Multiple atlases-based joint labeling of human cortical sulcal curves

Ilwoo Lyu, Gang Li, Minjeong Kim, Dinggang Shen

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

1 Citation (Scopus)

Abstract

We present a spectral-based sulcal curve labeling method by considering geometrical information of neighboring curves in a multiple atlases-based framework. Compared to the conventional method, we propose to use neighboring curves for avoiding ambiguity in curve-by-curve labeling and to integrate the labeling results obtained from multiple atlases for consistent labeling. In particular, we compute a histogram of points on the neighboring curves as a new feature descriptor for each point on a sulcal curve under consideration. To better resolve ambiguity in the curve labeling, we also employ the neighboring curves that are parallel to major sulcal curves. Moreover, we further integrate all the results from multiple atlases into a linear system, by solving which our method ultimately gives accurate labels to the major curves in the subjects. Experimental results on evaluation of 12 major sulcal curves of 12 human cortical surfaces indicate that our method achieves higher labeling accuracy 7.87% compared to the conventional method, while reducing 4.41% of false positive labeling errors on average.

Original languageEnglish
Title of host publicationMedical Computer Vision
Subtitle of host publicationRecognition Techniques and Applications in Medical Imaging - Second International MICCAI Workshop, MCV 2012, Revised Selected Papers
Pages124-132
Number of pages9
DOIs
Publication statusPublished - 2013 Mar 25
Externally publishedYes
Event2nd MICCAI Workshop on Medical Computer Vision, MICCAI-MCV 2012, Held in Conjunction with the 15th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2012 - Nice, France
Duration: 2012 Oct 52012 Oct 5

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7766 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other2nd MICCAI Workshop on Medical Computer Vision, MICCAI-MCV 2012, Held in Conjunction with the 15th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2012
CountryFrance
CityNice
Period12/10/512/10/5

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Keywords

  • multiple atlases
  • spectral matching
  • sulcal curve labeling

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Lyu, I., Li, G., Kim, M., & Shen, D. (2013). Multiple atlases-based joint labeling of human cortical sulcal curves. In Medical Computer Vision: Recognition Techniques and Applications in Medical Imaging - Second International MICCAI Workshop, MCV 2012, Revised Selected Papers (pp. 124-132). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7766 LNCS). https://doi.org/10.1007/978-3-642-36620-8_13