3 citations · 9 across the 16 of their papers we have counts for
16 papers
MVMGNN;Multi-View Masked Graph Neural Network for Alzheimer's Disease Diagnosis using Structural MRI
Ni Yao, Zhenxu Wang, Danyang Sun +6
Alzheimer's disease (AD) is a common neurodegenerative disorder, and early diagnosis is of great significance for delaying disease progression and enabling timely intervention. Mil…
Point Cloud Registration for Fusion between SPECT MPI and CTA Images
Ni Yao, Xiangyu Liu, Shaojie Tang +9
Clinical fusion of Single Photon Emission Computed Tomography Myocardial Perfusion Imaging (SPECT MPI) and Computed Tomography Angiography (CTA) remains limited by cross-modality m…
UG-FedDA: Uncertainty-Guided Federated Domain Adaptation for Multi-Center Alzheimer's Disease Detection
Fubao Zhu, Zhanyuan Jia, Zhiguo Wang +7
Alzheimer's disease (AD) is an irreversible neurodegenerative disorder, and early diagnosis is critical for timely intervention. However, most existing classification frameworks fa…
UPMAD-Net: A Brain Tumor Segmentation Network with Uncertainty Guidance and Adaptive Multimodal Feature Fusion
Zhanyuan Jia, Ni Yao, Danyang Sun +6
Background: Brain tumor segmentation has a significant impact on the diagnosis and treatment of brain tumors. Accurate brain tumor segmentation remains challenging due to their irr…
Myocardial Region-guided Feature Aggregation Net for Automatic Coronary artery Segmentation and Stenosis Assessment using Coronary Computed Tomography Angiography
Ni Yao, Xiangyu Liu, Danyang Sun +7
Coronary artery disease (CAD) remains a leading cause of mortality worldwide, requiring accurate segmentation and stenosis detection using Coronary Computed Tomography angiography…
Diagnosis of Pulmonary Hypertension by Integrating Multimodal Data with a Hybrid Graph Convolutional and Transformer Network
Fubao Zhu, Yang Zhang, Gengmin Liang +13
Early and accurate diagnosis of pulmonary hypertension (PH) is essential for optimal patient management. Differentiating between pre-capillary and post-capillary PH is critical for…
MsMorph: An Unsupervised pyramid learning network for brain image registration
Jiaofen Nan, Gaodeng Fan, Kaifan Zhang +3
In the field of medical image analysis, image registration is a crucial technique. Despite the numerous registration models that have been proposed, existing methods still fall sho…
A review on machine learning for arterial extraction and quantitative assessment on invasive coronary angiograms
Pukar Baral, Chen Zhao, Michele Esposito +1
Purpose of Review Recently, machine learning has developed rapidly in the field of medicine, playing an important role in disease diagnosis. Our aim of this paper is to provide an…
Point cloud-based registration and image fusion between cardiac SPECT MPI and CTA
Shaojie Tang, Penpen Miao, Xingyu Gao +10
A method was proposed for the point cloud-based registration and image fusion between cardiac single photon emission computed tomography (SPECT) myocardial perfusion images (MPI) a…
3D Lymphoma Segmentation on PET/CT Images via Multi-Scale Information Fusion with Cross-Attention
Huan Huang, Liheng Qiu, Shenmiao Yang +7
Background: Accurate segmentation of diffuse large B-cell lymphoma (DLBCL) lesions is challenging due to their complex patterns in medical imaging. Objective: This study aims to de…
A Robust Deep Learning Method with Uncertainty Estimation for the Pathological Classification of Renal Cell Carcinoma based on CT Images
Ni Yao, Hang Hu, Kaicong Chen +9
Objectives To develop and validate a deep learning-based diagnostic model incorporating uncertainty estimation so as to facilitate radiologists in the preoperative differentiation…
Multi-View Variational Autoencoder for Missing Value Imputation in Untargeted Metabolomics
Chen Zhao, Kuan-Jui Su, Chong Wu +13
Background: Missing data is a common challenge in mass spectrometry-based metabolomics, which can lead to biased and incomplete analyses. The integration of whole-genome sequencing…
A new method of modeling the multi-stage decision-making process of CRT using machine learning with uncertainty quantification
Kristoffer Larsen, Chen Zhao, Joyce Keyak +7
Aims. The purpose of this study is to create a multi-stage machine learning model to predict cardiac resynchronization therapy (CRT) response for heart failure (HF) patients. This…
Hyper Association Graph Matching with Uncertainty Quantification for Coronary Artery Semantic Labeling
Chen Zhao, Michele Esposito, Zhihui Xu +1
Coronary artery disease (CAD) is one of the primary causes leading to death worldwide. Accurate extraction of individual arterial branches on invasive coronary angiograms (ICA) is…
MLA-BIN: Model-level Attention and Batch-instance Style Normalization for Domain Generalization of Federated Learning on Medical Image Segmentation
Fubao Zhu, Yanhui Tian, Chuang Han +4
The privacy protection mechanism of federated learning (FL) offers an effective solution for cross-center medical collaboration and data sharing. In multi-site medical image segmen…
Automatic Identification of the End-Diastolic and End-Systolic Cardiac Frames from Invasive Coronary Angiography Videos
Yinghui Meng, Minghao Dong, Xumin Dai +8
Automatic identification of proper image frames at the end-diastolic (ED) and end-systolic (ES) frames during the review of invasive coronary angiograms (ICA) is important to asses…