Region of Interest Prediction by Intra-stack Attention Neural Network

Manual prescription of the field of view (FOV) by MRI technologists is variable and prolongs the scanning process. Often, the FOV is too large or crops critical anatomy. We propose a deep-learning framework, trained by radiologists’ supervision, for predicting region of interest (ROI) and automating FOV prescription. The proposed ROI prediction model achieves an average IoU of 0.867, significantly better (P<0.05) than two baseline models and not significantly different from a radiologist (P>0.12). The FOV prescribed by the proposed framework achieves an acceptance rate of 92% from an experienced radiologist.