United States can cost $40,000 compared to $13,000 in Singapore.A new industry, medical tourism, has been created to advise patients on the appropriate facility in the right country for their condition, handle all travel arrangements, teleconference with physicians, and send medical records. To respond to the growth in medical travel, the Joint Commission (formerly the Joint Commission on Accreditation of Health Care Organizations) initiated the Joint Commission International (JCI) to accredit hospitals worldwide. Although outcome statistics from hospitals outside the United States are rare, first-person reports on quality are numerous. Making surgery possible for uninsured and underinsured individuals or self-insured state, municipal, and private entities is a major benefit of medical tourism. Mitigating against medical travel are the lack of legal remedies in place for malpractice and the possibility that travel itself can impose risk to patients. For example, lengthy air flights where the patient is in a fixed position for hours at a time can cause embolisms. If the trend toward medical tourism continues, continuing education, credentialing, and certification services may be required to help assure patient safety.

An information gathering system for medical image inspection

NASA Astrophysics Data System (ADS)

Lee, Young-Jin; Bajcsy, Peter

2005-04-01

We present an information gathering system for medical image inspection that consists of software tools for capturing computer-centric and human-centric information. Computer-centric information includes (1) static annotations, such as (a) image drawings enclosing any selected area, a set of areas with similar colors, a set of salient points, and (b) textual descriptions associated with either image drawings or links between pairs of image drawings, and (2) dynamic (or temporal) information, such as mouse movements, zoom level changes, image panning and frame selections from an image stack. Human-centric information is represented by video and audio signals that are acquired by computer-mounted cameras and microphones. The short-term goal of the presented system is to facilitate learning of medical novices from medical experts, while the long-term goal is to data mine all information about image inspection for assisting in making diagnoses. In this work, we built basic software functionality for gathering computer-centric and human-centric information of the aforementioned variables. Next, we developed the information playback capabilities of all gathered information for educational purposes. Finally, we prototyped text-based and image template-based search engines to retrieve information from recorded annotations, for example, (a) find all annotations containing the word "blood vessels", or (b) search for similar areas to a selected image area. The information gathering system for medical image inspection reported here has been tested with images from the Histology Atlas database.

Deformable Medical Image Registration: A Survey

PubMed Central

Sotiras, Aristeidis; Davatzikos, Christos; Paragios, Nikos

2013-01-01

Deformable image registration is a fundamental task in medical image processing. Among its most important applications, one may cite: i) multi-modality fusion, where information acquired by different imaging devices or protocols is fused to facilitate diagnosis and treatment planning; ii) longitudinal studies, where temporal structural or anatomical changes are investigated; and iii) population modeling and statistical atlases used to study normal anatomical variability. In this paper, we attempt to give an overview of deformable registration methods, putting emphasis on the most recent advances in the domain. Additional emphasis has been given to techniques applied to medical images. In order to study image registration methods in depth, their main components are identified and studied independently. The most recent techniques are presented in a systematic fashion. The contribution of this paper is to provide an extensive account of registration techniques in a systematic manner. PMID:23739795

Human Factors and ISS Medical Systems: Highlights of Procedures and Equipment Findings

NASA Technical Reports Server (NTRS)

Byrne, V. E.; Hudy, C.; Smith, D.; Whitmore, M.

2005-01-01

As part of the Space Human Factors Engineering Critical Questions Roadmap, a three year Technology Development Project (TDP) was funded by NASA Headquarters to examine emergency medical procedures on ISS. The overall aim of the emergency medical procedures project was to determine the human factors issues in the procedures, training, communications and equipment, and to recommend solutions that will improve the survival rate of crewmembers in the event of a medical emergency. Currently, each ISS crew remains on orbit for six month intervals. As there is not standing requirement for a physician crewmember, during such time, the maintenance of crew health is dependant on individual crewmembers. Further, in the event of an emergency, crew will need to provide prolonged maintenance care, as well as emergency treatment, to an injured crewmember while awaiting transport to Earth. In addition to the isolation of the crew, medical procedures must be carried out within the further limitations imposed by the physical environment of the space station. For example, in order to administer care on ISS without the benefit of gravity, the Crew Medical Officers (CMOs) must restrain the equipment required to perform the task, restrain the injured crewmember, and finally, restrain themselves. Both the physical environment and the physical space available further limit the technology that can be used onboard. Equipment must be compact, yet able to withstand high levels of radiation and function without gravity. The focus here is to highlight the human factors impacts from our three year project involving the procedures and equipment areas that have been investigated and provided valuable to ISS and provide groundwork for human factors requirements for medical applications for exploration missions.

Improved Interactive Medical-Imaging System

NASA Technical Reports Server (NTRS)

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.

Ontology modularization to improve semantic medical image annotation.

PubMed

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.

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

PubMed

Granot, Yair; Ivorra, Antoni; Rubinsky, Boris

2008-04-30

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.

Nazi Medical Research in Neuroscience: Medical Procedures, Victims, and Perpetrators.

PubMed

Loewenau, Aleksandra; Weindling, Paul J

Issues relating to the euthanasia killings of the mentally ill, the medical research conducted on collected body parts, and the clinical investigations on living victims under National Socialism are among the best-known abuses in medical history. But to date, there have been no statistics compiled regarding the extent and number of the victims and perpetrators, or regarding their identities in terms of age, nationality, and gender. "Victims of Unethical Human Experiments and Coerced Research under National Socialism," a research project based at Oxford Brookes University, has established an evidence-based documentation of the overall numbers of victims and perpetrators through specific record linkages of the evidence from the period of National Socialism, as well as from post-WWII trials and other records. This article examines the level and extent of these unethical medical procedures as they relate to the field of neuroscience. It presents statistical information regarding the victims, as well as detailing the involvement of the perpetrators and Nazi physicians with respect to their post-war activities and subsequent court trials.

Hello World Deep Learning in Medical Imaging.

PubMed

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.

Procedures for cryogenic X-ray ptychographic imaging of biological samples

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yusuf, M.; Zhang, F.; Chen, B.

Biological sample-preparation procedures have been developed for imaging human chromosomes under cryogenic conditions. A new experimental setup, developed for imaging frozen samples using beamline I13 at Diamond Light Source, is described. This paper describes the equipment and experimental procedures as well as the authors' first ptychographic reconstructions using X-rays.

Procedures for cryogenic X-ray ptychographic imaging of biological samples

DOE PAGES

Yusuf, M.; Zhang, F.; Chen, B.; ...

2017-01-12

Biological sample-preparation procedures have been developed for imaging human chromosomes under cryogenic conditions. A new experimental setup, developed for imaging frozen samples using beamline I13 at Diamond Light Source, is described. This paper describes the equipment and experimental procedures as well as the authors' first ptychographic reconstructions using X-rays.

The Pediatric Urinary Tract and Medical Imaging.

PubMed

Penny, Steven M

2016-01-01

The pediatric urinary tract often is assessed with medical imaging. Consequently, it is essential for medical imaging professionals to have a fundamental understanding of pediatric anatomy, physiology, and common pathology of the urinary tract to provide optimal patient care. This article provides an overview of fetal development, pediatric urinary anatomy and physiology, and common diseases and conditions of the pediatric urinary tract.

Use of mobile devices for medical imaging.

PubMed

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.

Neural networks: Application to medical imaging

NASA Technical Reports Server (NTRS)

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.

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

NASA Astrophysics Data System (ADS)

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

2011-03-01

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

NiftyNet: a deep-learning platform for medical imaging.

PubMed

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

Using GOMS models and hypertext to create representations of medical procedures for online display

NASA Technical Reports Server (NTRS)

Gugerty, Leo; Halgren, Shannon; Gosbee, John; Rudisill, Marianne

1991-01-01

This study investigated two methods to improve organization and presentation of computer-based medical procedures. A literature review suggested that the GOMS (goals, operators, methods, and selecton rules) model can assist in rigorous task analysis, which can then help generate initial design ideas for the human-computer interface. GOMS model are hierarchical in nature, so this study also investigated the effect of hierarchical, hypertext interfaces. We used a 2 x 2 between subjects design, including the following independent variables: procedure organization - GOMS model based vs. medical-textbook based; navigation type - hierarchical vs. linear (booklike). After naive subjects studies the online procedures, measures were taken of their memory for the content and the organization of the procedures. This design was repeated for two medical procedures. For one procedure, subjects who studied GOMS-based and hierarchical procedures remembered more about the procedures than other subjects. The results for the other procedure were less clear. However, data for both procedures showed a 'GOMSification effect'. That is, when asked to do a free recall of a procedure, subjects who had studies a textbook procedure often recalled key information in a location inconsistent with the procedure they actually studied, but consistent with the GOMS-based procedure.

[A study on medical image fusion].

PubMed

Zhang, Er-hu; Bian, Zheng-zhong

2002-09-01

Five algorithms with its advantages and disadvantage for medical image fusion are analyzed. Four kinds of quantitative evaluation criteria for the quality of image fusion algorithms are proposed and these will give us some guidance for future research.

An application of digital network technology to medical image management.

PubMed

Chu, W K; Smith, C L; Wobig, R K; Hahn, F A

1997-01-01

With the advent of network technology, there is considerable interest within the medical community to manage the storage and distribution of medical images by digital means. Higher workflow efficiency leading to better patient care is one of the commonly cited outcomes [1,2]. However, due to the size of medical image files and the unique requirements in detail and resolution, medical image management poses special challenges. Storage requirements are usually large, which implies expenses or investment costs make digital networking projects financially out of reach for many clinical institutions. New advances in network technology and telecommunication, in conjunction with the decreasing cost in computer devices, have made digital image management achievable. In our institution, we have recently completed a pilot project to distribute medical images both within the physical confines of the clinical enterprise as well as outside the medical center campus. The design concept and the configuration of a comprehensive digital image network is described in this report.

The effect of dose heterogeneity on radiation risk in medical imaging.

PubMed

Samei, Ehsan; Li, Xiang; Chen, Baiyu; Reiman, Robert

2013-06-01

The current estimations of risk associated with medical imaging procedures rely on assessing the organ dose via direct measurements or simulation. The dose to each organ is assumed to be homogeneous. To take into account the differences in radiation sensitivities, the mean organ doses are weighted by a corresponding tissue-weighting coefficients provided by ICRP to calculate the effective dose, which has been used as a surrogate of radiation risk. However, those coefficients were derived under the assumption of a homogeneous dose distribution within each organ. That assumption is significantly violated in most medical-imaging procedures. In helical chest CT, for example, superficial organs (e.g. breasts) demonstrate a heterogeneous dose distribution, whereas organs on the peripheries of the irradiation field (e.g. liver) might possess a discontinuous dose profile. Projection radiography and mammography involve an even higher level of organ dose heterogeneity spanning up to two orders of magnitude. As such, mean dose or point measured dose values do not reflect the maximum energy deposited per unit volume of the organ. In this paper, the magnitude of the dose heterogeneity in both CT and projection X-ray imaging was reported, using Monte Carlo methods. The lung dose demonstrated factors of 1.7 and 2.2 difference between the mean and maximum dose for chest CT and radiography, respectively. The corresponding values for the liver were 1.9 and 3.5. For mammography and breast tomosynthesis, the difference between mean glandular dose and maximum glandular dose was 3.1. Risk models based on the mean dose were found to provide a reasonable reflection of cancer risk. However, for leukaemia, they were found to significantly under-represent the risk when the organ dose distribution is heterogeneous. A systematic study is needed to develop a risk model for heterogeneous dose distributions.

