Towards a parts-based approach to sub-cortical brain structure parsing

Digvijay Gagneja, Caiming Xiong, Jason J. Corso

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The automatic localization and segmentation, or parsing, of neuroanatomical brain structures is a key step in many neuroscience tasks. However, the inherent variability in these brain structures and their appearance continues to challenge medical image processing methods. The state of the art primarily relies upon local voxelbased morphometry, Markov random field, and probabilistic atlas based approaches, which limits the ability to explicitly capture the parts-based structure inherent in the brain. We propose a method that defines a principled parts-based representation of the sub-cortical brain structures. Our method is based on the pictorial structures model and jointly models the appearance of each part as well as the layout of the parts as a whole. Inference is cast as a maximum a posteriori problem and solved in a steepest-descent manner. Experimental results on a 28-case data set demonstrate high accuracy of our method and substantiate our claim that there is significant promise in a parts-based approach to modeling medical imaging structures.

Original languageEnglish
Title of host publicationMedical Imaging 2011
Subtitle of host publicationImage Processing
DOIs
StatePublished - 2011
EventMedical Imaging 2011: Image Processing - Lake Buena Vista, FL, United States
Duration: 14 Feb 201116 Feb 2011

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume7962
ISSN (Print)1605-7422

Conference

ConferenceMedical Imaging 2011: Image Processing
Country/TerritoryUnited States
CityLake Buena Vista, FL
Period14/02/1116/02/11

Keywords

  • neuroimaging
  • parts-based representation
  • pictorial structures
  • segmentation
  • sub-cortical structures

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