Modelling screening mammography images: A probabilistic relational approach

Nivea Ferreira; Peter J.F. Lucas

doi:10.1007/978-3-642-02976-9_57

Modelling screening mammography images: A probabilistic relational approach

Nivea Ferreira^*
, Peter J.F. Lucas

^*Corresponding author for this work

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

Abstract

Computer-aided detection systems have as aim the increase of detection rates when analysing mammograms, by identifying features that are characteristic for breast cancer. In this research we aimed at using the features extracted from mammographic images in order to analyse the development of suspicious lesions. Different from other approaches, we based our data modelling on object orientation. This allowed not only for a description of domain entities and their intrinsic relationships, but also for the application of relational probabilistic techniques, which can handle heterogeneous data instances both in terms of learning and inference.

Original language	English
Title of host publication	Artificial Intelligence in Medicine - 12th Conference on Artificial Intelligence in Medicine, AIME 2009, Proceedings
Pages	405-409
Number of pages	5
DOIs	https://doi.org/10.1007/978-3-642-02976-9_57
Publication status	Published - 2009
Externally published	Yes
Event	12th Conference on Artificial Intelligence In Medicine, AIME 2009 - Verona, Italy Duration: 18 Jul 2009 → 22 Jul 2009 Conference number: 12 http://aimedicine.info/aime09/

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	5651 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	12th Conference on Artificial Intelligence In Medicine, AIME 2009
Abbreviated title	AIME
Country/Territory	Italy
City	Verona
Period	18/07/09 → 22/07/09
Internet address	http://aimedicine.info/aime09/

UN SDGs

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

SDG 3 Good Health and Well-being

Keywords

n/a OA procedure

Access to Document

10.1007/978-3-642-02976-9_57

Cite this

Ferreira, N., & Lucas, P. J. F. (2009). Modelling screening mammography images: A probabilistic relational approach. In Artificial Intelligence in Medicine - 12th Conference on Artificial Intelligence in Medicine, AIME 2009, Proceedings (pp. 405-409). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5651 LNAI). https://doi.org/10.1007/978-3-642-02976-9_57

Ferreira, Nivea ; Lucas, Peter J.F. / Modelling screening mammography images : A probabilistic relational approach. Artificial Intelligence in Medicine - 12th Conference on Artificial Intelligence in Medicine, AIME 2009, Proceedings. 2009. pp. 405-409 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Modelling screening mammography images: A probabilistic relational approach",

abstract = "Computer-aided detection systems have as aim the increase of detection rates when analysing mammograms, by identifying features that are characteristic for breast cancer. In this research we aimed at using the features extracted from mammographic images in order to analyse the development of suspicious lesions. Different from other approaches, we based our data modelling on object orientation. This allowed not only for a description of domain entities and their intrinsic relationships, but also for the application of relational probabilistic techniques, which can handle heterogeneous data instances both in terms of learning and inference.",

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author = "Nivea Ferreira and Lucas, \{Peter J.F.\}",

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booktitle = "Artificial Intelligence in Medicine - 12th Conference on Artificial Intelligence in Medicine, AIME 2009, Proceedings",

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Ferreira, N & Lucas, PJF 2009, Modelling screening mammography images: A probabilistic relational approach. in Artificial Intelligence in Medicine - 12th Conference on Artificial Intelligence in Medicine, AIME 2009, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5651 LNAI, pp. 405-409, 12th Conference on Artificial Intelligence In Medicine, AIME 2009, Verona, Italy, 18/07/09. https://doi.org/10.1007/978-3-642-02976-9_57

Modelling screening mammography images: A probabilistic relational approach. / Ferreira, Nivea; Lucas, Peter J.F.
Artificial Intelligence in Medicine - 12th Conference on Artificial Intelligence in Medicine, AIME 2009, Proceedings. 2009. p. 405-409 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5651 LNAI).

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

TY - GEN

T1 - Modelling screening mammography images

T2 - 12th Conference on Artificial Intelligence In Medicine, AIME 2009

AU - Ferreira, Nivea

AU - Lucas, Peter J.F.

N1 - Conference code: 12

PY - 2009

Y1 - 2009

N2 - Computer-aided detection systems have as aim the increase of detection rates when analysing mammograms, by identifying features that are characteristic for breast cancer. In this research we aimed at using the features extracted from mammographic images in order to analyse the development of suspicious lesions. Different from other approaches, we based our data modelling on object orientation. This allowed not only for a description of domain entities and their intrinsic relationships, but also for the application of relational probabilistic techniques, which can handle heterogeneous data instances both in terms of learning and inference.

AB - Computer-aided detection systems have as aim the increase of detection rates when analysing mammograms, by identifying features that are characteristic for breast cancer. In this research we aimed at using the features extracted from mammographic images in order to analyse the development of suspicious lesions. Different from other approaches, we based our data modelling on object orientation. This allowed not only for a description of domain entities and their intrinsic relationships, but also for the application of relational probabilistic techniques, which can handle heterogeneous data instances both in terms of learning and inference.

KW - n/a OA procedure

UR - https://www.scopus.com/pages/publications/70350219104

U2 - 10.1007/978-3-642-02976-9_57

DO - 10.1007/978-3-642-02976-9_57

M3 - Conference contribution

AN - SCOPUS:70350219104

SN - 3642029752

SN - 9783642029752

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 405

EP - 409

BT - Artificial Intelligence in Medicine - 12th Conference on Artificial Intelligence in Medicine, AIME 2009, Proceedings

Y2 - 18 July 2009 through 22 July 2009

ER -

Ferreira N, Lucas PJF. Modelling screening mammography images: A probabilistic relational approach. In Artificial Intelligence in Medicine - 12th Conference on Artificial Intelligence in Medicine, AIME 2009, Proceedings. 2009. p. 405-409. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-02976-9_57

Modelling screening mammography images: A probabilistic relational approach

Abstract

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UN SDGs

Keywords

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