|International Journal of Applied Information Systems|
|Foundation of Computer Science (FCS), NY, USA|
|Volume 3 - Number 1|
|Year of Publication: 2012|
|Authors: Ajala F.a, Emuoyibofarhe J.o|
Ajala F.a, Emuoyibofarhe J.o . Enhanced Geometric Active Contour Segmentation Model (ENGAC) For Medical Image Segmentation. International Journal of Applied Information Systems. 3, 1 ( July 2012), 1-8. DOI=http:/ijais12-450422
Segmentation is an aspect of computer vision that deals with partitioning of an image into homogeneneous region. Medical image segmentation is an indispensable tool for medical image diagnoses. This work built on Geometric active contour (GAC) segmentation which is one of the outstanding model used in machine learning community to solve the problem of medical image segmentation. However, GAC has problem of deviation from the true outline of the target feature and it generates spurious edge caused by noise that normally stop the evolution of the surface to be extracted.