Independent Component Analysis to Detect Clustered Microcalcification Breast Cancers
The presence of clustered microcalcifications is one of the earliest signs in breast cancer detection. Although there exist many studies broaching this problem, most of them are nonreproducible due to the use of proprietary image datasets. We use a known subset of the currently largest publicly avai...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2012-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1100/2012/540457 |
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| author | R. Gallardo-Caballero C. J. García-Orellana A. García-Manso H. M. González-Velasco M. Macías-Macías |
| author_facet | R. Gallardo-Caballero C. J. García-Orellana A. García-Manso H. M. González-Velasco M. Macías-Macías |
| author_sort | R. Gallardo-Caballero |
| collection | DOAJ |
| description | The presence of clustered microcalcifications is one of the earliest signs in breast cancer detection. Although there exist many studies broaching this problem, most of them are nonreproducible due to the use of proprietary image datasets. We use a known subset of the currently largest publicly available mammography database, the Digital Database for Screening Mammography (DDSM), to develop a computer-aided detection system that outperforms the
current reproducible studies on the same mammogram set. This proposal is mainly based on the use of extracted image features obtained by independent component analysis, but we also study the inclusion of the patient’s age as a nonimage feature which requires no human expertise. Our system achieves an average of 2.55 false positives per image at a sensitivity of 81.8% and 4.45 at a sensitivity of 91.8% in diagnosing the BCRP_CALC_1 subset of DDSM. |
| format | Article |
| id | doaj-art-8f5e3c4671e247e4a3d3ccc7636a67fa |
| institution | Kabale University |
| issn | 1537-744X |
| language | English |
| publishDate | 2012-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-8f5e3c4671e247e4a3d3ccc7636a67fa2025-02-03T01:25:28ZengWileyThe Scientific World Journal1537-744X2012-01-01201210.1100/2012/540457540457Independent Component Analysis to Detect Clustered Microcalcification Breast CancersR. Gallardo-Caballero0C. J. García-Orellana1A. García-Manso2H. M. González-Velasco3M. Macías-Macías4CAPI Research Group, University of Extremadura, Avenida de la Universidad s/n, 10003 Cáceres, SpainCAPI Research Group, University of Extremadura, Avenida de la Universidad s/n, 10003 Cáceres, SpainCAPI Research Group, University of Extremadura, Avenida de la Universidad s/n, 10003 Cáceres, SpainCAPI Research Group, University of Extremadura, Avenida de la Universidad s/n, 10003 Cáceres, SpainCAPI Research Group, University of Extremadura, Avenida de la Universidad s/n, 10003 Cáceres, SpainThe presence of clustered microcalcifications is one of the earliest signs in breast cancer detection. Although there exist many studies broaching this problem, most of them are nonreproducible due to the use of proprietary image datasets. We use a known subset of the currently largest publicly available mammography database, the Digital Database for Screening Mammography (DDSM), to develop a computer-aided detection system that outperforms the current reproducible studies on the same mammogram set. This proposal is mainly based on the use of extracted image features obtained by independent component analysis, but we also study the inclusion of the patient’s age as a nonimage feature which requires no human expertise. Our system achieves an average of 2.55 false positives per image at a sensitivity of 81.8% and 4.45 at a sensitivity of 91.8% in diagnosing the BCRP_CALC_1 subset of DDSM.http://dx.doi.org/10.1100/2012/540457 |
| spellingShingle | R. Gallardo-Caballero C. J. García-Orellana A. García-Manso H. M. González-Velasco M. Macías-Macías Independent Component Analysis to Detect Clustered Microcalcification Breast Cancers The Scientific World Journal |
| title | Independent Component Analysis to Detect Clustered Microcalcification Breast Cancers |
| title_full | Independent Component Analysis to Detect Clustered Microcalcification Breast Cancers |
| title_fullStr | Independent Component Analysis to Detect Clustered Microcalcification Breast Cancers |
| title_full_unstemmed | Independent Component Analysis to Detect Clustered Microcalcification Breast Cancers |
| title_short | Independent Component Analysis to Detect Clustered Microcalcification Breast Cancers |
| title_sort | independent component analysis to detect clustered microcalcification breast cancers |
| url | http://dx.doi.org/10.1100/2012/540457 |
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