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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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10/24/2022
NVIDIA FLARE: Federated Learning from Simulation to Real-World
Federated learning (FL) enables the building of robust and generalizable...
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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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08/22/2022
Split-U-Net: Preventing Data Leakage in Split Learning for Collaborative Multi-Modal Brain Tumor Segmentation
Split learning (SL) has been proposed to train deep learning models in a...
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02/14/2022
Do Gradient Inversion Attacks Make Federated Learning Unsafe?
Federated learning (FL) allows the collaborative training of AI models w...
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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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11/15/2021
T-AutoML: Automated Machine Learning for Lesion Segmentation using Transformers in 3D Medical Imaging
Lesion segmentation in medical imaging has been an important topic in cl...
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11/01/2021
Redundancy Reduction in Semantic Segmentation of 3D Brain Tumor MRIs
Another year of the multimodal brain tumor segmentation challenge (BraTS...
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11/01/2021
Accounting for Dependencies in Deep Learning Based Multiple Instance Learning for Whole Slide Imaging
Multiple instance learning (MIL) is a key algorithm for classification o...
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07/16/2021
Federated Whole Prostate Segmentation in MRI with Personalized Neural Architectures
Building robust deep learning-based models requires diverse training dat...
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07/12/2021
The Power of Proxy Data and Proxy Networks for Hyper-Parameter Optimization in Medical Image Segmentation
Deep learning models for medical image segmentation are primarily data-d...
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04/20/2021
Auto-FedAvg: Learnable Federated Averaging for Multi-Institutional Medical Image Segmentation
Federated learning (FL) enables collaborative model training while prese...
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11/23/2020
Federated Semi-Supervised Learning for COVID Region Segmentation in Chest CT using Multi-National Data from China, Italy, Japan
The recent outbreak of COVID-19 has led to urgent needs for reliable dia...
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05/29/2020
Enhancing Foreground Boundaries for Medical Image Segmentation
Object segmentation plays an important role in the modern medical image ...
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02/11/2020
Edge-Gated CNNs for Volumetric Semantic Segmentation of Medical Images
Textures and edges contribute different information to image recognition...
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01/06/2020
Robust Semantic Segmentation of Brain Tumor Regions from 3D MRIs
Multimodal brain tumor segmentation challenge (BraTS) brings together re...
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10/04/2019
NeurReg: Neural Registration and Its Application to Image Segmentation
Registration is a fundamental task in medical image analysis which can b...
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09/14/2019
3D Kidneys and Kidney Tumor Semantic Segmentation using Boundary-Aware Networks
Automated segmentation of kidneys and kidney tumors is an important step...
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08/21/2019
Boundary Aware Networks for Medical Image Segmentation
Fully convolutional neural networks (CNNs) have proven to be effective a...
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06/17/2019
4D CNN for semantic segmentation of cardiac volumetric sequences
We propose a 4D convolutional neural network (CNN) for the segmentation ...
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06/07/2019
When Unseen Domain Generalization is Unnecessary? Rethinking Data Augmentation
Recent advances in deep learning for medical image segmentation demonstr...
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11/05/2018
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge
Gliomas are the most common primary brain malignancies, with different d...
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10/27/2018
3D MRI brain tumor segmentation using autoencoder regularization
Automated segmentation of brain tumors from 3D magnetic resonance images...
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06/17/2009
Adaptive Regularization of Ill-Posed Problems: Application to Non-rigid Image Registration
We introduce an adaptive regularization approach. In contrast to convent...
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05/15/2009
Point-Set Registration: Coherent Point Drift
Point set registration is a key component in many computer vision tasks....
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04/09/2009