Accurate 3D Reconstruction of a Whole Pancreatic Cancer Tumor from Pathology Images with Different Stains

Mauricio Kugler, Yushi Goto, Naoki Kawamura, Hirokazu Kobayashi, Tatsuya Yokota, Chika Iwamoto, Kenoki Ohuchida, Makoto Hashizume, Hidekata Hontani

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

3 Citations (Scopus)

Abstract

When applied to 3D image reconstruction, conventional landmark-based registration methods tend to generate unnatural vertical structures due to inconsistencies between the employed model and the real tissue. This paper demonstrates a fully non-rigid image registration method for 3D image reconstruction which considers the spatial continuity and smoothness of each constituent part of the microstructures in the tissue. Corresponding landmarks are detected along the images, defining a set of trajectories, which are smoothed out in order to define a diffeomorphic mapping. The resulting reconstructed 3D image preserves the original tissue architecture, allowing the observation of fine details and structures.

Original languageEnglish
Title of host publicationComputational Pathology and Ophthalmic Medical Image Analysis - First International Workshop, COMPAY 2018, and 5th International Workshop, OMIA 2018, Held in Conjunction with MICCAI 2018, Proceedings
EditorsZeike Taylor, Hrvoje Bogunovic, David Snead, Mona K. Garvin, Xin Jan Chen, Francesco Ciompi, Yanwu Xu, Lena Maier-Hein, Mitko Veta, Emanuele Trucco, Danail Stoyanov, Nasir Rajpoot, Jeroen van der Laak, Anne Martel, Stephen McKenna
PublisherSpringer Verlag
Pages35-43
Number of pages9
ISBN (Print)9783030009489
DOIs
Publication statusPublished - Jan 1 2018
Event1st International Workshop on Computational Pathology, COMPAY 2018 and 5th International Workshop on Ophthalmic Medical Image Analysis, OMIA 2018 Held in Conjunction with MICCAI 2018 - Granada, Spain
Duration: Sep 16 2018Sep 20 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11039 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other1st International Workshop on Computational Pathology, COMPAY 2018 and 5th International Workshop on Ophthalmic Medical Image Analysis, OMIA 2018 Held in Conjunction with MICCAI 2018
CountrySpain
CityGranada
Period9/16/189/20/18

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Kugler, M., Goto, Y., Kawamura, N., Kobayashi, H., Yokota, T., Iwamoto, C., Ohuchida, K., Hashizume, M., & Hontani, H. (2018). Accurate 3D Reconstruction of a Whole Pancreatic Cancer Tumor from Pathology Images with Different Stains. In Z. Taylor, H. Bogunovic, D. Snead, M. K. Garvin, X. J. Chen, F. Ciompi, Y. Xu, L. Maier-Hein, M. Veta, E. Trucco, D. Stoyanov, N. Rajpoot, J. van der Laak, A. Martel, & S. McKenna (Eds.), Computational Pathology and Ophthalmic Medical Image Analysis - First International Workshop, COMPAY 2018, and 5th International Workshop, OMIA 2018, Held in Conjunction with MICCAI 2018, Proceedings (pp. 35-43). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11039 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-00949-6_5