Zhigao Zeng1,2, Aoting Tang1,2, Shengqiu Yi1,2, Xinpan Yuan1,2, Yanhui Zhu1,2,*
CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2277-2293, 2024, DOI:10.32604/cmc.2024.047989
- 15 May 2024
Abstract Radiomics is a non-invasive method for extracting quantitative and higher-dimensional features from medical images for diagnosis. It has received great attention due to its huge application prospects in recent years. We can know that the number of features selected by the existing radiomics feature selection methods is basically about ten. In this paper, a heuristic feature selection method based on frequency iteration and multiple supervised training mode is proposed. Based on the combination between features, it decomposes all features layer by layer to select the optimal features for each layer, then fuses the optimal features More >