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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 ...
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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...
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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...
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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...
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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...
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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...
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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)...
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08/08/2022
Data-centric AI approach to improve optic nerve head segmentation and localization in OCT en face images
The automatic detection and localization of anatomical features in retin...
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08/04/2022
Metadata-enhanced contrastive learning from retinal optical coherence tomography images
Supervised deep learning algorithms hold great potential to automate scr...
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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 ...
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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...
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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...
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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...
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10/21/2019
Modeling Disease Progression In Retinal OCTs With Longitudinal Self-Supervised Learning
Longitudinal imaging is capable of capturing the static anatomical struc...
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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...
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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...
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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...
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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...
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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...
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05/08/2018
Fully Automated Segmentation of Hyperreflective Foci in Optical Coherence Tomography Images
The automatic detection of disease related entities in retinal imaging d...
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03/17/2017
Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery
Obtaining models that capture imaging markers relevant for disease progr...
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12/02/2016