CCA-Net: Clinical-awareness attention network for nuclear cataract classification in AS-OCT

(CCA-Net) to classify NC severity levels automatically. In CCA-Net, we design a practical yet effective clinical-aware attention block, which not only uses the mixed pooling operator to extract clinical features from each channel but also applies the designed clinical integration operator to focus on salient channels. We conduct extensive experiments on one clinical AS-OCT image dataset and two publicly available ophthalmology datasets. The results demonstrate that the CCA-Net outperforms state-of-the-art attention-based CNNs and strong baselines. Moreover, we also provide in-depth analysis to explain the internal behaviors of our method, enhancing the interpretation ability of our method.