The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Zoom-in-Net: Deep Mining Lesions for Diabetic Retinopathy Detection
Open accessAbstract
We propose a convolution neural network based algorithm for simultaneously diagnosing diabetic retinopathy and highlighting suspicious regions. Our contributions are two folds: (1) a network termed Zoom-in-Net which mimics the zoom-in process of a clinician to examine the retinal images. Trained with only image-level supervisions, Zoom-in-Net can generate attention maps which highlight suspicious regions, and predicts the disease level accurately based on both the whole image and its high resolution suspicious patches. (2) Only four bounding boxes generated from the automatically learned attention maps are enough to cover 80% of the lesions labeled by an experienced ophthalmologist, which shows good localization ability of the attention maps. By clustering features at high response locations on the attention maps, we discover meaningful clusters which contain potential lesions in diabetic retinopathy. Experiments show that our algorithm outperform the state-of-the-art methods on two datasets, EyePACS and Messidor.
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LIBSVM: A library for support vector machines
Chang, C.-C., & Lin, C.-J. (2011) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/1961189.1961199 · Cited by 40,918
Rethinking the Inception Architecture for Computer Vision
Szegedy, C., Vanhoucke, V., Ioffe, S., Shlens, J., & Wojna, Z. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.308 · Cited by 32,138
Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning
Szegedy, C., Ioffe, S., Vanhoucke, V., & Alemi, A. (2017) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v31i1.11231 · Cited by 4,636
Abràmoff, M. D., Lou, Y., Erginay, A., Clarida, W., Amelon, R., Folk, J. C., & Niemeijer, M. (2016) · Investigative Opthalmology & Visual Science · doi:10.1167/iovs.16-19964 · Cited by 1,101
Cited by
CE-Net: Context Encoder Network for 2D Medical Image Segmentation
Gu, Z., Cheng, J., Fu, H., Zhou, K., Hao, H., Zhao, Y., Zhang, T., Gao, S., & Liu, J. (2019) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2019.2903562 · Cited by 2,267
A Deep Learning Ensemble Approach for Diabetic Retinopathy Detection
Qummar, S., Khan, F. G., Shah, S., Khan, A., Shamshirband, S., Rehman, Z. U., Ahmed Khan, I., & Jadoon, W. (2019) · IEEE Access · doi:10.1109/access.2019.2947484 · Cited by 622
Applications of deep learning in fundus images: A review
Li, T., Bo, W., Hu, C., Kang, H., Liu, H., Wang, K., & Fu, H. (2021) · Medical Image Analysis · doi:10.1016/j.media.2021.101971 · Cited by 396
Deep learning for diabetic retinopathy detection and classification based on fundus images: A review
Tsiknakis, N., Theodoropoulos, D., Manikis, G., Ktistakis, E., Boutsora, O., Berto, A., Scarpa, F., Scarpa, A., Fotiadis, D. I., & Marias, K. (2021) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2021.104599 · Cited by 328
Qiao, L., Zhu, Y., & Zhou, H. (2020) · IEEE Access · doi:10.1109/access.2020.2993937 · Cited by 304
Metadata
- Authors
- Wang, Z., Yin, Y., Shi, J., Fang, W., Li, H., & Wang, X.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2017
- Pages
- 267-275
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2626629100
- Cited by
- 281
- References
- 4
- FWCI
- 43.91
- Type
- conference paper
- Language
- en
- Open access
- green
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