Registering histological and MR images of prostate for image-based cancer detection

Yiqiang Zhan, Michael Feldman, John Tomaszeweski, Christos Davatzikos, Dinggang Shen

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

Abstract

This paper presents a deformable registration method to co-register histological images with MR images of the same prostate. By considering various distortion and cutting artifacts in histological images and also fundamentally different nature of histological and MR images, our registration method is thus guided by two types of landmark points that can be reliably detected in both histological and MR images, i.e., prostate boundary points, and internal salient points that can be identified by a scale-space analysis method. The similarity between these automatically detected landmarks in histological and MR images are defined by geometric features and normalized mutual information, respectively. By optimizing a function, which integrates the similarities between landmarks with spatial constraints, the correspondences between the landmarks as well as the deformable transformation between histological and MR images can be simultaneously obtained. The performance of our proposed registration algorithm has been evaluated by various designed experiments. This work is part of a larger effort to develop statistical atlases of prostate cancer using both imaging and histological information, and to use these atlases for optimal biopsy and therapy planning.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages620-628
Number of pages9
Volume4191 LNCS - II
Publication statusPublished - 2006 Oct 30
Externally publishedYes
Event9th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2006 - Copenhagen, Denmark
Duration: 2006 Oct 12006 Oct 6

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4191 LNCS - II
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other9th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2006
CountryDenmark
CityCopenhagen
Period06/10/106/10/6

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ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

Cite this

Zhan, Y., Feldman, M., Tomaszeweski, J., Davatzikos, C., & Shen, D. (2006). Registering histological and MR images of prostate for image-based cancer detection. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4191 LNCS - II, pp. 620-628). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4191 LNCS - II).