Atlas-guided multi-channel forest learning for human brain labeling

Guangkai Ma, Yaozong Gao, Guorong Wu, Ligang Wu, Dinggang Shen

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

3 Citations (Scopus)

Abstract

Labeling MR brain images into anatomically meaningful regions is important in quantitative brain researches. Previous works can be roughly categorized into two classes: multi-atlas and learning based labeling methods. These methods all suffer from their own limitations. For multi-atlas based methods, the label fusion step is often handcrafted based on the predefined similarity metrics between voxels in the target and atlas images. For learning based methods, the spatial correspondence information encoded in the atlases is lost since they often use only the target image appearance for classification. In this paper, we propose a novel atlas-guided multi-channel forest learning, which could effectively address the aforementioned limitations. Instead of handcrafting the label fusion step, we learn a non-linear classification forest for automatically fusing both image appearance and label information of the atlas with the image appearance of the target image. Validated on LONI-LBPA40 dataset, our method outperforms several traditional labeling approaches.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages97-104
Number of pages8
Volume8848
ISBN (Print)9783319139715
DOIs
Publication statusPublished - 2014 Jan 1
Externally publishedYes
EventInternational Workshop on Medical Computer Vision: Algorithms for Big Data was held in conjunction with 17th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI-bigMCV 2014 - Cambridge, United States
Duration: 2014 Sep 182014 Sep 18

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8848
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

OtherInternational Workshop on Medical Computer Vision: Algorithms for Big Data was held in conjunction with 17th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI-bigMCV 2014
CountryUnited States
CityCambridge
Period14/9/1814/9/18

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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