2002
DOI: 10.1111/j.1749-6632.2002.tb04896.x
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A Review of Medical Imaging Informatics

Abstract: This review of medical imaging informatics is a survey of current developments in an exciting field. The focus is on informatics issues rather than traditional data processing and information systems, such as picture archiving and communications systems (PACS) and image processing and analysis systems. In this review, we address imaging informatics issues within the requirements of an informatics system defined by the American Medical Informatics Association. With these requirements as a framework, we review, … Show more

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Cited by 30 publications
(9 citation statements)
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References 83 publications
(85 reference statements)
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“…Content-based image retrieval and classification in medical applications has been a very active research domain over the last 15 years and is often proposed as very important for the future of medical data management and diagnostic aid 3,8,9 . One reason for this is the ever-increasing production of medical images in today's modern hospitals.…”
Section: Image-based Diagnostic Aid Systems and Databases For Ildsmentioning
confidence: 99%
“…Content-based image retrieval and classification in medical applications has been a very active research domain over the last 15 years and is often proposed as very important for the future of medical data management and diagnostic aid 3,8,9 . One reason for this is the ever-increasing production of medical images in today's modern hospitals.…”
Section: Image-based Diagnostic Aid Systems and Databases For Ildsmentioning
confidence: 99%
“…In this section, we focus on a few of these areas such as text mining, systems biology, and the semantic web. Some additional emerging areas such as image analysis (117), grid computing (46,49), directed evolution (29), rational protein design (81), microRNA-related bioinformatics (21), and modeling in epigenomics (43) are not covered due to the limitation of space.…”
Section: Emerging Areas In Bioinformaticsmentioning
confidence: 99%
“…A high amount of a priori knowledge about the structure of the images is used for these preprocessing steps for computed tomographies (CT) of the head [4]. Sinha [8] investigates the use of the eigenimage methodology with focus on the image preprocessing steps required to increase the accuracy of diagnosis. An improved minutia preserving smoothing algorithm for preprocessing of MRI is given in [11] based on solving a nonlinear diffusion equation.…”
Section: Introductionmentioning
confidence: 99%