TY - GEN
T1 - Multiple cortical surface correspondence using pairwise shape similarity
AU - Dalal, Pahal
AU - Shi, Feng
AU - Shen, Dinggang
AU - Wang, Song
N1 - Copyright:
Copyright 2010 Elsevier B.V., All rights reserved.
PY - 2010
Y1 - 2010
N2 - Accurately corresponding a population of human cortical surfaces provides important shape information for the diagnosis of many brain diseases. This problem is very challenging due to the highly convoluted nature of cortical surfaces. Pairwise methods using a fixed template may not handle well the case when a target cortical surface is substantially different from the template. In this paper, we develop a new method to organize the population of cortical surfaces into pairs with high shape similarity and only correspond such similar pairs to achieve a higher accuracy. In particular, we use the geometric information to identify co-located gyri and sulci for defining a new measure of shape similarity. We conduct experiments on 40 instances of the cortical surface, resulting in an improved performance over several existing shape-correspondence methods.
AB - Accurately corresponding a population of human cortical surfaces provides important shape information for the diagnosis of many brain diseases. This problem is very challenging due to the highly convoluted nature of cortical surfaces. Pairwise methods using a fixed template may not handle well the case when a target cortical surface is substantially different from the template. In this paper, we develop a new method to organize the population of cortical surfaces into pairs with high shape similarity and only correspond such similar pairs to achieve a higher accuracy. In particular, we use the geometric information to identify co-located gyri and sulci for defining a new measure of shape similarity. We conduct experiments on 40 instances of the cortical surface, resulting in an improved performance over several existing shape-correspondence methods.
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U2 - 10.1007/978-3-642-15705-9_43
DO - 10.1007/978-3-642-15705-9_43
M3 - Conference contribution
C2 - 20879250
AN - SCOPUS:80055040135
SN - 3642157041
SN - 9783642157042
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 349
EP - 356
BT - Medical Image Computing and Computer-Assisted Intervention, MICCAI2010 - 13th International Conference, Proceedings
T2 - 13th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2010
Y2 - 20 September 2010 through 24 September 2010
ER -