Author : S.Piramu Kailasam 1
Date of Publication :31st December 2017
Abstract: Machine learning techniques used in diagnosing cancerous lesions in medical images. The phenotype features of the pulmonary nodule in CT images are important cues for the malignancy prediction. This can improve radiologist make decisions which are difficult to identify, improving the accuracy of efficiency. Deep Learning or hierarchical learning as a major area of machine learning in the field of medical imaging hopefully faster and gives best results. Using parallel computing techniques speed up matrix operation with more parameters. Compared to the conventional machine learning methods deep learning has shown a superior performance in visual media. In this study, we develop EXHOG descriptor to characterize semantic features in deep convolutional Neural Network. An SVM classifier finds the nodule types with richer accuracy from LIDC lung medical image data set.
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