Smoothness-based forces for deformable models: a long-range force and a corner fitting force.

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Show simple item record Zhang, Z Braun, M 2009-12-21T02:31:06Z 2003-01
dc.identifier.citation Computers in biology and medicine, 2003, 33 (1), pp. 91 - 112
dc.identifier.issn 0010-4825
dc.identifier.other C1 en_US
dc.description.abstract Deformable models, originally proposed by Terzopoulos et al. (Artif. Intell. 36 (1988) 91) and Kass et al. (Int. J. Comput. Vision 1 (1988) 321) in 1988, have been widely used in medical image segmentation. However, they manifest two well-known limitations: the lack of an appropriate long-range force to drive the model surface towards the object boundary and poor performance at high curvature boundaries (such as corners) due to the models' intrinsic smoothness constraint. In this paper, a new smoothness force with local control is proposed. The local control is used to devise a long-range force, referred to as the self-zoom force, and a corner fitting force. The self-zoom force enables the model surface to expand and shrink without a limit in range. The corner fitting force propels the model surface to fit high-curvature boundaries. Experiments demonstrate that the model surface is driven to the object boundary by the new forces even if the initial estimate is not close and the object is nonconvex or has a high local curvature.
dc.format Print
dc.language eng
dc.relation.hasversion Accepted manuscript version en_US
dc.relation.isbasedon 10.1016/s0010-4825(02)00028-8
dc.title Smoothness-based forces for deformable models: a long-range force and a corner fitting force.
dc.type Journal Article
dc.parent Computers in biology and medicine
dc.journal.volume 1
dc.journal.volume 33
dc.journal.number 1 en_US
dc.publocation Oxford, England en_US
dc.identifier.startpage 91 en_US
dc.identifier.endpage 112 en_US SCI.Physics and Advanced Materials en_US
dc.conference Verified OK en_US
dc.for 0802 Computation Theory and Mathematics
dc.personcode 910301
dc.percentage 100 en_US Computation Theory and Mathematics en_US
dc.classification.type FOR-08 en_US
dc.description.keywords Humans
dc.description.keywords Tibia
dc.description.keywords Kidney
dc.description.keywords Tomography, X-Ray Computed
dc.description.keywords Imaging, Three-Dimensional
dc.description.keywords Magnetic Resonance Imaging
dc.description.keywords Computer Simulation
dc.description.keywords Image Processing, Computer-Assisted
dc.description.keywords Pattern Recognition, Visual
dc.description.keywords Models, Biological
pubs.embargo.period Not known
pubs.organisational-group /University of Technology Sydney
pubs.organisational-group /University of Technology Sydney/Faculty of Science
pubs.organisational-group /University of Technology Sydney/Faculty of Science/School of Physics and Advanced Materials
utslib.copyright.status Open Access 2015-04-15 12:23:47.074767+10
pubs.consider-herdc true

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