Next: Introduction
Deformable Boundary Finding Influenced by Region
Homogeneity
Amit Chakraborty
, L.H. Staib
and James S. Duncan
Departments of Electrical Engineering
and Diagnostic Radiology
Yale University,
333 Cedar Street, New Haven, CT 06520-8042
Email: chakrab@noodle.med.yale.edu
Keywords: biomedical image analysis, image segmentation, boundary finding, region based segmentation, MAP
Abstract:
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.