Segmentation Subject to Stitching Constraints: Finding Many Small Structures in a Large Image

International Conference on Medical Image Computing and Computer Assisted Intervention, Beijing, China, 20-24 September 2010 Extracting numerous cells in a large microscopic image is often required in medical research. The challenge is to reduce the segmentation complexity on a large image without losing the fine segmentation granularity of small structures. We propose a constrained spectral graph partitioning approach where the segmentation of the entire image is obtained from a set of patch segmentations, independently derived but subject to stitching constraints between neighboring patches. The constraints come from mutual agreement analysis on patch segmentations from a previous round. Our experimental results demonstrate that the constrained segmentation not only stitches solutions seamlessly along overlapping patch borders but also refines the segmentation in the patch interiors.

• Type: Journal
• Year: 2010
• Where: MICCAI
• Authors: Elena Bernardis, Stella X. Yu
• Keywords: Image, Medical Imaging, MICCAI 2010, Patch Segmentations, fine Segmentation Granularity