An attention enriched encoder–decoder architecture with CLSTM and RES unit for segmenting exudate in retinal images
Author:
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11760-024-02996-7.pdf
Reference56 articles.
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2. Harangi, B., Hajdu, A.: Detection of exudates in fundus images using a Markovian segmentation model. In: 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 130–133. IEEE (2014)
3. Pereira, C., Gonçalves, L., Ferreira, M.: Exudate segmentation in fundus images using an ant colony optimization approach. Inf. Sci. (N.Y.) 296, 14–24 (2015)
4. Sánchez, C.I., García, M., Mayo, A., López, M.I., Hornero, R.: Retinal image analysis based on mixture models to detect hard exudates. Med. Image Anal. 13, 650–658 (2009)
5. Sopharak, A., Uyyanonvara, B., Barman, S., Williamson, T.H.: Automatic detection of diabetic retinopathy exudates from non-dilated retinal images using mathematical morphology methods. Comput. Med. Imaging Graph. 32, 720–727 (2008)
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