AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Retinal Vessels

Showing 161 to 170 of 208 articles

Clear Filters

A novel retinal vessel detection approach based on multiple deep convolution neural networks.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Computer aided detection (CAD) offers an efficient way to assist doctors to interpret fundus images. In a CAD system, retinal vessel (RV) detection is a crucial step to identify the retinal disease regions. However, RV detec...

A Three-Stage Deep Learning Model for Accurate Retinal Vessel Segmentation.

IEEE journal of biomedical and health informatics
Automatic retinal vessel segmentation is a fundamental step in the diagnosis of eye-related diseases, in which both thick vessels and thin vessels are important features for symptom detection. All existing deep learning models attempt to segment both...

Synthesizing retinal and neuronal images with generative adversarial nets.

Medical image analysis
This paper aims at synthesizing multiple realistic-looking retinal (or neuronal) images from an unseen tubular structured annotation that contains the binary vessel (or neuronal) morphology. The generated phantoms are expected to preserve the same tu...

Retinal blood vessel segmentation using fully convolutional network with transfer learning.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Since the retinal blood vessel has been acknowledged as an indispensable element in both ophthalmological and cardiovascular disease diagnosis, the accurate segmentation of the retinal vessel tree has become the prerequisite step for automated or com...

Joint Segment-Level and Pixel-Wise Losses for Deep Learning Based Retinal Vessel Segmentation.

IEEE transactions on bio-medical engineering
OBJECTIVE: Deep learning based methods for retinal vessel segmentation are usually trained based on pixel-wise losses, which treat all vessel pixels with equal importance in pixel-to-pixel matching between a predicted probability map and the correspo...

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.