Share Email Print

Proceedings Paper

Masses classification using fuzzy active contours and fuzzy decision trees
Author(s): G. J. Palma; G. Peters; S. Muller; I. Bloch
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

In this paper we propose a method to classify masses in digital breast tomosynthesis (DBT) datasets. First, markers of potential lesions are extracted and matched over the different projections. Then two level-set models are applied on each finding corresponding to spiculated and circumscribed mass assumptions respectively. The formulation of the active contours within this framework leads to several candidate contours for each finding. In addition, a membership value to the class contour is derived from the energy of the segmentation model, and allows associating several fuzzy contours from different projections to each set of markers corresponding to a lesion. Fuzzy attributes are computed for each fuzzy contour. Then the attributes corresponding to fuzzy contours associated to each set of markers are aggregated. Finally, these cumulated fuzzy attributes are processed by two distinct fuzzy decision trees in order to validate/invalidate the spiculated or circumscribed mass assumptions. The classification has been validated on a database of 23 real lesions using the leave-one-out method. An error classification rate of 9% was obtained with these data, which confirms the interest of the proposed approach.

Paper Details

Date Published: 17 March 2008
PDF: 11 pages
Proc. SPIE 6915, Medical Imaging 2008: Computer-Aided Diagnosis, 691509 (17 March 2008); doi: 10.1117/12.770078
Show Author Affiliations
G. J. Palma, GE Healthcare Europe (France)
Ecole Nationale Supérieure des Télécommunications (France)
G. Peters, Fenics (France)
S. Muller, GE Healthcare Europe (France)
I. Bloch, Ecole Nationale Supérieure des Télécommunications (France)

Published in SPIE Proceedings Vol. 6915:
Medical Imaging 2008: Computer-Aided Diagnosis
Maryellen L. Giger; Nico Karssemeijer, Editor(s)

© SPIE. Terms of Use
Back to Top