6533b85dfe1ef96bd12bf081

RESEARCH PRODUCT

Efficient Multi-scale Patch-Based Segmentation

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description

The objective of this paper is to devise an efficient and accurate patch-based method for image segmentation. The method presented in this paper builds on the work of Wu et al. [14] with the introduction of a compact multi-scale feature representation and heuristics to speed up the process. A smaller patch representation along with hierarchical pruning allowed the inclusion of more prior knowledge, resulting in a more accurate segmentation. We also propose an intuitive way of optimizing the search strategy to find similar voxel, making the method computationally efficient. An additional approach at improving the speed was explored with the integration of our method with Optimised PatchMatch [11]. The proposed method was validated using the 100 hippocampus images with ground truth segmentation from ADNI-1 (mean DSC = 0.892) and the MICCAI SATA segmentation challenge dataset (mean DSC = 0.8587).