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Medical Image Segmentation by Transferring Ground Truth Segmentation Based upon Top Down and Bottom Up Approach

Authors

Aseem Vyas and Won-Sook Lee, University of Ottawa, Canada

Abstract

In this paper, we present a novel method for image segmentation of the hip joint structure. The key idea is to transfer the ground truth segmentation from the database to the test image. The ground truth segmentation of MR images is done by medical experts. The process includes the top down approach which register the shape of the test image globally and locally with the database of train images. The goal of top down approach is to find the best train image for each of the local test image parts. The bottom up approach replaces the local test parts by best train image parts, and inverse transform the best train image parts to represent a test image by the mosaic of best train image parts. The ground truth segmentation is transferred from best train image parts to their corresponding location in the test image.

Keywords

Shape matching, Hausdorff distance, affine transformation, Medical image segmentation, simulated annealing optimization

Full Text  Volume 5, Number 1