TY - GEN
T1 - Automatic boundary evolution tracking via a combined level set method and mesh warping technique
T2 - MICCAI 2012 International Workshop on Mesh Processing in Medical Image Analysis, MeshMed 2012
AU - Park, Jeonghyung
AU - Shontz, Suzanne M.
AU - Drapaca, Corina S.
N1 - Funding Information:
The work of the first author was funded by NSF CAREER Award OCI-1054459; the work of the second author was funded in part by NSF CAREER Award OCI-1054459 and NSF grant CNS-0720749.
PY - 2012
Y1 - 2012
N2 - Hydrocephalus is a neurological disease which causes ventricular dilation due to abnormalities in the cerebrospinal fluid (CSF) circulation. Although treatment via a CSF shunt in the brain ventricles has been performed, poor rates of patient responses continue. Thus, to aid surgeons in hydrocephalus treatment planning, we propose a geometric computational approach for tracking hydrocephalus ventricular boundary evolution via the level set method and a mesh warping technique. In our previous work [1], we evolved the ventricular boundary in 2D CT images which required a backtracking line search for obtaining valid intermediate meshes. In this paper, we automatically detect the ventricular boundary evolution for 2D CT images. To help surgeons determine where to implant the shunt, we also compute the brain ventricle volume evolution for 3D MR images using our approach.
AB - Hydrocephalus is a neurological disease which causes ventricular dilation due to abnormalities in the cerebrospinal fluid (CSF) circulation. Although treatment via a CSF shunt in the brain ventricles has been performed, poor rates of patient responses continue. Thus, to aid surgeons in hydrocephalus treatment planning, we propose a geometric computational approach for tracking hydrocephalus ventricular boundary evolution via the level set method and a mesh warping technique. In our previous work [1], we evolved the ventricular boundary in 2D CT images which required a backtracking line search for obtaining valid intermediate meshes. In this paper, we automatically detect the ventricular boundary evolution for 2D CT images. To help surgeons determine where to implant the shunt, we also compute the brain ventricle volume evolution for 3D MR images using our approach.
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U2 - 10.1007/978-3-642-33463-4_13
DO - 10.1007/978-3-642-33463-4_13
M3 - Conference contribution
AN - SCOPUS:84871428446
SN - 9783642334627
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 122
EP - 133
BT - Mesh Processing in Medical Image Analysis - MICCAI 2012 International Workshop, MeshMed 2012, Proceedings
Y2 - 1 October 2012 through 1 October 2012
ER -