Title: Computer-aided mammography techniques for detection and classification of microcalcifications in digital mammograms

Authors: S. Punitha; S. Ravi; M. Anousouya Devi; J. Vaishnavi

Addresses: Department of Computer Science, Pondicherry University, Pondicherry, 605014, India ' Department of Computer Science, Pondicherry University, Pondicherry, 605014, India ' Department of Computer Science, Pondicherry University, Pondicherry, 605014, India ' Department of Computer Science, Pondicherry University, Pondicherry, 605014, India

Abstract: Recent techniques that are developed in computer-aided mammography (CAM) produce more accurate results in detection and diagnosis of microcalcifications in its earlier state that can lead to breast cancers among women. These techniques aim at the reduction of false positive rates through which the number of biopsies and surgeries can be greatly reduced. This paper gives a detailed study of the existing techniques available in CAM for the segmentation and classification of the microcalcifications present in the di0067ital mammograms which help the radiologists to take quick and accurate diagnosis decisions.

Keywords: segmentation; classification; CAM; computer aided mammography; MCC; microcalcification clusters; ROC; receiver operating characteristics; ANN; artificial neural networks.

DOI: 10.1504/IJIM.2018.093032

International Journal of Image Mining, 2018 Vol.3 No.1, pp.48 - 66

Received: 24 Dec 2016
Accepted: 15 Aug 2017
Published online: 04 Jul 2018 *