b'Dong Yang'

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 ...
03/30/2021 ∙ by Xiaosong Wang, et al. ∙ 0 ∙ share

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DiNTS: Differentiable Neural Network Topology Search for 3D Medical Image Segmentation

Recently, neural architecture search (NAS) has been applied to automatic...
03/29/2021 ∙ by Yufan He, et al. ∙ 0 ∙ share

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Biomedical Convergence Facilitated by the Emergence of Technological and Informatic Capabilities

We analyzed Medical Subject Headings (MeSH) from 21.6 million research a...
03/19/2021 ∙ by Dong Yang, et al. ∙ 0 ∙ share

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UNETR: Transformers for 3D Medical Image Segmentation

Fully Convolutional Neural Networks (FCNNs) with contracting and expansi...
03/18/2021 ∙ by Ali Hatamizadeh, et al. ∙ 0 ∙ share

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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 ...
03/04/2021 ∙ by Meng Ye, et al. ∙ 20 ∙ share

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SR-Affine: High-quality 3D hand model reconstruction from UV Maps

Under various poses and heavy occlusions,3D hand model reconstruction ba...
02/07/2021 ∙ by Ping Chen, et al. ∙ 3 ∙ share

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Diminishing Uncertainty within the Training Pool: Active Learning for Medical Image Segmentation

Active learning is a unique abstraction of machine learning techniques w...
01/07/2021 ∙ by Vishwesh Nath, et al. ∙ 25 ∙ share

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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...
11/23/2020 ∙ by Dong Yang, et al. ∙ 5 ∙ share

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Automated Pancreas Segmentation Using Multi-institutional Collaborative Deep Learning

The performance of deep learning-based methods strongly relies on the nu...
09/28/2020 ∙ by Pochuan Wang, et al. ∙ 71 ∙ share

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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, ...
09/25/2020 ∙ by Vikash Gupta1, et al. ∙ 7 ∙ share

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Going to Extremes: Weakly Supervised Medical Image Segmentation

Medical image annotation is a major hurdle for developing precise and ro...
09/25/2020 ∙ by Holger R. Roth, et al. ∙ 39 ∙ share

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Learning Image Labels On-the-fly for Training Robust Classification Models

Current deep learning paradigms largely benefit from the tremendous amou...
09/22/2020 ∙ by Xiaosong Wang, et al. ∙ 36 ∙ share

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Enhanced MRI Reconstruction Network using Neural Architecture Search

The accurate reconstruction of under-sampled magnetic resonance imaging ...
08/19/2020 ∙ by Qiaoying Huang, et al. ∙ 44 ∙ share

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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...
08/18/2020 ∙ by Meng Ye, et al. ∙ 16 ∙ share

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Time-aware Graph Embedding: A temporal smoothness and task-oriented approach

Knowledge graph embedding, which aims to learn the low-dimensional repre...
07/22/2020 ∙ by Yonghui Xu, et al. ∙ 1 ∙ share

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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...
06/28/2020 ∙ by Yingda Xia, et al. ∙ 3 ∙ share

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Searching Learning Strategy with Reinforcement Learning for 3D Medical Image Segmentation

Deep neural network (DNN) based approaches have been widely investigated...
06/10/2020 ∙ by Dong Yang, et al. ∙ 2 ∙ share

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Enhancing Foreground Boundaries for Medical Image Segmentation

Object segmentation plays an important role in the modern medical image ...
05/29/2020 ∙ by Dong Yang, et al. ∙ 9 ∙ share

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Centrality Graph Convolutional Networks for Skeleton-based Action Recognition

The topological structure of skeleton data plays a significant role in h...
03/06/2020 ∙ by Dong Yang, et al. ∙ 0 ∙ share

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VerSe: A Vertebrae Labelling and Segmentation Benchmark

In this paper we report the challenge set-up and results of the Large Sc...
01/24/2020 ∙ by Anjany Sekuboyina, et al. ∙ 0 ∙ share

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C2FNAS: Coarse-to-Fine Neural Architecture Search for 3D Medical Image Segmentation

3D convolution neural networks (CNN) have been proved very successful in...
12/20/2019 ∙ by Qihang Yu, et al. ∙ 46 ∙ share

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End-to-End Adversarial Shape Learning for Abdomen Organ Deep Segmentation

Automatic segmentation of abdomen organs using medical imaging has many ...
10/15/2019 ∙ by Jinzheng Cai, et al. ∙ 0 ∙ share

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Cardiac Segmentation of LGE MRI with Noisy Labels

In this work, we attempt the segmentation of cardiac structures in late ...
10/02/2019 ∙ by Holger Roth, et al. ∙ 0 ∙ share

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Weakly supervised segmentation from extreme points

Annotation of medical images has been a major bottleneck for the develop...
10/02/2019 ∙ by Holger Roth, et al. ∙ 0 ∙ share

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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 ...
07/08/2019 ∙ by Ziyue Xu, et al. ∙ 0 ∙ share

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4D CNN for semantic segmentation of cardiac volumetric sequences

We propose a 4D convolutional neural network (CNN) for the segmentation ...
06/17/2019 ∙ by Andriy Myronenko, et al. ∙ 0 ∙ share

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When Unseen Domain Generalization is Unnecessary? Rethinking Data Augmentation

Recent advances in deep learning for medical image segmentation demonstr...
06/07/2019 ∙ by Ling Zhang, et al. ∙ 0 ∙ share

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V-NAS: Neural Architecture Search for Volumetric Medical Image Segmentation

Deep learning algorithms, in particular 2D and 3D fully convolutional ne...
06/06/2019 ∙ by Zhuotun Zhu, et al. ∙ 1 ∙ share

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An Alarm System For Segmentation Algorithm Based On Shape Model

It is usually hard for a learning system to predict correctly on rare ev...
03/26/2019 ∙ by Fengze Liu, et al. ∙ 0 ∙ share

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3D Semi-Supervised Learning with Uncertainty-Aware Multi-View Co-Training

We propose a novel framework, uncertainty-aware multi-view co-training (...
11/29/2018 ∙ by Yingda Xia, et al. ∙ 0 ∙ share

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MRI Reconstruction via Cascaded Channel-wise Attention Network

We consider an MRI reconstruction problem with input of k-space data at ...
10/18/2018 ∙ by Qiaoying Huang, et al. ∙ 0 ∙ share

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Important Attribute Identification in Knowledge Graph

The knowledge graph(KG) composed of entities with their descriptions and...
10/12/2018 ∙ by Shengjie Sun, et al. ∙ 0 ∙ share

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Saliency deep embedding for aurora image search

Deep neural networks have achieved remarkable success in the field of im...
05/23/2018 ∙ by Xi Yang, et al. ∙ 0 ∙ share

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Automatic Liver Segmentation Using an Adversarial Image-to-Image Network

Automatic liver segmentation in 3D medical images is essential in many c...
07/25/2017 ∙ by Dong Yang, et al. ∙ 0 ∙ share

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Automatic Vertebra Labeling in Large-Scale 3D CT using Deep Image-to-Image Network with Message Passing and Sparsity Regularization

Automatic localization and labeling of vertebra in 3D medical images pla...
05/17/2017 ∙ by Dong Yang, et al. ∙ 0 ∙ share

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Collaborative Discriminant Locality Preserving Projections With its Application to Face Recognition

We present a novel Discriminant Locality Preserving Projections (DLPP) a...
12/28/2013 ∙ by Sheng Huang, et al. ∙ 0 ∙ share

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Dong Yang

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