185 citations · 379 across the 14 of their papers we have counts for
14 papers
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…
DeepTag: An Unsupervised Deep Learning Method for Motion Tracking on Cardiac Tagging Magnetic Resonance Images
Meng Ye, Mikael Kanski, Dong Yang +5
Cardiac tagging magnetic resonance imaging (t-MRI) is the gold standard for regional myocardium deformation and cardiac strain estimation. However, this technique has not been wide…
CAFE: Coarse-to-Fine Neural Symbolic Reasoning for Explainable Recommendation
Yikun Xian, Zuohui Fu, Handong Zhao +8
Recent research explores incorporating knowledge graphs (KG) into e-commerce recommender systems, not only to achieve better recommendation performance, but more importantly to gen…
Oriented Object Detection in Aerial Images with Box Boundary-Aware Vectors
Jingru Yi, Pengxiang Wu, Bo Liu +3
Oriented object detection in aerial images is a challenging task as the objects in aerial images are displayed in arbitrary directions and are usually densely packed. Current orien…
Measure Anatomical Thickness from Cardiac MRI with Deep Neural Networks
Qiaoying Huang, Eric Z. Chen, Hanchao Yu +4
Accurate estimation of shape thickness from medical images is crucial in clinical applications. For example, the thickness of myocardium is one of the key to cardiac disease diagno…
Enhanced MRI Reconstruction Network using Neural Architecture Search
Qiaoying Huang, Dong Yang, Yikun Xian +4
The accurate reconstruction of under-sampled magnetic resonance imaging (MRI) data using modern deep learning technology, requires significant effort to design the necessary comple…
PC-U Net: Learning to Jointly Reconstruct and Segment the Cardiac Walls in 3D from CT Data
Meng Ye, Qiaoying Huang, Dong Yang +4
The 3D volumetric shape of the heart's left ventricle (LV) myocardium (MYO) wall provides important information for diagnosis of cardiac disease and invasive procedure navigation.…
Neural-Symbolic Reasoning over Knowledge Graph for Multi-stage Explainable Recommendation
Yikun Xian, Zuohui Fu, Qiaoying Huang +2
Recent work on recommender systems has considered external knowledge graphs as valuable sources of information, not only to produce better recommendations but also to provide expla…
Weakly Supervised Deep Nuclei Segmentation Using Partial Points Annotation in Histopathology Images
Hui Qu, Pengxiang Wu, Qiaoying Huang +7
Nuclei segmentation is a fundamental task in histopathology image analysis. Typically, such segmentation tasks require significant effort to manually generate accurate pixel-wise a…
Fairness-Aware Explainable Recommendation over Knowledge Graphs
Zuohui Fu, Yikun Xian, Ruoyuan Gao +8
There has been growing attention on fairness considerations recently, especially in the context of intelligent decision making systems. Explainable recommendation systems, in parti…
Vertebra-Focused Landmark Detection for Scoliosis Assessment
Jingru Yi, Pengxiang Wu, Qiaoying Huang +2
Adolescent idiopathic scoliosis (AIS) is a lifetime disease that arises in children. Accurate estimation of Cobb angles of the scoliosis is essential for clinicians to make diagnos…
Multi-scale Cell Instance Segmentation with Keypoint Graph based Bounding Boxes
Jingru Yi, Pengxiang Wu, Qiaoying Huang +4
Most existing methods handle cell instance segmentation problems directly without relying on additional detection boxes. These methods generally fails to separate touching cells du…
Brain Segmentation from k-space with End-to-end Recurrent Attention Network
Qiaoying Huang, Xiao Chen, Dimitris Metaxas +1
The task of medical image segmentation commonly involves an image reconstruction step to convert acquired raw data to images before any analysis. However, noises, artifacts and los…
MRI Reconstruction via Cascaded Channel-wise Attention Network
Qiaoying Huang, Dong Yang, Pengxiang Wu +3
We consider an MRI reconstruction problem with input of k-space data at a very low undersampled rate. This can practically benefit patient due to reduced time of MRI scan, but it i…