3D Liver Contour Reconstruction from Dual Ultrasound Slices Using Active Contour Model Segmentation and Image-Guided Tracking
Date Issued
2012
Date
2012
Author(s)
Lin, Feng-Chih
Abstract
An image-guided system for a liver tracking is presented in this thesis. Traditional medical image-guided systems include computed tomography (CT), magnetic resonance imaging (MRI) and ultrasound image (US). While considering frame rate and invasiveness, the ultrasound image-guided system is proposed for tracking the liver motion. The main objective is to use ultrasound image for continuously tracking liver motion and for tumor treatment. Traditional template matching cannot describe the non-rigid body motion, and consume a large amount of computational time. To improve the accuracy and computation speed, two tracking methods are tested, including optical flow and neural network. Two different scenarios are experimentally tested. In the first scenario, the “subject” breathes normally. In the second scenario, the “subject” varies between taking deep and slow breathes, holding his breath, or panting rapidly. For the first scenario, all three methods could track the target motion successfully, while, for the second scenario, all methods might lose the target occasionally.
The primary methods of existing 3D contour reconstruction scan a static organ with moving probe. However, this idea is not suitable for dynamic organ. A low-cost and flexible ultrasound imaging system which combines contour registration with image segmentation for 3D reconstructions from limited numbers of 2D contours is presented. The proposed approach is based on a fixed ultrasound probe system that collect each partial 2D imaging through the liver motion due to respiration. For reliable reconstruction performance, a new method for image segmentation and contour registration is developed. A new hybrid approach that provides reliable segmentation performance with texture distance image and active contour model is presented. Second, using the segmented contour, a new dual contours registration method is introduced. The approach uses additional probe to track the position of acquisition of images during scanning. Then, the contour registration is performed using contour for iterative closest point (ICP) matching. This registration system allows for accurate 3D reconstructions from sparse 2D image slices.
Subjects
ultrasound
image tracking
image segmentation
3D contour reconstruction
image registration
Type
thesis
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