Nonlinear Adaptive Convergence Index Filters and Their Characteristics
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 3
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ICPR '96 Proceedings of the 13th International Conference on Pattern Recognition - Volume 2
Detection of Lung Nodule Candidates in Chest Radiographs
IbPRIA '07 Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part II
An evaluation of contrast enhancement techniques for mammographic breast masses
IEEE Transactions on Information Technology in Biomedicine
Convergence index filter for vector fields
IEEE Transactions on Image Processing
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ICIAR'10 Proceedings of the 7th international conference on Image Analysis and Recognition - Volume Part II
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The aim of this paper is to evaluate and compare the performance of three convergence index (CI) filters when applied to the enhancement of chest radiographs, aiming at the detection of lung nodules. One of these filters, the sliding band filter (SBF), is the proposal of an innovative operator, while the other two CI class members, the iris filter (IF) and the adaptive ring filter (ARF), are already known in this application. To demonstrate the adequacy of the new filter for the enhancement of chest x-ray images, we calculated several figures of merit with the goal of comparing (i) the contrast enhancement capability of the filters, and (ii) the behavior of the filters for the detection of lung nodules. The results obtained for 154 images with nodules of the JSRT database show that the SBF outperforms both the IF and ARF. The proposed filter demonstrated to be a promising enhancement method, thus justifying its use in the first stage of a computer-aided diagnosis system for the detection of lung nodules.