Geometric statistically based methods for the segmentation and registration of medical imagery

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Please use this identifier to cite or link to this item: http://hdl.handle.net/1853/39644

Title: Geometric statistically based methods for the segmentation and registration of medical imagery
Author: Gao, Yi
Abstract: Medical image analysis aims at developing techniques to extract information from medical images. Among its many sub-fields, image registration and segmentation are two important topics. In this report, we present four pieces of work, addressing different problems as well as coupling them into a unified framework of shape based image segmentation. Specifically: 1. We link the image registration with the point set registration, and propose a globally optimal diffeomorphic registration technique for point set registration. 2. We propose an image segmentation technique which incorporates the robust statistics of the image and the multiple contour evolution. Therefore, the method is able to simultaneously extract multiple targets from the image. 3. By combining the image registration, statistical learning, and image segmentation, we perform a shape based method which not only utilizes the image information but also the shape knowledge. 4. A multi-scale shape representation based on the wavelet transformation is proposed. In particular, the shape is represented by wavelet coefficients in a hierarchical way in order to decompose the shape variance in multiple scales. Furthermore, the statistical shape learning and shape based segmentation is performed under such multi-scale shape representation framework.
Type: Dissertation
URI: http://hdl.handle.net/1853/39644
Date: 2010-12-22
Publisher: Georgia Institute of Technology
Subject: Computer vision
Medical image analysis
Image segmentation
Image registration
Shape analysis
Imaging systems in medicine
Image analysis
Image registration
Image processing Digital techniques
Department: Biomedical Engineering
Advisor: Committee Chair: Tannenbaum, Allen; Committee Co-Chair: Giddens, Don; Committee Member: Hu, Xiaoping; Committee Member: Stillman, Arthur; Committee Member: Yezzi, Anthony
Degree: Ph.D.

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