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Proceedings Paper

Explanation of the mechanism by which CAD assistance improves diagnostic performance when reading CT images
Author(s): Toru Matsumoto; Shinichi Wada; Shinji Yamamoto; Kohei Murao; Akira Furukawa; Masahiro Endo; Mitsuomi Matsumoto; Shusuke Sone
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Paper Abstract

The purpose of our research is to make clear the mechanism that a reader (physician or radiological technologist) effectively identify abnormal findings in CT images of lung cancer screening by using with CAD system. A method guessing the 2X2 decision matrix between reader / CAD and reader / reader with CAD was investigated. We suppose the next scene to be it. At first, a reader judges whether abnormal findings per one patient per one CT image are present (1) or absent (0) without CAD results. The second, a reader judges whether abnormal findings are present (1) or absent (0) with CAD results. We expresses the correlation between diagnoses by a reader and CAD system for abnormal cases and for normal cases by following formula using phi correlation coefficient:φ=(cd-ab)/√(a+c)(b+d)(b+c)(a+d). a,b,c,d: 2X2 decision matrix parameters. If TPR1=(a+c)/n, TPR2=(b+c)/n and TPR3=(a+b+c)/n for abnormal cases, TPR3=TPR1+TPR2 - TPR1×TRR2 - φ√TPR1(1-TPR1)TPR2(1-TPR2). Therefore, a=n (TPR3 - TPR1), b=n (TPR3 - TPR2), c=n (TPR1 + TPR2 -TPR3), d=n (1.0 - TPR3). This theory was applied for the experimental data. The 41 students interpreted the same CT images [no training]. A second interpretation was performed after they had been instructed on how to interpret CT images [training], and third was assisted by a virtual CAD [training + CAD]. The mechanism that makes up for a good point of a reader and a CAD with CAD in interpreting CT images was theoretically and experimentally investigated. We concluded that a method guessing the decision matrix (2X2) between a reader and a CAD decided the "presence" or "absence" of abnormal findings explain the improvement mechanism of diagnostic performance with CAD system.

Paper Details

Date Published: 17 March 2006
PDF: 14 pages
Proc. SPIE 6146, Medical Imaging 2006: Image Perception, Observer Performance, and Technology Assessment, 614619 (17 March 2006); doi: 10.1117/12.652928
Show Author Affiliations
Toru Matsumoto, National Institute of Radiological Sciences (Japan)
Shinichi Wada, Niigata Univ. (Japan)
Shinji Yamamoto, Chukyo Univ. (Japan)
Kohei Murao, Fujitsu Ltd. (Japan)
Akira Furukawa, National Institute of Radiological Sciences (Japan)
Masahiro Endo, National Institute of Radiological Sciences (Japan)
Mitsuomi Matsumoto, Diichi Hospital (Japan)
Shusuke Sone, JA Azumi General Hospital (Japan)

Published in SPIE Proceedings Vol. 6146:
Medical Imaging 2006: Image Perception, Observer Performance, and Technology Assessment
Yulei Jiang; Miguel P. Eckstein, Editor(s)

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