Development and Application of Multifunctional Lanthanide-Doped Nanoparticles in Medical Imaging

NASA Astrophysics Data System (ADS)

Pedraza, Francisco J., III

Medical imaging has become one of the most important tools of modern medicine soon after it was developed. Presently, several imaging modalities are available to clinicians for the detection of skeletal fractures and functional abnormalities of organs and tissues; and also an excellent tool during surgical procedures. Unfortunately, each imaging technique possesses its own strengths and inherent limitations which can be mitigated via the use of multiple imaging modalities and imaging probes. Through the use of multiple imaging modalities, it is possible to gather complementary information for a more reliable diagnosis. Each imaging technique requires its own imaging probes, providing selectivity and improved contrast. However, conventional contrast agents are incapable of providing what the new generation of multifunctional nanomaterials offer. In addition to improved selectivity and contrast, multifunctional materials possess therapeutic capabilities such as photo-thermal therapy and controlled drug delivery. Lanthanide-based nanomaterials are viable candidates for multimodal imaging agents due to possessing multifunctional capabilities, optical and chemical stability, and an intense tunable emission. This doctoral dissertation will delve into the development of lanthanide-based nanoparticles by proposing a novel multifunctional contrast agent for Near Infrared Fluorescence Imaging and Magnetic Resonance Imaging. Furthermore, the study of surface modification effects on upconversion emission and nanoparticle-cell interactions was performed. Results presented will confirm the potential application of multifunctional lanthanide-based nanomaterials as multimodal imaging probes.

Novel medical image enhancement algorithms

NASA Astrophysics Data System (ADS)

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.

An open architecture for medical image workstation

NASA Astrophysics Data System (ADS)

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.

Iterative deep convolutional encoder-decoder network for medical image segmentation.

PubMed

Jung Uk Kim; Hak Gu Kim; Yong Man Ro

2017-07-01

In this paper, we propose a novel medical image segmentation using iterative deep learning framework. We have combined an iterative learning approach and an encoder-decoder network to improve segmentation results, which enables to precisely localize the regions of interest (ROIs) including complex shapes or detailed textures of medical images in an iterative manner. The proposed iterative deep convolutional encoder-decoder network consists of two main paths: convolutional encoder path and convolutional decoder path with iterative learning. Experimental results show that the proposed iterative deep learning framework is able to yield excellent medical image segmentation performances for various medical images. The effectiveness of the proposed method has been proved by comparing with other state-of-the-art medical image segmentation methods.

Quantitative imaging features: extension of the oncology medical image database

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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.

18 CFR 1301.16 - Special procedures-medical records.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 18 Conservation of Power and Water Resources 2 2011-04-01 2011-04-01 false Special procedures-medical records. 1301.16 Section 1301.16 Conservation of Power and Water Resources TENNESSEE VALLEY... individual could have an adverse effect upon such individual, TVA may refuse to disclose such information...

12 CFR 1102.104 - Special procedure: Medical records.

Code of Federal Regulations, 2013 CFR

2013-01-01

... Subcommittee § 1102.104 Special procedure: Medical records. (a) Statement of physician or mental health... or a mental health professional indicating that, in his or her opinion, disclosure of the requested...) Designation of physician or mental health professional to receive records. If the ASC believes, in good faith...

12 CFR 1102.104 - Special procedure: Medical records.

Code of Federal Regulations, 2014 CFR

2014-01-01

... Subcommittee § 1102.104 Special procedure: Medical records. (a) Statement of physician or mental health... or a mental health professional indicating that, in his or her opinion, disclosure of the requested...) Designation of physician or mental health professional to receive records. If the ASC believes, in good faith...

12 CFR 1102.104 - Special procedure: Medical records.

Code of Federal Regulations, 2010 CFR

2010-01-01

... Subcommittee § 1102.104 Special procedure: Medical records. (a) Statement of physician or mental health... or a mental health professional indicating that, in his or her opinion, disclosure of the requested...) Designation of physician or mental health professional to receive records. If the ASC believes, in good faith...

12 CFR 1102.104 - Special procedure: Medical records.

Code of Federal Regulations, 2011 CFR

2011-01-01

... Subcommittee § 1102.104 Special procedure: Medical records. (a) Statement of physician or mental health... or a mental health professional indicating that, in his or her opinion, disclosure of the requested...) Designation of physician or mental health professional to receive records. If the ASC believes, in good faith...

12 CFR 1102.104 - Special procedure: Medical records.

Code of Federal Regulations, 2012 CFR

2012-01-01

... Subcommittee § 1102.104 Special procedure: Medical records. (a) Statement of physician or mental health... or a mental health professional indicating that, in his or her opinion, disclosure of the requested...) Designation of physician or mental health professional to receive records. If the ASC believes, in good faith...

Medical image segmentation based on SLIC superpixels model

NASA Astrophysics Data System (ADS)

Chen, Xiang-ting; Zhang, Fan; Zhang, Ruo-ya

2017-01-01

Medical imaging has been widely used in clinical practice. It is an important basis for medical experts to diagnose the disease. However, medical images have many unstable factors such as complex imaging mechanism, the target displacement will cause constructed defect and the partial volume effect will lead to error and equipment wear, which increases the complexity of subsequent image processing greatly. The segmentation algorithm which based on SLIC (Simple Linear Iterative Clustering, SLIC) superpixels is used to eliminate the influence of constructed defect and noise by means of the feature similarity in the preprocessing stage. At the same time, excellent clustering effect can reduce the complexity of the algorithm extremely, which provides an effective basis for the rapid diagnosis of experts.

Real-time image mosaicing for medical applications.

PubMed

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.

Medical imaging and registration in computer assisted surgery.

PubMed

Simon, D A; Lavallée, S

1998-09-01

Imaging, sensing, and computing technologies that are being introduced to aid in the planning and execution of surgical procedures are providing orthopaedic surgeons with a powerful new set of tools for improving clinical accuracy, reliability, and patient outcomes while reducing costs and operating times. Current computer assisted surgery systems typically include a measurement process for collecting patient specific medical data, a decision making process for generating a surgical plan, a registration process for aligning the surgical plan to the patient, and an action process for accurately achieving the goals specified in the plan. Some of the key concepts in computer assisted surgery applied to orthopaedics with a focus on the basic framework and underlying technologies is outlined. In addition, technical challenges and future trends in the field are discussed.

Assessment of Restoration Methods of X-Ray Images with Emphasis on Medical Photogrammetric Usage

NASA Astrophysics Data System (ADS)

Hosseinian, S.; Arefi, H.

2016-06-01

Nowadays, various medical X-ray imaging methods such as digital radiography, computed tomography and fluoroscopy are used as important tools in diagnostic and operative processes especially in the computer and robotic assisted surgeries. The procedures of extracting information from these images require appropriate deblurring and denoising processes on the pre- and intra-operative images in order to obtain more accurate information. This issue becomes more considerable when the X-ray images are planned to be employed in the photogrammetric processes for 3D reconstruction from multi-view X-ray images since, accurate data should be extracted from images for 3D modelling and the quality of X-ray images affects directly on the results of the algorithms. For restoration of X-ray images, it is essential to consider the nature and characteristics of these kinds of images. X-ray images exhibit severe quantum noise due to limited X-ray photons involved. The assumptions of Gaussian modelling are not appropriate for photon-limited images such as X-ray images, because of the nature of signal-dependant quantum noise. These images are generally modelled by Poisson distribution which is the most common model for low-intensity imaging. In this paper, existing methods are evaluated. For this purpose, after demonstrating the properties of medical X-ray images, the more efficient and recommended methods for restoration of X-ray images would be described and assessed. After explaining these approaches, they are implemented on samples from different kinds of X-ray images. By considering the results, it is concluded that using PURE-LET, provides more effective and efficient denoising than other examined methods in this research.

Client-side Medical Image Colorization in a Collaborative Environment.

PubMed

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

2015-01-01

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

Practicality of performing medical procedures in chemical protective ensembles.

PubMed

Garner, Alan; Laurence, Helen; Lee, Anna

2004-04-01

To determine whether certain life saving medical procedures can be successfully performed while wearing different levels of personal protective equipment (PPE), and whether these procedures can be performed in a clinically useful time frame. We assessed the capability of eight medical personnel to perform airway maintenance and antidote administration procedures on manikins, in all four described levels of PPE. The levels are: Level A--a fully encapsulated chemically resistant suit; Level B--a chemically resistant suit, gloves and boots with a full-faced positive pressure supplied air respirator; Level C--a chemically resistant splash suit, boots and gloves with an air-purifying positive or negative pressure respirator; Level D--a work uniform. Time in seconds to inflate the lungs of the manikin with bag-valve-mask, laryngeal mask airway (LMA) and endotracheal tube (ETT) were determined, as was the time to secure LMAs and ETTs with either tape or linen ties. Time to insert a cannula in a manikin was also determined. There was a significant difference in time taken to perform procedures in differing levels of personal protective equipment (F21,72 = 1.75, P = 0.04). Significant differences were found in: time to lung inflation using an endotracheal tube (A vs. C mean difference and standard error 75.6 +/- 23.9 s, P = 0.03; A vs. D mean difference and standard error 78.6 +/- 23.9 s, P = 0.03); time to insert a cannula (A vs. D mean difference and standard error 63.6 +/- 11.1 s, P < 0.001; C vs. D mean difference and standard error 40.0 +/- 11.1 s, P = 0.01). A significantly greater time to complete procedures was documented in Level A PPE (fully encapsulated suits) compared with Levels C and D. There was however, no significant difference in times between Level B and Level C. The common practice of equipping hospital and medical staff with only Level C protection should be re-evaluated.

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

PubMed

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

2017-10-01

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

Abdominal aortic aneurysms: pre- and post-procedural imaging.

PubMed

Hallett, Richard L; Ullery, Brant W; Fleischmann, Dominik

2018-05-01

Abdominal aortic aneurysm (AAA) is a relatively common, potentially life-threatening disorder. Rupture of AAA is potentially catastrophic with high mortality. Intervention for AAA is indicated when the aneurysm reaches 5.0-5.5 cm or more, when symptomatic, or when increasing in size > 10 mm/year. AAA can be accurately assessed by cross-sectional imaging including computed tomography angiography and magnetic resonance angiography. Current options for intervention in AAA patients include open surgery and endovascular aneurysm repair (EVAR), with EVAR becoming more prevalent over time. Cross-sectional imaging plays a crucial role in AAA surveillance, pre-procedural assessment, and post-EVAR management. This paper will discuss the current role of imaging in the assessment of AAA patients prior to intervention, in evaluation of procedural complications, and in long-term follow-up of EVAR patients.

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

PubMed

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.

19 CFR 201.27 - Special procedures: Medical records.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 19 Customs Duties 3 2011-04-01 2011-04-01 false Special procedures: Medical records. 201.27 Section 201.27 Customs Duties UNITED STATES INTERNATIONAL TRADE COMMISSION GENERAL RULES OF GENERAL... Act request to the Privacy Act Officer as called for in § 201.24(a) of this part, specify a physician...

19 CFR 201.27 - Special procedures: Medical records.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 19 Customs Duties 3 2010-04-01 2010-04-01 false Special procedures: Medical records. 201.27 Section 201.27 Customs Duties UNITED STATES INTERNATIONAL TRADE COMMISSION GENERAL RULES OF GENERAL... Act request to the Privacy Act Officer as called for in § 201.24(a) of this part, specify a physician...

Machine Learning in Medical Imaging.

PubMed

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.

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

PubMed

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

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

PubMed

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.

Visualization index for image-enabled medical records

NASA Astrophysics Data System (ADS)

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.

Image acquisition context: procedure description attributes for clinically relevant indexing and selective retrieval of biomedical images.

