Literature DB >> 15917443

Current status and future potential of computer-aided diagnosis in medical imaging.

K Doi1.   

Abstract

Computer-aided diagnosis (CAD) has become one of the major research subjects in medical imaging and diagnostic radiology. The basic concept of CAD is to provide a computer output as a second opinion to assist radiologists' image interpretation by improving the accuracy and consistency of radiological diagnosis and also by reducing the image reading time. In this article, a number of CAD schemes are presented, with emphasis on potential clinical applications. These schemes include: (1) detection and classification of lung nodules on digital chest radiographs; (2) detection of nodules in low dose CT; (3) distinction between benign and malignant nodules on high resolution CT; (4) usefulness of similar images for distinction between benign and malignant lesions; (5) quantitative analysis of diffuse lung diseases on high resolution CT; and (6) detection of intracranial aneurysms in magnetic resonance angiography. Because CAD can be applied to all imaging modalities, all body parts and all kinds of examinations, it is likely that CAD will have a major impact on medical imaging and diagnostic radiology in the 21st century.

Entities:  

Mesh:

Year:  2005        PMID: 15917443     DOI: 10.1259/bjr/82933343

Source DB:  PubMed          Journal:  Br J Radiol        ISSN: 0007-1285            Impact factor:   3.039


  57 in total

1.  Automatic detection and classification of nasopharyngeal carcinoma on PET/CT with support vector machine.

Authors:  Bangxian Wu; Pek-Lan Khong; Tao Chan
Journal:  Int J Comput Assist Radiol Surg       Date:  2012-01-04       Impact factor: 2.924

2.  Detection of noncalcified pulmonary nodules on low-dose MDCT: comparison of the sensitivity of two CAD systems by using a double reference standard.

Authors:  A R Larici; M Amato; P Ordóñez; F Maggi; L Menchini; A Caulo; L Calandriello; G Vallati; S Giunta; M Crecco; L Bonomo
Journal:  Radiol Med       Date:  2012-02-10       Impact factor: 3.469

3.  Evaluation of objective similarity measures for selecting similar images of mammographic lesions.

Authors:  Ryohei Nakayama; Hiroyuki Abe; Junji Shiraishi; Kunio Doi
Journal:  J Digit Imaging       Date:  2011-02       Impact factor: 4.056

4.  Computer-aided measurement of liver volumes in CT by means of geodesic active contour segmentation coupled with level-set algorithms.

Authors:  Kenji Suzuki; Ryan Kohlbrenner; Mark L Epstein; Ademola M Obajuluwa; Jianwu Xu; Masatoshi Hori
Journal:  Med Phys       Date:  2010-05       Impact factor: 4.071

5.  Evaluation of a method of computer-aided detection (CAD) of pulmonary nodules with computed tomography.

Authors:  G Foti; N Faccioli; M D'Onofrio; A Contro; T Milazzo; R Pozzi Mucelli
Journal:  Radiol Med       Date:  2010-06-23       Impact factor: 3.469

6.  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

7.  Computer-aided diagnosis for contrast-enhanced ultrasound in the liver.

Authors:  Katsutoshi Sugimoto; Junji Shiraishi; Fuminori Moriyasu; Kunio Doi
Journal:  World J Radiol       Date:  2010-06-28

8.  Multi-object segmentation framework using deformable models for medical imaging analysis.

Authors:  Rafael Namías; Juan Pablo D'Amato; Mariana Del Fresno; Marcelo Vénere; Nicola Pirró; Marc-Emmanuel Bellemare
Journal:  Med Biol Eng Comput       Date:  2015-09-21       Impact factor: 2.602

9.  Applying Distance Histogram to retrieve 3D cardiac medical models.

Authors:  Leila C C Bergamasco; Fátima L S Nunes
Journal:  AMIA Annu Symp Proc       Date:  2013-11-16

10.  A review of computer-aided diagnosis in thoracic and colonic imaging.

Authors:  Kenji Suzuki
Journal:  Quant Imaging Med Surg       Date:  2012-09
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