Overview of Deep Learning Methods for Retinal Vessel Segmentation-Reference-Cited by-同舟云学术

Overview of Deep Learning Methods for Retinal Vessel Segmentation

Published:2024 Issue: Volume: Page:81-92
ISSN:2367-3370
Container-title:Lecture Notes in Networks and Systems
language:en
Short-container-title:

Author:

Gojić Gorana^ORCID,Kundačina Ognjen^ORCID,Mišković Dragiša^ORCID,Dragan Dinu^ORCID

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-50755-7_9

Reference39 articles.

1. Cheung, C.S., Butty, Z., Tehrani, N.N., Lam, W.C.: Computer-assisted image analysis of temporal retinal vessel width and tortuosity in retinopathy of prematurity for the assessment of disease severity and treatment outcome. JAAPOS 15(4), 374–380 (2011)

2. Gojić, G., et al.: Deep learning methods for retinal blood vessel segmentation: evaluation on images with retinopathy of prematurity. In: Proceedings of the SISY 2020, pp. 131–136 (2020)

3. Fraz, M., et al.: Blood vessel segmentation methodologies in retinal images – a survey. Comput. Meth. Prog. Biomed. 108(1), 407–433 (2012)

4. Li, Q., You, J., Zhang, D.: Vessel segmentation and width estimation in retinal images using multiscale production of matched filter responses. Exp. Syst. Appl. 39(9), 7600–7610 (2012)

5. Mookiah, M.R.K., et al.: A review of machine learning methods for retinal blood vessel segmentation and artery/vein classification. Med. Image Anal. 68, 101905 (2021)

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. Enhanced Retinal Vessel Segmentation Using U-Net Framework;2024 IEEE International Conference on Contemporary Computing and Communications (InC4);2024-03-15