Multi-Class SVMs Based on Priority for Computer-Aided Diagnosis of Lung Nodules in CT Images

Qing Zhu Wang; Xin Zhu Wang; Ji Song Bie; Bin Wang

doi:10.4028/www.scientific.net/AMR.291-294.2742

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 291-294Multi-Class SVMs Based on Priority for...

Multi-Class SVMs Based on Priority for Computer-Aided Diagnosis of Lung Nodules in CT Images

Abstract:

A priority based ‘One against all (OAA)’ Multi-class Least Square-Support Vector Machines is designed to remove the unclassifiable regions exist in basic OAA. POAA develops the sensitivity and specificity in Computer-aided Diagnosis (CAD) for detection of lung nodules.

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Materials Processing Technology, AEMT2011

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Periodical:

Advanced Materials Research (Volumes 291-294)

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2742-2745

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https://doi.org/10.4028/www.scientific.net/AMR.291-294.2742

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Online since:

July 2011

Authors:

Qing Zhu Wang, Xin Zhu Wang, Ji Song Bie, Bin Wang

Keywords:

Compute Tomography (CT) Image, Lung Nodules, Multi-Class Svms

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