540 citations · 701 across the 18 of their papers we have counts for
19 papers
MEGAN: Memory Enhanced Graph Attention Network for Space-Time Video Super-Resolution
Chenyu You, Lianyi Han, Aosong Feng +3
Space-time video super-resolution (STVSR) aims to construct a high space-time resolution video sequence from the corresponding low-frame-rate, low-resolution video sequence. Inspir…
Object-Guided Instance Segmentation With Auxiliary Feature Refinement for Biological Images
Jingru Yi, Pengxiang Wu, Hui Tang +7
Instance segmentation is of great importance for many biological applications, such as study of neural cell interactions, plant phenotyping, and quantitatively measuring how cells…
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…
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…
MM-Hand: 3D-Aware Multi-Modal Guided Hand Generative Network for 3D Hand Pose Synthesis
Zhenyu Wu, Duc Hoang, Shih-Yao Lin +5
Estimating the 3D hand pose from a monocular RGB image is important but challenging. A solution is training on large-scale RGB hand images with accurate 3D hand keypoint annotation…
Bipartite Distance for Shape-Aware Landmark Detection in Spinal X-Ray Images
Abdullah-Al-Zubaer Imran, Chao Huang, Hui Tang +5
Scoliosis is a congenital disease that causes lateral curvature in the spine. Its assessment relies on the identification and localization of vertebrae in spinal X-ray images, conv…
Partly Supervised Multitask Learning
Abdullah-Al-Zubaer Imran, Chao Huang, Hui Tang +5
Semi-supervised learning has recently been attracting attention as an alternative to fully supervised models that require large pools of labeled data. Moreover, optimizing a model…
Analysis of Scoliosis From Spinal X-Ray Images
Abdullah-Al-Zubaer Imran, Chao Huang, Hui Tang +5
Scoliosis is a congenital disease in which the spine is deformed from its normal shape. Measurement of scoliosis requires labeling and identification of vertebrae in the spine. Spi…
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…
Shape-Aware Organ Segmentation by Predicting Signed Distance Maps
Yuan Xue, Hui Tang, Zhi Qiao +6
In this work, we propose to resolve the issue existing in current deep learning based organ segmentation systems that they often produce results that do not capture the overall sha…
Object-Guided Instance Segmentation for Biological Images
Jingru Yi, Hui Tang, Pengxiang Wu +5
Instance segmentation of biological images is essential for studying object behaviors and properties. The challenges, such as clustering, occlusion, and adhesion problems of the ob…
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…
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…
DeepLung: Deep 3D Dual Path Nets for Automated Pulmonary Nodule Detection and Classification
Wentao Zhu, Chaochun Liu, Wei Fan +1
In this work, we present a fully automated lung computed tomography (CT) cancer diagnosis system, DeepLung. DeepLung consists of two components, nodule detection (identifying the l…
DeepLung: 3D Deep Convolutional Nets for Automated Pulmonary Nodule Detection and Classification
Wentao Zhu, Chaochun Liu, Wei Fan +1
In this work, we present a fully automated lung CT cancer diagnosis system, DeepLung. DeepLung contains two parts, nodule detection and classification. Considering the 3D nature of…
Lesion detection and Grading of Diabetic Retinopathy via Two-stages Deep Convolutional Neural Networks
Yehui Yang, Tao Li, Wensi Li +3
We propose an automatic diabetic retinopathy (DR) analysis algorithm based on two-stages deep convolutional neural networks (DCNN). Compared to existing DCNN-based DR detection met…
Variational hybridization and transformation for large inaccurate noisy-or networks
Yusheng Xie, Nan Du, Wei Fan +2
Variational inference provides approximations to the computationally intractable posterior distribution in Bayesian networks. A prominent medical application of noisy-or Bayesian n…
Large-Scale Multi-Label Learning with Incomplete Label Assignments
Xiangnan Kong, Zhaoming Wu, Li-Jia Li +4
Multi-label learning deals with the classification problems where each instance can be assigned with multiple labels simultaneously. Conventional multi-label learning approaches ma…