Image Segmentation Errors Correction by Mesh Segmentation and Deformation

Abstract

Volumetric image segmentation methods often produce delineations of anatomical structures and pathologies that require user modifications. We present a new method for the correction of segmentation errors. Given an initial geometrical mesh, our method semi automatically identifies the mesh vertices in erroneous regions with min-cut segmentation. It then deforms the mesh by correcting its vertex coordinates with Laplace deformation based on local geometrical properties. The key advantages of our method are that: (1) it supports fast user interaction on a single surface rendered 2D view; (2) its parameters values are fixed to the same value for all cases; (3) it is independent of the initial segmentation method, and; (4) it is applicable to a variety of anatomical structures and pathologies. Experimental evaluation on 44 initial segmentations of kidney and kidney vessels from CT scans show an improvement of 83% and 75% in the average surface distance and the volume overlap error between the initial and the corrected segmentations with respect to the ground-truth.