# BiRA-Net: Bilinear Attention Net for Diabetic Retinopathy Grading

arXiv: https://arxiv.org/abs/1905.06312 · HTML: https://mlsanity.com/paper/1905.06312/

## Key facts

- Cited by 15 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 15 May 2019.

## Built on by (most cited first, 15 of 15)

- [A Foundation Language-Image Model of the Retina (FLAIR): Encoding Expert Knowledge in Text Supervision](https://mlsanity.com/paper/2308.07898/) (2023)
- [Applications of Deep Learning in Fundus Images: A Review](https://mlsanity.com/paper/2101.09864/) (2021)
- [MM-Retinal: Knowledge-Enhanced Foundational Pretraining with Fundus Image-Text Expertise](https://mlsanity.com/paper/2405.11793/) (2024)
- [Image Quality-aware Diagnosis via Meta-knowledge Co-embedding](https://mlsanity.com/paper/2303.15038/) (2023)
- [Two Eyes Are Better Than One: Exploiting Binocular Correlation for Diabetic Retinopathy Severity Grading](https://mlsanity.com/paper/2108.06763/) (2021)
- [Time Majority Voting, a PC-based EEG Classifier for Non-expert Users](https://mlsanity.com/paper/2207.12662/) (2022)
- [Trends in Machine Learning and Electroencephalogram (EEG): A Review for Undergraduate Researchers](https://mlsanity.com/paper/2307.02819/) (2023)
- [ACT-Net: Asymmetric Co-Teacher Network for Semi-supervised Memory-efficient Medical Image Segmentation](https://mlsanity.com/paper/2207.01900/) (2022)
- [Multimodal Medical Image Binding via Shared Text Embeddings](https://mlsanity.com/paper/2506.18072/) (2025)
- [Object-Aware Self-supervised Multi-Label Learning](https://mlsanity.com/paper/2205.07028/) (2022)
- [Residual Channel Attention Network for Brain Glioma Segmentation](https://mlsanity.com/paper/2205.10758/) (2022)
- [Too Fine or Too Coarse? The Goldilocks Composition of Data Complexity for Robust Left-Right Eye-Tracking Classifiers](https://mlsanity.com/paper/2209.03761/) (2022)
- [PSScreen: Partially Supervised Multiple Retinal Disease Screening](https://mlsanity.com/paper/2508.10549/) (2025)
- [EEG4Students: An Experimental Design for EEG Data Collection and Machine Learning Analysis](https://mlsanity.com/paper/2208.11743/) (2022)
- [PSScreen V2: Partially Supervised Multiple Retinal Disease Screening](https://mlsanity.com/paper/2510.22589/) (2025)

## Abstract (arXiv)

Diabetic retinopathy (DR) is a common retinal disease that leads to blindness. For diagnosis purposes, DR image grading aims to provide automatic DR grade classification, which is not addressed in conventional research methods of binary DR image classification. Small objects in the eye images, like lesions and microaneurysms, are essential to DR grading in medical imaging, but they could easily be influenced by other objects. To address these challenges, we propose a new deep learning architecture, called BiRA-Net, which combines the attention model for feature extraction and bilinear model for fine-grained classification. Furthermore, in considering the distance between different grades of different DR categories, we propose a new loss function, called grading loss, which leads to improved training convergence of the proposed approach. Experimental results are provided to demonstrate the superior performance of the proposed approach.