research
∙
06/21/2023
A Reliable and Interpretable Framework of Multi-view Learning for Liver Fibrosis Staging
Staging of liver fibrosis is important in the diagnosis and treatment pl...
share
research
∙
03/03/2023
BayeSeg: Bayesian Modeling for Medical Image Segmentation with Interpretable Generalizability
Due to the cross-domain distribution shift aroused from diverse medical ...
research
∙
02/07/2023
Aligning Multi-Sequence CMR Towards Fully Automated Myocardial Pathology Segmentation
Myocardial pathology segmentation (MyoPS) is critical for the risk strat...
research
∙
01/15/2023
Unsupervised Cardiac Segmentation Utilizing Synthesized Images from Anatomical Labels
Cardiac segmentation is in great demand for clinical practice. Due to th...
research
∙
01/13/2023
Multi-Target Landmark Detection with Incomplete Images via Reinforcement Learning and Shape Prior
Medical images are generally acquired with limited field-of-view (FOV), ...
research
∙
01/12/2023
ZScribbleSeg: Zen and the Art of Scribble Supervised Medical Image Segmentation
Curating a large scale fully-annotated dataset can be both labour-intens...
research
∙
11/06/2022
MyoPS-Net: Myocardial Pathology Segmentation with Flexible Combination of Multi-Sequence CMR Images
Myocardial pathology segmentation (MyoPS) can be a prerequisite for the ...
research
∙
11/03/2022
𝒳-Metric: An N-Dimensional Information-Theoretic Framework for Groupwise Registration and Deep Combined Computing
This paper presents a generic probabilistic framework for estimating the...
research
∙
08/26/2022
Multi-Modality Cardiac Image Computing: A Survey
Multi-modality cardiac imaging plays a key role in the management of pat...
research
∙
06/18/2022
Deep Compatible Learning for Partially-Supervised Medical Image Segmentation
Partially-supervised learning can be challenging for segmentation due to...
research
∙
06/10/2022
Decoupling Predictions in Distributed Learning for Multi-Center Left Atrial MRI Segmentation
Distributed learning has shown great potential in medical image analysis...
research
∙
06/09/2022
Joint Modeling of Image and Label Statistics for Enhancing Model Generalizability of Medical Image Segmentation
Although supervised deep-learning has achieved promising performance in ...
research
∙
06/06/2022
Bayesian intrinsic groupwise registration via explicit hierarchical disentanglement
Previous methods on multimodal groupwise registration typically require ...
research
∙
06/05/2022
ShapePU: A New PU Learning Framework Regularized by Global Consistency for Scribble Supervised Cardiac Segmentation
Cardiac segmentation is an essential step for the diagnosis of cardiovas...
research
∙
03/31/2022
Bayesian Image Super-Resolution with Deep Modeling of Image Statistics
Modeling statistics of image priors is useful for image super-resolution...
research
∙
03/03/2022
CycleMix: A Holistic Strategy for Medical Image Segmentation from Scribble Supervision
Curating a large set of fully annotated training data can be costly, esp...
research
∙
01/14/2022
AWSnet: An Auto-weighted Supervision Attention Network for Myocardial Scar and Edema Segmentation in Multi-sequence Cardiac Magnetic Resonance Images
Multi-sequence cardiac magnetic resonance (CMR) provides essential patho...
research
∙
01/10/2022
MyoPS: A Benchmark of Myocardial Pathology Segmentation Combining Three-Sequence Cardiac Magnetic Resonance Images
Assessment of myocardial viability is essential in diagnosis and treatme...
research
∙
11/08/2021
Multi-Modality Cardiac Image Analysis with Deep Learning
Accurate cardiac computing, analysis and modeling from multi-modality im...
research
∙
09/05/2021
Right Ventricular Segmentation from Short- and Long-Axis MRIs via Information Transition
Right ventricular (RV) segmentation from magnetic resonance imaging (MRI...
research
∙
06/18/2021
Medical Image Analysis on Left Atrial LGE MRI for Atrial Fibrillation Studies: A Review
Late gadolinium enhancement magnetic resonance imaging (LGE MRI) is comm...
research
∙
06/16/2021
Unsupervised Domain Adaptation with Variational Approximation for Cardiac Segmentation
Unsupervised domain adaptation is useful in medical image segmentation. ...
research
∙
06/16/2021
AtrialGeneral: Domain Generalization for Left Atrial Segmentation of Multi-Center LGE MRIs
Left atrial (LA) segmentation from late gadolinium enhanced magnetic res...
