0000000000670979

AUTHOR

S. Stumbo

showing 5 related works from this author

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…

breast cancerComputer-aided diagnosis. Digital imaging. Image analysis. MammographysegmentationCAD systems mammographyclassification systemROC curve
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Dissimilarity Application for Medical Imaging Classification

2005

In the traditional way of learning from examples of objects the classifiers are built in a feature space. However, 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) die training samples. The use of the dissimilarities is especially of interest when features are difficult to obtain or when they have a little discriminative power. 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 col…

Breast cancerDissimilarityComputer assisted diagnosiComputer aided diagnosimammographyCo-occurrence matrixMedical image processingimage segmentationNeural network
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The MAGIC-5 Project: Medical Applications on a Grid Infrastructure Connection

2004

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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…

DissimilarityBreast CancerNeural NetworkCooccurrence matrixComputer Aided Detection.
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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…

SPECTRA
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