PubMed

Bidgood, W D; Bray, B; Brown, N; Mori, A R; Spackman, K A; Golichowski, A; Jones, R H; Korman, L; Dove, B; Hildebrand, L; Berg, M

1999-01-01

To support clinically relevant indexing of biomedical images and image-related information based on the attributes of image acquisition procedures and the judgments (observations) expressed by observers in the process of image interpretation. The authors introduce the notion of "image acquisition context," the set of attributes that describe image acquisition procedures, and present a standards-based strategy for utilizing the attributes of image acquisition context as indexing and retrieval keys for digital image libraries. The authors' indexing strategy is based on an interdependent message/terminology architecture that combines the Digital Imaging and Communication in Medicine (DICOM) standard, the SNOMED (Systematized Nomenclature of Human and Veterinary Medicine) vocabulary, and the SNOMED DICOM microglossary. The SNOMED DICOM microglossary provides context-dependent mapping of terminology to DICOM data elements. The capability of embedding standard coded descriptors in DICOM image headers and image-interpretation reports improves the potential for selective retrieval of image-related information. This favorably affects information management in digital libraries.

[An improved medical image fusion algorithm and quality evaluation].

PubMed

Chen, Meiling; Tao, Ling; Qian, Zhiyu

2009-08-01

Medical image fusion is of very important value for application in medical image analysis and diagnosis. In this paper, the conventional method of wavelet fusion is improved,so a new algorithm of medical image fusion is presented and the high frequency and low frequency coefficients are studied respectively. When high frequency coefficients are chosen, the regional edge intensities of each sub-image are calculated to realize adaptive fusion. The choice of low frequency coefficient is based on the edges of images, so that the fused image preserves all useful information and appears more distinctly. We apply the conventional and the improved fusion algorithms based on wavelet transform to fuse two images of human body and also evaluate the fusion results through a quality evaluation method. Experimental results show that this algorithm can effectively retain the details of information on original images and enhance their edge and texture features. This new algorithm is better than the conventional fusion algorithm based on wavelet transform.

A survey of medical image registration - under review.

PubMed

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

2016-10-01

A retrospective view on the past two decades of the field of medical image registration is presented, guided by the article "A survey of medical image registration" (Maintz and Viergever, 1998). It shows that the classification of the field introduced in that article is still usable, although some modifications to do justice to advances in the field would be due. The main changes over the last twenty years are the shift from extrinsic to intrinsic registration, the primacy of intensity-based registration, the breakthrough of nonlinear registration, the progress of inter-subject registration, and the availability of generic image registration software packages. Two problems that were called urgent already 20 years ago, are even more urgent nowadays: Validation of registration methods, and translation of results of image registration research to clinical practice. It may be concluded that the field of medical image registration has evolved, but still is in need of further development in various aspects. Copyright © 2016 Elsevier B.V. All rights reserved.

Adapting smartphones for low-cost optical medical imaging

NASA Astrophysics Data System (ADS)

Pratavieira, Sebastião.; Vollet-Filho, José D.; Carbinatto, Fernanda M.; Blanco, Kate; Inada, Natalia M.; Bagnato, Vanderlei S.; Kurachi, Cristina

2015-06-01

Optical images have been used in several medical situations to improve diagnosis of lesions or to monitor treatments. However, most systems employ expensive scientific (CCD or CMOS) cameras and need computers to display and save the images, usually resulting in a high final cost for the system. Additionally, this sort of apparatus operation usually becomes more complex, requiring more and more specialized technical knowledge from the operator. Currently, the number of people using smartphone-like devices with built-in high quality cameras is increasing, which might allow using such devices as an efficient, lower cost, portable imaging system for medical applications. Thus, we aim to develop methods of adaptation of those devices to optical medical imaging techniques, such as fluorescence. Particularly, smartphones covers were adapted to connect a smartphone-like device to widefield fluorescence imaging systems. These systems were used to detect lesions in different tissues, such as cervix and mouth/throat mucosa, and to monitor ALA-induced protoporphyrin-IX formation for photodynamic treatment of Cervical Intraepithelial Neoplasia. This approach may contribute significantly to low-cost, portable and simple clinical optical imaging collection.

Color transfer algorithm in medical images

NASA Astrophysics Data System (ADS)

Wang, Weihong; Xu, Yangfa

2007-12-01

In digital virtual human project, image data acquires from the freezing slice of human body specimen. The color and brightness between a group of images of a certain organ could be quite different. The quality of these images could bring great difficulty in edge extraction, segmentation, as well as 3D reconstruction process. Thus it is necessary to unify the color of the images. The color transfer algorithm is a good algorithm to deal with this kind of problem. This paper introduces the principle of this algorithm and uses it in the medical image processing.

The Handbook of Medical Image Perception and Techniques

NASA Astrophysics Data System (ADS)

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

The Handbook of Medical Image Perception and Techniques

NASA Astrophysics Data System (ADS)

Samei, Ehsan; Krupinski, Elizabeth

2009-12-01

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

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

PubMed

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.

Empirical analysis of domestic medical travel for elective cardiovascular procedures.

PubMed

Langley, Jacob D; Johnson, Tricia J; Hohmann, Samuel F; Meurer, Steve J; Garman, Andy N

2013-10-01

To investigate whether domestic medical travel (DMT; traveling outside of one's home region but within the United States for medical care) and surgeon volume affect clinical outcomes and costs for patients undergoing elective cardiovascular procedures. Retrospective, cross-sectional analysis of patient discharge data from US academic medical centers. Patients were classified as medical travelers if they received elective, nonemergent care more than 250 miles from home. High-volume surgeons (HVSs) were those above the 75th percentile compared with other study surgeons in the annual number of cardiovascular surgeries performed. Multivariable regression models were fit to test the relationships among complications, mortality, length of stay (LOS), cost, DMT status, and surgeon volume, controlling for sociodemographic and clinical factors. Patients who traveled to HVSs were more likely to be male, white, have lower severity of illness, and have health insurance through an indemnity plan or preferred provider organization with coverage outside of the patient's home region. Patients who traveled to HVSs had shorter LOS and fewer complications than those who received care from local, low-volume surgeons. There was no significant difference in mortality between travelers and nontravelers. Patients who travelled to HVSs for elective cardiovascular procedures had outcomes similar to or better than those of patients who received care locally from low-volume surgeons. We found no increase in complications or LOS, despite potentially complex logistical arrangements required by travelers. More work is needed to evaluate the potential of DMT to improve the value of care provided for selected procedures.

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

PubMed

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

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

PubMed Central

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

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

PubMed Central

Yin, HM; Sun, LZ; Wang, G; Yamada, T; Wang, J; Vannier, MW

2004-01-01

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. PMID:15461787

Improved Software to Browse the Serial Medical Images for Learning.

PubMed

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.

Metadata requirements for results of diagnostic imaging procedures: a BIIF profile to support user applications

NASA Astrophysics Data System (ADS)

Brown, Nicholas J.; Lloyd, David S.; Reynolds, Melvin I.; Plummer, David L.

2002-05-01

A visible digital image is rendered from a set of digital image data. Medical digital image data can be stored as either: (a) pre-rendered format, corresponding to a photographic print, or (b) un-rendered format, corresponding to a photographic negative. The appropriate image data storage format and associated header data (metadata) required by a user of the results of a diagnostic procedure recorded electronically depends on the task(s) to be performed. The DICOM standard provides a rich set of metadata that supports the needs of complex applications. Many end user applications, such as simple report text viewing and display of a selected image, are not so demanding and generic image formats such as JPEG are sometimes used. However, these are lacking some basic identification requirements. In this paper we make specific proposals for minimal extensions to generic image metadata of value in various domains, which enable safe use in the case of two simple healthcare end user scenarios: (a) viewing of text and a selected JPEG image activated by a hyperlink and (b) viewing of one or more JPEG images together with superimposed text and graphics annotation using a file specified by a profile of the ISO/IEC Basic Image Interchange Format (BIIF).

Medical Operations Console Procedure Evaluation: BME Response to Crew Call Down for an Emergency

NASA Technical Reports Server (NTRS)

Johnson-Troop; Pettys, Marianne; Hurst, Victor, IV; Smaka, Todd; Paul, Bonnie; Rosenquist, Kevin; Gast, Karin; Gillis, David; McCulley, Phyllis

2006-01-01

International Space Station (ISS) Mission Operations are managed by multiple flight control disciplines located at the lead Mission Control Center (MCC) at NASA-Johnson Space Center (JSC). ISS Medical Operations are supported by the complementary roles of Flight Surgeons (Surgeon) and Biomedical Engineer (BME) flight controllers. The Surgeon, a board certified physician, oversees all medical concerns of the crew and the BME provides operational and engineering support for Medical Operations Crew Health Care System. ISS Medical Operations is currently addressing the coordinated response to a crew call down for an emergent medical event, in particular when the BME is the only Medical Operations representative in MCC. In this case, the console procedure BME Response to Crew Call Down for an Emergency will be used. The procedure instructs the BME to contact a Surgeon as soon as possible, coordinate with other flight disciplines to establish a Private Medical Conference (PMC) for the crew and Surgeon, gather information from the crew if time permits, and provide Surgeon with pertinent console resources. It is paramount that this procedure is clearly written and easily navigated to assist the BME to respond consistently and efficiently. A total of five BME flight controllers participated in the study. Each BME participant sat in a simulated MCC environment at a console configured with resources specific to the BME MCC console and was presented with two scripted emergency call downs from an ISS crew member. Each participant used the procedure while interacting with analog MCC disciplines to respond to the crew call down. Audio and video recordings of the simulations were analyzed and each BME participant's actions were compared to the procedure. Structured debriefs were conducted at the conclusion of both simulations. The procedure was evaluated for its ability to elicit consistent responses from each BME participant. Trials were examined for deviations in procedure task

FAST: framework for heterogeneous medical image computing and visualization.

PubMed

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.

A Review on Medical Image Registration as an Optimization Problem

PubMed Central

Song, Guoli; Han, Jianda; Zhao, Yiwen; Wang, Zheng; Du, Huibin

2017-01-01

Objective: In the course of clinical treatment, several medical media are required by a phy-sician in order to provide accurate and complete information about a patient. Medical image registra-tion techniques can provide a richer diagnosis and treatment information to doctors and to provide a comprehensive reference source for the researchers involved in image registration as an optimization problem. Methods: The essence of image registration is associating two or more different images spatial asso-ciation, and getting the translation of their spatial relationship. For medical image registration, its pro-cess is not absolute. Its core purpose is finding the conversion relationship between different images. Result: The major step of image registration includes the change of geometrical dimensions, and change of the image of the combination, image similarity measure, iterative optimization and interpo-lation process. Conclusion: The contribution of this review is sort of related image registration research methods, can provide a brief reference for researchers about image registration. PMID:28845149

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

PubMed

Fesharaki, Nooshin Jafari; Pourghassem, Hossein

2013-07-01

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

Request redirection paradigm in medical image archive implementation.

PubMed

Dragan, Dinu; Ivetić, Dragan

2012-08-01

It is widely recognized that the JPEG2000 facilitates issues in medical imaging: storage, communication, sharing, remote access, interoperability, and presentation scalability. Therefore, JPEG2000 support was added to the DICOM standard Supplement 61. Two approaches to support JPEG2000 medical image are explicitly defined by the DICOM standard: replacing the DICOM image format with corresponding JPEG2000 codestream, or by the Pixel Data Provider service, DICOM supplement 106. The latest one supposes two-step retrieval of medical image: DICOM request and response from a DICOM server, and then JPIP request and response from a JPEG2000 server. We propose a novel strategy for transmission of scalable JPEG2000 images extracted from a single codestream over DICOM network using the DICOM Private Data Element without sacrificing system interoperability. It employs the request redirection paradigm: DICOM request and response from JPEG2000 server through DICOM server. The paper presents programming solution for implementation of request redirection paradigm in a DICOM transparent manner. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

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

PubMed

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.

