TY - JOUR
T1 - Semiautomatic Segmentation of Brain Subcortical Structures from High-Field MRI
AU - Kim, Jinyoung
AU - Lenglet, Christophe
AU - Duchin, Yuval
AU - Sapiro, Guillermo
AU - Harel, Noam
N1 - Publisher Copyright:
© 2013 IEEE.
PY - 2014/9
Y1 - 2014/9
N2 - Volumetric segmentation of subcortical structures, such as the basal ganglia and thalamus, is necessary for noninvasive diagnosis and neurosurgery planning. This is a challenging problem due in part to limited boundary information between structures, similar intensity profiles across the different structures, and low contrast data. This paper presents a semiautomatic segmentation system exploiting the superior image quality of ultrahigh field (7 T) MRI. The proposed approach utilizes the complementary edge information in the multiple structural MRI modalities. It combines optimally selected two modalities from susceptibility-weighted, T2-weighted, and diffusion MRI, and introduces a tailored new edge indicator function. In addition to this, we employ prior shape and configuration knowledge of the subcortical structures in order to guide the evolution of geometric active surfaces. Neighboring structures are segmented iteratively, constraining oversegmentation at their borders with a nonoverlapping penalty. Several experiments with data acquired on a 7 T MRI scanner demonstrate the feasibility and power of the approach for the segmentation of basal ganglia components critical for neurosurgery applications such as deep brain stimulation surgery.
AB - Volumetric segmentation of subcortical structures, such as the basal ganglia and thalamus, is necessary for noninvasive diagnosis and neurosurgery planning. This is a challenging problem due in part to limited boundary information between structures, similar intensity profiles across the different structures, and low contrast data. This paper presents a semiautomatic segmentation system exploiting the superior image quality of ultrahigh field (7 T) MRI. The proposed approach utilizes the complementary edge information in the multiple structural MRI modalities. It combines optimally selected two modalities from susceptibility-weighted, T2-weighted, and diffusion MRI, and introduces a tailored new edge indicator function. In addition to this, we employ prior shape and configuration knowledge of the subcortical structures in order to guide the evolution of geometric active surfaces. Neighboring structures are segmented iteratively, constraining oversegmentation at their borders with a nonoverlapping penalty. Several experiments with data acquired on a 7 T MRI scanner demonstrate the feasibility and power of the approach for the segmentation of basal ganglia components critical for neurosurgery applications such as deep brain stimulation surgery.
KW - Basal ganglia and thalamus
KW - deep brain stimulation (DBS)
KW - geodesic active surface (GAS)
KW - segmentation
KW - ultrahigh field MRI
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U2 - 10.1109/JBHI.2013.2292858
DO - 10.1109/JBHI.2013.2292858
M3 - Article
C2 - 25192576
AN - SCOPUS:84962539820
SN - 2168-2194
VL - 18
SP - 1678
EP - 1695
JO - IEEE Journal of Biomedical and Health Informatics
JF - IEEE Journal of Biomedical and Health Informatics
IS - 5
M1 - 6676825
ER -