Next: Introduction

Deformable Boundary Finding Influenced by Region Homogeneity

Amit Chakraborty, L.H. Staiband James S. Duncan
Departments of Electrical Engineeringand Diagnostic Radiology
Yale University,
333 Cedar Street, New Haven, CT 06520-8042


Keywords: biomedical image analysis, image segmentation, boundary finding, region based segmentation, MAP


Accurately segmenting and quantifying structures is a key issue in biomedical image analysis. The two conventional methods of image segmentation, region based segmentation and boundary finding, often suffer from a variety of limitations. Here we propose a method which endeavors to integrate the two approaches in an effort to form a unified approach that is robust to noise and poor initialization. Our approach uses Green's theorem to derive the boundary of a homogeneous region-classified area in the image and integrates this with a grey-level-gradient-based boundary finder. This combines the perceptual notions of edge/shape information with grey level homogeneity. A number of experiments were performed both on synthetic and real medical images of the brain and heart to evaluate the new approach and it is shown that the integrated method typically performs better when compared to conventional gradient based boundary finding. Further, this method yields these improvements with little increase in computational overhead, an advantage derived from the application of the Green's theorem.

Mon Mar 21 19:45:28 EST 1994