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Found 7 papers, 0 papers with code
Weakly-supervised detection of AMD-related lesions in color fundus images using explainable deep learning
This is possible thanks to the use of a CNN with a custom setting that links the lesions and the diagnosis.
Improving AMD diagnosis by the simultaneous identification of associated retinal lesions
To overcome these issues, several works have proposed automatic methods for the detection of AMD in retinography images, the most widely used modality for the screening of the disease.
Multi-stage transfer learning for lung segmentation using portable X-ray devices for patients with COVID-19
This is the case during the current pandemic of COVID-19.
Automatic segmentation of the Foveal Avascular Zone in ophthalmological OCT-A images
Angiography by Optical Coherence Tomography is a non-invasive retinal imaging modality of recent appearance that allows the visualization of the vascular structure at predefined depths based on the detection of the blood movement.
Multimodal Registration of Retinal Images Using Domain-Specific Landmarks and Vessel Enhancement
The analysis of different image modalities is frequently performed in ophthalmology as it provides complementary information for the diagnosis and follow-up of relevant diseases, like hypertension or diabetes.
A Wavefront Marching Method for Solving the Eikonal Equation on Cartesian Grids
This paper presents a new wavefront propagation method for dealing with the classic Eikonal equation.
Unsupervised Trajectory Modelling using Temporal Information via Minimal Paths
This paper presents a novel methodology for modelling pedestrian trajectories over a scene, based in the hypothesis that, when people try to reach a destination, they use the path that takes less time, taking into account environmental information like the type of terrain or what other people did before.
