Literature DB >> 12297976

Computer-aided detection and diagnosis at the start of the third millennium.

Bradley J Erickson1, Brian Bartholmai.   

Abstract

Computer-aided diagnosis has been under development for more than 3 decades. The rate of progress appears exponential, with either recent approval or pending approval for devices focusing on mammography, chest radiographs, and chest CT. Related technologies improve diagnosis for many other types of medical images including virtual colonography, vascular imaging, as well as automated quantitation of image-derived metrics. A variety of techniques are currently employed with success, likely reflecting the variety of imagery used, as well as the variety of tasks. Most areas of medical imaging have had efforts at computer assistance, and some have even received FDA approval and can be reimbursed. We anticipate that the rapid advance of these technologies will continue, and that application will broaden to cover much of medical imaging. Acceptance of, and integration of computer-aided diagnosis technology with the electronic radiology practice is a current challenge. These challenges will be overcome, and we expect that computer-aided diagnosis will be routinely applied to medical images.

Mesh:

Year:  2002        PMID: 12297976      PMCID: PMC3611610          DOI: 10.1007/s10278-002-0011-x

Source DB:  PubMed          Journal:  J Digit Imaging        ISSN: 0897-1889            Impact factor:   4.056


  14 in total

1.  Impact of a computer-aided detection (CAD) system integrated into a picture archiving and communication system (PACS) on reader sensitivity and efficiency for the detection of lung nodules in thoracic CT exams.

Authors:  Luca Bogoni; Jane P Ko; Jeffrey Alpert; Vikram Anand; John Fantauzzi; Charles H Florin; Chi Wan Koo; Derek Mason; William Rom; Maria Shiau; Marcos Salganicoff; David P Naidich
Journal:  J Digit Imaging       Date:  2012-12       Impact factor: 4.056

2.  An improved brain image classification technique with mining and shape prior segmentation procedure.

Authors:  P Rajendran; M Madheswaran
Journal:  J Med Syst       Date:  2010-06-25       Impact factor: 4.460

3.  Medical decision-making system of ultrasound carotid artery intima-media thickness using neural networks.

Authors:  N Santhiyakumari; P Rajendran; M Madheswaran
Journal:  J Digit Imaging       Date:  2011-12       Impact factor: 4.056

4.  Pattern recognition for cache management in distributed medical imaging environments.

Authors:  Carlos Viana-Ferreira; Luís Ribeiro; Sérgio Matos; Carlos Costa
Journal:  Int J Comput Assist Radiol Surg       Date:  2015-08-05       Impact factor: 2.924

5.  [Computer assisted radiological diagnostics of arthritic joint alterations].

Authors:  F Kainberger; G Langs; P Peloschek; T Schlager; C Schüller-Weidekamm; A Valentinitsch
Journal:  Z Rheumatol       Date:  2006-12       Impact factor: 1.372

6.  A hybrid fuzzy-neural system for computer-aided diagnosis of ultrasound kidney images using prominent features.

Authors:  K Bommanna Raja; M Madheswaran; K Thyagarajah
Journal:  J Med Syst       Date:  2008-02       Impact factor: 4.460

Review 7.  Computer-aided diagnosis in medical imaging: historical review, current status and future potential.

Authors:  Kunio Doi
Journal:  Comput Med Imaging Graph       Date:  2007-03-08       Impact factor: 4.790

8.  A pilot study of architectural distortion detection in mammograms based on characteristics of line shadows.

Authors:  Mitsutaka Nemoto; Soshi Honmura; Akinobu Shimizu; Daisuke Furukawa; Hidefumi Kobatake; Shigeru Nawano
Journal:  Int J Comput Assist Radiol Surg       Date:  2008-10-28       Impact factor: 2.924

9.  An online evidence-based decision support system for distinguishing benign from malignant vertebral compression fractures by magnetic resonance imaging feature analysis.

Authors:  Kenneth C Wang; Anthony Jeanmenne; Griffin M Weber; Shrey K Thawait; Shrey Thawait; John A Carrino
Journal:  J Digit Imaging       Date:  2011-06       Impact factor: 4.056

10.  Heterogeneity of focal breast lesions and surrounding tissue assessed by mammographic texture analysis: preliminary evidence of an association with tumor invasion and estrogen receptor status.

Authors:  Balaji Ganeshan; Olga Strukowska; Karoline Skogen; Rupert Young; Chris Chatwin; Ken Miles
Journal:  Front Oncol       Date:  2011-10-17       Impact factor: 6.244

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