Evaluation and selection of morphological procedures for automatic detection of micro-calcifications in mammography images

Claudia C. Diaz-Huerta; Edgardo M. Felipe-Riverón; Luis M. Montaño-Zetina

doi:10.1007/978-3-642-33275-3_71

Evaluation and selection of morphological procedures for automatic detection of micro-calcifications in mammography images

Claudia C. Diaz-Huerta, Edgardo M. Felipe-Riverón, Luis M. Montaño-Zetina

Centro de Investigación en Computación (CIC)

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

2 Scopus citations

Abstract

In this paper, we present an evaluation of four different algorithms, based on Mathematical Morphology, to detect the occurrence of micro-calcifications in digital mammogram images from the mini-MIAS database. Results provided by TMVA produced the ranking of features that allowed discrimination between real micro-calcifications and normal tissue. ROC area measures the performance of automatic classification, which produced its highest value 0.976 for Gaussian kernel, followed by polynomial kernel, which produced 0.972. An additional parameter, called Signal Efficiency*Purity (SE*P), is proposed as a measure of the number of micro-calcifications with the lowest quantity of noise.

Original language	English
Title of host publication	Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications - 17th Iberoamerican Congress, CIARP 2012, Proceedings
Pages	575-582
Number of pages	8
DOIs	https://doi.org/10.1007/978-3-642-33275-3_71
State	Published - 2012
Event	17th Iberoamerican Congress on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, CIARP 2012 - Buenos Aires, Argentina Duration: 3 Sep 2012 → 6 Sep 2012

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	7441 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	17th Iberoamerican Congress on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, CIARP 2012
Country/Territory	Argentina
City	Buenos Aires
Period	3/09/12 → 6/09/12

Keywords

Mammography image
Mathematical Morphology
digital mammography
mage reconstruction
micro-calcification detection

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10.1007/978-3-642-33275-3_71

Cite this

Diaz-Huerta, C. C., Felipe-Riverón, E. M., & Montaño-Zetina, L. M. (2012). Evaluation and selection of morphological procedures for automatic detection of micro-calcifications in mammography images. In Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications - 17th Iberoamerican Congress, CIARP 2012, Proceedings (pp. 575-582). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7441 LNCS). https://doi.org/10.1007/978-3-642-33275-3_71

Diaz-Huerta, Claudia C. ; Felipe-Riverón, Edgardo M. ; Montaño-Zetina, Luis M. / Evaluation and selection of morphological procedures for automatic detection of micro-calcifications in mammography images. Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications - 17th Iberoamerican Congress, CIARP 2012, Proceedings. 2012. pp. 575-582 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "In this paper, we present an evaluation of four different algorithms, based on Mathematical Morphology, to detect the occurrence of micro-calcifications in digital mammogram images from the mini-MIAS database. Results provided by TMVA produced the ranking of features that allowed discrimination between real micro-calcifications and normal tissue. ROC area measures the performance of automatic classification, which produced its highest value 0.976 for Gaussian kernel, followed by polynomial kernel, which produced 0.972. An additional parameter, called Signal Efficiency*Purity (SE*P), is proposed as a measure of the number of micro-calcifications with the lowest quantity of noise.",

keywords = "Mammography image, Mathematical Morphology, digital mammography, mage reconstruction, micro-calcification detection",

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Diaz-Huerta, CC, Felipe-Riverón, EM & Montaño-Zetina, LM 2012, Evaluation and selection of morphological procedures for automatic detection of micro-calcifications in mammography images. in Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications - 17th Iberoamerican Congress, CIARP 2012, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7441 LNCS, pp. 575-582, 17th Iberoamerican Congress on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, CIARP 2012, Buenos Aires, Argentina, 3/09/12. https://doi.org/10.1007/978-3-642-33275-3_71

Evaluation and selection of morphological procedures for automatic detection of micro-calcifications in mammography images. / Diaz-Huerta, Claudia C.; Felipe-Riverón, Edgardo M.; Montaño-Zetina, Luis M.
Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications - 17th Iberoamerican Congress, CIARP 2012, Proceedings. 2012. p. 575-582 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7441 LNCS).

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

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AU - Montaño-Zetina, Luis M.

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AB - In this paper, we present an evaluation of four different algorithms, based on Mathematical Morphology, to detect the occurrence of micro-calcifications in digital mammogram images from the mini-MIAS database. Results provided by TMVA produced the ranking of features that allowed discrimination between real micro-calcifications and normal tissue. ROC area measures the performance of automatic classification, which produced its highest value 0.976 for Gaussian kernel, followed by polynomial kernel, which produced 0.972. An additional parameter, called Signal Efficiency*Purity (SE*P), is proposed as a measure of the number of micro-calcifications with the lowest quantity of noise.

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KW - digital mammography

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

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BT - Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications - 17th Iberoamerican Congress, CIARP 2012, Proceedings

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Y2 - 3 September 2012 through 6 September 2012

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Diaz-Huerta CC, Felipe-Riverón EM, Montaño-Zetina LM. Evaluation and selection of morphological procedures for automatic detection of micro-calcifications in mammography images. In Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications - 17th Iberoamerican Congress, CIARP 2012, Proceedings. 2012. p. 575-582. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-33275-3_71

Evaluation and selection of morphological procedures for automatic detection of micro-calcifications in mammography images

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