A decision support system for breast cancer detection in screening programs

Marina Velikova; Peter J.F. Lucas; Nivea Ferreira; Maurice Samulski; Nico Karssemeijer

doi:10.3233/978-1-58603-891-5-658

A decision support system for breast cancer detection in screening programs

Marina Velikova
, Peter J.F. Lucas
, Nivea Ferreira
, Maurice Samulski
, Nico Karssemeijer

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

10 Citations (Scopus)

4 Downloads (Pure)

Abstract

The goal of breast cancer screening programs is to detect cancers at an early (preclinical) stage, by using periodic mammographic examinations in asymptomatic women. In evaluating cases, mammographers insist on reading multiple images (at least two) of each breast as a cancerous lesion tends to be observed in different breast projections (views). Most computer-aided detection (CAD) systems, on the other hand, only analyze single views independently, and thus fail to account for the interaction between the views. In this paper, we propose a Bayesian framework for exploiting multi-view dependencies between the suspected regions detected by a single-view CAD system. The results from experiments with real-life data show that our approach outperforms the single-view CAD system in distinguishing between normal and abnormal cases. Such a system can support screening radiologists to improve the evaluation of breast cancer cases.

Original language	English
Title of host publication	Frontiers in Artificial Intelligence and Applications
Publisher	IOS
Pages	658-662
Number of pages	5
ISBN (Print)	978158603891
DOIs	https://doi.org/10.3233/978-1-58603-891-5-658
Publication status	Published - Jun 2008
Externally published	Yes
Event	18th European Conference on Artificial Intelligence, ECAI 2008 - Patras, Greece Duration: 21 Jul 2008 → 25 Jul 2008 Conference number: 18

Publication series

Name	Frontiers in Artificial Intelligence and Applications
Volume	178
ISSN (Print)	0922-6389
ISSN (Electronic)	1879-8314

Conference

Conference	18th European Conference on Artificial Intelligence, ECAI 2008
Abbreviated title	ECAI 2008
Country/Territory	Greece
City	Patras
Period	21/07/08 → 25/07/08

UN SDGs

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

SDG 3 Good Health and Well-being

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10.3233/978-1-58603-891-5-658Licence: CC BY-NC

FAIA178-0658Final published version, 359 KBLicence: CC BY-NC

Cite this

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title = "A decision support system for breast cancer detection in screening programs",

abstract = "The goal of breast cancer screening programs is to detect cancers at an early (preclinical) stage, by using periodic mammographic examinations in asymptomatic women. In evaluating cases, mammographers insist on reading multiple images (at least two) of each breast as a cancerous lesion tends to be observed in different breast projections (views). Most computer-aided detection (CAD) systems, on the other hand, only analyze single views independently, and thus fail to account for the interaction between the views. In this paper, we propose a Bayesian framework for exploiting multi-view dependencies between the suspected regions detected by a single-view CAD system. The results from experiments with real-life data show that our approach outperforms the single-view CAD system in distinguishing between normal and abnormal cases. Such a system can support screening radiologists to improve the evaluation of breast cancer cases.",

author = "Marina Velikova and Lucas, \{Peter J.F.\} and Nivea Ferreira and Maurice Samulski and Nico Karssemeijer",

note = "Publisher Copyright: {\textcopyright} 2008 The authors and IOS Press. All rights reserved.; 18th European Conference on Artificial Intelligence, ECAI 2008, ECAI 2008 ; Conference date: 21-07-2008 Through 25-07-2008",

year = "2008",

month = jun,

doi = "10.3233/978-1-58603-891-5-658",

language = "English",

isbn = "978158603891",

series = "Frontiers in Artificial Intelligence and Applications",

publisher = "IOS",

pages = "658--662",

booktitle = "Frontiers in Artificial Intelligence and Applications",

address = "Netherlands",

}

Velikova, M, Lucas, PJF, Ferreira, N, Samulski, M & Karssemeijer, N 2008, A decision support system for breast cancer detection in screening programs. in Frontiers in Artificial Intelligence and Applications. Frontiers in Artificial Intelligence and Applications, vol. 178, IOS, pp. 658-662, 18th European Conference on Artificial Intelligence, ECAI 2008, Patras, Greece, 21/07/08. https://doi.org/10.3233/978-1-58603-891-5-658

A decision support system for breast cancer detection in screening programs. / Velikova, Marina; Lucas, Peter J.F.; Ferreira, Nivea et al.
Frontiers in Artificial Intelligence and Applications. IOS, 2008. p. 658-662 (Frontiers in Artificial Intelligence and Applications; Vol. 178).

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

TY - GEN

T1 - A decision support system for breast cancer detection in screening programs

AU - Velikova, Marina

AU - Lucas, Peter J.F.

AU - Ferreira, Nivea

AU - Samulski, Maurice

AU - Karssemeijer, Nico

N1 - Conference code: 18

PY - 2008/6

Y1 - 2008/6

N2 - The goal of breast cancer screening programs is to detect cancers at an early (preclinical) stage, by using periodic mammographic examinations in asymptomatic women. In evaluating cases, mammographers insist on reading multiple images (at least two) of each breast as a cancerous lesion tends to be observed in different breast projections (views). Most computer-aided detection (CAD) systems, on the other hand, only analyze single views independently, and thus fail to account for the interaction between the views. In this paper, we propose a Bayesian framework for exploiting multi-view dependencies between the suspected regions detected by a single-view CAD system. The results from experiments with real-life data show that our approach outperforms the single-view CAD system in distinguishing between normal and abnormal cases. Such a system can support screening radiologists to improve the evaluation of breast cancer cases.

AB - The goal of breast cancer screening programs is to detect cancers at an early (preclinical) stage, by using periodic mammographic examinations in asymptomatic women. In evaluating cases, mammographers insist on reading multiple images (at least two) of each breast as a cancerous lesion tends to be observed in different breast projections (views). Most computer-aided detection (CAD) systems, on the other hand, only analyze single views independently, and thus fail to account for the interaction between the views. In this paper, we propose a Bayesian framework for exploiting multi-view dependencies between the suspected regions detected by a single-view CAD system. The results from experiments with real-life data show that our approach outperforms the single-view CAD system in distinguishing between normal and abnormal cases. Such a system can support screening radiologists to improve the evaluation of breast cancer cases.

UR - https://www.scopus.com/pages/publications/84983473766

U2 - 10.3233/978-1-58603-891-5-658

DO - 10.3233/978-1-58603-891-5-658

M3 - Conference contribution

AN - SCOPUS:84983473766

SN - 978158603891

T3 - Frontiers in Artificial Intelligence and Applications

SP - 658

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BT - Frontiers in Artificial Intelligence and Applications

PB - IOS

T2 - 18th European Conference on Artificial Intelligence, ECAI 2008

Y2 - 21 July 2008 through 25 July 2008

ER -

A decision support system for breast cancer detection in screening programs

Abstract

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UN SDGs

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