Topology Simplification Algorithm for Segmentation of Medical Scans : Application to the Segmentation of Brain MRI Images

Sylvain Jaume

ISBN 10: 3838317629 / ISBN 13: 9783838317625

Published by LAP LAMBERT Academic Publishing, 2009

About this Item

nach der Bestellung gedruckt Neuware - Printed after ordering.

Seller Inventory # 9783838317625

Bibliographic Details

• Title: Topology Simplification Algorithm for Segmentation of Medical Scans : Application to the Segmentation of Brain MRI Images
• Publisher: LAP LAMBERT Academic Publishing
• Publication Date: 2009
• Language: English
• ISBN 10: 3838317629
• ISBN 13: 9783838317625
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 8D millimeters 220 millimeters width by 150 millimeters height by 8 millimeters depth
• Weight: 215 grams

About this title

Synopsis

Magnetic Resonance Imaging, Computed Tomography, and other technologies of 3D medical imaging are routinely used to visualize a particular structure in the patient?s body. The classification of the image region corresponding to this structure is called segmentation. For applications in Neuroscience, it is paramount for the segmentation of a brain scan to represent the brain boundary as a folded surface with no holes. However, in practice, a brain scan segmentation generally exhibits many erroneous holes. To address this issue which affects Medicine, Graphics and Industrial Design, I focused my PhD work on developing an algorithm for automatically correcting holes in 3D scanned data. Upon concepts of Discrete Topology and Computational Geometry, my topology simplification algorithm built upon the construction of front propagations and Reeb graphs. Based on experiments with clinical data, I proved that my algorithm successfully corrected the erroneous holes with high accuracy and low complexity even for images that exceeded the computer main memory. To enable radiologists to obtain a correct segmentation, I made the software that I developed available at http://www.opentopology.org.

About the Author

Sylvain Jaume graduated in 2004 with a PhD in Electrical Engineering from Universite catholique de Louvain (UCL). From 2005 to 2009 he worked at Kitware Inc. and Siemens Corporate Research USA. He now holds a dual appointment with MIT Computer Science and Artificial Intelligence Laboratory and Harvard Medical School.