Spatial-temporal constraint for segmentation of serial infant brain MR images

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

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

12 Citations (Scopus)


Longitudinal infant studies offer a unique opportunity for revealing the dynamics of rapid human brain development in the first year of life. To this end, it is important to develop tissue segmentation and registration techniques for facilitating the detection of global and local morphological changes of brain structures in an infant population. However, there are two inherent challenges involved in development of such techniques. First, the MR images of the isointense stage - the duration between infantile and early adult stages in the first year of life - have low gray-white matter contrast. Second, temporal consistency cannot be preserved if segmentation and registration are performed separately for different time-points. In this paper, we proposed a 4D joint registration and segmentation framework for serial infant brain MR images. Specifically, a spatial-temporal constraint is formulated to make optimal use of T1 and T2 images, as well as adaptively propagate prior probability maps among time-points. In this process, 4D registration is employed to determine anatomical correspondence across time-points, and also a multi-channel segmentation algorithm, guided by spatial-temporally constrained prior tissue probability maps, is applied to segment the T1 and T2 images simultaneously at each time-point. Registration and segmentation are iterated as an Expectation-Maximization (EM) process until convergence. The infant segmentations yielded by the proposed method show high agreement with the results given by a manual rater and outperform the results when no temporal information is considered.

Original languageEnglish
Title of host publicationMedical Imaging and Augmented Reality - 5th International Workshop, MIAR 2010, Proceedings
Number of pages9
Publication statusPublished - 2010
Externally publishedYes
Event5th International Workshop on Medical Imaging and Augmented Reality, MIAR 2010 - Beijing, China
Duration: 2010 Sept 192010 Sept 20

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6326 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other5th International Workshop on Medical Imaging and Augmented Reality, MIAR 2010

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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