Towards Better Soft-Tissue Segmentation Based on Gestalt Psychology

Abstract

According to gestalt psychology theory, the human brain merges and simplifies unrelated units by some relations through eyes for subsequent cognition. We introduce a new segmentation framework based on gestalt psychology in this paper. An input image is first divided into visual patches using two gestalt principles, similarity and proximity, by a clustering method, and then the visual patches are grouped to form soft tissues by a classification step using the spatial relationship and texture features. We evaluated the proposed method using TCIA database at both sectional level and volumetric level. The experimental results demonstrated the efficiency and robustness of the presented method and indicated its promising applications in the field of medical image processing.