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Computer Aided Detection of prostate cancer based on GDA and predictive deconvolution

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4 Author(s)
Maggio, S. ; DEIS-ARCES, Univ. of Bologna, Bologna ; Alessandrini, M. ; De Marchi, L. ; Speciale, N.

A Computer-Aided Detection (CAD) scheme to support prostate cancer diagnosis based on ultrasound images is presented. The approach described in this work employs a multifeature classification model. To indentify features highly correlated to the pathologic state of the tissue we use a Feature Selection algorithm based on mutual information. System-dependent effects are removed through predictive deconvolution and this operation results in increasing quality of images and discriminating power of features. A comparison of the classification model applied before and after deconvolution shows a gain in accuracy and area under the ROC curve. The use of deconvolution as preprocessing step in CAD schemes can improve prostate cancer detection.

Published in:

Ultrasonics Symposium, 2008. IUS 2008. IEEE

Date of Conference:

2-5 Nov. 2008