IterNet++: An improved model for retinal image segmentation by curvelet enhancing, guided filtering, offline hard‐sample mining, and test‐time augmenting-Reference-Cited by-同舟云学术

IterNet++: An improved model for retinal image segmentation by curvelet enhancing, guided filtering, offline hard‐sample mining, and test‐time augmenting

Published:2022-08-08 Issue:13 Volume:16 Page:3617-3633
ISSN:1751-9659
Container-title:IET Image Processing
language:en
Short-container-title:IET Image Processing

Author:

Zhu M.¹,Zeng K.¹^ORCID,Lin G.¹,Gong Y.²,Hao T.³,Wattanachote K.²,Luo X.⁴

Affiliation:

1. School of Computer Science and Engineering Sun Yat‐Sen University Guangzhou China

2. Guangdong University of Foreign Studies Guangzhou China

3. School of Computer Science South China Normal University Guangzhou China

4. National & Local Joint Engineering Research Center of Satellite Navigation and Location Service Guilin University of Electronic Technology Guilin China

Funder

National Natural Science Foundation of China

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/ipr2.12580

Reference47 articles.

1. ROSE: A Retinal OCT-Angiography Vessel Segmentation Dataset and New Model

2. Retinal image analysis: Concepts, applications and potential

3. Retinal Imaging and Image Analysis