Haemorrhage diagnosis in colour fundus images using a fast-convolutional neural network based on a modified U-Net-Reference-Cited by-同舟云学术

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Haemorrhage diagnosis in colour fundus images using a fast-convolutional neural network based on a modified U-Net

Published:2024-02-12 Issue: Volume: Page:1-22
ISSN:0954-898X
Container-title:Network: Computation in Neural Systems
language:en
Short-container-title:Network: Computation in Neural Systems

Author:

Sathiyaseelan Rathinavelu¹,Ranganathan Krishnamoorthy²,Ramamoorthy Ramesh³,Pedda Chennaiah M.⁴

Affiliation:

1. Department of CSE, Arunai Engineering College, Thiruvanamalai, India

2. Centre for Advanced Wireless Integrated Technology, Chennai Institute of Technology, Chennai, India

3. Department of CSE, Chennai Institute of Technology, India

4. Department of ECE, Vemu Institute of Technology, A.P, India

Funder

no funding associated with the work featured in this article

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/0954898X.2024.2310687

Reference23 articles.

1. Combining Artificial Intelligence and Image Processing for Diagnosing Diabetic Retinopathy in Retinal Fundus Images

2. Deep learning-based hemorrhage detection for diabetic retinopathy screening

3. Screening of idiopathic epiretinal membrane using fundus images combined with blood oxygen saturation and vascular morphological features

4. Scale-adaptive model for detection and grading of age-related macular degeneration from color retinal fundus images

5. Applied CNN for Automatic Diabetic Retinopathy Assessment Using Fundus Images

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1. Synergizing Deep Learning-Enabled Preprocessing and Human–AI Integration for Efficient Automatic Ground Truth Generation;Bioengineering;2024-04-28

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