Deep learning for tissue microarray image-based outcome prediction in patients with colorectal cancer

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Original languageEnglish
Title of host publicationMedical Imaging 2016: Digital Pathology
EditorsMetin N. Gurcan, Anant Madabhushi
Number of pages6
PublisherSPIE - INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING
Publication date2016
Pages979115
ISBN (Print)978-1-5106-0026-3
DOIs
Publication statusPublished - 2016
MoE publication typeA4 Article in conference proceedings
EventConference on Medical Imaging - Digital Pathology - San Diego, CA, United States
Duration: 2 Mar 20163 Mar 2016

Publication series

NameProceedings of SPIE
PublisherSPIE-INT SOC OPTICAL ENGINEERING
Volume9791
ISSN (Print)0277-786X

Fields of Science

  • colorectal cancer
  • outcome prediction
  • gland segmentation
  • computer assisted diagnostics
  • deep learning
  • supervised convolutional neural networks
  • 3122 Cancers

Cite this

Bychkov, D., Turkki, R., Haglund, C., Linder, N., & Lundin, J. (2016). Deep learning for tissue microarray image-based outcome prediction in patients with colorectal cancer. In M. N. Gurcan, & A. Madabhushi (Eds.), Medical Imaging 2016: Digital Pathology (pp. 979115). (Proceedings of SPIE; Vol. 9791). SPIE - INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING. https://doi.org/10.1117/12.2217072
Bychkov, Dmitrii ; Turkki, Riku ; Haglund, Caj ; Linder, Nina ; Lundin, Johan. / Deep learning for tissue microarray image-based outcome prediction in patients with colorectal cancer. Medical Imaging 2016: Digital Pathology. editor / Metin N. Gurcan ; Anant Madabhushi. SPIE - INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING, 2016. pp. 979115 (Proceedings of SPIE).
@inproceedings{6935dfec1b8140a080fb5912f9d16588,
title = "Deep learning for tissue microarray image-based outcome prediction in patients with colorectal cancer",
keywords = "colorectal cancer, outcome prediction, gland segmentation, computer assisted diagnostics, deep learning, supervised convolutional neural networks, 3122 Cancers",
author = "Dmitrii Bychkov and Riku Turkki and Caj Haglund and Nina Linder and Johan Lundin",
note = "Volume: Proceeding volume:",
year = "2016",
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publisher = "SPIE - INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING",
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editor = "Gurcan, {Metin N.} and Anant Madabhushi",
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Bychkov, D, Turkki, R, Haglund, C, Linder, N & Lundin, J 2016, Deep learning for tissue microarray image-based outcome prediction in patients with colorectal cancer. in MN Gurcan & A Madabhushi (eds), Medical Imaging 2016: Digital Pathology. Proceedings of SPIE, vol. 9791, SPIE - INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING, pp. 979115, Conference on Medical Imaging - Digital Pathology, San Diego, CA, United States, 02/03/2016. https://doi.org/10.1117/12.2217072

Deep learning for tissue microarray image-based outcome prediction in patients with colorectal cancer. / Bychkov, Dmitrii; Turkki, Riku; Haglund, Caj; Linder, Nina; Lundin, Johan.

Medical Imaging 2016: Digital Pathology. ed. / Metin N. Gurcan; Anant Madabhushi. SPIE - INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING, 2016. p. 979115 (Proceedings of SPIE; Vol. 9791).

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

TY - GEN

T1 - Deep learning for tissue microarray image-based outcome prediction in patients with colorectal cancer

AU - Bychkov, Dmitrii

AU - Turkki, Riku

AU - Haglund, Caj

AU - Linder, Nina

AU - Lundin, Johan

N1 - Volume: Proceeding volume:

PY - 2016

Y1 - 2016

KW - colorectal cancer

KW - outcome prediction

KW - gland segmentation

KW - computer assisted diagnostics

KW - deep learning

KW - supervised convolutional neural networks

KW - 3122 Cancers

U2 - 10.1117/12.2217072

DO - 10.1117/12.2217072

M3 - Conference contribution

SN - 978-1-5106-0026-3

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BT - Medical Imaging 2016: Digital Pathology

A2 - Gurcan, Metin N.

A2 - Madabhushi, Anant

PB - SPIE - INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING

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Bychkov D, Turkki R, Haglund C, Linder N, Lundin J. Deep learning for tissue microarray image-based outcome prediction in patients with colorectal cancer. In Gurcan MN, Madabhushi A, editors, Medical Imaging 2016: Digital Pathology. SPIE - INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING. 2016. p. 979115. (Proceedings of SPIE). https://doi.org/10.1117/12.2217072