Computational intelligence for the detection and classification of malignant lesions in screening mammography

Panourgias,Evangelia; Tsakonas,Athanasios; Dounias,Georgios; Panagi,Georgia

doi:10.3892/or.15.4.1037

April 2006 Volume 15 Issue 4

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April 2006 Volume 15 Issue 4

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Article

Computational intelligence for the detection and classification of malignant lesions in screening mammography

Authors:
- Evangelia Panourgias
- Athanasios Tsakonas
- Georgios Dounias
- Georgia Panagi
View Affiliations / Copyright

Affiliations: Department of Radiology, Euroclinic Hospital, 11521 Athens, Greece
Pages: 1037-1041
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Published online on: April 1, 2006

https://doi.org/10.3892/or.15.4.1037
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Abstract

This report deals with the discussion of the findings obtained from the application of two computational intelligence methodologies for the detection of microcalcifications in screening mammography data. Genetic programming and inductive machine learning have been applied, in order to produce meaningful diagnostic rules for the medical staff. The data used in the experiments correspond to information acquired from two images of each breast of the patient, along with some associated patient information such as the age at time of study. Similar datasets have been previously used in an attempt to facilitate the development of computer algorithms to aid screening. Experienced screening radio-logists have double-read the screening mammograms, they have weighted the malignancy ratings and averaged out the levels of suspiciousness assigned to each finding in the screenings. The diagnostic rules which were obtained from both genetic programming and machine learning have been evaluated in detail and then analyzed and discussed by collaborative medical experts, in parallel to findings from related literature. Results seem encouraging for further use and analysis by medical staff specializing in screening mammography.

Journals

International Journal of Molecular Medicine

International Journal of Oncology

Molecular Medicine Reports

Oncology Reports

Experimental and Therapeutic Medicine

Oncology Letters

Biomedical Reports

Molecular and Clinical Oncology

World Academy of Sciences Journal

International Journal of Functional Nutrition

International Journal of Epigenetics

Medicine International

Computational intelligence for the detection and classification of malignant lesions in screening mammography

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Abstract

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