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

doi:10.1007/978-3-030-00949-6_5

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 proceeding › Conference contribution

4 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 language	English
Title of host publication	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
Editors	Zeike 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
Publisher	Springer Verlag
Pages	35-43
Number of pages	9
ISBN (Print)	9783030009489
DOIs	https://doi.org/10.1007/978-3-030-00949-6_5
Publication status	Published - 2018
Event	1st 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: Sept 16 2018 → Sept 20 2018

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11039 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	1st International Workshop on Computational Pathology, COMPAY 2018 and 5th International Workshop on Ophthalmic Medical Image Analysis, OMIA 2018 Held in Conjunction with MICCAI 2018
Country/Territory	Spain
City	Granada
Period	9/16/18 → 9/20/18

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
Computer Science(all)

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-3-030-00949-6_5

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

Accurate 3D Reconstruction of a Whole Pancreatic Cancer Tumor from Pathology Images with Different Stains. / Kugler, Mauricio; Goto, Yushi; Kawamura, Naoki et al.
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. ed. / Zeike 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. Springer Verlag, 2018. p. 35-43 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11039 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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, MK Garvin, XJ 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. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11039 LNCS, Springer Verlag, pp. 35-43, 1st 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, 9/16/18. https://doi.org/10.1007/978-3-030-00949-6_5

Kugler M, Goto Y, Kawamura N, Kobayashi H, Yokota T, Iwamoto C et al. Accurate 3D Reconstruction of a Whole Pancreatic Cancer Tumor from Pathology Images with Different Stains. In Taylor Z, Bogunovic H, Snead D, Garvin MK, Chen XJ, Ciompi F, Xu Y, Maier-Hein L, Veta M, Trucco E, Stoyanov D, Rajpoot N, van der Laak J, Martel A, McKenna S, editors, 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. Springer Verlag. 2018. p. 35-43. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-00949-6_5

Kugler, Mauricio ; Goto, Yushi ; Kawamura, Naoki et al. / Accurate 3D Reconstruction of a Whole Pancreatic Cancer Tumor from Pathology Images with Different Stains. 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. editor / Zeike 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. Springer Verlag, 2018. pp. 35-43 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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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.",

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AU - Iwamoto, Chika

AU - Ohuchida, Kenoki

AU - Hashizume, Makoto

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

Abstract

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All Science Journal Classification (ASJC) codes

UN SDGs

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