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Found 19 papers, 11 papers with code
MV-Swin-T: Mammogram Classification with Multi-view Swin Transformer
Traditional deep learning approaches for breast cancer classification has predominantly concentrated on single-view analysis.
Revolutionizing Space Health (Swin-FSR): Advancing Super-Resolution of Fundus Images for SANS Visual Assessment Technology
However, due to the unavailability of experts in these locations, the data has to be transferred to an urban healthcare facility (AMD and glaucoma) or a terrestrial station (e. g, SANS) for more precise disease identification.
SwinVFTR: A Novel Volumetric Feature-learning Transformer for 3D OCT Fluid Segmentation
To address these issues, we propose SwinVFTR, a new transformer-based architecture designed for precise fluid segmentation in 3D volumetric OCT images.
SWIN-SFTNet : Spatial Feature Expansion and Aggregation using Swin Transformer For Whole Breast micro-mass segmentation
We also incorporate a novel embedding loss that calculates similarities between linear feature embeddings of the encoder and decoder blocks.
ConnectedUNets++: Mass Segmentation from Whole Mammographic Images
Deep learning has made a breakthrough in medical image segmentation in recent years due to its ability to extract high-level features without the need for prior knowledge.
Virtual-Reality based Vestibular Ocular Motor Screening for Concussion Detection using Machine-Learning
Therefore, for the assessment and management of concussion detection, standardization is required to lower the risk of injury and increase the validation among clinicians.
VR-SFT: Reproducing Swinging Flashlight Test in Virtual Reality to Detect Relative Afferent Pupillary Defect
The relative afferent asymmetry between two eyes can be diagnosed using swinging flashlight test, also known as the alternating light test.
Analysis of Smooth Pursuit Assessment in Virtual Reality and Concussion Detection using BiLSTM
The sport-related concussion (SRC) battery relies heavily upon subjective symptom reporting in order to determine the diagnosis of a concussion.
Feature Representation Learning for Robust Retinal Disease Detection from Optical Coherence Tomography Images
Ophthalmic images may contain identical-looking pathologies that can cause failure in automated techniques to distinguish different retinal degenerative diseases.
ECG-ATK-GAN: Robustness against Adversarial Attacks on ECGs using Conditional Generative Adversarial Networks
The experiment confirms that our model is more robust against such adversarial attacks for classifying arrhythmia with high accuracy.
ECG-Adv-GAN: Detecting ECG Adversarial Examples with Conditional Generative Adversarial Networks
Moreover, the model is conditioned on class-specific ECG signals to synthesize realistic adversarial examples.
VTGAN: Semi-supervised Retinal Image Synthesis and Disease Prediction using Vision Transformers
The only non-invasive method for capturing retinal vasculature is optical coherence tomography-angiography (OCTA).
RV-GAN: Segmenting Retinal Vascular Structure in Fundus Photographs using a Novel Multi-scale Generative Adversarial Network
In order to avoid the loss of fidelity suffered by traditional GAN-based segmentation systems, we introduce a novel weighted feature matching loss.
Ranked #2 on
Retinal Vessel Segmentation
on STARE
Generative Adversarial Network
Retinal Vessel Segmentation
+2
Attention2AngioGAN: Synthesizing Fluorescein Angiography from Retinal Fundus Images using Generative Adversarial Networks
Fluorescein Angiography (FA) is a technique that employs the designated camera for Fundus photography incorporating excitation and barrier filters.
Improving Robustness using Joint Attention Network For Detecting Retinal Degeneration From Optical Coherence Tomography Images
Noisy data and the similarity in the ocular appearances caused by different ophthalmic pathologies pose significant challenges for an automated expert system to accurately detect retinal diseases.
Ranked #1 on
Retinal OCT Disease Classification
on Srinivasan2014
Fundus2Angio: A Conditional GAN Architecture for Generating Fluorescein Angiography Images from Retinal Fundus Photography
Angiography requires insertion of a dye that may cause severe adverse effects and can even be fatal.
Fundus to Angiography Generation
Generative Adversarial Network
A Parametric Perceptual Deficit Modeling and Diagnostics Framework for Retina Damage using Mixed Reality
Age-related Macular Degeneration (AMD) is a progressive visual impairment affecting millions of individuals.
Optic-Net: A Novel Convolutional Neural Network for Diagnosis of Retinal Diseases from Optical Tomography Images
Diagnosing different retinal diseases from Spectral Domain Optical Coherence Tomography (SD-OCT) images is a challenging task.
Ranked #1 on
Retinal OCT Disease Classification
on Srinivasan2014
An Automatic Digital Terrain Generation Technique for Terrestrial Sensing and Virtual Reality Applications
The identification and modeling of the terrain from point cloud data is an important component of Terrestrial Remote Sensing (TRS) applications.
