The computer-aided diagnosis (CAD) system for characterizing masses described in this paper is based on a three-stage algorithm: first, a segmentation technique ...

The segmentation algorithm works with a comparable efficiency both on malignant and benign masses. Sixteen features based on shape, size and intensity of the ...

Mar 10, 2008 · Sixteen features based on shape, size and intensity of the segmented masses are analyzed by a multi-layered perceptron neural network. A feature ...

A new computer aided mass detection for breast cancer diagnosis by focusing on wavelet filters enhancement which removes bright background due to dense ...

Mar 10, 2008 · The segmentation algorithm works with a comparable efficiency both on ma- lignant and benign masses. Sixteen features based on shape, size and ...

The computer-aided diagnosis (CAD) system we developed for the mass characterization is mainly based on a segmentation algorithm and on the neural ...

(2007) Characterization of Mammographic Masses Using a Gradient Based Segmentation Algorithm and a Neural Classifier. Computers in and Biology Medicine, 37 ...

It involves three major stages: mass segmentation, feature extraction, and classification. In this study, we combined stepwise feature selection and linear.

This study developed a series of algorithms to quantify the degree of sharpness and lobulation of a mass margin, and selected images selected from the ...

The purpose of this study was to develop an automated method for mammographic mass segmentation and explore new image based features in combination with patient ...