Retinal blood vessel segmentation based on the Gaussian matched filter and U-net
Explore this paper's citation graph
- Type
- article
- Published
- 2017-10-01
- Cited by
- 37
- References
- 21
- OpenAlex
- https://openalex.org/W2792951596
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:3661124
Keywords
Segmentation, Artificial intelligence, Computer science, Convolutional neural network, Pattern recognition (psychology)
References
- Segmenting Retinal Blood Vessels With Deep Neural Networks
- Fully convolutional networks for semantic segmentation
- An Ensemble Classification-Based Approach Applied to Retinal Blood Vessel Segmentation
- Blood vessel segmentation methodologies in retinal images - A survey
- Hierarchical retinal blood vessel segmentation based on feature and ensemble learning
- Application of Morphological Bit Planes in Retinal Blood Vessel Extraction
- Retinal vessel segmentation employing ANN technique by Gabor and moment invariants-based features
- Trainable COSFIRE filters for vessel delineation with application to retinal images
- Retinal Blood Vessel Segmentation Using Line Operators and Support Vector Classification
- An improved matched filter for blood vessel detection of digital retinal images
- Retinal vessel extraction by matched filter with first-order derivative of Gaussian
- Retinal vessel segmentation using the 2-D Gabor wavelet and supervised classification
- Retinal blood vessels segmentation by using Gumbel probability distribution function based matched filter
- Ensemble of Deep Convolutional Neural Networks for Learning to Detect Retinal Vessels in Fundus Images
- Retinal Vessel Segmentation using Deep Neural Networks
- Retinal vessel segmentation via deep learning network and fully-connected conditional random fields
- A new supervised retinal vessel segmentation method based on robust hybrid features
- Supervised vessel delineation in retinal fundus images with the automatic selection of B-COSFIRE filters
- Deep neural ensemble for retinal vessel segmentation in fundus images towards achieving label-free angiography
- A fully convolutional neural network based structured prediction approach towards the retinal vessel segmentation
Cited by
- Extraction of Blood Vessels in Fundus Images of Retina through Hybrid Segmentation Approach
- Architecture and Factor Design of Fully Convolutional Neural Networks for Retinal Vessel Segmentation
- A Fundus Retinal Vessels Segmentation Scheme Based on the Improved Deep Learning U-Net Model
- Comparative Analysis of Vessel Segmentation Techniques in Retinal Images
- Fast and robust retinal biometric key generation using deep neural nets
- CGAN-based Synthetic Medical Image Augmentation between Retinal Fundus Images and Vessel Segmented Images
- Modified U-Net architecture for semantic segmentation of diabetic retinopathy images
- CSU-Net: A Context Spatial U-Net for Accurate Blood Vessel Segmentation in Fundus Images
- M-GAN: Retinal Blood Vessel Segmentation by Balancing Losses Through Stacked Deep Fully Convolutional Networks
- MRU-NET: A U-Shaped Network for Retinal Vessel Segmentation
- Retinal Vessel Segmentation Combined With Generative Adversarial Networks and Dense U-Net
- Retinal Blood Vessel Extraction Based on Adaptive Segmentation Algorithm
- Retinal Vessel Segmentation with Differentiated U-Net Network
- Improved optic disc and cup segmentation in Glaucomatic images using deep learning architecture
- Automatic Diabetic Retinopathy Grading System Based on Detecting Multiple Retinal Lesions
- Retinal vessel segmentation based on task-driven generative adversarial network
- 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
- Hybrid UNet Architecture based on Residual Learning of Fundus Images for Retinal Vessel Segmentation
- Retinal Vessel Extraction via Assisted Multi-Channel Feature Map and U-Net
- A Detailed Systematic Review on Retinal Image Segmentation Methods
Related papers
- An Adaptable Real-Time Object Detection for Traffic Surveillance using R-CNN over CNN with Improved Accuracy
- Ratiometric Analysis of In Vivo Optical Coherence Tomography Retinal Layer Thicknesses for Detection of Changes in Alzheimer’s Disease
- Convolutional Neural Network (CNN) Applied to the Risk Analysis of Accidents in Vessels Navigating the Amazon Rivers
- Retinal vascular image analysis as a potential screening tool for cerebrovascular disease: a rationale based on homology between cerebral and retinal microvasculatures
- SEGMENTATION OF MEDICAL IMAGES BY CONVOLUTIONAL NEURAL NETWORKS
- Convolutional Neural Network for Automated Analyzing of Medical Images
- Ocular Disease Detection Using Convolutional Neural Networks
- Video-based Estimation System Using Convolutional Neural Networks for Audiences’ State in the Classroom and Discussion of its Essential Image Features
- Age Estimation Method based on Comparative Convolutional Neural Network using Inception Module
- Retinal vascular characteristics and the strategy to manage retinal vascular diseases