research
∙
08/18/2023
SAMedOCT: Adapting Segment Anything Model (SAM) for Retinal OCT
The Segment Anything Model (SAM) has gained significant attention in the...
share
research
∙
07/25/2023
Pretrained Deep 2.5D Models for Efficient Predictive Modeling from Retinal OCT
In the field of medical imaging, 3D deep learning models play a crucial ...
research
∙
07/13/2023
Transformer-based end-to-end classification of variable-length volumetric data
The automatic classification of 3D medical data is memory-intensive. Als...
research
∙
07/06/2023
Self-supervised learning via inter-modal reconstruction and feature projection networks for label-efficient 3D-to-2D segmentation
Deep learning has become a valuable tool for the automation of certain m...
research
∙
05/13/2023
PALM: Open Fundus Photograph Dataset with Pathologic Myopia Recognition and Anatomical Structure Annotation
Pathologic myopia (PM) is a common blinding retinal degeneration suffere...
research
∙
04/17/2023
Morph-SSL: Self-Supervision with Longitudinal Morphing to Predict AMD Progression from OCT
The lack of reliable biomarkers makes predicting the conversion from int...
research
∙
01/11/2023
Clustering disease trajectories in contrastive feature space for biomarker discovery in age-related macular degeneration
Age-related macular degeneration (AMD) is the leading cause of blindness...
research
∙
11/08/2022
Learning Spatio-Temporal Model of Disease Progression with NeuralODEs from Longitudinal Volumetric Data
Robust forecasting of the future anatomical changes inflicted by an ongo...
research
∙
10/26/2022
Segmentation of Bruch's Membrane in retinal OCT with AMD using anatomical priors and uncertainty quantification
Bruch's membrane (BM) segmentation on optical coherence tomography (OCT)...
research
∙
08/04/2022
Metadata-enhanced contrastive learning from retinal optical coherence tomography images
Supervised deep learning algorithms hold great potential to automate scr...
research
∙
07/01/2022
SD-LayerNet: Semi-supervised retinal layer segmentation in OCT using disentangled representation with anatomical priors
Optical coherence tomography (OCT) is a non-invasive 3D modality widely ...
research
∙
06/30/2022
TINC: Temporally Informed Non-Contrastive Learning for Disease Progression Modeling in Retinal OCT Volumes
Recent contrastive learning methods achieved state-of-the-art in low lab...
research
∙
02/25/2022
Deep Dirichlet uncertainty for unsupervised out-of-distribution detection of eye fundus photographs in glaucoma screening
The development of automatic tools for early glaucoma diagnosis with col...
research
∙
02/18/2022
REFUGE2 Challenge: Treasure for Multi-Domain Learning in Glaucoma Assessment
Glaucoma is the second leading cause of blindness and is the leading cau...
research
∙
02/16/2022
ADAM Challenge: Detecting Age-related Macular Degeneration from Fundus Images
Age-related macular degeneration (AMD) is the leading cause of visual im...
research
∙
02/14/2022
GAMMA Challenge:Glaucoma grAding from Multi-Modality imAges
Color fundus photography and Optical Coherence Tomography (OCT) are the ...
research
∙
08/02/2021
Projective Skip-Connections for Segmentation Along a Subset of Dimensions in Retinal OCT
In medical imaging, there are clinically relevant segmentation tasks whe...
research
∙
05/05/2020
AGE Challenge: Angle Closure Glaucoma Evaluation in Anterior Segment Optical Coherence Tomography
Angle closure glaucoma (ACG) is a more aggressive disease than open-angl...
research
∙
12/11/2019
U-Net with spatial pyramid pooling for drusen segmentation in optical coherence tomography
The presence of drusen is the main hallmark of early/intermediate age-re...
research
∙
10/21/2019
Modeling Disease Progression In Retinal OCTs With Longitudinal Self-Supervised Learning
Longitudinal imaging is capable of capturing the static anatomical struc...
research
∙
06/18/2019
Multiclass segmentation as multitask learning for drusen segmentation in retinal optical coherence tomography
Automated drusen segmentation in retinal optical coherence tomography (O...
research
∙
05/29/2019
Exploiting Epistemic Uncertainty of Anatomy Segmentation for Anomaly Detection in Retinal OCT
Diagnosis and treatment guidance are aided by detecting relevant biomark...
research
∙
01/24/2019
Using CycleGANs for effectively reducing image variability across OCT devices and improving retinal fluid segmentation
Optical coherence tomography (OCT) has become the most important imaging...
research
∙
01/23/2019
U2-Net: A Bayesian U-Net model with epistemic uncertainty feedback for photoreceptor layer segmentation in pathological OCT scans
In this paper, we introduce a Bayesian deep learning based model for seg...
research
∙
10/31/2018
Unsupervised Identification of Disease Marker Candidates in Retinal OCT Imaging Data
The identification and quantification of markers in medical images is cr...
research
∙
06/06/2018
Is the winner really the best? A critical analysis of common research practice in biomedical image analysis competitions
International challenges have become the standard for validation of biom...
research
∙
05/08/2018