A multiple classifier system for classification of breast lesions using dynamic and morphological features in DCE-MRI

Roberta Fusco; Mario Sansone; Antonella Petrillo; Carlo Sansone

doi:10.1007/978-3-642-34166-3_75

A multiple classifier system for classification of breast lesions using dynamic and morphological features in DCE-MRI

Roberta Fusco, Mario Sansone, Antonella Petrillo, Carlo Sansone

Istituto Nazionale Tumori Fondazione G. Pascale

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In this paper we propose a Multiple Classifier System (MCS) for classifying breast lesions in Dynamic Contrast Enhanced-Magnetic Resonance Imaging (DCE-MRI). The proposed MCS combines the results of two classifiers trained with dynamic and morphological features respectively. Twenty-one malignant and seventeen benign breast lesions, histologically proven, were analyzed. Volumes of Interest (VOIs) have been automatically extracted via a segmentation procedure assessed in a previous study. The performance of the MCS have been compared with histological classification. Results indicated that with automatic segmented VOIs 90% of test-set lesions were correctly classified.

Original language	English
Title of host publication	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages	684-692
Number of pages	9
Volume	7626 LNCS
DOIs	https://doi.org/10.1007/978-3-642-34166-3_75
Publication status	Published - 2012
Event	Joint IAPR International Workshops on Structural and Syntactic PatternRecognition, SSPR 2012 and Statistical Techniques in Pattern Recognition,SPR 2012 - Hiroshima, Japan Duration: Nov 7 2012 → Nov 9 2012

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	7626 LNCS
ISSN (Print)	03029743
ISSN (Electronic)	16113349

Other

Other	Joint IAPR International Workshops on Structural and Syntactic PatternRecognition, SSPR 2012 and Statistical Techniques in Pattern Recognition,SPR 2012
Country	Japan
City	Hiroshima
Period	11/7/12 → 11/9/12

Keywords

breast DCE-MRI
morphological and dynamic features
multiple classification system

ASJC Scopus subject areas

Computer Science(all)
Theoretical Computer Science

Access to Document

10.1007/978-3-642-34166-3_75

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Cite this

Fusco, R., Sansone, M., Petrillo, A., & Sansone, C. (2012). A multiple classifier system for classification of breast lesions using dynamic and morphological features in DCE-MRI. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7626 LNCS, pp. 684-692). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7626 LNCS). https://doi.org/10.1007/978-3-642-34166-3_75

A multiple classifier system for classification of breast lesions using dynamic and morphological features in DCE-MRI. / Fusco, Roberta; Sansone, Mario; Petrillo, Antonella; Sansone, Carlo.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7626 LNCS 2012. p. 684-692 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7626 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Fusco, R, Sansone, M, Petrillo, A & Sansone, C 2012, A multiple classifier system for classification of breast lesions using dynamic and morphological features in DCE-MRI. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 7626 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7626 LNCS, pp. 684-692, Joint IAPR International Workshops on Structural and Syntactic PatternRecognition, SSPR 2012 and Statistical Techniques in Pattern Recognition,SPR 2012, Hiroshima, Japan, 11/7/12. https://doi.org/10.1007/978-3-642-34166-3_75

Fusco R, Sansone M, Petrillo A, Sansone C. A multiple classifier system for classification of breast lesions using dynamic and morphological features in DCE-MRI. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7626 LNCS. 2012. p. 684-692. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-34166-3_75

Fusco, Roberta ; Sansone, Mario ; Petrillo, Antonella ; Sansone, Carlo. / A multiple classifier system for classification of breast lesions using dynamic and morphological features in DCE-MRI. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7626 LNCS 2012. pp. 684-692 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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