Automatic detection of microcalcifications using mathematical morphology and a support vector machine
| Autor: | Fan Wang, Erhu Zhang, Xiaonan Bai, Yongchao Li |
|---|---|
| Rok vydání: | 2013 |
| Předmět: |
Support Vector Machine
Databases Factual Computer science Feature extraction ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Biomedical Engineering Mathematical morphology Sensitivity and Specificity Biomaterials Svm classifier Breast Diseases medicine False positive paradox Humans Computer vision False Positive Reactions Breast Electronic Data Processing business.industry Calcinosis Reproducibility of Results Pattern recognition General Medicine Models Theoretical Support vector machine Radiographic Image Enhancement Gamma correction Radiographic Image Interpretation Computer-Assisted Female Artificial intelligence Microcalcification medicine.symptom business Algorithms Mammography |
| Zdroj: | Bio-medical materials and engineering. 24(1) |
| ISSN: | 1878-3619 |
| Popis: | In this paper, we propose a novel method for the detection of microcalcifications using mathematical morphology and a support vector machine (SVM). First, the contrast in the original mammogram was improved by gamma correction and two carefully designed structural elements were used to enhance any microcalcifications. Next, the potential regions were extracted using our proposed dual-threshold technique. Finally, a SVM classifier was used to reduce the number of false positives. The performance of the proposed method was evaluated using the MIAS database. The experimental results demonstrated the efficiency and effectiveness of our method. |
| Databáze: | OpenAIRE |
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