TY - JOUR
T1 - A discrete region competition approach incorporating weak edge enhancement for ultrasound image segmentation
AU - Chen, Chung Ming
AU - Horng-Shing Lu, Henry
AU - Chen, Yao Lin
PY - 2003/2/1
Y1 - 2003/2/1
N2 - Ultrasound images are inherently difficult to analyze due to their echo texture, speckle noise and weak edges. Taking into account these characteristics, we present a new region-based approach for ultrasound image segmentation. It is composed of two primary algorithms, discrete region competition and weak edge enhancement. The discrete region competition features four techniques, region competition, statistical modeling of speckle, early vision modeling, and discrete concepts. In addition, to prevent regions from leaking out of the desired area across weak edges, edges located on the slowly varying slope are enhanced according to their position on the slope and the length of the slope. This new approach has been implemented and verified on clinical ultrasound images.
AB - Ultrasound images are inherently difficult to analyze due to their echo texture, speckle noise and weak edges. Taking into account these characteristics, we present a new region-based approach for ultrasound image segmentation. It is composed of two primary algorithms, discrete region competition and weak edge enhancement. The discrete region competition features four techniques, region competition, statistical modeling of speckle, early vision modeling, and discrete concepts. In addition, to prevent regions from leaking out of the desired area across weak edges, edges located on the slowly varying slope are enhanced according to their position on the slope and the length of the slope. This new approach has been implemented and verified on clinical ultrasound images.
KW - Early vision
KW - Region segmentation
KW - Speckle
KW - Ultrasound image segmentation
UR - http://www.scopus.com/inward/record.url?scp=0037290156&partnerID=8YFLogxK
U2 - 10.1016/S0167-8655(02)00175-7
DO - 10.1016/S0167-8655(02)00175-7
M3 - Article
AN - SCOPUS:0037290156
SN - 0167-8655
VL - 24
SP - 693
EP - 704
JO - Pattern Recognition Letters
JF - Pattern Recognition Letters
IS - 4-5
ER -