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07/31/2023
Disruptive Autoencoders: Leveraging Low-level features for 3D Medical Image Pre-training
Harnessing the power of pre-training on large-scale datasets like ImageN...
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03/10/2023
Deformable Cross-Attention Transformer for Medical Image Registration
Transformers have recently shown promise for medical image applications,...
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03/10/2023
Spatially-varying Regularization with Conditional Transformer for Unsupervised Image Registration
In the past, optimization-based registration models have used spatially-...
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11/04/2022
MONAI: An open-source framework for deep learning in healthcare
Artificial Intelligence (AI) is having a tremendous impact across most a...
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09/22/2022
Automated head and neck tumor segmentation from 3D PET/CT
Head and neck tumor segmentation challenge (HECKTOR) 2022 offers a platf...
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09/21/2022
Automated segmentation of intracranial hemorrhages from 3D CT
Intracranial hemorrhage segmentation challenge (INSTANCE 2022) offers a ...
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09/20/2022
Automated ischemic stroke lesion segmentation from 3D MRI
Ischemic Stroke Lesion Segmentation challenge (ISLES 2022) offers a plat...
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12/20/2021
HyperSegNAS: Bridging One-Shot Neural Architecture Search with 3D Medical Image Segmentation using HyperNet
Semantic segmentation of 3D medical images is a challenging task due to ...
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11/19/2021
TransMorph: Transformer for unsupervised medical image registration
In the last decade, convolutional neural networks (ConvNets) have domina...
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04/13/2021
ViT-V-Net: Vision Transformer for Unsupervised Volumetric Medical Image Registration
In the last decade, convolutional neural networks (ConvNets) have domina...
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03/29/2021
DiNTS: Differentiable Neural Network Topology Search for 3D Medical Image Segmentation
Recently, neural architecture search (NAS) has been applied to automatic...
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03/24/2021
Information-based Disentangled Representation Learning for Unsupervised MR Harmonization
Accuracy and consistency are two key factors in computer-assisted magnet...
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07/07/2020
Self domain adapted network
Domain shift is a major problem for deploying deep networks in clinical ...
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02/11/2020
Validating uncertainty in medical image translation
Medical images are increasingly used as input to deep neural networks to...
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02/11/2020
Finding novelty with uncertainty
Medical images are often used to detect and characterize pathology and d...
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03/14/2018
Topology guaranteed segmentation of the human retina from OCT using convolutional neural networks
Optical coherence tomography (OCT) is a noninvasive imaging modality whi...
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08/05/2015
