DocumentCode
1750072
Title
Level set regularizers for shape recovery in medical images
Author
Suri, Jasjit S. ; Liu, Kecheng
Author_Institution
Marconi Med. Syst. Inc., Cleveland, OH, USA
fYear
2001
fDate
2001
Firstpage
369
Lastpage
374
Abstract
Due to the recent growth of level sets and partial differential equation (PDE) based approaches, the importance of designing regularizers has risen steadily. This paper presents a classification tree for regularizers and the design of regularization forces for the robust segmentation of static and motion imagery
Keywords
computational geometry; computer vision; image classification; image restoration; image segmentation; medical image processing; motion estimation; partial differential equations; trees (mathematics); classification tree; level sets; low-level vision; medical images; motion estimation; motion imagery; partial differential equation; regularization forces; regularizers; robust image segmentation; shape recovery; static imagery; topology; Biomedical imaging; Classification tree analysis; Deformable models; Equations; IEEE members; Image segmentation; Level set; Shape; Topology; USA Councils;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer-Based Medical Systems, 2001. CBMS 2001. Proceedings. 14th IEEE Symposium on
Conference_Location
Bethesda, MD
ISSN
1063-7125
Print_ISBN
0-7695-1004-3
Type
conf
DOI
10.1109/CBMS.2001.941747
Filename
941747
Link To Document