Explanipedia

Image harmonization and de-harmonization based on singular value decomposition (SVD) in medical domain Open

H. Q. CHEN, Xinze Li, Ka‐Hou Chan, Yue Sun, Rongsheng Wang , et al. · 2025

The proposed SVD-based harmonization and de-harmonization algorithms present a robust solution to the challenges of image variability in medical imaging. By addressing inconsistencies across different datasets and imaging modalities, while…

NTIRE 2025 Image Shadow Removal Challenge Report Open

Florin-Alexandru Vasluianu, Tim Seizinger, Zhuyun Zhou, Cailian Chen, Zongwei Wu , et al. · 2025

This work examines the findings of the NTIRE 2025 Shadow Removal Challenge. A total of 306 participants have registered, with 17 teams successfully submitting their solutions during the final evaluation phase. Following the last two editio…

Contrastive learning through randomly generated dynamic supervision signals Open

Shibo Wang, Yaofei Duan, Zili Ma, Ka‐Hou Chan, Yue Sun , et al. · 2025

MSAN-Net: An End-to-End Multi-Scale Attention Network for Universal Industrial Defect Detection Open

Zelu Wang, Ming Luo, Xinghe Xie, Yue Sun, Xinyu Tian , et al. · 2025

With the rapid advancement of automation and intelligence in the electronics manufacturing industry, the throughput of a single production line was grown exponentially. Although high efficiency brought significant cost and time advantages,…

Itgo: A General Framework for Text-Guided Image Outpainting Open

Nu Nu, Yuanbo Zhou, Xinlin Zhang, Yuanbin Chen, Hui Tang , et al. · 2025

Itgo: A General Framework for Text-Guided Image Outpainting Open

Nu Nu, Yuanbo Zhou, Xinlin Zhang, Yuanbin Chen, Hui Tang , et al. · 2025

Comprehensive Mendelian randomization analysis of low-density lipoprotein cholesterol and multiple cancers Open

Haozhao Liang, Chunling Tang, Yue Sun, Mingwei Wang, Tong Tong , et al. · 2024

Comprehensive Mendelian randomization analysis of low-density lipoprotein cholesterol and multiple cancers Open

Haozhao Liang, Chunling Tang, Yue Sun, Mingwei Wang, Tong Tong , et al. · 2024

Purpose: The aim of this study was to investigate the causal relationship between low-density lipoprotein cholesterol (LDL-C) and five cancers (breast, cervical, thyroid, prostate and colorectal) using the Mendelian Randomization (MR) meth…

DIffSteISR: Harnessing Diffusion Prior for Superior Real-world Stereo Image Super-Resolution Open

Yuanbo Zhou, Xinlin Zhang, Wei Deng, Tao Wang, Tao Tan , et al. · 2024

We introduce DiffSteISR, a pioneering framework for reconstructing real-world stereo images. DiffSteISR utilizes the powerful prior knowledge embedded in pre-trained text-to-image model to efficiently recover the lost texture details in lo…

ASteISR: Adapting Single Image Super-resolution Pre-trained Model for Efficient Stereo Image Super-resolution Open

Yuanbo Zhou, Yuyang Xue, Wei Deng, Xinlin Zhang, Qinquan Gao , et al. · 2024

Despite advances in the paradigm of pre-training then fine-tuning in low-level vision tasks, significant challenges persist particularly regarding the increased size of pre-trained models such as memory usage and training time. Another con…

A blind image super-resolution network guided by kernel estimation and structural prior knowledge Open

Jiajun Zhang, Yuanbo Zhou, Jiang Bi, Yuyang Xue, Wei Deng , et al. · 2024

NTIRE 2024 Challenge on Low Light Image Enhancement: Methods and Results Open

Xiaoning Liu, Zongwei Wu, Ao Li, Florin-Alexandru Vasluianu, Yulun Zhang , et al. · 2024

This paper reviews the NTIRE 2024 low light image enhancement challenge, highlighting the proposed solutions and results. The aim of this challenge is to discover an effective network design or solution capable of generating brighter, clea…

Innovative Quantitative Analysis for Disease Progression Assessment in Familial Cerebral Cavernous Malformations Open

Ruige Zong, Tao Wang, Chunwang Li, Xinlin Zhang, Yuanbin Chen , et al. · 2024

Familial cerebral cavernous malformation (FCCM) is a hereditary disorder characterized by abnormal vascular structures within the central nervous system. The FCCM lesions are often numerous and intricate, making quantitative analysis of th…

Distance Guided Generative Adversarial Network for Explainable Binary Classifications Open

Xiangyu Xiong, Yue Sun, Xiaohong Liu, Wei Ke, Chan–Tong Lam , et al. · 2023

Despite the potential benefits of data augmentation for mitigating the data insufficiency, traditional augmentation methods primarily rely on the prior intra-domain knowledge. On the other hand, advanced generative adversarial networks (GA…

Toward Real World Stereo Image Super-Resolution via Hybrid Degradation Model and Discriminator for Implied Stereo Image Information Open

Yuanbo Zhou, Yuyang Xue, Jiang Bi, Wenlin He, Xinlin Zhang , et al. · 2023

Real-world stereo image super-resolution has a significant influence on enhancing the performance of computer vision systems. Although existing methods for single-image super-resolution can be applied to improve stereo images, these method…

A Parameterized Generative Adversarial Network Using Cyclic Projection for Explainable Medical Image Classification Open

