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09/21/2023
A Switch Architecture for Time-Triggered Transmission with Best-Effort Delivery
In Time-Triggered (TT) or time-sensitive networks, the transmission of a...
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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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07/15/2023
Neural Deformable Models for 3D Bi-Ventricular Heart Shape Reconstruction and Modeling from 2D Sparse Cardiac Magnetic Resonance Imaging
We propose a novel neural deformable model (NDM) targeting at the recons...
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06/06/2023
Prompt Space Optimizing Few-shot Reasoning Success with Large Language Models
Prompt engineering is an essential technique for enhancing the abilities...
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03/28/2023
Communication-Efficient Vertical Federated Learning with Limited Overlapping Samples
Federated learning is a popular collaborative learning approach that ena...
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03/22/2023
Data-Driven Leader-following Consensus for Nonlinear Multi-Agent Systems against Composite Attacks: A Twins Layer Approach
This paper studies the leader-following consensuses of uncertain and non...
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02/27/2023
Duration-aware pause insertion using pre-trained language model for multi-speaker text-to-speech
Pause insertion, also known as phrase break prediction and phrasing, is ...
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02/15/2023
Fast Blind Audio Copy-Move Detection and Localization Using Local Feature Tensors in Noise
The increasing availability of audio editing software altering digital a...
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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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09/13/2022
Warm Start Active Learning with Proxy Labels & Selection via Semi-Supervised Fine-Tuning
Which volume to annotate next is a challenging problem in building medic...
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07/23/2022
Low-Complexity Acoustic Echo Cancellation with Neural Kalman Filtering
The Kalman filter has been adopted in acoustic echo cancellation due to ...
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04/01/2022
UNetFormer: A Unified Vision Transformer Model and Pre-Training Framework for 3D Medical Image Segmentation
Vision Transformers (ViT)s have recently become popular due to their out...
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03/18/2022
Closing the Generalization Gap of Cross-silo Federated Medical Image Segmentation
Cross-silo federated learning (FL) has attracted much attention in medic...
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03/12/2022
Auto-FedRL: Federated Hyperparameter Optimization for Multi-institutional Medical Image Segmentation
Federated learning (FL) is a distributed machine learning technique that...
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01/04/2022
Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Images
Semantic segmentation of brain tumors is a fundamental medical image ana...
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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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11/29/2021
Self-Supervised Pre-Training of Swin Transformers for 3D Medical Image Analysis
Vision Transformers (ViT)s have shown great performance in self-supervis...
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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
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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08/19/2021
Multi-task Federated Learning for Heterogeneous Pancreas Segmentation
Federated learning (FL) for medical image segmentation becomes more chal...
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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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03/30/2021
Self-supervised Image-text Pre-training With Mixed Data In Chest X-rays
Pre-trained models, e.g., from ImageNet, have proven to be effective in ...
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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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03/19/2021
Biomedical Convergence Facilitated by the Emergence of Technological and Informatic Capabilities
We analyzed Medical Subject Headings (MeSH) from 21.6 million research a...
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03/18/2021
UNETR: Transformers for 3D Medical Image Segmentation
Fully Convolutional Neural Networks (FCNNs) with contracting and expansi...
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03/04/2021
DeepTag: An Unsupervised Deep Learning Method for Motion Tracking on Cardiac Tagging Magnetic Resonance Images
Cardiac tagging magnetic resonance imaging (t-MRI) is the gold standard ...
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02/07/2021
SR-Affine: High-quality 3D hand model reconstruction from UV Maps
Under various poses and heavy occlusions,3D hand model reconstruction ba...
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01/07/2021
Diminishing Uncertainty within the Training Pool: Active Learning for Medical Image Segmentation
Active learning is a unique abstraction of machine learning techniques w...
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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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09/28/2020
Automated Pancreas Segmentation Using Multi-institutional Collaborative Deep Learning
The performance of deep learning-based methods strongly relies on the nu...
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09/25/2020
Democratizing Artificial Intelligence in Healthcare: A Study of Model Development Across Two Institutions Incorporating Transfer Learning
The training of deep learning models typically requires extensive data, ...
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09/25/2020
Going to Extremes: Weakly Supervised Medical Image Segmentation
Medical image annotation is a major hurdle for developing precise and ro...
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09/22/2020
Learning Image Labels On-the-fly for Training Robust Classification Models
Current deep learning paradigms largely benefit from the tremendous amou...
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08/19/2020
Enhanced MRI Reconstruction Network using Neural Architecture Search
The accurate reconstruction of under-sampled magnetic resonance imaging ...
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08/18/2020
PC-U Net: Learning to Jointly Reconstruct and Segment the Cardiac Walls in 3D from CT Data
The 3D volumetric shape of the heart's left ventricle (LV) myocardium (M...
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07/22/2020
Time-aware Graph Embedding: A temporal smoothness and task-oriented approach
Knowledge graph embedding, which aims to learn the low-dimensional repre...
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06/28/2020
Uncertainty-aware multi-view co-training for semi-supervised medical image segmentation and domain adaptation
Although having achieved great success in medical image segmentation, de...
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06/10/2020
Searching Learning Strategy with Reinforcement Learning for 3D Medical Image Segmentation
Deep neural network (DNN) based approaches have been widely investigated...
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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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03/06/2020
Centrality Graph Convolutional Networks for Skeleton-based Action Recognition
The topological structure of skeleton data plays a significant role in h...
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01/24/2020
VerSe: A Vertebrae Labelling and Segmentation Benchmark
In this paper we report the challenge set-up and results of the Large Sc...
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12/20/2019
C2FNAS: Coarse-to-Fine Neural Architecture Search for 3D Medical Image Segmentation
3D convolution neural networks (CNN) have been proved very successful in...
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10/15/2019
End-to-End Adversarial Shape Learning for Abdomen Organ Deep Segmentation
Automatic segmentation of abdomen organs using medical imaging has many ...
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10/02/2019