research
∙
05/20/2021
A low-rank representation for unsupervised registration of medical images
Registration networks have shown great application potentials in medical...
research
∙
05/16/2021
Unsupervised MMRegNet based on Spatially Encoded Gradient Information
Multi-modality medical images can provide relevant and complementary ana...
research
∙
04/17/2021
VSpSR: Explorable Super-Resolution via Variational Sparse Representation
Super-resolution (SR) is an ill-posed problem, which means that infinite...
research
∙
12/16/2020
Learning-Based Algorithms for Vessel Tracking: A Review
Developing efficient vessel-tracking algorithms is crucial for imaging-b...
research
∙
11/25/2020
Rank-One Network: An Effective Framework for Image Restoration
The principal rank-one (RO) components of an image represent the self-si...
research
∙
11/17/2020
Anatomy Prior Based U-net for Pathology Segmentation with Attention
Pathological area segmentation in cardiac magnetic resonance (MR) images...
research
∙
11/17/2020
Recognition and standardization of cardiac MRI orientation via multi-tasking learning and deep neural networks
In this paper, we study the problem of imaging orientation in cardiac MR...
research
∙
10/29/2020
Brain Tumor Segmentation Network Using Attention-based Fusion and Spatial Relationship Constraint
Delineating the brain tumor from magnetic resonance (MR) images is criti...
research
∙
08/27/2020
Random Style Transfer based Domain Generalization Networks Integrating Shape and Spatial Information
Deep learning (DL)-based models have demonstrated good performance in me...
research
∙
08/15/2020
Cross-Modality Multi-Atlas Segmentation Using Deep Neural Networks
Both image registration and label fusion in the multi-atlas segmentation...
research
∙
08/11/2020
AtrialJSQnet: A New Framework for Joint Segmentation and Quantification of Left Atrium and Scars Incorporating Spatial and Shape Information
Left atrial (LA) and atrial scar segmentation from late gadolinium enhan...
research
∙
06/28/2020
MvMM-RegNet: A new image registration framework based on multivariate mixture model and neural network estimation
Current deep-learning-based registration algorithms often exploit intens...
research
∙
06/23/2020
Joint Left Atrial Segmentation and Scar Quantification Based on a DNN with Spatial Encoding and Shape Attention
We propose an end-to-end deep neural network (DNN) which can simultaneou...
research
∙
08/23/2019
Mutual information neural estimation in CNN-based end-to-end medical image registration
Image registration is one of the most underlined processes in medical im...
research
∙
06/18/2019
Cardiac Segmentation from LGE MRI Using Deep Neural Network Incorporating Shape and Spatial Priors
Cardiac segmentation from late gadolinium enhancement MRI is an importan...
research
∙
04/24/2019
Multi-scale deep neural networks for real image super-resolution
Single image super-resolution (SR) is extremely difficult if the upscali...
research
∙
02/26/2019
A Fully-Automatic Framework for Parkinson's Disease Diagnosis by Multi-Modality Images
Background: Parkinson's disease (PD) is a prevalent long-term neurodegen...
research
∙
02/26/2019
Diagnosis of Alzheimer's Disease via Multi-modality 3D Convolutional Neural Network
Alzheimer's Disease (AD) is one of the most concerned neurodegenerative ...
research
∙
02/21/2019
Evaluation of Algorithms for Multi-Modality Whole Heart Segmentation: An Open-Access Grand Challenge
Knowledge of whole heart anatomy is a prerequisite for many clinical app...
research
∙
02/21/2019
Atrial Scar Quantification via Multi-scale CNN in the Graph-cuts Framework
Late gadolinium enhancement magnetic resonance imaging (LGE MRI) appears...
research
∙
12/19/2018
PnP-AdaNet: Plug-and-Play Adversarial Domain Adaptation Network with a Benchmark at Cross-modality Cardiac Segmentation
Deep convolutional networks have demonstrated the state-of-the-art perfo...
research
∙
10/22/2018
Atrial scars segmentation via potential learning in the graph-cuts framework
Late Gadolinium Enhancement Magnetic Resonance Imaging (LGE MRI) emerged...
research
∙
10/22/2018
Atrial fibrosis quantification based on maximum likelihood estimator of multivariate images
We present a fully-automated segmentation and quantification of the left...
research
∙
05/26/2017
Fully Automatic Segmentation and Objective Assessment of Atrial Scars for Longstanding Persistent Atrial Fibrillation Patients Using Late Gadolinium-Enhanced MRI
Purpose: Atrial fibrillation (AF) is the most common cardiac arrhythmia ...
research
∙
12/28/2016