Xiangyu Xiong, Yue Sun, Xiaohong Liu, ChanTong Lam, Tong Tong , et al. · 2023

Although current data augmentation methods are successful to alleviate the data insufficiency, conventional augmentation are primarily intra-domain while advanced generative adversarial networks (GANs) generate images remaining uncertain, …

Pseudo Label-Guided Data Fusion and Output Consistency for Semi-Supervised Medical Image Segmentation Open

Tao Wang, Yuanbin Chen, Xinlin Zhang, Yuanbo Zhou, Junlin Lan , et al. · 2023

Supervised learning algorithms based on Convolutional Neural Networks have become the benchmark for medical image segmentation tasks, but their effectiveness heavily relies on a large amount of labeled data. However, annotating medical ima…

KESPKSR: A Blind Image Super-resolution Network Combined Kernel Estimation and Structural Prior Knowledge Open

Jiajun Zhang, Yuanbo Zhou, Jiang Bi, Yuyang Xue, Wei Deng , et al. · 2023

The goal of blind image super-resolution (BISR) is to recover the corresponding high-resolution image from a given low-resolution image with unknown degradation. Prior related research has primarily focused effectively on utilizing the ker…

CoTrFuse: a novel framework by fusing CNN and transformer for medical image segmentation Open

Yuanbin Chen, Tao Wang, Hui Tang, Longxuan Zhao, Xinlin Zhang , et al. · 2023

Medical image segmentation is a crucial and intricate process in medical image processing and analysis. With the advancements in artificial intelligence, deep learning techniques have been widely used in recent years for medical image segm…

PCDAL: A Perturbation Consistency-Driven Active Learning Approach for Medical Image Segmentation and Classification Open

Tao Wang, Xinlin Zhang, Yuanbo Zhou, Junlin Lan, Tao Tan , et al. · 2023

In recent years, deep learning has become a breakthrough technique in assisting medical image diagnosis. Supervised learning using convolutional neural networks (CNN) provides state-of-the-art performance and has served as a benchmark for …

LightR-YOLOv5: A compact rotating detector for SARS-CoV-2 antigen-detection rapid diagnostic test results Open

Rongsheng Wang, Yaofei Duan, Menghan Hu, Xiaohong Liu, Yukun Li , et al. · 2023

Deeper or Wider? A Guidance for Future Single Image Super-Resolution Neural Network Open

Yuanbo Zhou, Yuyang Xue, Wei Deng, Nuofeng Nie, Yuh-Ting Lin , et al. · 2023

Prediction of Lymph Node Metastasis in Primary Gastric Cancer from Pathological Images and Clinical Data by Multimodal Multiscale Deep Learning Open

Zhechen Guo, Junlin Lan, Jianchao Wang, Ziwei Hu, Zhida Wu , et al. · 2023

O-Net: A Novel Framework With Deep Fusion of CNN and Transformer for Simultaneous Segmentation and Classification Open

Tao Wang, Junlin Lan, Zixin Han, Ziwei Hu, Yuxiu Huang , et al. · 2022

The application of deep learning in the medical field has continuously made huge breakthroughs in recent years. Based on convolutional neural network (CNN), the U-Net framework has become the benchmark of the medical image segmentation tas…

A Deep Learning Quantification Algorithm for HER2 Scoring of Gastric Cancer Open

Zixin Han, Junlin Lan, Tao Wang, Ziwei Hu, Yuxiu Huang , et al. · 2022

Gastric cancer is the third most common cause of cancer-related death in the world. Human epidermal growth factor receptor 2 (HER2) positive is an important subtype of gastric cancer, which can provide significant diagnostic information fo…

A Multi-Scale Densely Connected Convolutional Neural Network for Automated Thyroid Nodule Classification Open

Luoyan Wang, Xiaogen Zhou, Xingqing Nie, Xingtao Lin, Jing Li , et al. · 2022

Automated thyroid nodule classification in ultrasound images is an important way to detect thyroid nodules and to make a more accurate diagnosis. In this paper, we propose a novel deep convolutional neural network (CNN) model, called n-Cls…

Utility of Polygenic Risk Scoring to Predict Cognitive Impairment as Measured by Preclinical Alzheimer Cognitive Composite Score. Open

Qinquan Gao, Paula Daunt, A M Gibson, Richard Pither · 2022

Our findings have shown that polygenic risk score provides a promising tool to identify those with higher risk to decline over 5 years regardless of their APOE alleles according to modified PACC profile, especially its ability to identify …

UTILITY OF POLYGENIC RISK SCORING TO PREDICT COGNITIVE IMPAIRMENT AS MEASURED BY PRECLINICAL ALZHEIMER COGNITIVE COMPOSITE SCORE Open

Qinquan Gao, Paula Daunt, A.M. Gibson, Richard Pither · 2022

An Improved Vehicle Detection Algorithm Based on Multi-Intermediate State Machine Open

Baosen Xiao, Jingbo Xia, Xiaolu Li, Qinquan Gao · 2021

The vehicle detection algorithm is an important part of the intelligent transportation system. The accuracy of the algorithm will determine whether accurate vehicle information can be obtained. The system contains several functional module…

Bidirectional Mapping of Brain MRI and PET With 3D Reversible GAN for the Diagnosis of Alzheimer’s Disease Open

Wanyun Lin, Wei-Ming Lin, Gang Chen, Hejun Zhang, Qinquan Gao , et al. · 2021

Combining multi-modality data for brain disease diagnosis such as Alzheimer’s disease (AD) commonly leads to improved performance than those using a single modality. However, it is still challenging to train a multi-modality model since it…

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