Skip to main navigation Skip to search Skip to main content

Area preserving brain mapping

  • Zhengyu Su
  • , Wei Zeng
  • , Rui Shi
  • , Yalin Wang
  • , Jian Sun
  • , Xianfeng Gu
  • Stony Brook University
  • Florida International University
  • Arizona State University
  • Tsinghua University

Research output: Contribution to journal › Conference article › peer-review

35 Scopus citations

Abstract

Brain mapping transforms the brain cortical surface to canonical planar domains, which plays a fundamental role in morphological study. Most existing brain mapping methods are based on angle preserving maps, which may introduce large area distortions. This work proposes an area preserving brain mapping method based on Monge-Brenier theory. The brain mapping is intrinsic to the Riemannian metric, unique, and diffeomorphic. The computation is equivalent to convex energy minimization and power Voronoi diagram construction. Comparing to the existing approaches based on Monge-Kantorovich theory, the proposed one greatly reduces the complexity (from n 2 unknowns to n ), and improves the simplicity and efficiency. Experimental results on caudate nucleus surface mapping and cortical surface mapping demonstrate the efficacy and efficiency of the proposed method. Conventional methods for caudate nucleus surface mapping may suffer from numerical instability, in contrast, current method produces diffeomorpic mappings stably. In the study of cortical surface classification for recognition of Alzheimer's Disease, the proposed method outperforms some other morphometry features.

Original languageEnglish
Article number6619134
Pages (from-to)2235-2242
Number of pages8
JournalProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
DOIs
StatePublished - 2013
Event26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2013 - Portland, OR, United States
Duration: Jun 23 2013 → Jun 28 2013

Fingerprint

Dive into the research topics of 'Area preserving brain mapping'. Together they form a unique fingerprint.

Cite this