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

Dmitrii Bychkov; Riku Turkki; Caj Haglund; Nina Linder; Johan Lundin

doi:10.1117/12.2217072

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

Dmitrii Bychkov, Riku Turkki, Caj Haglund, Nina Linder, Johan Lundin

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

Original language	English
Title of host publication	Medical Imaging 2016: Digital Pathology
Editors	Metin N. Gurcan, Anant Madabhushi
Number of pages	6
Publisher	SPIE - INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING
Publication date	2016
Pages	979115
ISBN (Print)	978-1-5106-0026-3
DOIs	https://doi.org/10.1117/12.2217072
Publication status	Published - 2016
MoE publication type	A4 Article in conference proceedings
Event	Conference on Medical Imaging - Digital Pathology - San Diego, CA, United States Duration: 2 Mar 2016 → 3 Mar 2016

Publication series

Name	Proceedings of SPIE
Publisher	SPIE-INT SOC OPTICAL ENGINEERING
Volume	9791
ISSN (Print)	0277-786X

Fields of Science

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

Access to Document

10.1117/12.2217072

SPIE Medical Imaging
Riku Turkki (Poster Presentation)
10 Feb 2016 → 15 Feb 2016
Activity: Participating in or organising an event types › Organisation and participation in conferences, workshops, courses, seminars

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

@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",

year = "2016",

doi = "10.1117/12.2217072",

language = "English",

isbn = "978-1-5106-0026-3",

series = "Proceedings of SPIE",

publisher = "SPIE - INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING",

pages = "979115",

editor = "Gurcan, {Metin N.} and Anant Madabhushi",

booktitle = "Medical Imaging 2016: Digital Pathology",

address = "United States",

note = "Conference on Medical Imaging - Digital Pathology ; Conference date: 02-03-2016 Through 03-03-2016",

}

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 et al.

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 proceeding › Conference contribution › Scientific › peer-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

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

T3 - Proceedings of SPIE

SP - 979115

BT - Medical Imaging 2016: Digital Pathology

A2 - Gurcan, Metin N.

A2 - Madabhushi, Anant

PB - SPIE - INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING

T2 - Conference on Medical Imaging - Digital Pathology

Y2 - 2 March 2016 through 3 March 2016

ER -

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

Publication series

Fields of Science

Access to Document

Activities

SPIE Medical Imaging

Cite this