A computer-assisted diagnostic (CAD) method and appara tus are described for the
enhancement and detection of suspicious regions in digital X-ray images. with particular …

The adaptive contrast enhancement (ACE) algorithm, which uses contrast gains (CGs) to
adjust the high-frequency components of images, is a well-known technique for medical …

Contrast enhancement of radiographies based on a multiscale decomposition of the images
recently has proven to be a far more versatile and efficient method than regular unsharp …

We present an evaluation and comparison of the performance of four different texture and
shape feature extraction methods for classification of benign and malignant …

In this work, the effect of an image enhancement processing stage and the parameter tuning
of a computer-aided detection (CAD) system for the detection of microcalcifications in …

This paper presents a new algorithm for enhancement of microcalcifications in
mammograms. The main novelty is the application of techniques we have developed for …

Considering the difficulties in finding good-quality images for the development and test of
computer-aided diagnosis (CAD), this paper presents a public online mammographic …

Mammography is considered the most effective method for early detection of breast cancers.
However, it is difficult for radiologists to detect microcalcification clusters. Therefore, we have …

A workstation-user interface for evaluating computer assisted diagnosis (CAD) methods for
digital mammography is disclosed. Implementation of such an interface enables multiple …

A computationally efficient mixed feature based neural network (MFNN) is proposed for the
detection of microcalcification clusters (MCCs) in digitized mammograms. The MFNN …