Computer-Aided Diagnosis for Early-Stage Lung Cancer Based on Longitudinal and Balanced Data

Abstract

With textural features extracted from a Curvelet transformation and other parameters, a sensitive support vector machine prediction model can increase the rate of diagnosis for early-stage lung cancer. This scheme can be used as an auxiliary tool to differentiate between benign and malignant early-stage lung cancers in CT images.