Technical Program

Paper Detail

Paper:	SU-AM-PS3.8
Session:	Image Guided Detection and Diagnosis
Time:	Sunday, April 9, 10:50 - 12:10
Presentation:	Poster
Title:	A Flexible Machine Learning Image Analysis System for High-Precision Computer-Assisted Segmentation of Multispectral MRI Data Sets in Patients with Multiple Sclerosis
Authors:	Axel Wismueller; University of Munich
	Anke Meyer-Baese; Florida State University
	Johannes Behrends; University of Munich
	Oliver Lange; University of Munich
	Mirjana Jukic; University of Munich
	Maximilian Reiser; University of Munich
	Dorothee Auer; University of Nottingham
Abstract:	Automatic brain segmentation is an issue of specific clinical relevance in both diagnosis and therapy control of patients with demyelinating diseases such as Multiple Sclerosis (MS). We present a complete system for high-precision computer-assisted image analysis of multispectral MRI data based on a flexible machine learning approach. Careful quality evaluation shows that the system outperforms conventional threshold based techniques w.r.t. inter-observer agreement levels for the quantification of relevant clinical parameters, such as white matter lesion load and brain parenchyma volume.

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