0000000000429137
AUTHOR
Sonia Tangaro
A massive lesion detection algorithm in mammography
A new algorithm for massive lesion detection in mammography is presented. The algorithm consists in three main steps : 1) reduction of the dimension of the image to be processed through the identifi cation of regions of interest (rois) as candidates for massive lesions ; 2) characterization of the roi by means of suitable feature extraction ; 3) pattern classifi cation through supervised neural networks. Suspect regions are detected by searching for local maxima of the pixel grey level intensity. A ring of increasing radius, centered on a maximum, is considered until the mean intensity in the ring decreases to a defi ned fraction of the maximum. The rois thus obtained are described by avera…
The CALMA system: an artificial neural network method for detecting masses and microcalcifications in digitized mammograms
The CALMA (Computer Assisted Library for MAmmography) project is a five years plan developed in a physics research frame in collaboration between INFN (Istituto Nazionale di Fisica Nucleare) and many Italian hospitals. At present a large database of digitized mammographic images (more than 6000) was collected and a software based on neural network algorithms for the search of suspicious breast lesions was developed. Two tools are available: a microcalcification clusters hunter, based on supervised and unsupervised feedforward neural network, and a massive lesions searcher, based on a hibrid approach. Both the algorithms analyzed preprocessed digitized images by high frequency filters. Clini…