Rotator Cuff Tears (RCTs) are primarily age-related musculoskeletal disorders affecting the shoulder region. In this paper, we present a research effort that aims to construct a Computer-Aided Diagnosis (CAD) model for RCTs. The model utilizes three-plane MRI slides coupled with diagnostic outcomes. To enhance model interpretability, we employed MRNet, conducting training on each anatomical plane, and subsequently merged the results using logistic regression. At the individual plane level and the fusion level, we applied Grad-CAM and SHapley Additive exPlanations (SHAP), respectively. Additionally, we introduce CAMscore, a method using Grad-CAM, designed to quantitatively determine the diagnostic relevance of individual MRI slides. When fusing the three planes, we achieved a maximum F1-score of 0.9508. Additionally, we observed a notably higher diagnostic efficacy in the sagittal plane compared to the axial and coronal planes. However, our study has certain limitations, including the need for greater dataset diversity and the necessity for verification by medical professionals. Nevertheless, our study advances the field of CAD by improving the understanding of the decision-making processes of models utilizing three-plane fusion.
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