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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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03/22/2022
GradViT: Gradient Inversion of Vision Transformers
In this work we demonstrate the vulnerability of vision transformers (Vi...
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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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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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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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11/01/2021
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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07/12/2021
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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03/29/2021
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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03/18/2021
UNETR: Transformers for 3D Medical Image Segmentation
Fully Convolutional Neural Networks (FCNNs) with contracting and expansi...
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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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09/22/2020
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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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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06/22/2020
LAMP: Large Deep Nets with Automated Model Parallelism for Image Segmentation
Deep Learning (DL) models are becoming larger, because the increase in m...
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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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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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10/04/2019
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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10/02/2019
Cardiac Segmentation of LGE MRI with Noisy Labels
In this work, we attempt the segmentation of cardiac structures in late ...
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10/02/2019
Weakly supervised segmentation from extreme points
Annotation of medical images has been a major bottleneck for the develop...
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07/08/2019
Correlation via synthesis: end-to-end nodule image generation and radiogenomic map learning based on generative adversarial network
Radiogenomic map linking image features and gene expression profiles is ...
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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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03/19/2019
Interactive segmentation of medical images through fully convolutional neural networks
Image segmentation plays an essential role in medicine for both diagnost...
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11/29/2018
3D Semi-Supervised Learning with Uncertainty-Aware Multi-View Co-Training
We propose a novel framework, uncertainty-aware multi-view co-training (...
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11/17/2017
Towards dense volumetric pancreas segmentation in CT using 3D fully convolutional networks
Pancreas segmentation in computed tomography imaging has been historical...
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10/15/2017
Towards Automatic Abdominal Multi-Organ Segmentation in Dual Energy CT using Cascaded 3D Fully Convolutional Network
Automatic multi-organ segmentation of the dual energy computed tomograph...
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08/14/2014