Masses classification using fuzzy active contours and fuzzy decision trees

G. J. Palma; G. Peters; S. Muller; I. Bloch

doi:10.1117/12.770078

17 March 2008 Masses classification using fuzzy active contours and fuzzy decision trees

G. J. Palma, G. Peters, S. Muller, I. Bloch

Proceedings Volume 6915, Medical Imaging 2008: Computer-Aided Diagnosis; 691509 (2008) https://doi.org/10.1117/12.770078
Event: Medical Imaging, 2008, San Diego, California, United States

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.

Citation Download Citation

G. J. Palma, G. Peters, S. Muller, and I. Bloch "Masses classification using fuzzy active contours and fuzzy decision trees", Proc. SPIE 6915, Medical Imaging 2008: Computer-Aided Diagnosis, 691509 (17 March 2008); https://doi.org/10.1117/12.770078

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available