Efficient Pyramid Channel Attention Network for Pathological Myopia Detection

Pathological myopia (PM) is the leading ocular disease for impaired vision and blindness worldwide. The key to detecting PM as early as possible is to detect informative features in global and local lesion regions, such as fundus tessellation, atrophy and maculopathy. However, applying classical convolutional neural networks (CNNs) to efficiently highlight global and local lesion context information in feature maps is quite challenging. To tackle this issue, we aim to fully leverage the potential of global and local lesion information with attention module design. Based on this, we propose an efficient pyramid channel attention (EPCA) module, which dynamically explores the relative importance of global and local lesion context information in feature maps. Then we combine the EPCA module with the backbone network to construct EPCA-Net for automatic PM detection based on fundus images. In addition, we construct a PM dataset termed PM-fundus by collecting fundus images of PM from publicly available datasets (e.g., the PALM dataset and ODIR dataset). The comprehensive experiments are conducted on three datasets, demonstrating that our EPCA-Net outperforms state-of-the-art methods in detecting PM. Furthermore, motivated by the recent pretraining-and-finetuning paradigm, we attempt to adapt pre-trained natural image models for PM detection by freezing them and treating the EPCA module and other attention modules as the adapters. The results show that our method with the pretraining-and-finetuning paradigm achieves competitive performance through comparisons to part of methods with traditional fine-tuning methods with fewer tunable parameters.Comment: 12 page

Increased Connexin36 Phosphorylation in AII Amacrine Cell Coupling of the Mouse Myopic Retina.

Myopia is a substantial public health problem worldwide. In the myopic retina, distant images are focused in front of the photoreceptors. The cells and mechanisms for retinal signaling that account either for emmetropization (i.e., normal refraction) or for refractive errors have remained elusive. Gap junctions play a key component in enhancement of signal transmission in visual pathways. AII amacrine cells (ACs), coupled by connexin36, segregate signals into ON and OFF pathways. Coupling between AII ACs is actively modulated through phosphorylation at serine 293 via dopamine in the mouse retina. In this study, form deprivation mouse myopia models were used to evaluate the expression patterns of connexin36-positive plaques (structural assay) and the state of connexin36 phosphorylation (functional assay) in AII ACs, which was green fluorescent protein-expressing in the Fam81a mouse line. Single-cell RNA sequencing showed dopaminergic synapse and gap junction pathways of AII ACs were downregulated in the myopic retina, although Gjd2 mRNA expression remained the same. Compared with the normal refractive eye, phosphorylation of connexin36 was increased in the myopic retina, but expression of connexin36 remained unchanged. This increased phosphorylation of Cx36 could indicate increased functional gap junction coupling of AII ACs in the myopic retina, a possible adaptation to adjust to the altered noisy signaling status