FGB: FEATURE GUIDANCE BRANCH FOR ORGAN DETECTION IN MEDICAL IMAGES

In this paper, we propose a novel method that detects and locates different abdominal organs from CT images. We 1) utilize the distributions of organs on CT images as a prior to guide object localization; 2) design an efficient guidance map and propose an interpretable scoring method, feature guidance branch(FGB) to filtrate low-level feature maps by scoring for them; 3) establish effective relations among feature maps by visualization to enhance interpretability. Evaluated with three public datasets, the proposed method outperforms the baseline model on all tasks with a remarkable margin. Furthermore, we conduct exhaustive visualization experiments to verify the rationality and effectiveness of our proposed model.