TY - GEN
T1 - Penalized geodesic tractography for mitigating gyral bias
AU - Wu, Ye
AU - Feng, Yuanjing
AU - Shen, Dinggang
AU - Yap, Pew Thian
N1 - Funding Information:
This work was supported by NIH grants (NS093842, EB022880, EB006733, EB009634, AG041721, MH100217, and AA012388) and NSFC grants (61379020, 61703369).
Publisher Copyright:
© Springer Nature Switzerland AG 2018.
PY - 2018
Y1 - 2018
N2 - In this paper, we introduce a penalized geodesic tractography (PGT) algorithm for mitigating gyral bias in cortical tractography, which is essential for improving cortical connectomics. Unlike deterministic and probabilistic tractography algorithms that perform one-way tracking, PGT solves a global optimization problem in estimating the pathways connecting multiple regions, instead of local step-by-step orientation tracing. PGT is unconfounded by local false-positive or false-negative fiber orientations and ensures that fiber streamlines that are intended to connect two regions do not terminate prematurely. We show that PGT reduces gyral bias by allowing streamlines to make sharper turns into the cortical gyral matter and results in a significantly more uniform spatial distribution of cortical connections.
AB - In this paper, we introduce a penalized geodesic tractography (PGT) algorithm for mitigating gyral bias in cortical tractography, which is essential for improving cortical connectomics. Unlike deterministic and probabilistic tractography algorithms that perform one-way tracking, PGT solves a global optimization problem in estimating the pathways connecting multiple regions, instead of local step-by-step orientation tracing. PGT is unconfounded by local false-positive or false-negative fiber orientations and ensures that fiber streamlines that are intended to connect two regions do not terminate prematurely. We show that PGT reduces gyral bias by allowing streamlines to make sharper turns into the cortical gyral matter and results in a significantly more uniform spatial distribution of cortical connections.
UR - http://www.scopus.com/inward/record.url?scp=85053890362&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-00931-1_2
DO - 10.1007/978-3-030-00931-1_2
M3 - Conference contribution
AN - SCOPUS:85053890362
SN - 9783030009304
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 12
EP - 19
BT - Medical Image Computing and Computer Assisted Intervention – MICCAI 2018 - 21st International Conference, 2018, Proceedings
A2 - Frangi, Alejandro F.
A2 - Davatzikos, Christos
A2 - Fichtinger, Gabor
A2 - Alberola-López, Carlos
A2 - Schnabel, Julia A.
PB - Springer Verlag
T2 - 21st International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2018
Y2 - 16 September 2018 through 20 September 2018
ER -