Research outputs
2027
Hierarchical Disentangled Consistency Learning for Semi-supervised Multi-modal Medical Image Segmentation
Zhou, F., Gao, Z., Xie, J., Li, K., Wang, F., Chen, L., . . . Zheng, Y. (2027). Hierarchical Disentangled Consistency Learning for Semi-supervised Multi-modal Medical Image Segmentation. In Medical Image Computing and Computer Assisted Intervention – MICCAI 2026 (Vol. 16880, pp. 260-270). Springer Nature. doi:10.1007/978-3-032-38069-2_25
Towards Class-Aware Semantic Decoupling in Multi-modal Disease Diagnosis with Missing Modalities
Zhou, F., Xie, J., Gao, Z., Yu, Q., Li, J., Chen, L., . . . Zheng, Y. (2027). Towards Class-Aware Semantic Decoupling in Multi-modal Disease Diagnosis with Missing Modalities. In Medical Image Computing and Computer Assisted Intervention – MICCAI 2026 (Vol. 16885, pp. 607-617). Springer Nature. doi:10.1007/978-3-032-38091-3_58
2026
Development and Validation of the GLORIA-AF Stroke Weighted Risk Score for Patients with Atrial Fibrillation.
Xie, Y., Li, W., Meng, Y., Huang, T., Zheng, Y., Huisman, M. V., . . . Lip, G. Y. H. (2026). Development and Validation of the GLORIA-AF Stroke Weighted Risk Score for Patients with Atrial Fibrillation.. Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology, euag236. doi:10.1093/europace/euag236
Clinician-Friendly Foundation Models for Ophthalmic Image Diagnostics without Fine-Tuning or Technical Barriers
Development and external validation of the GLORIA-AF Bleeding Weighted Risk Score for patients with atrial fibrillation
Xie, Y., Li, W., Meng, Y., Huang, T., Zheng, Y., Huisman, M. V., . . . Lip, G. Y. H. (2026). Development and external validation of the GLORIA-AF Bleeding Weighted Risk Score for patients with atrial fibrillation. EUROPEAN JOURNAL OF PREVENTIVE CARDIOLOGY, 9 pages. doi:10.1093/eurjpc/zwag447
DiffGeo-AOR: Diffusion-Optimized Medical Grading via Geometric Priors Enhanced Autoregressive Ordinal Regression
Yu, Q., Zhao, H., Xu, Y., Wang, M., Zhao, Y., Fu, H., . . . Meng, Y. (2026). DiffGeo-AOR: Diffusion-Optimized Medical Grading via Geometric Priors Enhanced Autoregressive Ordinal Regression. IEEE TRANSACTIONS ON MEDICAL IMAGING, 45(9), 4846-4860. doi:10.1109/TMI.2026.3710844
Beyond Correlation: Causal Intervention for Multi-Label Medical Image Diagnosis
Xie, J., Zhao, Y., Chen, X., Meng, Y., Zhao, H., Alam, U., . . . Zheng, Y. (2026). Beyond Correlation: Causal Intervention for Multi-Label Medical Image Diagnosis. IEEE TRANSACTIONS ON MEDICAL IMAGING, 45(8), 4315-4326. doi:10.1109/TMI.2026.3698052
Super-Resolution Reconstruction of OCTA via Multi-Field-of-View Representation Learning
Hao, H., Leng, S., Meng, Y., Liu, Y., Zheng, Y., Fu, H., . . . Zhao, Y. (2026). Super-Resolution Reconstruction of OCTA via Multi-Field-of-View Representation Learning. IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 30(8), 7309-7321. doi:10.1109/JBHI.2025.3593149
UTriGate-Net: Uncertainty-aware brain tumor segmentation via triaxial context encoding and gated modality fusion
Zhou, T., Ruan, S., Meng, Y., Duan, J., Hu, H., Jiang, B., . . . Lei, B. (2026). UTriGate-Net: Uncertainty-aware brain tumor segmentation via triaxial context encoding and gated modality fusion. EXPERT SYSTEMS WITH APPLICATIONS, 321, 13 pages. doi:10.1016/j.eswa.2026.132258
A hierarchical teacher-student learning framework with adaptive cross-modal fusion for brain tumor segmentation
Zhou, T., Ruan, S., Duan, J., Hu, H., Meng, Y., Huang, L., . . . Lei, B. (2026). A hierarchical teacher-student learning framework with adaptive cross-modal fusion for brain tumor segmentation. Expert Systems with Applications, 311. doi:10.1016/j.eswa.2026.131371
Artifact-suppressed 3D retinal microvascular segmentation via multi-scale topology regulation
