Technical Program

Paper Detail

Paper:	FR-PM-PS2.9
Session:	Image Registration
Time:	Friday, April 7, 13:30 - 14:50
Presentation:	Poster
Title:	Does Registration Improve the Performance of a Computer Aided Diagnosis System for Dynamic Contrast-Enhanced MR Mammography?
Authors:	Christine Tanner; University College London
	David J. Hawkes; University College London
	Michael Khazen; Institute of Cancer Research & Royal Marsden NHS Trust
	Preminda Kessar; Institute of Cancer Research & Royal Marsden NHS Trust
	Martin O. Leach; Institute of Cancer Research & Royal Marsden NHS Trust
Abstract:	This study investigated whether image registration improves the classification performance of a computer aided diagnosis (CAD) system for dynamic contrast-enhanced (DCE) MR mammography. The CAD system that we developed included image registration, semi-automatic lesion segmentation, 3D image features extraction, and feature selection and combination by logistic regression analysis. The CAD system achieved a leave-one-out area under the ROC curve of 0.86, which is within the range of reported classification performances. This performance was not the artifact of the feature selection process or the leave-one-out test procedure. Worse results were obtained without segmentation refinement and image registration. Rigid image registration led to a statistically significant increase of the area under the ROC curve from 0.81 to 0.86.

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