TY  - JOUR
T1  - Curve Evolution Using Integration of Image Region and Edge Information To Detect Cyst
AU - , Janet, J. AU - , T.R. Natesan AU - , R. Betsy 
JO  - International Journal of Soft Computing
VL  - 1
IS  - 1
SP  - 71
EP  - 75
PY  - 2006
DA  - 2001/08/19
SN  - 1816-9503
DO  - ijscomp.2006.71.75
UR  - https://makhillpublications.co/view-article.php?doi=ijscomp.2006.71.75
KW  - Integration
KW  -image
KW  -region
KW  -edge
KW  -information
AB  - Image segmentation is very important to complete many image processing and computer vision tasks. It can be defined as a partitioning of the image into homogenous regions and semantic objects. One of the popular approaches to image segmentation is curve evolution and active contour models. The main aim of the paper is to segment the medical images to detect ultrasound cyst in order to aid telemedicine and to determine the edge information or regional properties or a combination of them. Curve evolution methods usually result in closed contours as opposed to disconnected edges resulting from filtering methods. Edge based active contours try to fit an initial closed contour to an edge function generated from the original image.
ER  -