Evaluating computer-aided detection algorithms

被引:38
|
作者
Yoon, Hong Jun
Zheng, Bin
Sahiner, Berkman
Chakraborty, Dev P. [1 ]
机构
[1] Univ Pittsburgh, Dept Radiol, Pittsburgh, PA 15261 USA
[2] Univ Michigan, Dept Radiol, Ann Arbor, MI 48109 USA
关键词
CAD evaluation; free-response; FROC curves; lesion localization; search model; maximum likelihood; figure of merit; imaging system optimization;
D O I
10.1118/1.2736289
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Computer-aided detection (CAD) has been attracting extensive research interest during the last two decades. It is recognized that the full potential of CAD can only be realized by improving the performance and robustness of CAD algorithms and this requires good evaluation methodology that would permit CAD designers to optimize their algorithms. Free-response receiver operating characteristic (FROC) curves are widely used to assess CAD performance, however, evaluation rarely proceeds beyond determination of lesion localization fraction (sensitivity) at an arbitrarily selected value of nonlesion localizations (false marks) per image. This work describes a FROC curve fitting procedure that uses a recent model of visual search that serves as a framework for the free-response task. A maximum likelihood procedure for estimating the parameters of the model from free-response data and fitting CAD generated FROC curves was implemented. Procedures were implemented to estimate two figures of merit and associated statistics such as 95% confidence intervals and goodness of fit. One of the figures of merit does not require the arbitrary specification of an operating point at which to evaluate CAD performance. For comparison a related method termed initial detection and candidate analysis was also implemented that is applicable when all suspicious regions are reported. The two methods were tested on seven mammography CAD data sets and both yielded good to excellent fits. The search model approach has the advantage that it can potentially be applied to radiologist generated free-response data where not all suspicious regions are reported, only the ones that are deemed sufficiently suspicious to warrant clinical follow-up. This work represents the first practical application of the search model to an important evaluation problem in diagnostic radiology. Software based on this work is expected to benefit CAD developers working in diverse areas of medical imaging. (c) 2007 American Association of Physicists in Medicine.
引用
收藏
页码:2024 / 2038
页数:15
相关论文
共 50 条
  • [31] On Combining Computer-Aided Detection Systems
    Niemeijer, Meindert
    Loog, Marco
    Abramoff, Michael David
    Viergever, Max A.
    Prokop, Mathias
    van Ginneken, Bram
    IEEE TRANSACTIONS ON MEDICAL IMAGING, 2011, 30 (02) : 215 - 223
  • [32] Computer-aided detection for screening mammography
    Astley, SM
    CARS 2003: COMPUTER ASSISTED RADIOLOGY AND SURGERY, PROCEEDINGS, 2003, 1256 : 927 - 932
  • [33] Breast imaging and computer-aided detection
    Hall, Ferris M.
    NEW ENGLAND JOURNAL OF MEDICINE, 2007, 356 (14): : 1464 - 1466
  • [34] Computer-Aided Detection for CT Colonography
    徐嫣然
    赵俊
    JournalofShanghaiJiaotongUniversity(Science), 2014, 19 (05) : 531 - 537
  • [35] Computer-aided detection for pulmonary nodules
    Koroglu, M
    Ernst, RD
    Oto, A
    Hardie, RC
    Gurcan, MN
    Allen, BH
    AMERICAN JOURNAL OF ROENTGENOLOGY, 2004, 182 (04) : 85 - 85
  • [36] Performance of mammographic computer-aided detection
    Collins, M
    Mitchell, R
    Worrell, S
    Hoffmeister, JW
    Bauer, K
    Rogers, SK
    Kabrisky, M
    CARS 2000: COMPUTER ASSISTED RADIOLOGY AND SURGERY, 2000, 1214 : 1041 - 1041
  • [37] Computer-Aided Detection of Retroflexion in Colonoscopy
    Wang, Yi
    Tavanapong, Wallapak
    Wong, Johnny
    Oh, JungHwan
    de Groen, Piet C.
    2011 24TH INTERNATIONAL SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS (CBMS), 2011,
  • [38] Computer-aided detection and interpretation in mammography
    Karssemeijer, N
    IWDM 2000: 5TH INTERNATIONAL WORKSHOP ON DIGITAL MAMMOGRAPHY, 2001, : 243 - 252
  • [39] Computer-Aided Support of the Detection of Deception
    Judee K. Burgoon
    Jay F. Nunamaker
    Group Decision and Negotiation, 2004, 13 : 107 - 110
  • [40] Computer-aided detection of prostate cancer
    Llobet, Rafael
    Perez-Cortes, Juan C.
    Toselli, Alejandro H.
    Juan, Alfons
    INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS, 2007, 76 (07) : 547 - 556