Yibo Dan1, Hongyue Tao2, Yida Wang1, Chengxiu Zhang1, Chenglong Wang1, Shuang Chen2, and Guang Yang1
1Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, shanghai, China, 2Department of Radiology, Huashan Hospital, Fudan University, shanghai, China
1Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, shanghai, China, 2Department of Radiology, Huashan Hospital, Fudan University, shanghai, China
We proposed a heuristic method for
effective dimension reduction and feature selection, which built scout models for
each categories of features to select useful features for final model building.
Figure 1. Flowchart of the modeling process
for BraTS 2019 dataset. Pipeline for CAI dataset is similar but for the number
of selected features from each category.
Table 1. Comparison of performance of
proposed approach with classic feature selectors over BraTS2019 dataset.