Promoting medical tourism to India: messages, images, and the marketing of international patient travel.

PubMed

Crooks, Valorie A; Turner, Leigh; Snyder, Jeremy; Johnston, Rory; Kingsbury, Paul

2011-03-01

The practice of medical tourism depends on successfully informing potential patients about procedure options, treatment facilities, tourism opportunities, travel arrangements, and destination countries. The promotion of medical tourism includes a wide range of marketing materials such as flyers, booklets, and websites. Yet, there is a paucity of knowledge about the dissemination, content, and reception of these promotional materials. Drawing on a thematic content analysis of the promotional print material distributed at the first medical tourism trade show in Canada in 2009, the main purpose of this article is to identify and understand the messages and images that companies use to market India as a global destination. While researchers and news media frequently cite low cost procedures as a key determinant for international patient travel, particularly to developing nations, our analysis reveals few low cost-related images or messages in the promotional materials distributed at the trade show. To help explain this surprising disjuncture, we consider four related issues: (1) promotional materials may be designed to be circulated amongst potential patients' concerned family and friends who privilege knowing about things such as the use of advanced technologies; (2) developing nations need to portray safe and advanced treatment facilities in order to dispel potential patients' suspicions that their medical care is inferior; (3) companies may avoid making cost saving claims that cannot be fulfilled for all of their international patients, especially those traveling from developing nations; and (4) messages of low cost may detract from and even undermine messages about quality. We conclude by identifying numerous avenues for future research by social and health scientists, and by considering the implications of our findings for existing knowledge gaps and debates within health geography specifically. Copyright © 2011 Elsevier Ltd. All rights reserved.

Automatic glaucoma diagnosis through medical imaging informatics.

PubMed

Liu, Jiang; Zhang, Zhuo; Wong, Damon Wing Kee; Xu, Yanwu; Yin, Fengshou; Cheng, Jun; Tan, Ngan Meng; Kwoh, Chee Keong; Xu, Dong; Tham, Yih Chung; Aung, Tin; Wong, Tien Yin

2013-01-01

Computer-aided diagnosis for screening utilizes computer-based analytical methodologies to process patient information. Glaucoma is the leading irreversible cause of blindness. Due to the lack of an effective and standard screening practice, more than 50% of the cases are undiagnosed, which prevents the early treatment of the disease. To design an automatic glaucoma diagnosis architecture automatic glaucoma diagnosis through medical imaging informatics (AGLAIA-MII) that combines patient personal data, medical retinal fundus image, and patient's genome information for screening. 2258 cases from a population study were used to evaluate the screening software. These cases were attributed with patient personal data, retinal images and quality controlled genome data. Utilizing the multiple kernel learning-based classifier, AGLAIA-MII, combined patient personal data, major image features, and important genome single nucleotide polymorphism (SNP) features. Receiver operating characteristic curves were plotted to compare AGLAIA-MII's performance with classifiers using patient personal data, images, and genome SNP separately. AGLAIA-MII was able to achieve an area under curve value of 0.866, better than 0.551, 0.722 and 0.810 by the individual personal data, image and genome information components, respectively. AGLAIA-MII also demonstrated a substantial improvement over the current glaucoma screening approach based on intraocular pressure. AGLAIA-MII demonstrates for the first time the capability of integrating patients' personal data, medical retinal image and genome information for automatic glaucoma diagnosis and screening in a large dataset from a population study. It paves the way for a holistic approach for automatic objective glaucoma diagnosis and screening.

Object-oriented design of medical imaging software.

PubMed

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.

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

PubMed

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.

New image-processing and noise-reduction software reduces radiation dose during complex endovascular procedures.

PubMed

Kirkwood, Melissa L; Guild, Jeffrey B; Arbique, Gary M; Tsai, Shirling; Modrall, J Gregory; Anderson, Jon A; Rectenwald, John; Timaran, Carlos

2016-11-01

A new proprietary image-processing system known as AlluraClarity, developed by Philips Healthcare (Best, The Netherlands) for radiation-based interventional procedures, claims to lower radiation dose while preserving image quality using noise-reduction algorithms. This study determined whether the surgeon and patient radiation dose during complex endovascular procedures (CEPs) is decreased after the implementation of this new operating system. Radiation dose to operators, procedure type, reference air kerma, kerma area product, and patient body mass index were recorded during CEPs on two Philips Allura FD 20 fluoroscopy systems with and without Clarity. Operator dose during CEPs was measured using optically stimulable, luminescent nanoDot (Landauer Inc, Glenwood, Ill) detectors placed outside the lead apron at the left upper chest position. nanoDots were read using a microStar ii (Landauer Inc) medical dosimetry system. For the CEPs in the Clarity group, the radiation dose to surgeons was also measured by the DoseAware (Philips Healthcare) personal dosimetry system. Side-by-side measurements of DoseAware and nanoDots allowed for cross-calibration between systems. Operator effective dose was determined using a modified Niklason algorithm. To control for patient size and case complexity, the average fluoroscopy dose rate and the dose per radiographic frame were adjusted for body mass index differences and then compared between the groups with and without Clarity by procedure. Additional factors, for example, physician practice patterns, that may have affected operator dose were inferred by comparing the ratio of the operator dose to procedural kerma area product with and without Clarity. A one-sided Wilcoxon rank sum test was used to compare groups for radiation doses, reference air kermas, and operating practices for each procedure type. The analysis included 234 CEPs; 95 performed without Clarity and 139 with Clarity. Practice patterns of operators during

Near-infrared spectroscopic tissue imaging for medical applications

DOEpatents

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

2006-03-21

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.

Near-infrared spectroscopic tissue imaging for medical applications

DOEpatents

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.

[Video recording system of endoscopic procedures for digital forensics].

PubMed

Endo, Chiaki; Sakurada, A; Kondo, T

2009-07-01

Recently, endoscopic procedures including surgery, intervention, and examination have been widely performed. Medical practitioners are required to record the procedures precisely in order to check the procedures retrospectively and to get the legally reliable record. Medical Forensic System made by KS Olympus Japan offers 2 kinds of movie and patient's data, such as heart rate, blood pressure, and Spo, which are simultaneously recorded. We installed this system into the bronchoscopy room and have experienced its benefit. Under this system, we can get bronchoscopic image, bronchoscopy room view, and patient's data simultaneously. We can check the quality of the bronchoscopic procedures retrospectively, which is useful for bronchoscopy staff training. Medical Forensic System should be installed in any kind of endoscopic procedures.

Etiology of Readmissions Following Orthopaedic Procedures and Medical Admissions. A Comparative Analysis.

PubMed

Maslow, Jed; Hutzler, Lorraine; Slover, James; Bosco, Joseph

2015-12-01

The Federal Government, the largest payer of health care, considers readmission within 30 days of discharge an indicator of quality of care. Many studies have focused on causes for and strategies to reduce readmissions following medical admissions. However, few studies have focused on the differences between them. We believe that the causes for readmission following orthopaedic surgery are markedly different than those following medical admissions, and therefore, the strategies developed to reduce medical readmissions will not be as effective in reducing readmissions after elective orthopaedic surgery. All unplanned 30-day readmissions following an index hospitalization for an elective orthopaedic procedure (primary and revision total joint arthroplasty and spine procedure) or for one of the three publicly reported medical conditions (AMI, HF, and pneumonia, which accounted for 11% of readmissions) were identified at our institution from 2010 through 2012. A total of 268 patients and 390 medical patients were identified as having an unplanned 30-day readmission. We reviewed a prospectively collected data base to determine the reason for readmission in each encounter. A total of 233 (86.9%) orthopaedic patients were readmitted for surgical complications, most commonly for a wound infection (56.0%) or wound complication (11.6%). Following an index admission of HF or AMI, the primary reason for readmission was a disease of the circulatory system (55.9% and 57.4%, respectively). Following an index admission for pneumonia, the primary reason for readmission was a disease of the respiratory system (34.5%). The causes of readmissions following orthopaedic surgery and medical admissions are different. Patients undergoing orthopaedic procedures are readmitted for surgical complications, frequently unrelated to aftercare, and medicine patients are readmitted for reasons related to the index diagnosis. Interventions designed to reduce orthopaedic readmissions must focus on

Challenges for data storage in medical imaging research.

PubMed

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.

Flexible medical image management using service-oriented architecture.

PubMed

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

2012-01-01

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

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

PubMed

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.

Transforming medical imaging applications into collaborative PACS-based telemedical systems

NASA Astrophysics Data System (ADS)

Maani, Rouzbeh; Camorlinga, Sergio; Arnason, Neil

2011-03-01

Telemedical systems are not practical for use in a clinical workflow unless they are able to communicate with the Picture Archiving and Communications System (PACS). On the other hand, there are many medical imaging applications that are not developed as telemedical systems. Some medical imaging applications do not support collaboration and some do not communicate with the PACS and therefore limit their usability in clinical workflows. This paper presents a general architecture based on a three-tier architecture model. The architecture and the components developed within it, transform medical imaging applications into collaborative PACS-based telemedical systems. As a result, current medical imaging applications that are not telemedical, not supporting collaboration, and not communicating with PACS, can be enhanced to support collaboration among a group of physicians, be accessed remotely, and be clinically useful. The main advantage of the proposed architecture is that it does not impose any modification to the current medical imaging applications and does not make any assumptions about the underlying architecture or operating system.

A web-based solution for 3D medical image visualization

NASA Astrophysics Data System (ADS)

Hou, Xiaoshuai; Sun, Jianyong; Zhang, Jianguo

2015-03-01

In this presentation, we present a web-based 3D medical image visualization solution which enables interactive large medical image data processing and visualization over the web platform. To improve the efficiency of our solution, we adopt GPU accelerated techniques to process images on the server side while rapidly transferring images to the HTML5 supported web browser on the client side. Compared to traditional local visualization solution, our solution doesn't require the users to install extra software or download the whole volume dataset from PACS server. By designing this web-based solution, it is feasible for users to access the 3D medical image visualization service wherever the internet is available.

A Comparison of Standard-Setting Procedures for an OSCE in Undergraduate Medical Education.

ERIC Educational Resources Information Center

Kaufman, David M.; Mann, Karen V.; Muijtjens, Arno M. M.; van der Vleuten, Cees P. M.

2000-01-01

Compared four standard-setting procedures for an objective structure clinical examination (OSCE) in medical education. Applied Angoff, borderline, relative, and holistic procedures to the data used to establish a cutoff score for a pass/fail decision. The Angoff and borderline procedures gave similar results; however, the relative and holistic…

Knowledge representation for fuzzy inference aided medical image interpretation.

PubMed

Gal, Norbert; Stoicu-Tivadar, Vasile

2012-01-01

Knowledge defines how an automated system transforms data into information. This paper suggests a representation method of medical imaging knowledge using fuzzy inference systems coded in XML files. The imaging knowledge incorporates features of the investigated objects in linguistic form and inference rules that can transform the linguistic data into information about a possible diagnosis. A fuzzy inference system is used to model the vagueness of the linguistic medical imaging terms. XML files are used to facilitate easy manipulation and deployment of the knowledge into the imaging software. Preliminary results are presented.

