In this paper, a new method for automatic detection of microcalcifications in digitized
mammograms is proposed. Based on mathematical morphology theory to deal with the …

Microcalcifications (MCs) are considered as the first indicator of breast cancer development.
Their morphology, in terms of shape and size, is considered as the most important criterion …

In this paper, we propose a new collaborative process that aims to detect macrocalcifications
from mammographic images while minimizing false negative detections. This process is …

In this paper, we propose a new Conditional Region Growing (CRG) approach with the
ability of finding the accurate MC boundaries starting from selected seed points. The starting …

In this paper, we propose a new morphological-based method for automatic detection of
microcalcifications in digitized mammograms. It uses various structuring elements to deal …

Ce travail s' intéresse à l'interprétation d'images mammographiques pour la détection des
MCs. Partant d'un prétraitement, nous proposons une première méthode basée sur la …

Breast cancer is the most life-threatening disease among women. The best way to decrease
the mortality is early detection of cancer from digital mammogram. The diagnosis can be …

Image mining deals with the extraction of knowledge from image data. As the image may
contain unwanted details the pre-processing plays a key role in image mining. Pre …