Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4219856 | Academic Radiology | 2009 | 10 Pages |
Abstract
This study demonstrates that for the optimum selection of features, each feature should be analyzed individually and collectively to evaluate the impact on the computer-aided diagnosis system on the basis of its class representation. This methodology will ultimately aid in improving the generalization capability of a classification module for early lung cancer diagnosis.
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Authors
Ravi MS, Wilfrido PhD, Yuncheng PhD, Wei PhD,