The application of coded excitation technology in medical ultrasonic Doppler imaging

NASA Astrophysics Data System (ADS)

Li, Weifeng; Chen, Xiaodong; Bao, Jing; Yu, Daoyin

2008-03-01

Medical ultrasonic Doppler imaging is one of the most important domains of modern medical imaging technology. The application of coded excitation technology in medical ultrasonic Doppler imaging system has the potential of higher SNR and deeper penetration depth than conventional pulse-echo imaging system, it also improves the image quality, and enhances the sensitivity of feeble signal, furthermore, proper coded excitation is beneficial to received spectrum of Doppler signal. Firstly, this paper analyzes the application of coded excitation technology in medical ultrasonic Doppler imaging system abstractly, showing the advantage and bright future of coded excitation technology, then introduces the principle and the theory of coded excitation. Secondly, we compare some coded serials (including Chirp and fake Chirp signal, Barker codes, Golay's complementary serial, M-sequence, etc). Considering Mainlobe Width, Range Sidelobe Level, Signal-to-Noise Ratio and sensitivity of Doppler signal, we choose Barker codes as coded serial. At last, we design the coded excitation circuit. The result in B-mode imaging and Doppler flow measurement coincided with our expectation, which incarnated the advantage of application of coded excitation technology in Digital Medical Ultrasonic Doppler Endoscope Imaging System.

User Oriented Platform for Data Analytics in Medical Imaging Repositories.

PubMed

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.

Performance assessment of 3D surface imaging technique for medical imaging applications

NASA Astrophysics Data System (ADS)

Li, Tuotuo; Geng, Jason; Li, Shidong

2013-03-01

Recent development in optical 3D surface imaging technologies provide better ways to digitalize the 3D surface and its motion in real-time. The non-invasive 3D surface imaging approach has great potential for many medical imaging applications, such as motion monitoring of radiotherapy, pre/post evaluation of plastic surgery and dermatology, to name a few. Various commercial 3D surface imaging systems have appeared on the market with different dimension, speed and accuracy. For clinical applications, the accuracy, reproducibility and robustness across the widely heterogeneous skin color, tone, texture, shape properties, and ambient lighting is very crucial. Till now, a systematic approach for evaluating the performance of different 3D surface imaging systems still yet exist. In this paper, we present a systematic performance assessment approach to 3D surface imaging system assessment for medical applications. We use this assessment approach to exam a new real-time surface imaging system we developed, dubbed "Neo3D Camera", for image-guided radiotherapy (IGRT). The assessments include accuracy, field of view, coverage, repeatability, speed and sensitivity to environment, texture and color.

[Medical image segmentation based on the minimum variation snake model].

PubMed

Zhou, Changxiong; Yu, Shenglin

2007-02-01

It is difficult for traditional parametric active contour (Snake) model to deal with automatic segmentation of weak edge medical image. After analyzing snake and geometric active contour model, a minimum variation snake model was proposed and successfully applied to weak edge medical image segmentation. This proposed model replaces constant force in the balloon snake model by variable force incorporating foreground and background two regions information. It drives curve to evolve with the criterion of the minimum variation of foreground and background two regions. Experiments and results have proved that the proposed model is robust to initial contours placements and can segment weak edge medical image automatically. Besides, the testing for segmentation on the noise medical image filtered by curvature flow filter, which preserves edge features, shows a significant effect.

Tools used to assess medical students competence in procedural skills at the end of a primary medical degree: a systematic review.

PubMed

Morris, Marie C; Gallagher, Tom K; Ridgway, Paul F

2012-01-01

The objective was to systematically review the literature to identify and grade tools used for the end point assessment of procedural skills (e.g., phlebotomy, IV cannulation, suturing) competence in medical students prior to certification. The authors searched eight bibliographic databases electronically - ERIC, Medline, CINAHL, EMBASE, Psychinfo, PsychLIT, EBM Reviews and the Cochrane databases. Two reviewers independently reviewed the literature to identify procedural assessment tools used specifically for assessing medical students within the PRISMA framework, the inclusion/exclusion criteria and search period. Papers on OSATS and DOPS were excluded as they focused on post-registration assessment and clinical rather than simulated competence. Of 659 abstracted articles 56 identified procedural assessment tools. Only 11 specifically assessed medical students. The final 11 studies consisted of 1 randomised controlled trial, 4 comparative and 6 descriptive studies yielding 12 heterogeneous procedural assessment tools for analysis. Seven tools addressed four discrete pre-certification skills, basic suture (3), airway management (2), nasogastric tube insertion (1) and intravenous cannulation (1). One tool used a generic assessment of procedural skills. Two tools focused on postgraduate laparoscopic skills and one on osteopathic students and thus were not included in this review. The levels of evidence are low with regard to reliability - κ = 0.65-0.71 and minimum validity is achieved - face and content. In conclusion, there are no tools designed specifically to assess competence of procedural skills in a final certification examination. There is a need to develop standardised tools with proven reliability and validity for assessment of procedural skills competence at the end of medical training. Medicine graduates must have comparable levels of procedural skills acquisition entering the clinical workforce irrespective of the country of training.

Refinement procedure for the image alignment in high-resolution electron tomography.

PubMed

Houben, L; Bar Sadan, M

2011-01-01

High-resolution electron tomography from a tilt series of transmission electron microscopy images requires an accurate image alignment procedure in order to maximise the resolution of the tomogram. This is the case in particular for ultra-high resolution where even very small misalignments between individual images can dramatically reduce the fidelity of the resultant reconstruction. A tomographic-reconstruction based and marker-free method is proposed, which uses an iterative optimisation of the tomogram resolution. The method utilises a search algorithm that maximises the contrast in tomogram sub-volumes. Unlike conventional cross-correlation analysis it provides the required correlation over a large tilt angle separation and guarantees a consistent alignment of images for the full range of object tilt angles. An assessment based on experimental reconstructions shows that the marker-free procedure is competitive to the reference of marker-based procedures at lower resolution and yields sub-pixel accuracy even for simulated high-resolution data. Copyright © 2011 Elsevier B.V. All rights reserved.

Chapter 8. Medical procedures. Recommendations and standard operating procedures for intensive care unit and hospital preparations for an influenza epidemic or mass disaster.

PubMed

Zimmerman, Janice L; Sprung, Charles L

2010-04-01

To provide recommendations and standard operating procedures for intensive care unit and hospital preparations for an influenza pandemic or mass disaster with a specific focus on ensuring that adequate resources are available and appropriate protocols are developed to safely perform procedures in patients with and without influenza illness. Based on a literature review and expert opinion, a Delphi process was used to define the essential topics including performing medical procedures. Key recommendations include: (1) specify high-risk procedures (aerosol generating-procedures); (2) determine if certain procedures will not be performed during a pandemic; (3) develop protocols for safe performance of high-risk procedures that include appropriateness, qualifications of personnel, site, personal protection equipment, safe technique and equipment needs; (4) ensure adequate training of personnel in high-risk procedures; (5) procedures should be performed at the bedside whenever possible; (6) ensure safe respiratory therapy practices to avoid aerosols; (7) provide safe respiratory equipment; and (8) determine criteria for cancelling and/or altering elective procedures. Judicious planning and adoption of protocols for safe performance of medical procedures are necessary to optimize outcomes during a pandemic.

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

PubMed

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

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

PubMed

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.

An efficient early phase 2 procedure to screen medications for efficacy in smoking cessation.

PubMed

Perkins, Kenneth A; Lerman, Caryn

2014-01-01

Initial screening of new medications for potential efficacy (i.e., Food and Drug Administration (FDA) early phase 2), such as in aiding smoking cessation, should be efficient in identifying which drugs do, or do not, warrant more extensive (and expensive) clinical testing. This focused review outlines our research on development, evaluation, and validation of an efficient crossover procedure for sensitivity in detecting medication efficacy for smoking cessation. First-line FDA-approved medications of nicotine patch, varenicline, and bupropion were tested as model drugs, in three separate placebo-controlled studies. We also tested specificity of our procedure in identifying a drug that lacks efficacy, using modafinil. This crossover procedure showed sensitivity (increased days of abstinence) during week-long "practice" quit attempts with each of the active cessation medications (positive controls) versus placebo, but not with modafinil (negative control) versus placebo, as hypothesized. Sensitivity to medication efficacy signal was observed only in smokers high in intrinsic quit motivation (i.e., already preparing to quit soon) and not smokers low in intrinsic quit motivation, even if monetarily reinforced for abstinence (i.e., given extrinsic motivation). A crossover procedure requiring less time and fewer subjects than formal trials may provide an efficient strategy for a go/no-go decision whether to advance to subsequent phase 2 randomized clinical trials with a novel drug. Future research is needed to replicate our results and evaluate this procedure with novel compounds, identify factors that may limit its utility, and evaluate its applicability to testing efficacy of compounds for treating other forms of addiction.

Integration of medical imaging into a multi-institutional hospital information system structure.

PubMed

Dayhoff, R E

1995-01-01

The Department of Veterans Affairs (VA) is providing integrated text and image data to its clinical users at its Washington and Baltimore medical centers and, soon, at nine other medical centers. The DHCP Imaging System records clinically significant diagnostic images selected by medical specialists in a variety of departments, including cardiology, gastroenterology, pathology, dermatology, surgery, radiology, podiatry, dentistry, and emergency medicine. These images, which include color and gray scale images, and electrocardiogram waveforms, are displayed on workstations located throughout the medical centers. Integration of clinical images with the VA's electronic mail system allows transfer of data from one medical center to another. The ability to incorporate transmitted text and image data into on-line patient records at the collaborating sites is an important aspect of professional consultation. In order to achieve the maximum benefits from an integrated patient record system, a critical mass of information must be available for clinicians. When there is also seamless support for administration, it becomes possible to re-engineer the processes involved in providing medical care.

Medical Image Authentication Using DPT Watermarking: A Preliminary Attempt

NASA Astrophysics Data System (ADS)

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

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

Medical image security using modified chaos-based cryptography approach

NASA Astrophysics Data System (ADS)

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.

Novel application of simultaneous multi-image display during complex robotic abdominal procedures

PubMed Central

2014-01-01

Background The surgical robot offers the potential to integrate multiple views into the surgical console screen, and for the assistant’s monitors to provide real-time views of both fields of operation. This function has the potential to increase patient safety and surgical efficiency during an operation. Herein, we present a novel application of the multi-image display system for simultaneous visualization of endoscopic views during various complex robotic gastrointestinal operations. All operations were performed using the da Vinci Surgical System (Intuitive Surgical, Sunnyvale, CA, USA) with the assistance of Tilepro, multi-input display software, during employment of the intraoperative scopes. Three robotic operations, left hepatectomy with intraoperative common bile duct exploration, low anterior resection, and radical distal subtotal gastrectomy with intracorporeal gastrojejunostomy, were performed by three different surgeons at a tertiary academic medical center. Results The three complex robotic abdominal operations were successfully completed without difficulty or intraoperative complications. The use of the Tilepro to simultaneously visualize the images from the colonoscope, gastroscope, and choledochoscope made it possible to perform additional intraoperative endoscopic procedures without extra monitors or interference with the operations. Conclusion We present a novel use of the multi-input display program on the da Vinci Surgical System to facilitate the performance of intraoperative endoscopies during complex robotic operations. Our study offers another potentially beneficial application of the robotic surgery platform toward integration and simplification of combining additional procedures with complex minimally invasive operations. PMID:24628761

Academic medical libraries' policies and procedures for notifying library users of retracted scientific publications.

PubMed

Hughes, C

1998-01-01

Academic medical libraries have a responsibility to inform library users regarding retracted publications. Many have created policies and procedures that identify flawed journal articles. A questionnaire was sent to the 129 academic medical libraries in the United States and Canada to find out how many had policies and procedures for identifying retracted publications. Of the returned questionnaires, 59% had no policy and no practice for calling the attention of the library user to retracted publications. Forty-one percent of the libraries called attention to retractions with or without a formal policy for doing so. Several responding libraries included their policy statement with the survey. The increasing number of academic medical libraries that realize the importance of having policies and practices in place highlights the necessity for this procedure.

Selection and Presentation of Imaging Figures in the Medical Literature

PubMed Central

Siontis, George C. M.; Patsopoulos, Nikolaos A.; Vlahos, Antonios P.; Ioannidis, John P. A.

