We present a novel multiresolution scheme for the detection of spiculated lesions in digital
mammograms. First, a multiresolution representation of the original mammogram is obtained …

A multiresolution statistical method for identifying clinically normal tissue in digitized
mammograms is used to construct an algorithm for separating normal regions from …

In this paper, we present a new technique for the detection of spiculated masses in digitized
mammograms. The techniques consist of two stages, enhancement of spiculations followed …

This paper presents an approach for detecting micro-calcifications in digital mammograms
employing wavelet-based subband image decomposition. The microcalcifications appear in …

Scale is an important issue in the automated detection of masses in mammograms, due to
the range of possible sizes masses can have. In this work, it was examined if detection of …

Clusters of fine, granular microcalcifications in mammograms may be an early sign of
disease. Individual grains are difficult to detect and segment due to size and shape …

A computerized scheme for the automated detection of clustered microcalcifications in digital
mammograms is being developed. This scheme is part of an overall package for computer …

Clustered microcalcifcations (MCs) in digitized mammograms has been widely recognized
as an early sign of breast cancer in women. This work is devoted to developing a computer …

Computer-aided mammographic prompting systems require the reliable detection of a
variety of signs of cancer. In this paper we concentrate on the detection of spiculated lesions …

A method for automatic detection of mammographic masses is presented. As part of this
method, an enhancement algorithm that improves image contrast based on local statistical …