Applications of Gabor filter -based features and Gabor filter apart from computed tomography texture analysis

Abstract Background : The aim of our study is to explore the performance of grey level co- occurrence texture features and Gabor texture features in the prediction of Fuhrman nuclear grades of clear cell renal cell carcinoma(cCRCC).Besides, applications of Gabor filter based features and Gabor filter were reviewed. Methods : One hundred and ten two- dimension images from 109 cCRCC patients were recruited from The Cancer Image Archives website . Then Images texture features regarding grey level co-occurrence texture features and Gabor texture features were extracted from the enhanced abdominal computed tomography images of clear cell renal cell carcinoma of The Cancer Image Archives websites.The performance of grey level co-occurrence texture features and Gabor texture features in the prediction of Fuhrman nuclear grades of clear cell were calculated by WEKA open source software. Result : Non-inferior performance of Gabor texture features was found while compared with the performance of grey level co-occurrence texture features in the prediction of Fuhrman nuclear grades of clear cell renal cell carcinoma. . Discussion : While implementation of image features in the prediction of Fuhrman nuclear grades of clear cell renal cell carcinoma, extraction of Gabor texture features from the image should be considered.