Explanipedia

A collaborative inference strategy for medical image diagnosis in mobile edge computing environment Open

Shiqian Zhang, Yong Cui, Dandan Xu, Yusong Lin · 2025

The popularity and convenience of mobile medical image analysis and diagnosis in mobile edge computing (MEC) environments have greatly improved the efficiency and quality of healthcare services, necessitating the use of deep neural network…

Traffic Flow Prediction Model Based on Transformer and Dynamic Graph Convolutional Networks Open

Tian Zhao, Honghui Dong, Yusong Lin · 2025

Traffic congestion is a major challenge in urban life, and traffic flow prediction, as a critical task in intelligent transportation management, can effectively alleviate congestion and enhance traffic control efficiency. Although deep lea…

Lightweight deep learning method for end-to-end point cloud registration Open

Linjun Jiang, Yue Liu, Zhiyuan Dong, Yinghao Li, Yusong Lin · 2024

Point cloud registration, a fundamental task in computer science and artificial intelligence, involves rigidly transforming point clouds from different perspectives into a common coordinate system. Traditional registration methods often la…

DRL-based dependent task offloading with delay-energy tradeoff in medical image edge computing Open

Qi Liu, Zhao Tian, Ning Wang, Yusong Lin · 2024

Task offloading solves the problem that the computing resources of terminal devices in hospitals are limited by offloading massive radiomics-based medical image diagnosis model (RIDM) tasks to edge servers (ESs). However, sequential offloa…

Group-Mix Attention Network for Unsupervised Medical Image Registration Open

Yinghao Li, Zhiyuan Dong, Mengyuan Yao, Yue Liu, Yusong Lin · 2024

Automatic Lightweight Gan-Based Transfer Function Generation in Mobile Medical Imaging Open

Dandan Xu, Yong Cui, Yucong Liu, Shiqian Zhang, Yusong Lin · 2024

Testing the evolutionary driving forces on display signal complexity in an Asian agamid lizard Open

Yusong Lin, Xia Qiu, Jinzhong Fu, Richard Peters, Yin Qi · 2023

Elucidating the factors behind the evolution of signal complexity is essential in understanding animal communication. Compared to vocal and color signals, dynamic display signals only start to attract attention recently. In this study, we …

Multi-user multi-objective computation offloading for medical image diagnosis Open

Qi Liu, Tian Zhao, Guohua Zhao, Yong Cui, Yusong Lin · 2023

Computation offloading has effectively solved the problem of terminal devices computing resources limitation in hospitals by shifting the medical image diagnosis task to the edge servers for execution. Appropriate offloading strategies for…

Adaptive PromptNet For Auxiliary Glioma Diagnosis without Contrast-Enhanced MRI Open

Yeqi Wang, Weijian Huang, Cheng Li, Xiawu Zheng, Yusong Lin , et al. · 2022

Multi-contrast magnetic resonance imaging (MRI)-based automatic auxiliary glioma diagnosis plays an important role in the clinic. Contrast-enhanced MRI sequences (e.g., contrast-enhanced T1-weighted imaging) were utilized in most of the ex…

Multiparametric Magnetic Resonance Imaging Information Fusion Using Graph Convolutional Network for Glioma Grading Open

Peiying Guo, Longfei Li, Cheng Li, Weijian Huang, Guohua Zhao , et al. · 2022

Accurate preoperative glioma grading is essential for clinical decision-making and prognostic evaluation. Multiparametric magnetic resonance imaging (mpMRI) serves as an important diagnostic tool for glioma patients due to its superior per…

Short-Axis PET Image Quality Improvement by Attention CycleGAN Using Total-Body PET Open

Chong Shang, Guohua Zhao, Yamei Li, Jianmin Yuan, Meiyun Wang , et al. · 2022

The quality of positron emission tomography (PET) imaging is positively correlated with scanner sensitivity, which is closely related to the axial field of view (FOV). Conventional short-axis PET scanners (200–350 mm FOV) reduce the imagin…

Expert Knowledge-guided Geometric Representation Learning for Magnetic Resonance Imaging-based Glioma Grading Open

Yeqi Wang, Longfei Li, Cheng Li, Yan Xi, Hairong Zheng , et al. · 2022

Radiomics and deep learning have shown high popularity in automatic glioma grading. Radiomics can extract hand-crafted features that quantitatively describe the expert knowledge of glioma grades, and deep learning is powerful in extracting…

Radiomic biomarker extracted from PI-RADS 3 patients support more eìcient and robust prostate cancer diagnosis: a multi-center study Open

Longfei Li, Rui Yang, Xin Chen, Cheng Li, Hairong Zheng , et al. · 2021

Prostate Imaging Reporting and Data System (PI-RADS) based on multi-parametric MRI classiêes patients into 5 categories (PI-RADS 1-5) for routine clinical diagnosis guidance. However, there is no consensus on whether PI-RADS 3 patients sho…

Bayesian Fully Convolutional Networks for Brain Image Registration Open

Kunpeng Cui, Panpan Fu, Yinghao Li, Yusong Lin · 2021

The purpose of medical image registration is to find geometric transformations that align two medical images so that the corresponding voxels on two images are spatially consistent. Nonrigid medical image registration is a key step in medi…

Identification of Arrhythmia by Using a Decision Tree and Gated Network Fusion Model Open

Peng Lu, Yabin Zhang, Bing Zhou, Hongpo Zhang, Li-Wei Chen , et al. · 2021

In recent years, deep learning (DNN) based methods have made leapfrogging level breakthroughs in detecting cardiac arrhythmias as the cost effectiveness of arithmetic power, and data size has broken through the tipping point. However, the …

Fproi-GAN with Fused Regional Features for the Synthesis of High-Quality Paired Medical Images Open

