Breast tissue segmentation and mammographic risk scoring using deep learning

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

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Breast tissue segmentation and mammographic risk scoring using deep learning. / Petersen, Peter Kersten; Nielsen, Mads; Diao, Pengfei; Karssemeijer, Nico; Lillholm, Martin.

Breast imaging: 12th International Workshop, IWDM 2014, Gifu City, Japan, June 29 – July 2, 2014. Proceedings. red. / Hiroshi Fujita; Takeshi Hara; Chisako Muramatsu. Springer Science+Business Media, 2014. s. 88-94 (Lecture notes in computer science, Bind 8539).

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

Harvard

Petersen, PK, Nielsen, M, Diao, P, Karssemeijer, N & Lillholm, M 2014, Breast tissue segmentation and mammographic risk scoring using deep learning. i H Fujita, T Hara & C Muramatsu (red), Breast imaging: 12th International Workshop, IWDM 2014, Gifu City, Japan, June 29 – July 2, 2014. Proceedings. Springer Science+Business Media, Lecture notes in computer science, bind 8539, s. 88-94, International Workshop, IWDM 2014, Gifu City, Japan, 29/06/2014. https://doi.org/10.1007/978-3-319-07887-8_13

APA

Petersen, P. K., Nielsen, M., Diao, P., Karssemeijer, N., & Lillholm, M. (2014). Breast tissue segmentation and mammographic risk scoring using deep learning. I H. Fujita, T. Hara, & C. Muramatsu (red.), Breast imaging: 12th International Workshop, IWDM 2014, Gifu City, Japan, June 29 – July 2, 2014. Proceedings (s. 88-94). Springer Science+Business Media. Lecture notes in computer science, Bind. 8539 https://doi.org/10.1007/978-3-319-07887-8_13

Vancouver

Petersen PK, Nielsen M, Diao P, Karssemeijer N, Lillholm M. Breast tissue segmentation and mammographic risk scoring using deep learning. I Fujita H, Hara T, Muramatsu C, red., Breast imaging: 12th International Workshop, IWDM 2014, Gifu City, Japan, June 29 – July 2, 2014. Proceedings. Springer Science+Business Media. 2014. s. 88-94. (Lecture notes in computer science, Bind 8539). https://doi.org/10.1007/978-3-319-07887-8_13

Author

Petersen, Peter Kersten ; Nielsen, Mads ; Diao, Pengfei ; Karssemeijer, Nico ; Lillholm, Martin. / Breast tissue segmentation and mammographic risk scoring using deep learning. Breast imaging: 12th International Workshop, IWDM 2014, Gifu City, Japan, June 29 – July 2, 2014. Proceedings. red. / Hiroshi Fujita ; Takeshi Hara ; Chisako Muramatsu. Springer Science+Business Media, 2014. s. 88-94 (Lecture notes in computer science, Bind 8539).

Bibtex

@inproceedings{938dbc4aab944e6eba3c3781255ed831,
title = "Breast tissue segmentation and mammographic risk scoring using deep learning",
keywords = "Unsupervised feature learning, deep learning, breast cancer, mammograms, prognosis, risk factor, segmentation",
author = "Petersen, {Peter Kersten} and Mads Nielsen and Pengfei Diao and Nico Karssemeijer and Martin Lillholm",
year = "2014",
doi = "10.1007/978-3-319-07887-8_13",
language = "English",
isbn = "978-3-319-07886-1",
series = "Lecture notes in computer science",
publisher = "Springer Science+Business Media",
pages = "88--94",
editor = "Hiroshi Fujita and Takeshi Hara and Chisako Muramatsu",
booktitle = "Breast imaging",
address = "Singapore",
note = "null ; Conference date: 29-06-2014 Through 02-07-2014",

}

RIS

TY - GEN

T1 - Breast tissue segmentation and mammographic risk scoring using deep learning

AU - Petersen, Peter Kersten

AU - Nielsen, Mads

AU - Diao, Pengfei

AU - Karssemeijer, Nico

AU - Lillholm, Martin

N1 - Conference code: 12

PY - 2014

Y1 - 2014

KW - Unsupervised feature learning

KW - deep learning

KW - breast cancer

KW - mammograms

KW - prognosis

KW - risk factor

KW - segmentation

U2 - 10.1007/978-3-319-07887-8_13

DO - 10.1007/978-3-319-07887-8_13

M3 - Article in proceedings

SN - 978-3-319-07886-1

T3 - Lecture notes in computer science

SP - 88

EP - 94

BT - Breast imaging

A2 - Fujita, Hiroshi

A2 - Hara, Takeshi

A2 - Muramatsu, Chisako

PB - Springer Science+Business Media

Y2 - 29 June 2014 through 2 July 2014

ER -

ID: 132042313