2010-01-01

Background Images are important for conveying information, but there is no empirical evidence on whether imaging figures are properly selected and presented in the published medical literature. We therefore evaluated the selection and presentation of radiological imaging figures in major medical journals. Methodology/Principal Findings We analyzed articles published in 2005 in 12 major general and specialty medical journals that had radiological imaging figures. For each figure, we recorded information on selection, study population, provision of quantitative measurements, color scales and contrast use. Overall, 417 images from 212 articles were analyzed. Any comment/hint on image selection was made in 44 (11%) images (range 0–50% across the 12 journals) and another 37 (9%) (range 0–60%) showed both a normal and abnormal appearance. In 108 images (26%) (range 0–43%) it was unclear whether the image came from the presented study population. Eighty-three images (20%) (range 0–60%) had any quantitative or ordered categorical value on a measure of interest. Information on the distribution of the measure of interest in the study population was given in 59 cases. For 43 images (range 0–40%), a quantitative measurement was provided for the depicted case and the distribution of values in the study population was also available; in those 43 cases there was no over-representation of extreme than average cases (p = 0.37). Significance The selection and presentation of images in the medical literature is often insufficiently documented; quantitative data are sparse and difficult to place in context. PMID:20526360

[Exploring the dark continent: medical image and brain].

PubMed

Garcia-Molina, A; Ensenat, A

2017-04-01

Until the late 19th century, direct observation of the central nervous system was practically impossible. The discovery of X-rays in 1895 and their subsequent application in the field of medicine brought about a shift of paradigm that completely revolutionised the way in which neurology was practised. The possibility of viewing the inside of the brain had a pronounced impact on clinical practice, and enriched the diagnosis and treatment of brain pathologies in a manner that was unimaginable up until then. The aim of this study is to describe the birth and development of medical imaging of the brain, from the discovery of X-rays and the early days of radiography to the appearance of computerised tomography and magnetic resonance in the 60s, both of which are techniques that were to change the world of diagnostic imaging forever. This brief overview of the history of radiology also includes the origins of angiography and other techniques that are no longer in use, but which were ground-breaking innovations in their time, such as ventriculography or pneumoencephalography. The procedures and techniques described in this article made it possible to view the inside of the brain, thereby facilitating the diagnosis and treatment of a number of neurological processes.

A RESTful image gateway for multiple medical image repositories.

PubMed

Valente, Frederico; Viana-Ferreira, Carlos; Costa, Carlos; Oliveira, José Luis

2012-05-01

Mobile technologies are increasingly important components in telemedicine systems and are becoming powerful decision support tools. Universal access to data may already be achieved by resorting to the latest generation of tablet devices and smartphones. However, the protocols employed for communicating with image repositories are not suited to exchange data with mobile devices. In this paper, we present an extensible approach to solving the problem of querying and delivering data in a format that is suitable for the bandwidth and graphic capacities of mobile devices. We describe a three-tiered component-based gateway that acts as an intermediary between medical applications and a number of Picture Archiving and Communication Systems (PACS). The interface with the gateway is accomplished using Hypertext Transfer Protocol (HTTP) requests following a Representational State Transfer (REST) methodology, which relieves developers from dealing with complex medical imaging protocols and allows the processing of data on the server side.

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

ERIC Educational Resources Information Center

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…

Multimodal Medical Image Fusion by Adaptive Manifold Filter.

PubMed

Geng, Peng; Liu, Shuaiqi; Zhuang, Shanna

2015-01-01

Medical image fusion plays an important role in diagnosis and treatment of diseases such as image-guided radiotherapy and surgery. The modified local contrast information is proposed to fuse multimodal medical images. Firstly, the adaptive manifold filter is introduced into filtering source images as the low-frequency part in the modified local contrast. Secondly, the modified spatial frequency of the source images is adopted as the high-frequency part in the modified local contrast. Finally, the pixel with larger modified local contrast is selected into the fused image. The presented scheme outperforms the guided filter method in spatial domain, the dual-tree complex wavelet transform-based method, nonsubsampled contourlet transform-based method, and four classic fusion methods in terms of visual quality. Furthermore, the mutual information values by the presented method are averagely 55%, 41%, and 62% higher than the three methods and those values of edge based similarity measure by the presented method are averagely 13%, 33%, and 14% higher than the three methods for the six pairs of source images.

Improved Software to Browse the Serial Medical Images for Learning

PubMed Central

2017-01-01

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. PMID:28581279

Is airport baggage inspection just another medical image?

NASA Astrophysics Data System (ADS)

Gale, Alastair G.; Mugglestone, Mark D.; Purdy, Kevin J.; McClumpha, A.

2000-04-01

A similar inspection situation to medical imaging appears to be that of the airport security screener who examines X-ray images of passenger baggage. There is, however, little research overlap between the two areas. Studies of observer performance in examining medical images have led to a conceptual model which has been used successfully to understand diagnostic errors and develop appropriate training strategies. The model stresses three processes of; visual search, detection of potential targets, and interpretation of these areas; with most errors being due to the latter two factors. An initial study is reported on baggage inspection, using several brief image presentations, to examine the applicability of such a medical model to this domain. The task selected was the identification of potential Improvised Explosive Devices (IEDs). Specifically investigated was the visual search behavior of inspectors. It was found that IEDs could be identified in a very brief image presentation, with increased presentation time this performance improved. Participants fixated on IEDs very early on and sometimes concentrated wholly on this part of the baggage display. When IEDs were missed this was mainly due to interpretative factors rather than visual search or IED detection. It is argued that the observer model can be applied successfully to this scenario.

Medical Image Analysis Facility

NASA Technical Reports Server (NTRS)

1978-01-01

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

Medical imaging.

PubMed Central

Kreel, L.

1991-01-01

There is now a wide choice of medical imaging to show both focal and diffuse pathologies in various organs. Conventional radiology with plain films, fluoroscopy and contrast medium have many advantages, being readily available with low-cost apparatus and a familiarity that almost leads to contempt. The use of plain films in chest disease and in trauma does not need emphasizing, yet there are still too many occasions when the answer obtainable from a plain radiograph has not been available. The film may have been mislaid, or the examination was not requested, or the radiograph had been misinterpreted. The converse is also quite common. Examinations are performed that add nothing to patient management, such as skull films when CT will in any case be requested or views of the internal auditory meatus and heal pad thickness in acromegaly, to quote some examples. Other issues are more complicated. Should the patient who clinically has gall-bladder disease have more than a plain film that shows gall-stones? If the answer is yes, then why request a plain film if sonography will in any case be required to 'exclude' other pathologies especially of the liver or pancreas? But then should cholecystography, CT or scintigraphy be added for confirmation? Quite clearly there will be individual circumstances to indicate further imaging after sonography but in the vast majority of patients little or no extra information will be added. Statistics on accuracy and specificity will, in the case of gall-bladder pathology, vary widely if adenomyomatosis is considered by some to be a cause of symptoms or if sonographic examinations 'after fatty meals' are performed. The arguments for or against routine contrast urography rather than sonography are similar but the possibility of contrast reactions and the need to limit ionizing radiation must be borne in mind. These diagnostic strategies are also being influenced by their cost and availability; purely pragmatic considerations are not

Physical And Medical Attributes Of Six Contemporary Noninvasive Imaging Techniques

NASA Astrophysics Data System (ADS)

Budinger, Thomas F.

1981-11-01

Digital subtraction angiography(DSA)is compared to five other noninvasive imaging methods with respect to physical attributes and medical applications. 1) Digital subtraction angiography measures flow channel (vessel) anatomy and vascular leaks in regions where signals from under and overlying vascular pools do not conflict in strength with the vessel or tissue of interest. 2) X-ray computed tomography, in principle, can separate the under and overlying signals, yet presently it is limited in speed, axial coverage, and computational burden for tasks DSA can efficiently perform. Possible exceptions are the dynamic spatial reconstructor (DSR) of Mayo Clinic and the system under construction at the University of California, San Francisco. 3) Heavy ion imaging measures electron density and is less sensitive to injected contrast than x-ray imaging which has the advantage of the photoelectric effect. A unique attribute of heavy ion imaging is its potential for treatment planning and the fact that beam hardening is not a physical problem. 4) Ultrasound detects surfaces, bulk tissue characteristics, and blood velocity. Doppler ultrasound competes with DSA in some regions of the body and generally involves less equipment and patient procedures. Ultrasound vessel imaging and range-gated Doppler have limitations due to sound absorption by atheromatous tissue and available imaging windows. 5) Emission tomography measures receptor site distribution, metabolism, permeability, and tissue perfusion. Resolution is limited to 7mm full width half maximum (FWHM) in the near future, and extraction of metabolic and perfusion information usually requires kinetic analyses with statistically poor data. The ability of positron tomography to measure metabolism (sugar, fatty acid, and oxygen utilization) and the ability to measure tissue perfusion with single photon tomography (17 mm FWHM) or PET (7 mm FWHM) using non-cyclotron produced radionuclides are the major unique features of emission

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

NASA Astrophysics Data System (ADS)

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.

[Design of visualized medical images network and web platform based on MeVisLab].

PubMed

Xiang, Jun; Ye, Qing; Yuan, Xun

2017-04-01

With the trend of the development of "Internet +", some further requirements for the mobility of medical images have been required in the medical field. In view of this demand, this paper presents a web-based visual medical imaging platform. First, the feasibility of medical imaging is analyzed and technical points. CT (Computed Tomography) or MRI (Magnetic Resonance Imaging) images are reconstructed three-dimensionally by MeVisLab and packaged as X3D (Extensible 3D Graphics) files shown in the present paper. Then, the B/S (Browser/Server) system specially designed for 3D image is designed by using the HTML 5 and WebGL rendering engine library, and the X3D image file is parsed and rendered by the system. The results of this study showed that the platform was suitable for multiple operating systems to realize the platform-crossing and mobilization of medical image data. The development of medical imaging platform is also pointed out in this paper. It notes that web application technology will not only promote the sharing of medical image data, but also facilitate image-based medical remote consultations and distance learning.

[Medical image, telemedicine and medical teleassistance].

PubMed

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

2010-02-01

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

47 CFR 15.513 - Technical requirements for medical imaging systems.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 47 Telecommunication 1 2010-10-01 2010-10-01 false Technical requirements for medical imaging systems. 15.513 Section 15.513 Telecommunication FEDERAL COMMUNICATIONS COMMISSION GENERAL RADIO FREQUENCY DEVICES Ultra-Wideband Operation § 15.513 Technical requirements for medical imaging systems. (a) The UWB...

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

PubMed

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

An evaluation on CT image acquisition method for medical VR applications

NASA Astrophysics Data System (ADS)

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.

A similarity-based data warehousing environment for medical images.

PubMed

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.

Ultrasound imaging in medical student education: Impact on learning anatomy and physical diagnosis.

PubMed

So, Sokpoleak; Patel, Rita M; Orebaugh, Steven L

2017-03-01

Ultrasound use has expanded dramatically among the medical specialties for diagnostic and interventional purposes, due to its affordability, portability, and practicality. This imaging modality, which permits real-time visualization of anatomic structures and relationships in vivo, holds potential for pre-clinical instruction of students in anatomy and physical diagnosis, as well as providing a bridge to the eventual use of bedside ultrasound by clinicians to assess patients and guide invasive procedures. In many studies, but not all, improved understanding of anatomy has been demonstrated, and in others, improved accuracy in selected aspects of physical diagnosis is evident. Most students have expressed a highly favorable impression of this technology for anatomy education when surveyed. Logistic issues or obstacles to the integration of ultrasound imaging into anatomy teaching appear to be readily overcome. The enthusiasm of students and anatomists for teaching with ultrasound has led to widespread implementation of ultrasound-based teaching initiatives in medical schools the world over, including some with integration throughout the entire curriculum; a trend that likely will continue to grow. Anat Sci Educ 10: 176-189. © 2016 American Association of Anatomists. © 2016 American Association of Anatomists.

