A ranklet-based CAD for digital mammography

Angelini, Enrico ; Campanini, Renato ; Iampieri, Emiro ; Masotti, Matteo ; Petkov, Todor ; Roffilli, Matteo (2006) A ranklet-based CAD for digital mammography. Proceedings of the 8th International Workshop on Digital Mammography . pp. 340-346.
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Abstract

A novel approach to the detection of masses and clustered microcalcification is presented. Lesion detection is considered as a two-class pattern recognition problem. In order to get an effective and stable representation, the detection scheme codifies the image by using a ranklet transform. The vectors of ranklet coefficients obtained are classified by means of an SVM classifier. Our approach has two main advantages. First it does not need any feature selected by the trainer. Second, it is quite stable, with respect to the image histogram. That allows us to tune the detection parameters in one database and use the trained CAD on other databases without needing any adjustment. In this paper, training is accomplished on images coming from different databases (both digitized and digital). Test results are calculated on images coming from a few FFDM Giotto Image MD clinical units. The sensitivity of our CAD system is about 85% with a false-positive rate of 0.5 marks per image.

Abstract
Document type
Article
Creators
CreatorsAffiliationORCID
Angelini, Enrico
Campanini, Renato
Iampieri, Emiro
Masotti, Matteo
Petkov, Todor
Roffilli, Matteo
Keywords
Ranklet, Support Vector Machine, Computer-Aided Detection, Mammography
Subjects
DOI
Deposit date
25 Sep 2006
Last modified
16 May 2011 12:04
URI

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