Comparative Study of Feature classification Methods for Mass Lesion Recognition in Digitized Mammograms

2007

In this work a comparison of different classification methods for the identification of mass lesions in digitized mammograms is performed. These methods, used in order to develop Computer Aided Detection (CAD) systems, have been implemented in the framework of the MAGIC-5 Collaboration. The system for identification of mass lesions is based on a three-step procedure: a) preprocessing and segmentation, b) region of interest (ROI) searching, c) feature extraction and classification. It was tested on a very large mammographic database (3369 mammographic images from 967 patients). Each ROI is characterized by eight features extracted from a co-occurrence matrix containing spatial statistics inf…

Superior Performances of the Neural Network on the Masses Lesions Classification through Morphological Lesion Differences

2007

Purpose of this work is to develop an automatic classification system that could be useful for radiologists in the breast cancer investigation. The software has been designed in the framework of the MAGIC-5 collaboration. In an automatic classification system the suspicious regions with high probability to include a lesion are extracted from the image as regions of interest (ROIs). Each ROI is characterized by some features based generally on morphological lesion differences. A study in the space features representation is made and some classifiers are tested to distinguish the pathological regions from the healthy ones. The results provided in terms of sensitivity and specificity will be p…

Massive Lesions Classification using Features based on Morphological Lesion Differences

2007

Purpose of this work is the development of an automatic classification system which could be useful for radiologists in the investigation of breast cancer. The software has been designed in the framework of the MAGIC-5 collaboration. In the automatic classification system the suspicious regions with high probability to include a lesion are extracted from the image as regions of interest (ROIs). Each ROI is characterized by some features based on morphological lesion differences. Some classifiers as a Feed Forward Neural Network, a K-Nearest Neighbours and a Support Vector Machine are used to distinguish the pathological records from the healthy ones. The results obtained in terms of sensiti…

METODO AUTOMATICO PER LA RIVELAZIONE PRECOCE DI ZONE TUMORALI IN IMMAGINI BIOMEDICHE

2006

Circinus X-1 observed with BeppoSAX wide field cameras

1999

Abstract We present a sky image and spectra for various orbital phases of Circinus X-1 observed by B-SAX Wide Field Cameras. We suggest that the spectral shape is dependent on the orbital phase.

TAC applicata allo studio di rocce sedimentarie utilizzate nei Beni Culturali

2006

COMPUTER ASSISTED DIAGNOSIS (CAD) IN MAMMOGRAPHY. COMPARISON OF DIAGNOSTIC ACCURACY OF A NEW ALGORITHM (CYCLOPUS®, MEDICAD) WITH TWO COMMERCIAL SYSTE…

2008

Dissimilarity Application in Digitized Mammographic Images Classification.

2006

Purpose of this work is the development of an automatic classification system which could be useful for radiologists in the investigation of breast cancer. The software has been designed in the framework of the MAGIC-5 collaboration. In the traditional way of learning from examples of objects the classifiers are built in a feature space. However, an alternative ways can be found by constructing decision rules on dissimilarity (distance) representations. In such a recognition process a new object is described by its distances to (a subset of) the training samples. The use of the dissimilarities is especially of interest when features are difficult to obtain or when they have a little discrim…

Mammogram segmentation by contour searching and massive lesion classification with neural network

2004

The mammography is the most effective procedure for an early diagnosis of the breast cancer. In this paper, an algorithm for detecting massive lesions in mammographic images will be presented. The database consists of 3762 digital images acquired in several hospitals belonging to the MAGIC-5 collaboration. A reduction of the surface under investigation is achieved, without loss of meaningful information, through segmentation of the whole image, by means of a ROI Hunter algorithm. In the following classification step, feature extraction plays a fundamental role: some features give geometrical information, other ones provide shape parameters. Once the features are computed for each ROI, they …

Portable CdTe detection system for mammographic X-ray spectroscopy

2006

This paper describes a portable apparatus to be utilized in mammographic X-ray spectroscopy under clinical conditions. The system, based on a CdTe solid-state detector, is able to directly measure mammographic X-ray tube spectra. Good system response to monoenergetic photons was measured using X-ray and γ-ray calibration sources (109Cd and 241Am). The measured molybdenum X-ray spectra, in agreement with simulated spectra, show the good spectral capability of the system also at high photon fluence rates, as typical of clinical mammography. Low tailing, no secondary X-ray escape and low pile-up distortions in the measured spectra indicate that this portable system is suitable for mammographic…