Accurate and consistent 4D segmentation of serial infant brain MR images

Li Wang, Feng Shi, Pew Thian Yap, John H. Gilmore, Weili Lin, Dinggang Shen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages93-101
Number of pages9
Volume7012 LNCS
DOIs
Publication statusPublished - 2011 Oct 11
Externally publishedYes
Event1st 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 - Toronto, ON, Canada
Duration: 2011 Sep 182011 Sep 18

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7012 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other1st 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
CountryCanada
CityToronto, ON
Period11/9/1811/9/18

Fingerprint

Brain
Segmentation
Tissue
Level Set Method
Longitudinal Study
Lowest
Term
Range of data

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Wang, L., Shi, F., Yap, P. T., Gilmore, J. H., Lin, W., & Shen, D. (2011). Accurate and consistent 4D segmentation of serial infant brain MR images. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7012 LNCS, pp. 93-101). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7012 LNCS). https://doi.org/10.1007/978-3-642-24446-9_12

Accurate and consistent 4D segmentation of serial infant brain MR images. / Wang, Li; Shi, Feng; Yap, Pew Thian; Gilmore, John H.; Lin, Weili; Shen, Dinggang.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7012 LNCS 2011. p. 93-101 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7012 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Wang, L, Shi, F, Yap, PT, Gilmore, JH, Lin, W & Shen, D 2011, Accurate and consistent 4D segmentation of serial infant brain MR images. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 7012 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7012 LNCS, pp. 93-101, 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, Toronto, ON, Canada, 11/9/18. https://doi.org/10.1007/978-3-642-24446-9_12
Wang L, Shi F, Yap PT, Gilmore JH, Lin W, Shen D. Accurate and consistent 4D segmentation of serial infant brain MR images. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7012 LNCS. 2011. p. 93-101. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-24446-9_12
Wang, Li ; Shi, Feng ; Yap, Pew Thian ; Gilmore, John H. ; Lin, Weili ; Shen, Dinggang. / Accurate and consistent 4D segmentation of serial infant brain MR images. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7012 LNCS 2011. pp. 93-101 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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