AIMC Topic: Retinal Vessels

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End-to-End Adversarial Retinal Image Synthesis.

IEEE transactions on medical imaging
In medical image analysis applications, the availability of the large amounts of annotated data is becoming increasingly critical. However, annotated medical data is often scarce and costly to obtain. In this paper, we address the problem of synthesi...

Automated arteriole and venule classification using deep learning for retinal images from the UK Biobank cohort.

Computers in biology and medicine
The morphometric characteristics of the retinal vasculature are associated with future risk of many systemic and vascular diseases. However, analysis of data from large population based studies is needed to help resolve uncertainties in some of these...

Vascular tree tracking and bifurcation points detection in retinal images using a hierarchical probabilistic model.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Retinal vascular tree extraction plays an important role in computer-aided diagnosis and surgical operations. Junction point detection and classification provide useful information about the structure of the vascular network...

Improving dense conditional random field for retinal vessel segmentation by discriminative feature learning and thin-vessel enhancement.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: As retinal vessels in color fundus images are thin and elongated structures, standard pairwise based random fields, which always suffer the "shrinking bias" problem, are not competent for such segmentation task. Recently, a...

Feasibility study on robot-assisted retinal vascular bypass surgery in an ex vivo porcine model.

Acta ophthalmologica
PURPOSE: To describe a new robot-assisted surgical system for retinal vascular bypass surgery (RVBS) and to compare the success rate with freehand RVBS.

Multi-level deep supervised networks for retinal vessel segmentation.

International journal of computer assisted radiology and surgery
PURPOSE: Changes in the appearance of retinal blood vessels are an important indicator for various ophthalmologic and cardiovascular diseases, including diabetes, hypertension, arteriosclerosis, and choroidal neovascularization. Vessel segmentation f...

Retinal blood vessel extraction using tunable bandpass filter and fuzzy conditional entropy.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Extraction of blood vessels on retinal images plays a significant role for screening of different opthalmologic diseases. However, accurate extraction of the entire and individual type of vessel silhouette from the noisy im...

Retinal vessel segmentation in colour fundus images using Extreme Learning Machine.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Attributes of the retinal vessel play important role in systemic conditions and ophthalmic diagnosis. In this paper, a supervised method based on Extreme Learning Machine (ELM) is proposed to segment retinal vessel. Firstly, a set of 39-D discriminat...

Accelerating Convolutional Sparse Coding for Curvilinear Structures Segmentation by Refining SCIRD-TS Filter Banks.

IEEE transactions on medical imaging
Deep learning has shown great potential for curvilinear structure (e.g., retinal blood vessels and neurites) segmentation as demonstrated by a recent auto-context regression architecture based on filter banks learned by convolutional sparse coding. H...

Segmenting Retinal Blood Vessels With Deep Neural Networks.

IEEE transactions on medical imaging
The condition of the vascular network of human eye is an important diagnostic factor in ophthalmology. Its segmentation in fundus imaging is a nontrivial task due to variable size of vessels, relatively low contrast, and potential presence of patholo...