Instruct: Given the title of a paper, retrieve paper titles that are cited by the given paper.
Query: Segmentation of the Blood Vessels and Optic Disk in Retinal Images
A New Supervised Method for Blood Vessel Segmentation in Retinal Images by Using Gray-Level and Moment Invariants-Based Features
on : Blood Vessel Extraction and Eye Retinopathy Detection
Automatic Identification of Retinal Arteries and Veins in Fundus Images using Local Binary Patterns
A Cross-Modality Learning Approach for Vessel Segmentation in Retinal Images
Automatic optic disc segmentation with peripapillary atrophy elimination
Ensemble of Deep Convolutional Neural Networks for Learning to Detect Retinal Vessels in Fundus Images
Diagnosis of Diabetic Retinopathy: Automatic Extraction of Optic Disc and Exudates from Retinal Images using Marker-controlled Watershed Transformation
A Three-Stage Deep Learning Model for Accurate Retinal Vessel Segmentation
New feature-based detection of blood vessels and exudates in color fundus images
Integrated Optic Disc and Cup Segmentation with Deep Learning
FABC: Retinal Vessel Segmentation Using AdaBoost
Particle swarm optimization method for small retinal vessels detection on multiresolution fundus images
Automatic optic disc detection in digital fundus images using image processing
Automated Vessel Segmentation Using Infinite Perimeter Active Contour Model with Hybrid Region Information with Application to Retinal Images
A Discriminatively Trained Fully Connected Conditional Random Field Model for Blood Vessel Segmentation in Fundus Images
An Automatic Graph-Based Approach for Artery/Vein Classification in Retinal Images
Automatic localization of optic disc based on deep learning in fundus images
Detecting retinal microaneurysms and hemorrhages with robustness to the presence of blood vessels
Retinal Image Analysis : A Review
Deeply supervised neural network with short connections for retinal vessel segmentation
All about activity injection: Threats, semantics, and detection
Knowledge Via An Explanatory Graph
Minimal Change And Bounded Incremental Parsing
Application of Clustering Methods to Health Insurance Fraud Detection
Approximation Algorithms