Hippocampus segmentation from MR infant brain images via boundary regression

Yeqin Shao, Yanrong Guo, Yaozong Gao, Xin Yang, Dinggang Shen

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

2 Citations (Scopus)

Abstract

Hippocampus segmentation from MR infant brain images is indispensable for studying early brain development. However, most of hippocampus segmentation methods were developed for adult brain images, which are not suitable for infant brain images of the first year due to low image contrast and variable structural patterns of early hippocampal development. To address these challenges, we propose a boundary regression method to detect hippocampal boundaries in the infant brain images, and then use the obtained boundaries to guide the deformable segmentation. The advantages of our segmentation method are: (1) different from the recently-developed atlas-based hippocampus segmentation methods, our method does not perform time-consuming deformable registrations; (2) different from the conventional point-regression-based boundary detection methods, our boundary regression method can predict the whole hippocampal boundary by a single regression model. Experiments on MR infant brain images from 2-week-old to 1-year-old show promising hippocampus segmentation results.

Original languageEnglish
Title of host publicationMedical Computer Vision: Algorithms for Big Data - International Workshop, MCV 2015 and Held in Conjunction with MICCAI 2015, Revised Selected Papers
PublisherSpringer Verlag
Pages146-154
Number of pages9
Volume9601
ISBN (Print)9783319420158
DOIs
Publication statusPublished - 2016
Externally publishedYes
EventInternational Workshop on Medical Image Computing for Computer Assisted Intervention, 2015 MICCAI - Germany, Germany
Duration: 2015 Oct 92015 Oct 9

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9601
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

OtherInternational Workshop on Medical Image Computing for Computer Assisted Intervention, 2015 MICCAI
CountryGermany
CityGermany
Period15/10/915/10/9

    Fingerprint

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Shao, Y., Guo, Y., Gao, Y., Yang, X., & Shen, D. (2016). Hippocampus segmentation from MR infant brain images via boundary regression. In Medical Computer Vision: Algorithms for Big Data - International Workshop, MCV 2015 and Held in Conjunction with MICCAI 2015, Revised Selected Papers (Vol. 9601, pp. 146-154). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9601). Springer Verlag. https://doi.org/10.1007/978-3-319-42016-5_14