Towards Balancing the Complexity of Convolutional Neural Network with the Role of Optical Coherence Tomography in Retinal Conditions

Convolutional neural networks have shown impressive performance in the medical image domain, but medical experts are somewhat skeptical in their predictions since the features are not directly graspable. We are looking into one of the technical challenges, namely the explainability of the results, to try to find out some demonstration of the regions deemed abnormal by deep learning. Following the trend of heatmaps indicating which local morphology changes would modify the predictions, we are trying to verify the facilitation of the clinical understanding in the eyes of the ophthalmologist.