A cryptologic based trust center for medical images.

PubMed

Wong, S T

1996-01-01

To investigate practical solutions that can integrate cryptographic techniques and picture archiving and communication systems (PACS) to improve the security of medical images. The PACS at the University of California San Francisco Medical Center consolidate images and associated data from various scanners into a centralized data archive and transmit them to remote display stations for review and consultation purposes. The purpose of this study is to investigate the model of a digital trust center that integrates cryptographic algorithms and protocols seamlessly into such a digital radiology environment to improve the security of medical images. The timing performance of encryption, decryption, and transmission of the cryptographic protocols over 81 volumetric PACS datasets has been measured. Lossless data compression is also applied before the encryption. The transmission performance is measured against three types of networks of different bandwidths: narrow-band Integrated Services Digital Network, Ethernet, and OC-3c Asynchronous Transfer Mode. The proposed digital trust center provides a cryptosystem solution to protect the confidentiality and to determine the authenticity of digital images in hospitals. The results of this study indicate that diagnostic images such as x-rays and magnetic resonance images could be routinely encrypted in PACS. However, applying encryption in teleradiology and PACS is a tradeoff between communications performance and security measures. Many people are uncertain about how to integrate cryptographic algorithms coherently into existing operations of the clinical enterprise. This paper describes a centralized cryptosystem architecture to ensure image data authenticity in a digital radiology department. The system performance has been evaluated in a hospital-integrated PACS environment.

Use of Preclinical Drug vs. Food Choice Procedures to Evaluate Candidate Medications for Cocaine Addiction.

PubMed

Banks, Matthew L; Hutsell, Blake A; Schwienteck, Kathryn L; Negus, S Stevens

2015-06-01

Drug addiction is a disease that manifests as an inappropriate allocation of behavior towards the procurement and use of the abused substance and away from other behaviors that produce more adaptive reinforcers (e.g. exercise, work, family and social relationships). The goal of treating drug addiction is not only to decrease drug-maintained behaviors, but also to promote a reallocation of behavior towards alternative, nondrug reinforcers. Experimental procedures that offer concurrent access to both a drug reinforcer and an alternative, nondrug reinforcer provide a research tool for assessment of medication effects on drug choice and behavioral allocation. Choice procedures are currently the standard in human laboratory research on medications development. Preclinical choice procedures have been utilized in biomedical research since the early 1940's, and during the last 10-15 years, their use for evaluation of medications to treat drug addiction has increased. We propose here that parallel use of choice procedures in preclinical and clinical studies will facilitate translational research on development of medications to treat cocaine addiction. In support of this proposition, a review of the literature suggests strong concordance between preclinical effectiveness of candidate medications to modify cocaine choice in nonhuman primates and rodents and clinical effectiveness of these medications to modify either cocaine choice in human laboratory studies or metrics of cocaine abuse in patients with cocaine use disorder. The strongest evidence for medication effectiveness in preclinical choice studies has been obtained with maintenance on the monoamine releaser d -amphetamine, a candidate agonist medication for cocaine use analogous to use of methadone to treat heroin abuse or nicotine formulations to treat tobacco dependence.

Use of Preclinical Drug vs. Food Choice Procedures to Evaluate Candidate Medications for Cocaine Addiction

PubMed Central

Banks, Matthew L; Hutsell, Blake A; Schwienteck, Kathryn L; Negus, S. Stevens

2015-01-01

Opinion Statement Drug addiction is a disease that manifests as an inappropriate allocation of behavior towards the procurement and use of the abused substance and away from other behaviors that produce more adaptive reinforcers (e.g. exercise, work, family and social relationships). The goal of treating drug addiction is not only to decrease drug-maintained behaviors, but also to promote a reallocation of behavior towards alternative, nondrug reinforcers. Experimental procedures that offer concurrent access to both a drug reinforcer and an alternative, nondrug reinforcer provide a research tool for assessment of medication effects on drug choice and behavioral allocation. Choice procedures are currently the standard in human laboratory research on medications development. Preclinical choice procedures have been utilized in biomedical research since the early 1940’s, and during the last 10–15 years, their use for evaluation of medications to treat drug addiction has increased. We propose here that parallel use of choice procedures in preclinical and clinical studies will facilitate translational research on development of medications to treat cocaine addiction. In support of this proposition, a review of the literature suggests strong concordance between preclinical effectiveness of candidate medications to modify cocaine choice in nonhuman primates and rodents and clinical effectiveness of these medications to modify either cocaine choice in human laboratory studies or metrics of cocaine abuse in patients with cocaine use disorder. The strongest evidence for medication effectiveness in preclinical choice studies has been obtained with maintenance on the monoamine releaser d-amphetamine, a candidate agonist medication for cocaine use analogous to use of methadone to treat heroin abuse or nicotine formulations to treat tobacco dependence. PMID:26009706

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

PubMed

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.

Multimodality Image Fusion-Guided Procedures: Technique, Accuracy, and Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Abi-Jaoudeh, Nadine, E-mail: naj@mail.nih.gov; Kruecker, Jochen, E-mail: jochen.kruecker@philips.com; Kadoury, Samuel, E-mail: samuel.kadoury@polymtl.ca

2012-10-15

Personalized therapies play an increasingly critical role in cancer care: Image guidance with multimodality image fusion facilitates the targeting of specific tissue for tissue characterization and plays a role in drug discovery and optimization of tailored therapies. Positron-emission tomography (PET), magnetic resonance imaging (MRI), and contrast-enhanced computed tomography (CT) may offer additional information not otherwise available to the operator during minimally invasive image-guided procedures, such as biopsy and ablation. With use of multimodality image fusion for image-guided interventions, navigation with advanced modalities does not require the physical presence of the PET, MRI, or CT imaging system. Several commercially available methodsmore » of image-fusion and device navigation are reviewed along with an explanation of common tracking hardware and software. An overview of current clinical applications for multimodality navigation is provided.« less

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

PubMed

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.

Improved image alignment method in application to X-ray images and biological images.

PubMed

Wang, Ching-Wei; Chen, Hsiang-Chou

2013-08-01

Alignment of medical images is a vital component of a large number of applications throughout the clinical track of events; not only within clinical diagnostic settings, but prominently so in the area of planning, consummation and evaluation of surgical and radiotherapeutical procedures. However, image registration of medical images is challenging because of variations on data appearance, imaging artifacts and complex data deformation problems. Hence, the aim of this study is to develop a robust image alignment method for medical images. An improved image registration method is proposed, and the method is evaluated with two types of medical data, including biological microscopic tissue images and dental X-ray images and compared with five state-of-the-art image registration techniques. The experimental results show that the presented method consistently performs well on both types of medical images, achieving 88.44 and 88.93% averaged registration accuracies for biological tissue images and X-ray images, respectively, and outperforms the benchmark methods. Based on the Tukey's honestly significant difference test and Fisher's least square difference test tests, the presented method performs significantly better than all existing methods (P ≤ 0.001) for tissue image alignment, and for the X-ray image registration, the proposed method performs significantly better than the two benchmark b-spline approaches (P < 0.001). The software implementation of the presented method and the data used in this study are made publicly available for scientific communities to use (http://www-o.ntust.edu.tw/∼cweiwang/ImprovedImageRegistration/). cweiwang@mail.ntust.edu.tw.

Rotating Interns' Images of Practitioners of Five Medical Specialties.

ERIC Educational Resources Information Center

Sangal, Rahul

1979-01-01

A study of rotating interns' images of medical practitioners focuses on what images the interns have of obstetrician-gynecologists, pediatricians, internists, psychiatrists, and surgeons, and seeks to determine whether these images differ according to choice of specialty for postgraduate work. (JMD)

SemVisM: semantic visualizer for medical image

NASA Astrophysics Data System (ADS)

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

Multifunctional nanoparticles as a tissue adhesive and an injectable marker for image-guided procedures

NASA Astrophysics Data System (ADS)

Shin, Kwangsoo; Choi, Jin Woo; Ko, Giho; Baik, Seungmin; Kim, Dokyoon; Park, Ok Kyu; Lee, Kyoungbun; Cho, Hye Rim; Han, Sang Ihn; Lee, Soo Hong; Lee, Dong Jun; Lee, Nohyun; Kim, Hyo-Cheol; Hyeon, Taeghwan

2017-07-01

Tissue adhesives have emerged as an alternative to sutures and staples for wound closure and reconnection of injured tissues after surgery or trauma. Owing to their convenience and effectiveness, these adhesives have received growing attention particularly in minimally invasive procedures. For safe and accurate applications, tissue adhesives should be detectable via clinical imaging modalities and be highly biocompatible for intracorporeal procedures. However, few adhesives meet all these requirements. Herein, we show that biocompatible tantalum oxide/silica core/shell nanoparticles (TSNs) exhibit not only high contrast effects for real-time imaging but also strong adhesive properties. Furthermore, the biocompatible TSNs cause much less cellular toxicity and less inflammation than a clinically used, imageable tissue adhesive (that is, a mixture of cyanoacrylate and Lipiodol). Because of their multifunctional imaging and adhesive property, the TSNs are successfully applied as a hemostatic adhesive for minimally invasive procedures and as an immobilized marker for image-guided procedures.

A comparative study of deep learning models for medical image classification

NASA Astrophysics Data System (ADS)

Dutta, Suvajit; Manideep, B. C. S.; Rai, Shalva; Vijayarajan, V.

2017-11-01

Deep Learning(DL) techniques are conquering over the prevailing traditional approaches of neural network, when it comes to the huge amount of dataset, applications requiring complex functions demanding increase accuracy with lower time complexities. Neurosciences has already exploited DL techniques, thus portrayed itself as an inspirational source for researchers exploring the domain of Machine learning. DL enthusiasts cover the areas of vision, speech recognition, motion planning and NLP as well, moving back and forth among fields. This concerns with building models that can successfully solve variety of tasks requiring intelligence and distributed representation. The accessibility to faster CPUs, introduction of GPUs-performing complex vector and matrix computations, supported agile connectivity to network. Enhanced software infrastructures for distributed computing worked in strengthening the thought that made researchers suffice DL methodologies. The paper emphases on the following DL procedures to traditional approaches which are performed manually for classifying medical images. The medical images are used for the study Diabetic Retinopathy(DR) and computed tomography (CT) emphysema data. Both DR and CT data diagnosis is difficult task for normal image classification methods. The initial work was carried out with basic image processing along with K-means clustering for identification of image severity levels. After determining image severity levels ANN has been applied on the data to get the basic classification result, then it is compared with the result of DNNs (Deep Neural Networks), which performed efficiently because of its multiple hidden layer features basically which increases accuracy factors, but the problem of vanishing gradient in DNNs made to consider Convolution Neural Networks (CNNs) as well for better results. The CNNs are found to be providing better outcomes when compared to other learning models aimed at classification of images. CNNs are

Open-source software platform for medical image segmentation applications

NASA Astrophysics Data System (ADS)

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.

