Abstract #3747
THOMAS: Thalamus Optimized Multi-Atlas Segmentation
Jason Su 1,2 , Thomas Tourdias 3 , Manojkumar Saranathan 2 , and Brian K. Rutt 2
1
Electrical Engineering, Stanford University,
Stanford, California, United States,
2
Radiology,
Stanford University, Stanford, California, United
States,
3
Neuroradiology, Bordeaux University
Hospital, Bordeaux, France
A method for automatic segmentation of thalamic nuclei
was developed and optimized using 7T white-matter-nulled
MP-RAGE images, which provide excellent contrast and
detail for segmentation and for ANTS nonlinear
registration. The PICSL multi-atlas label fusion
algorithm by Wang and Yushkevich was optimized for 12
thalamic nuclei and validated in 9 subjects using an
atlas of prior manual delineations from 20 subjects,
including multiple sclerosis patients and healthy
controls. Performance in accuracy, resolution, and
acquisition time surpasses other published methods that
require DTI. The Dice coefficients for whole thalamus
(0.92), pulvinar nucleus (0.86), and mediodorsal nucleus
(0.87) were notably high.
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