Automatic segmentation of neonatal images using convex optimization and coupled level set method

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

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

2 Citations (Scopus)

Abstract

Accurate segmentation of neonatal brain MR images remains challenging mainly due to poor spatial resolution, low tissue contrast, high intensity inhomogeneity. Most existing methods for neonatal brain segmentation are atlas-based and voxel-wise. Although parametric or geometric deformable models have been successfully applied to adult brain segmentation, to the best of our knowledge, they are not explored in neonatal images. In this paper, we propose a novel neonatal image segmentation method, combining local intensity information, atlas spatial prior and cortical thickness constraint, in a level set framework. Besides, we also provide a robust and reliable tissue surfaces initialization for our proposed level set method by using a convex optimization technique. Validation is performed on 10 neonatal brain images 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)
Pages1-10
Number of pages10
Volume6326 LNCS
DOIs
Publication statusPublished - 2010 Nov 9
Externally publishedYes
Event5th International Workshop on Medical Imaging and Augmented Reality, MIAR 2010 - Beijing, China
Duration: 2010 Sep 192010 Sep 20

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6326 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other5th International Workshop on Medical Imaging and Augmented Reality, MIAR 2010
CountryChina
CityBeijing
Period10/9/1910/9/20

Fingerprint

Level Set Method
Convex optimization
Convex Optimization
Brain
Segmentation
Atlas
Tissue
Deformable Models
Geometric Model
Voxel
Image segmentation
Initialization
Inhomogeneity
Level Set
Image Segmentation
Spatial Resolution
Optimization Techniques

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Wang, L., Shi, F., Gilmore, J. H., Lin, W., & Shen, D. (2010). Automatic segmentation of neonatal images using convex optimization and coupled level set method. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6326 LNCS, pp. 1-10). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6326 LNCS). https://doi.org/10.1007/978-3-642-15699-1_1

Automatic segmentation of neonatal images using convex optimization and coupled level set method. / Wang, Li; Shi, Feng; 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. 6326 LNCS 2010. p. 1-10 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6326 LNCS).

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

Wang, L, Shi, F, Gilmore, JH, Lin, W & Shen, D 2010, Automatic segmentation of neonatal images using convex optimization and coupled level set method. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 6326 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6326 LNCS, pp. 1-10, 5th International Workshop on Medical Imaging and Augmented Reality, MIAR 2010, Beijing, China, 10/9/19. https://doi.org/10.1007/978-3-642-15699-1_1
Wang L, Shi F, Gilmore JH, Lin W, Shen D. Automatic segmentation of neonatal images using convex optimization and coupled level set method. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 6326 LNCS. 2010. p. 1-10. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-15699-1_1
Wang, Li ; Shi, Feng ; Gilmore, John H. ; Lin, Weili ; Shen, Dinggang. / Automatic segmentation of neonatal images using convex optimization and coupled level set method. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 6326 LNCS 2010. pp. 1-10 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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