TY - GEN
T1 - Accurate and consistent 4D segmentation of serial infant brain MR images
AU - Wang, Li
AU - Shi, Feng
AU - Yap, Pew Thian
AU - Gilmore, John H.
AU - Lin, Weili
AU - Shen, Dinggang
PY - 2011
Y1 - 2011
N2 - Accurate and consistent segmentation of infant brain MR images plays an important role in quantifying the early brain development, especially in longitudinal studies. However, due to rapid maturation and myelination of brain tissues in the first year of life, white-gray matter contrast undergoes dramatic changes. In fact, the contrast inverses around 6 months of age, where the white and gray matter tissues are isointense and hence exhibit the lowest contrast, posing significant challenges for segmentation algorithms. In this paper, we propose a novel longitudinally guided level set method for segmentation of serial infant brain MR images, acquired from 2 weeks up to 1.5 years of age. The proposed method makes optimal use of T1, T2 and the diffusion weighted images for complimentary tissue distribution information to address the difficulty caused by the low contrast. A longitudinally consistent term, which constrains the distance across the serial images within a biologically reasonable range, is employed to obtain temporally consistent segmentation results. The proposed method has been applied on 22 longitudinal infant subjects with promising results.
AB - Accurate and consistent segmentation of infant brain MR images plays an important role in quantifying the early brain development, especially in longitudinal studies. However, due to rapid maturation and myelination of brain tissues in the first year of life, white-gray matter contrast undergoes dramatic changes. In fact, the contrast inverses around 6 months of age, where the white and gray matter tissues are isointense and hence exhibit the lowest contrast, posing significant challenges for segmentation algorithms. In this paper, we propose a novel longitudinally guided level set method for segmentation of serial infant brain MR images, acquired from 2 weeks up to 1.5 years of age. The proposed method makes optimal use of T1, T2 and the diffusion weighted images for complimentary tissue distribution information to address the difficulty caused by the low contrast. A longitudinally consistent term, which constrains the distance across the serial images within a biologically reasonable range, is employed to obtain temporally consistent segmentation results. The proposed method has been applied on 22 longitudinal infant subjects with promising results.
UR - http://www.scopus.com/inward/record.url?scp=80053558474&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-24446-9_12
DO - 10.1007/978-3-642-24446-9_12
M3 - Conference contribution
AN - SCOPUS:80053558474
SN - 9783642244452
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 93
EP - 101
BT - Multimodal Brain Image Analysis - First International Workshop, MBIA 2011, Held in Conjunction with MICCAI 2011, Proceedings
T2 - 1st International Workshop on Multimodal Brain Image Analysis, MBIA 2011, in Conjunction with the 14th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2011
Y2 - 18 September 2011 through 18 September 2011
ER -