6533b862fe1ef96bd12c6229
RESEARCH PRODUCT
A Microcalcification Detection System in Mammograms based on ANN Clustering
Giuseppe RasoLeonardo AbbeneVincenzo TaorminaDonato Casciosubject
Computer sciencemammography02 engineering and technology030218 nuclear medicine & medical imaging03 medical and health sciencesDigital image0302 clinical medicineBreast cancer0202 electrical engineering electronic engineering information engineeringmedicineSegmentationSensitivity (control systems)Cluster analysisBreast canceimage segmentationArtificial neural networkbusiness.industryPattern recognitionmedicine.diseaseCad systemROC curveSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)020201 artificial intelligence & image processingArtificial intelligenceMicrocalcificationmedicine.symptombusinessANNclusteringdescription
Breast cancer is one of the leading causes to women mortality in the world. Clustered microcalcifications (MCs) in mammograms can be an important early sign of breast cancer, the detection is important to prevent and treat the disease. In this work, we present a novel method for the detection of MCs in mammograms which consists of regions of Interest (ROIs) segmentation, based on a spatial filter that allows the detection of small and large microcalcifications, clustering and classification of MCs by Artificial Neural Network. The system has been tested on a public dataset of digital images and compared with previous approaches. The results demonstrate that the proposed approach could achieve significantly higher FROC curves: our CAD system achieve a cluster-based sensitivity of 70, 80, and 90 % at 0.31, 0.69, and 1.6 FPs/image, respectively.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2018-11-01 |