Repeatability in computer-aided diagnosis: application to breast cancer diagnosis on sonography.

Medical Physics
Karen DrukkerMaryellen L Giger

Abstract

The aim of this study was to investigate the concept of repeatability in a case-based performance evaluation of two classifiers commonly used in computer-aided diagnosis in the task of distinguishing benign from malignant lesions. The authors performed .632+ bootstrap analyses using a data set of 1251 sonographic lesions of which 212 were malignant. Several analyses were performed investigating the impact of sample size and number of bootstrap iterations. The classifiers investigated were a Bayesian neural net (BNN) with five hidden units and linear discriminant analysis (LDA). Both used the same four input lesion features. While the authors did evaluate classifier performance using receiver operating characteristic (ROC) analysis, the main focus was to investigate case-based performance based on the classifier output for individual cases, i.e., the classifier outputs for each test case measured over the bootstrap iterations. In this case-based analysis, the authors examined the classifier output variability and linked it to the concept of repeatability. Repeatability was assessed on the level of individual cases, overall for all cases in the data set, and regarding its dependence on the case-based classifier output. The impact...Continue Reading

References

Oct 1, 1978·Seminars in Nuclear Medicine·C E Metz
Sep 11, 2001·Medical Physics·K HorschC J Vyborny
Feb 28, 2002·Medical Physics·Karla HorschCarl J Vyborny
May 19, 2004·Academic Radiology·Karen DrukkerEllen B Mendelson
May 16, 2007·Academic Radiology·Robert F WagnerGregory Campbell
Apr 22, 2008·Academic Radiology·Heang-Ping ChanBerkman Sahiner
May 22, 2008·Medical Physics·Berkman SahinerLubomir Hadjiiski
Sep 16, 2008·Academic Radiology·Nicholas P GruszauskasLorenzo L Pesce

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Citations

Mar 26, 2013·International Journal of Computer Assisted Radiology and Surgery·Karen DrukkerHiroyuki Abe
Dec 22, 2009·Future Oncology·Maryellen L Giger
Oct 28, 2018·Medical Physics·Berkman SahinerMaryellen L Giger

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