540 citations · 1.2k across the 38 of their papers we have counts for
38 papers
Diffeomorphic Image Registration with Neural Velocity Field
Kun Han, Shanlin sun, Xiangyi Yan +6
Diffeomorphic image registration, offering smooth transformation and topology preservation, is required in many medical image analysis tasks.Traditional methods impose certain mode…
Test-Time Training for Deformable Multi-Scale Image Registration
Wentao Zhu, Yufang Huang, Daguang Xu +3
Registration is a fundamental task in medical robotics and is often a crucial step for many downstream tasks such as motion analysis, intra-operative tracking and image segmentatio…
Spatial Context-Aware Self-Attention Model For Multi-Organ Segmentation
Hao Tang, Xingwei Liu, Kun Han +6
Multi-organ segmentation is one of most successful applications of deep learning in medical image analysis. Deep convolutional neural nets (CNNs) have shown great promise in achiev…
MVHM: A Large-Scale Multi-View Hand Mesh Benchmark for Accurate 3D Hand Pose Estimation
Liangjian Chen, Shih-Yao Lin, Yusheng Xie +2
Estimating 3D hand poses from a single RGB image is challenging because depth ambiguity leads the problem ill-posed. Training hand pose estimators with 3D hand mesh annotations and…
Temporal-Aware Self-Supervised Learning for 3D Hand Pose and Mesh Estimation in Videos
Liangjian Chen, Shih-Yao Lin, Yusheng Xie +2
Estimating 3D hand pose directly from RGB imagesis challenging but has gained steady progress recently bytraining deep models with annotated 3D poses. Howeverannotating 3D poses is…
DGGAN: Depth-image Guided Generative Adversarial Networks for Disentangling RGB and Depth Images in 3D Hand Pose Estimation
Liangjian Chen, Shih-Yao Lin, Yusheng Xie +3
Estimating3D hand poses from RGB images is essentialto a wide range of potential applications, but is challengingowing to substantial ambiguity in the inference of depth in-formati…
SIA-GCN: A Spatial Information Aware Graph Neural Network with 2D Convolutions for Hand Pose Estimation
Deying Kong, Haoyu Ma, Xiaohui Xie
Graph Neural Networks (GNNs) generalize neural networks from applications on regular structures to applications on arbitrary graphs, and have shown success in many application doma…
Rotation-invariant Mixed Graphical Model Network for 2D Hand Pose Estimation
Deying Kong, Haoyu Ma, Yifei Chen +1
In this paper, we propose a new architecture named Rotation-invariant Mixed Graphical Model Network (R-MGMN) to solve the problem of 2D hand pose estimation from a monocular RGB im…
Nonparametric Structure Regularization Machine for 2D Hand Pose Estimation
Yifei Chen, Haoyu Ma, Deying Kong +4
Hand pose estimation is more challenging than body pose estimation due to severe articulation, self-occlusion and high dexterity of the hand. Current approaches often rely on a pop…
AttentionAnatomy: A unified framework for whole-body organs at risk segmentation using multiple partially annotated datasets
Shanlin Sun, Yang Liu, Narisu Bai +5
Organs-at-risk (OAR) delineation in computed tomography (CT) is an important step in Radiation Therapy (RT) planning. Recently, deep learning based methods for OAR delineation have…
Network2Vec Learning Node Representation Based on Space Mapping in Networks
Huang Zhenhua, Wang Zhenyu, Zhang Rui +3
Complex networks represented as node adjacency matrices constrains the application of machine learning and parallel algorithms. To address this limitation, network embedding (i.e.,…
A Combined Deep Learning-Gradient Boosting Machine Framework for Fluid Intelligence Prediction
Yeeleng S. Vang, Yingxin Cao, Xiaohui Xie
The ABCD Neurocognitive Prediction Challenge is a community driven competition asking competitors to develop algorithms to predict fluid intelligence score from T1-w MRIs. In this…
Adaptive Graphical Model Network for 2D Handpose Estimation
Deying Kong, Yifei Chen, Haoyu Ma +2
In this paper, we propose a new architecture called Adaptive Graphical Model Network (AGMN) to tackle the task of 2D hand pose estimation from a monocular RGB image. The AGMN consi…
NoduleNet: Decoupled False Positive Reductionfor Pulmonary Nodule Detection and Segmentation
Hao Tang, Chupeng Zhang, Xiaohui Xie
Pulmonary nodule detection, false positive reduction and segmentation represent three of the most common tasks in the computeraided analysis of chest CT images. Methods have been p…
Neural Multi-Scale Self-Supervised Registration for Echocardiogram Dense Tracking
Wentao Zhu, Yufang Huang, Mani A Vannan +5
Echocardiography has become routinely used in the diagnosis of cardiomyopathy and abnormal cardiac blood flow. However, manually measuring myocardial motion and cardiac blood flow…
Automatic Pulmonary Lobe Segmentation Using Deep Learning
Hao Tang, Chupeng Zhang, Xiaohui Xie
Pulmonary lobe segmentation is an important task for pulmonary disease related Computer Aided Diagnosis systems (CADs). Classical methods for lobe segmentation rely on successful d…
An End-to-end Framework For Integrated Pulmonary Nodule Detection and False Positive Reduction
Hao Tang, Xingwei Liu, Xiaohui Xie
Pulmonary nodule detection using low-dose Computed Tomography (CT) is often the first step in lung disease screening and diagnosis. Recently, algorithms based on deep convolutional…
Automated pulmonary nodule detection using 3D deep convolutional neural networks
Hao Tang, Daniel R. Kim, Xiaohui Xie
Early detection of pulmonary nodules in computed tomography (CT) images is essential for successful outcomes among lung cancer patients. Much attention has been given to deep convo…
Parallel Clustering of Single Cell Transcriptomic Data with Split-Merge Sampling on Dirichlet Process Mixtures
Tiehang Duan, José P. Pinto, Xiaohui Xie
Motivation: With the development of droplet based systems, massive single cell transcriptome data has become available, which enables analysis of cellular and molecular processes a…
Sequential Embedding Induced Text Clustering, a Non-parametric Bayesian Approach
Tiehang Duan, Qi Lou, Sargur N. Srihari +1
Current state-of-the-art nonparametric Bayesian text clustering methods model documents through multinomial distribution on bags of words. Although these methods can effectively ut…
Generating Realistic Training Images Based on Tonality-Alignment Generative Adversarial Networks for Hand Pose Estimation
Liangjian Chen, Shih-Yao Lin, Yusheng Xie +5
Hand pose estimation from a monocular RGB image is an important but challenging task. The main factor affecting its performance is the lack of a sufficiently large training dataset…
AnatomyNet: Deep Learning for Fast and Fully Automated Whole-volume Segmentation of Head and Neck Anatomy
Wentao Zhu, Yufang Huang, Liang Zeng +6
Methods: Our deep learning model, called AnatomyNet, segments OARs from head and neck CT images in an end-to-end fashion, receiving whole-volume HaN CT images as input and generati…
DeepEM: Deep 3D ConvNets With EM For Weakly Supervised Pulmonary Nodule Detection
Wentao Zhu, Yeeleng S. Vang, Yufang Huang +1
Recently deep learning has been witnessing widespread adoption in various medical image applications. However, training complex deep neural nets requires large-scale datasets label…
Deep Learning Framework for Multi-class Breast Cancer Histology Image Classification
Yeeleng S. Vang, Zhen Chen, Xiaohui Xie
In this work, we present a deep learning framework for multi-class breast cancer image classification as our submission to the International Conference on Image Analysis and Recogn…