Retinal Image Pre-Processing Using Equalization and thResholding (RIPPER)-Reference-Cited by-同舟云学术

Retinal Image Pre-Processing Using Equalization and thResholding (RIPPER)

Published:2023-09-22 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2023 10th International Conference on Bioinformatics Research and Applications
language:
Short-container-title:

Author:

Nwanze Nnamdi¹^ORCID,Nwanze Chukwuemeka C.²^ORCID,Akinwale Abumere³^ORCID,Baitch Larry²^ORCID

Affiliation:

1. Computer Science & Engineering, North Central College, USA

2. School of Optometry, Mass. Coll. of Pharm & Health Sciences, USA

3. Department of Ophthalmology, Veterans Healthcare System, USA

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3632047.3632049

Reference43 articles.

1. Comprehensive review of retinal blood vessel segmentation and classification techniques: intelligent solutions for green computing in medical images, current challenges, open issues, and knowledge gaps in fundus medical images

2. Mohammed Al-Rawi, Munib Qutaishat, and Mohammed Arrar. 2007. An improved matched filter for blood vessel detection of digital retinal images. Computers in biology and medicine 37, 2 (2007), 262–267.

3. Minhaj Alam, Taeyoon Son, Devrim Toslak, Jennifer I Lim, and Xincheng Yao. 2018. Combining ODR and blood vessel tracking for artery–vein classification and analysis in color fundus images. Translational vision science & technology 7, 2 (2018), 23–23.

4. Image classification with deep learning in the presence of noisy labels: A survey

5. An Unsupervised Retinal Vessel Segmentation Using Hessian and Intensity Based Approach

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. MicroSeg: Multi-scale fusion learning for microaneurysms segmentation;Biomedical Signal Processing and Control;2024-11