Disc-Aware Ensemble Network for Glaucoma Screening From Fundus Image

By Huan Fu, Jun Cheng, Yanwu Xu, Changqing Zhang, Damon Wing Kee Wong, Jiang Liu, Xiaochun Cao. IEEE Transactions on Medical Imaging, 2018

404 citations recorded by the source corpus.

Glaucoma is a chronic eye disease that leads to irreversible vision loss. Most of the existing automatic screening methods first segment the main structure and subsequently calculate the clinical measurement for the detection and screening of glaucoma. However, these measurement-based methods rely heavily on the segmentation accuracy and ignore various visual features. In this paper, we introduce a deep learning technique to gain additional image-relevant information and screen glaucoma from the fundus image directly. Specifically, a novel disc-aware ensemble network for automatic glaucoma screening is proposed, which integrates the deep hierarchical context of the global fundus image and the local optic disc region. Four deep streams on different levels and modules are, respectively, considered as global image stream, segmentation-guided network, local disc region stream, and disc polar transformation stream. Finally, the output probabilities of different streams are fused as the final screening result. The experiments on two glaucoma data sets (SCES and new SINDI data sets) show that our method outperforms other state-of-the-art algorithms.

Subfields: Artificial Intelligence, Ophthalmology, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/88b91fb2834432273b915a8fb63ccf017e1bc034

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. P. Heng
2. Hao Chen
3. Lequan Yu
4. Chi-Wing Fu
5. Huan Fu
6. Kai Wang
7. Xiaomeng Li
8. Tao Li

In Ophthalmology

1. Huan Fu
2. Kai Wang
3. Tao Li

In Radiology, Nuclear Medicine and Imaging

1. P. Heng
2. Hao Chen
3. Lequan Yu
4. Chi-Wing Fu
5. Huan Fu
6. Kai Wang
7. Tao Li
8. Qi-Yan Dou

Citations in the corpus

• Transformation-Consistent Self-Ensembling Model for Semisupervised Medical Image Segmentation (2019, background): “Also, a disc-aware network [45] was designed for glaucoma screening by an ensemble of different feature streams of the network.”
• CABNet: Category Attention Block for Imbalanced Diabetic Retinopathy Grading (2020, background): “Thanks to the powerful capability of high-level feature extraction and representational ability of CNNs, they have also been widely used in medical image analysis tasks such as retinal blood vessel segmentation [7], optic disc segmentation [8] and glaucoma screening [9], [10].”