Jiale Dong, Caiwei Liu, Panpan Man, Guohua Zhao, Yaping Wu , et al. · 2021

The use of medical image synthesis with generative adversarial networks (GAN) is effective for expanding medical samples. The structural consistency between the synthesized and actual image is a key indicator of the quality of the synthesi…

MIE-NSCT: Adaptive MRI Enhancement Based on Nonsubsampled Contourlet Transform Open

Caiwei Liu, Guohua Zhao, Jiale Dong, Yusong Lin, Meiyun Wang · 2021

Image enhancement technology is often used to improve the quality of medical images and helps doctors or expert systems identify and diagnose diseases. This paper aimed at the characteristics of magnetic resonance imaging (MRI) with comple…

A Novel Algorithm for Breast Mass Classification in Digital Mammography Based on Feature Fusion Open

Qian Zhang, Yamei Li, Guohua Zhao, Panpan Man, Yusong Lin , et al. · 2020

Prompt diagnosis of benign and malignant breast masses is essential for early breast cancer screening. Convolutional neural networks (CNNs) can be used to assist in the classification of benign and malignant breast masses. A persistent pro…

A New Multichannel Parallel Network Framework for the Special Structure of Multilead ECG Open

Peng Lu, Hao Xi, Bing Zhou, Hongpo Zhang, Yusong Lin , et al. · 2020

Electrocardiogram (ECG) contains the rhythmic features of continuous heartbeat and morphological features of ECG waveforms and varies among different diseases. Based on ECG signal features, we propose a combination of multiple neural netwo…

Mammography-based radiomics nomogram: a potential biomarker to predict axillary lymph node metastasis in breast cancer Open

Hongna Tan, Yaping Wu, Fengchang Bao, Jing Zhou, Jianzhong Wan , et al. · 2020

Objective: To establish a radiomics nomogram by integrating clinical risk factors and radiomics features extracted from digital mammography (MG) images for pre-operative prediction of axillary lymph node (ALN) metastasis in breast cancer. …

Erratum to ‘Radiomics analysis of placenta on T2WI facilitates prediction of postpartum haemorrhage: A multicentre study’ Open

Qingxia Wu, Kuan Yao, Zhenyu Liu, Longfei Li, Xin Zhao , et al. · 2020

The publisher regrets that due to a production error Xiaoan Zhang was accidentally omitted from the author list in the published version of this research paper. The correct author list is given here and the original article has been update…

HS–GS: A Method for Multicenter MR Image Standardization Open

Guohua Zhao, Jie Bai, Pei Pei Wang, Guan Yang, Lei Shi , et al. · 2020

The access to and sharing of medical image data is essential to accelerate the research progress of complex diseases and sudden disease outbreaks. Multicenter image data is collected from different medical institutions, and the contrast an…

Automatic Histogram Specification for Glioma Grading Using Multicenter Data Open

Xi Chen, Yaping Wu, Guohua Zhao, Meiyun Wang, Gao Wen-yi , et al. · 2019

Multicenter sharing is an effective method to increase the data size for glioma research, but the data inconsistency among different institutions hindered the efficiency. This paper proposes a histogram specification with automatic selecti…

Radiomics analysis of placenta on T2WI facilitates prediction of postpartum haemorrhage: A multicentre study Open

Qingxia Wu, Kuan Yao, Zhenyu Liu, Longfei Li, Xin Zhao , et al. · 2019

A Non-invasive Radiomic Method Using 18F-FDG PET Predicts Isocitrate Dehydrogenase Genotype and Prognosis in Patients With Glioma Open

Longfei Li, Wei Mu, Yaning Wang, Zhenyu Liu, Zehua Liu , et al. · 2019

Purpose: We aimed to analyze ¹⁸F-fluorodeoxyglucose positron emission tomography (¹⁸F-FDG PET) images via the radiomic method to develop a model and validate the potential value of features reflecting glioma me…

Automatic glioma segmentation based on adaptive superpixel Open

Yaping Wu, Zhe Zhao, Weiguo Wu, Yusong Lin, Meiyun Wang · 2019

18F-FDG-PET-based Radiomics signature predicts MGMT promoter methylation status in primary diffuse glioma Open

Ziren Kong, Yusong Lin, Chendan Jiang, Longfei Li, Zehua Liu , et al. · 2019

¹⁸F-FDG-PET-based radiomics is a promising approach for preoperatively evaluating the MGMT promoter methylation status in glioma and predicting the prognosis of glioma patients noninvasively.

Identification of Cognitive Dysfunction in Patients with T2DM Using Whole Brain Functional Connectivity Open

Zhenyu Liu, Jiangang Liu, Huijuan Yuan, Taiyuan Liu, Xingwei Cui , et al. · 2019

Majority of type 2 diabetes mellitus (T2DM) patients are highly susceptible to several forms of cognitive impairments, particularly dementia. However, the underlying neural mechanism of these cognitive impairments remains unclear. We aimed…

Four-Sequence Maximum Entropy Discrimination Algorithm for Glioma Grading Open

Yaping Wu, Huihui Hao, Jie Li, Weiguo Wu, Yusong Lin , et al. · 2019

Grading of glioma is crucial for treatment decision making as well as prognostic assessments. In clinical routines, radiologists grade gliomas with multiple complementary magnetic resonance imaging (MRI) sequences, which is yet challenging…

Noninvasive Magnetic Resonance Imaging Models for Staging Hepatic Fibrosis and Grading Inflammatory Activity in Patients with Chronic Hepatitis B Open

Fangfang Fu, Xiaodong Li, Yusong Lin, Cuiyun Chen, Yan Bai , et al. · 2019

Yusong Lin YOU? Author Swipe