Clinical & experimental ophthalmology
Nov 11, 2019
BACKGROUND: To define a new quantitative grading criterion for retinal haemorrhages in term newborns based on the segmentation results of a deep convolutional neural network.
The difficulty of obtaining annotations to build training databases still slows down the adoption of recent deep learning approaches for biomedical image analysis. In this paper, we show that we can train a Deep Net to perform 3D volumetric delineati...
Recent studies have shown that convolutional neural networks (CNNs) can be more accurate, efficient and even deeper on their training if they include direct connections from the layers close to the input to those close to the output in order to trans...
Morphology reconstruction of tree-like structures in volumetric images, such as neurons, retinal blood vessels, and bronchi, is of fundamental interest for biomedical research. 3D branch points play an important role in many reconstruction applicatio...
BACKGROUND: The purpose of this study was to develop an automated diagnosis and quantitative analysis system for plus disease. The system provides a diagnostic decision but also performs quantitative analysis of the typical pathological features of t...
Computer methods and programs in biomedicine
Sep 27, 2019
BACKGROUND AND OBJECTIVES: The retinal fundus contains intricate vascular trees, some of which are mutually intersected and overlapped. The intersection and overlapping of retinal vessels represent vascular junctions (i.e. bifurcation and crossover) ...
IEEE transactions on neural networks and learning systems
Sep 13, 2019
Biomedical image segmentation is lately dominated by deep neural networks (DNNs) due to their surpassing expert-level performance. However, the existing DNN models for biomedical image segmentation are generally highly parameterized, which severely i...
We propose a novel deep learning based system for vessel segmentation. Existing methods using CNNs have mostly relied on local appearances learned on the regular image grid, without consideration of the graphical structure of vessel shape. Effective ...
Retinal oximetry is a non-invasive technique to investigate the hemodynamics, vasculature and health of the eye. Current techniques for retinal oximetry have been plagued by quantitatively inconsistent measurements and this has greatly limited their ...
OBJECTIVE: A novel supervised method that is based on the Multi-Proportion Channel Ensemble Model (MPC-EM) is proposed to obtain more vessel details with reduced computational complexity.