Luo, T., Zhang, J., Chen, T., He, Z., Meng, Y., Liu, M., . . . Zhang, D. (2026). Artifact-suppressed 3D retinal microvascular segmentation via multi-scale topology regulation. MEDICAL IMAGE ANALYSIS, 110, 13 pages. doi:10.1016/j.media.2026.103988
DFuse-Net: Disentangled feature fusion with uncertainty-aware learning for reliable multi-modal brain tumor segmentation
Zhou, T., Wang, Z., Ruan, S., Meng, Y., Duan, J., & Lei, B. (2026). DFuse-Net: Disentangled feature fusion with uncertainty-aware learning for reliable multi-modal brain tumor segmentation. MEDICAL IMAGE ANALYSIS, 109, 13 pages. doi:10.1016/j.media.2025.103923
GLCP: Global-to-Local Connectivity Preservation for Tubular Structure Segmentation
Zhou, F., Gao, Z., Zhao, H., Xie, J., Meng, Y., Zhao, Y., . . . Zheng, Y. (2026). GLCP: Global-to-Local Connectivity Preservation for Tubular Structure Segmentation. MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION - MICCAI 2025, PT XVI, 15975, 237-247. doi:10.1007/978-3-032-05325-1_23
StealthMark: Harmless and Stealthy Ownership Verification for Medical Segmentation via Uncertainty-Guided Backdoors
Yu, Q., Zhang, C., Jin, G., Huang, T., Zhou, W., Li, W., . . . Meng, Y. (2026). StealthMark: Harmless and Stealthy Ownership Verification for Medical Segmentation via Uncertainty-Guided Backdoors. IEEE TRANSACTIONS ON IMAGE PROCESSING, 35, 1290-1304. doi:10.1109/TIP.2026.3655563
2025
Enhancing diagnostic accuracy in rare and common fundus diseases with a knowledge-rich vision-language model
Wang, M., Lin, T., Lin, A., Yu, K., Peng, Y., Wang, L., . . . Fu, H. (2025). Enhancing diagnostic accuracy in rare and common fundus diseases with a knowledge-rich vision-language model. Nature Communications, 16(1). doi:10.1038/s41467-025-60577-9
Uncertainty Quantification for Multiple-Choice Questions is Just One-Token Deep
Zeng, Q., Jin, M., Yu, Q., Wang, Z., Hua, W., Sun, G., . . . Zhang, Y. (2025). Uncertainty Quantification for Multiple-Choice Questions is Just One-Token Deep. In Cikm 2025 Proceedings of the 34th ACM International Conference on Information and Knowledge Management (pp. 5474-5478). doi:10.1145/3746252.3760887
Health-LLM: Personalized Retrieval-Augmented Disease Prediction System
Incomplete Modality Disentangled Representation for Ophthalmic Disease Grading and Diagnosis
Liu, C., Huang, Z., Chen, Z., Tang, F., Tian, Y., Xu, Z., . . . Meng, Y. (2025). Incomplete Modality Disentangled Representation for Ophthalmic Disease Grading and Diagnosis. In THIRTY-NINTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, AAAI-25, VOL 39 NO 5 (pp. 5361-5369). Retrieved from https://www.webofscience.com/
Enhancing Diagnostic Accuracy in Rare and Common Fundus Diseases with a Knowledge-Rich Vision-Language Model
Incomplete Modality Disentangled Representation for Ophthalmic Disease Grading and Diagnosis
Exploring Concept Depth: How Large Language Models Acquire Knowledge and Concept at Different Layers?
Self-adaptive vision-language model for 3D segmentation of pulmonary artery and vein
Excavate the Potential of Single-Scale Features: A Decomposition Network for Water-Related Optical Image Enhancement
Cheng, Z., Wang, W., Chen, G. -Y., Ju, Y., Cheng, Y., Liu, Z., . . . Song, J. (2025). Excavate the Potential of Single-Scale Features: A Decomposition Network for Water-Related Optical Image Enhancement. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 18, 27163-27176. doi:10.1109/JSTARS.2025.3621304
Exploring Concept Depth: How Large Language Models Acquire Knowledge and Concepts at Different Layers?
Jin, M., Yu, Q., Huang, J., Zeng, Q., Wang, Z., Hua, W., . . . Zhang, Y. (2025). Exploring Concept Depth: How Large Language Models Acquire Knowledge and Concepts at Different Layers?. In Proceedings International Conference on Computational Linguistics Coling (pp. 558-573).