The compression and storage method of the same kind of medical images: DPCM

NASA Astrophysics Data System (ADS)

Zhao, Xiuying; Wei, Jingyuan; Zhai, Linpei; Liu, Hong

2006-09-01

Medical imaging has started to take advantage of digital technology, opening the way for advanced medical imaging and teleradiology. Medical images, however, require large amounts of memory. At over 1 million bytes per image, a typical hospital needs a staggering amount of memory storage (over one trillion bytes per year), and transmitting an image over a network (even the promised superhighway) could take minutes--too slow for interactive teleradiology. This calls for image compression to reduce significantly the amount of data needed to represent an image. Several compression techniques with different compression ratio have been developed. However, the lossless techniques, which allow for perfect reconstruction of the original images, yield modest compression ratio, while the techniques that yield higher compression ratio are lossy, that is, the original image is reconstructed only approximately. Medical imaging poses the great challenge of having compression algorithms that are lossless (for diagnostic and legal reasons) and yet have high compression ratio for reduced storage and transmission time. To meet this challenge, we are developing and studying some compression schemes, which are either strictly lossless or diagnostically lossless, taking advantage of the peculiarities of medical images and of the medical practice. In order to increase the Signal to Noise Ratio (SNR) by exploitation of correlations within the source signal, a method of combining differential pulse code modulation (DPCM) is presented.

What Is the Relevance of Procedural Fairness to Making Determinations about Medical Evidence?

PubMed

Persad, Govind

2017-02-01

Approaches relying on fair procedures rather than substantive principles have been proposed for answering dilemmas in medical ethics and health policy. These dilemmas generally involve two questions: the epistemological (factual) question of which benefits an intervention will have, and the ethical (value) question of how to distribute those benefits. This article focuses on the potential of fair procedures to help address epistemological and factual questions in medicine, using the debate over antidepressant efficacy as a test case. In doing so, it employs concepts from social epistemology such as testimonial injustice (bias resulting from the exclusion of evidence) and hermeneutical injustice (bias resulting from a prevailing discussion framework's conceptual limitations). This article also explores the relevance of scientific consensus to determinations regarding medical evidence. © 2017 American Medical Association. All Rights Reserved.

A cryptologic based trust center for medical images.

PubMed Central

Wong, S T

1996-01-01

OBJECTIVE: To investigate practical solutions that can integrate cryptographic techniques and picture archiving and communication systems (PACS) to improve the security of medical images. DESIGN: The PACS at the University of California San Francisco Medical Center consolidate images and associated data from various scanners into a centralized data archive and transmit them to remote display stations for review and consultation purposes. The purpose of this study is to investigate the model of a digital trust center that integrates cryptographic algorithms and protocols seamlessly into such a digital radiology environment to improve the security of medical images. MEASUREMENTS: The timing performance of encryption, decryption, and transmission of the cryptographic protocols over 81 volumetric PACS datasets has been measured. Lossless data compression is also applied before the encryption. The transmission performance is measured against three types of networks of different bandwidths: narrow-band Integrated Services Digital Network, Ethernet, and OC-3c Asynchronous Transfer Mode. RESULTS: The proposed digital trust center provides a cryptosystem solution to protect the confidentiality and to determine the authenticity of digital images in hospitals. The results of this study indicate that diagnostic images such as x-rays and magnetic resonance images could be routinely encrypted in PACS. However, applying encryption in teleradiology and PACS is a tradeoff between communications performance and security measures. CONCLUSION: Many people are uncertain about how to integrate cryptographic algorithms coherently into existing operations of the clinical enterprise. This paper describes a centralized cryptosystem architecture to ensure image data authenticity in a digital radiology department. The system performance has been evaluated in a hospital-integrated PACS environment. PMID:8930857

Watermarking of ultrasound medical images in teleradiology using compressed watermark

PubMed Central

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

2016-01-01

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

Real-time Magnetic Resonance Imaging Guidance for Cardiovascular Procedures

PubMed Central

Horvath, Keith A.; Li, Ming; Mazilu, Dumitru; Guttman, Michael A.; McVeigh, Elliot R.

2008-01-01

Magnetic resonance imaging (MRI) of the cardiovascular system has proven to be an invaluable diagnostic tool. Given the ability to allow for real-time imaging, MRI guidance of intraoperative procedures can provide superb visualization which can facilitate a variety of interventions and minimize the trauma of the operations as well. In addition to the anatomic detail, MRI can provide intraoperative assessment of organ and device function. Instruments and devices can be marked to enhance visualization and tracking. All of which is an advance over standard x-ray or ultrasonic imaging. PMID:18395633

Combined self-learning based single-image super-resolution and dual-tree complex wavelet transform denoising for medical images

NASA Astrophysics Data System (ADS)

Yang, Guang; Ye, Xujiong; Slabaugh, Greg; Keegan, Jennifer; Mohiaddin, Raad; Firmin, David

2016-03-01

In this paper, we propose a novel self-learning based single-image super-resolution (SR) method, which is coupled with dual-tree complex wavelet transform (DTCWT) based denoising to better recover high-resolution (HR) medical images. Unlike previous methods, this self-learning based SR approach enables us to reconstruct HR medical images from a single low-resolution (LR) image without extra training on HR image datasets in advance. The relationships between the given image and its scaled down versions are modeled using support vector regression with sparse coding and dictionary learning, without explicitly assuming reoccurrence or self-similarity across image scales. In addition, we perform DTCWT based denoising to initialize the HR images at each scale instead of simple bicubic interpolation. We evaluate our method on a variety of medical images. Both quantitative and qualitative results show that the proposed approach outperforms bicubic interpolation and state-of-the-art single-image SR methods while effectively removing noise.

Integrating DICOM structure reporting (SR) into the medical imaging informatics data grid

NASA Astrophysics Data System (ADS)

Lee, Jasper; Le, Anh; Liu, Brent

2008-03-01

The Medical Imaging Informatics (MI2) Data Grid developed at the USC Image Processing and Informatics Laboratory enables medical images to be shared securely between multiple imaging centers. Current applications include an imaging-based clinical trial setting where multiple field sites perform image acquisition and a centralized radiology core performs image analysis, often using computer-aided diagnosis tools (CAD) that generate a DICOM-SR to report their findings and measurements. As more and more CAD tools are being developed in the radiology field, the generated DICOM Structure Reports (SR) holding key radiological findings and measurements that are not part of the DICOM image need to be integrated into the existing Medical Imaging Informatics Data Grid with the corresponding imaging studies. We will discuss the significance and method involved in adapting DICOM-SR into the Medical Imaging Informatics Data Grid. The result is a MI2 Data Grid repository from which users can send and receive DICOM-SR objects based on the imaging-based clinical trial application. The services required to extract and categorize information from the structured reports will be discussed, and the workflow to store and retrieve a DICOM-SR file into the existing MI2 Data Grid will be shown.

A De-Identification Pipeline for Ultrasound Medical Images in DICOM Format.

PubMed

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

2017-05-01

Clinical data sharing between healthcare institutions, and between practitioners is often hindered by privacy protection requirements. This problem is critical in collaborative scenarios where data sharing is fundamental for establishing a workflow among parties. The anonymization of patient information burned in DICOM images requires elaborate processes somewhat more complex than simple de-identification of textual information. Usually, before sharing, there is a need for manual removal of specific areas containing sensitive information in the images. In this paper, we present a pipeline for ultrasound medical image de-identification, provided as a free anonymization REST service for medical image applications, and a Software-as-a-Service to streamline automatic de-identification of medical images, which is freely available for end-users. The proposed approach applies image processing functions and machine-learning models to bring about an automatic system to anonymize medical images. To perform character recognition, we evaluated several machine-learning models, being Convolutional Neural Networks (CNN) selected as the best approach. For accessing the system quality, 500 processed images were manually inspected showing an anonymization rate of 89.2%. The tool can be accessed at https://bioinformatics.ua.pt/dicom/anonymizer and it is available with the most recent version of Google Chrome, Mozilla Firefox and Safari. A Docker image containing the proposed service is also publicly available for the community.

Evidence-Based Imaging Guidelines and Medicare Payment Policy

PubMed Central

Sistrom, Christopher L; McKay, Niccie L

2008-01-01

Objective This study examines the relationship between evidence-based appropriateness criteria for neurologic imaging procedures and Medicare payment determinations. The primary research question is whether Medicare is more likely to pay for imaging procedures as the level of appropriateness increases. Data Sources The American College of Radiology Appropriateness Criteria (ACRAC) for neurological imaging, ICD-9-CM codes, CPT codes, and payment determinations by the Medicare Part B carrier for Florida and Connecticut. Study Design Cross-sectional study of appropriateness criteria and Medicare Part B payment policy for neurological imaging. In addition to descriptive and bivariate statistics, multivariate logistic regression on payment determination (yes or no) was performed. Data Collection Methods The American College of Radiology Appropriateness Criteria (ACRAC) documents specific to neurological imaging, ICD-9-CM codes, and CPT codes were used to create 2,510 medical condition/imaging procedure combinations, with associated appropriateness scores (coded as low/middle/high). Principal Findings As the level of appropriateness increased, more medical condition/imaging procedure combinations were payable (low = 61 percent, middle = 70 percent, and high = 74 percent). Logistic regression indicated that the odds of a medical condition/imaging procedure combination with a middle level of appropriateness being payable was 48 percent higher than for an otherwise similar combination with a low appropriateness score (95 percent CI on odds ratio=1.19–1.84). The odds ratio for being payable between high and low levels of appropriateness was 2.25 (95 percent CI: 1.66–3.04). Conclusions Medicare could improve its payment determinations by taking advantage of existing clinical guidelines, appropriateness criteria, and other authoritative resources for evidence-based practice. Such an approach would give providers a financial incentive that is aligned with best

[Medical Image Registration Method Based on a Semantic Model with Directional Visual Words].

PubMed

Jin, Yufei; Ma, Meng; Yang, Xin

2016-04-01

Medical image registration is very challenging due to the various imaging modality,image quality,wide inter-patients variability,and intra-patient variability with disease progressing of medical images,with strict requirement for robustness.Inspired by semantic model,especially the recent tremendous progress in computer vision tasks under bag-of-visual-word framework,we set up a novel semantic model to match medical images.Since most of medical images have poor contrast,small dynamic range,and involving only intensities and so on,the traditional visual word models do not perform very well.To benefit from the advantages from the relative works,we proposed a novel visual word model named directional visual words,which performs better on medical images.Then we applied this model to do medical registration.In our experiment,the critical anatomical structures were first manually specified by experts.Then we adopted the directional visual word,the strategy of spatial pyramid searching from coarse to fine,and the k-means algorithm to help us locating the positions of the key structures accurately.Sequentially,we shall register corresponding images by the areas around these positions.The results of the experiments which were performed on real cardiac images showed that our method could achieve high registration accuracy in some specific areas.

Automated synthesis of image processing procedures using AI planning techniques

NASA Technical Reports Server (NTRS)

Chien, Steve; Mortensen, Helen

1994-01-01

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

Applying Deep Learning in Medical Images: The Case of Bone Age Estimation.

PubMed

Lee, Jang Hyung; Kim, Kwang Gi

2018-01-01

A diagnostic need often arises to estimate bone age from X-ray images of the hand of a subject during the growth period. Together with measured physical height, such information may be used as indicators for the height growth prognosis of the subject. We present a way to apply the deep learning technique to medical image analysis using hand bone age estimation as an example. Age estimation was formulated as a regression problem with hand X-ray images as input and estimated age as output. A set of hand X-ray images was used to form a training set with which a regression model was trained. An image preprocessing procedure is described which reduces image variations across data instances that are unrelated to age-wise variation. The use of Caffe, a deep learning tool is demonstrated. A rather simple deep learning network was adopted and trained for tutorial purpose. A test set distinct from the training set was formed to assess the validity of the approach. The measured mean absolute difference value was 18.9 months, and the concordance correlation coefficient was 0.78. It is shown that the proposed deep learning-based neural network can be used to estimate a subject's age from hand X-ray images, which eliminates the need for tedious atlas look-ups in clinical environments and should improve the time and cost efficiency of the estimation process.