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Comparative study of feature classification methods for mass lesion recognition in digitized mammograms

Masala, Giovanni Luca Christian and Tangaro, Sonia and Golosio, Bruno and Oliva, Piernicola and Stumbo, Simone and Bellotti, Roberto and De Carlo, Francesco and Gargano, Gianfranco and Cascio, Donato and Fauci, Francesco and Magro, Rosario and Raso, Giuseppe and Bottigli, Ubaldo and Chincarini, Andrea and De Mitri, Ivan and De Nunzio, Giorgio and Gori, Ilaria and Retico, Alessandra and Cerello, Piergiorgio and Cheran, Sorin Cristian and Fulcheri, C. and Lopez Torres, Ernesto (2007) Comparative study of feature classification methods for mass lesion recognition in digitized mammograms. Il Nuovo cimento. C, Vol. 30 C (3), p. 305-316. eISSN 1826-9885. Article.

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DOI: 10.1393/ncc/i2007-10241-y

Abstract

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 information on the ROI pixel grey tones.

Item Type:Article
ID Code:1879
Status:Published
Refereed:Yes
Uncontrolled Keywords:Mammography, computer-aided diagnosis, digital imaging, image analysis
Subjects:Area 02 - Scienze fisiche > FIS/07 Fisica applicata (a beni culturali, ambientali, biologia e medicina)
Divisions:001 Università di Sassari > 03 Istituti > Matematica e fisica
Publisher:Società Italiana di Fisica
eISSN:1826-9885
Deposited On:18 Aug 2009 10:06

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