MR<SUP>2</SUP>-Net: Retinal OCTA Image Stitching via Multi-Scale Representation Learning and Dynamic Location Guidance
Mao, H., Ma, Y., Zhang, D., Meng, Y., Ma, S., Qiao, Y., . . . Zhang, J. (2025). MR<SUP>2</SUP>-Net: Retinal OCTA Image Stitching via Multi-Scale Representation Learning and Dynamic Location Guidance. IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 29(1), 482-494. doi:10.1109/JBHI.2024.3467256
Randomness-Restricted Diffusion Model for Ocular Surface Structure Segmentation
Guo, X., Wen, H., Hao, H., Zhao, Y., Meng, Y., Liu, J., . . . Zhao, Y. (2025). Randomness-Restricted Diffusion Model for Ocular Surface Structure Segmentation. IEEE TRANSACTIONS ON MEDICAL IMAGING, 44(3), 1359-1372. doi:10.1109/TMI.2024.3494762
2024
Editorial: Efficient artificial intelligence (AI) in ophthalmic imaging
Meng, Y., Wang, M., Chen, H., & Zheng, Y. (2024). Editorial: Efficient artificial intelligence (AI) in ophthalmic imaging. FRONTIERS IN MEDICINE, 11, 2 pages. doi:10.3389/fmed.2024.1523647
Dynamic Semantic-based Spatial-Temporal Graph Convolution Network for Skeleton-based Human Action Recognition
Xie, J., Meng, Y., Zhao, Y., Anh, N., Yang, X., & Zheng, Y. (2024). Dynamic Semantic-based Spatial-Temporal Graph Convolution Network for Skeleton-based Human Action Recognition. IEEE Transactions on Image Processing, 1. doi:10.1109/tip.2024.3497837
Artificial intelligence-based classification of cardiac autonomic neuropathy from retinal fundus images in patients with diabetes: The Silesia Diabetes Heart Study
Nabrdalik, K., Irlik, K., Meng, Y., Kwiendacz, H., Piasnik, J., Hendel, M., . . . Alam, U. (2024). Artificial intelligence-based classification of cardiac autonomic neuropathy from retinal fundus images in patients with diabetes: The Silesia Diabetes Heart Study. CARDIOVASCULAR DIABETOLOGY, 23(1), 10 pages. doi:10.1186/s12933-024-02367-z
Uncertainty is Fragile: Manipulating Uncertainty in Large Language Models
AI-driven generalized polynomial transformation models for unsupervised fundus image registration
Chen, X., Fan, X., Meng, Y., & Zheng, Y. (2024). AI-driven generalized polynomial transformation models for unsupervised fundus image registration. FRONTIERS IN MEDICINE, 11, 10 pages. doi:10.3389/fmed.2024.1421439
CLIP-DR: Textual Knowledge-Guided Diabetic Retinopathy Grading with Ranking-aware Prompting
The Impact of Reasoning Step Length on Large Language Models
Multi-granularity learning of explicit geometric constraint and contrast for label-efficient medical image segmentation and differentiable clinical function assessment.
Meng, Y., Zhang, Y., Xie, J., Duan, J., Joddrell, M., Madhusudhan, S., . . . Zheng, Y. (2024). Multi-granularity learning of explicit geometric constraint and contrast for label-efficient medical image segmentation and differentiable clinical function assessment.. Medical image analysis, 95, 103183. doi:10.1016/j.media.2024.103183
Dynamic Semantic-Based Spatial Graph Convolution Network for Skeleton-Based Human Action Recognition
Xie, J., Meng, Y., Zhao, Y., Anh, N., Yang, X., & Zheng, Y. (2024). Dynamic Semantic-Based Spatial Graph Convolution Network for Skeleton-Based Human Action Recognition. In THIRTY-EIGHTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, VOL 38 NO 6 (pp. 6225-6233). Retrieved from https://www.webofscience.com/
CLIP-DR: Textual Knowledge-Guided Diabetic Retinopathy Grading with Ranking-Aware Prompting
Yu, Q., Xie, J., Anh, N., Zhao, H., Zhang, J., Fu, H., . . . Meng, Y. (2024). CLIP-DR: Textual Knowledge-Guided Diabetic Retinopathy Grading with Ranking-Aware Prompting. In Unknown Book (Vol. 15001, pp. 667-677). doi:10.1007/978-3-031-72378-0_62
Clinical Insight-Augmented Multi-View Learning for Alzheimer's Detection in Retinal OCTA Images
Zhang, Y., Hao, J., Zheng, B., Liu, Y., Meng, Y., Zhang, J., . . . Zhao, Y. (2024). Clinical Insight-Augmented Multi-View Learning for Alzheimer's Detection in Retinal OCTA Images. In Proceedings 2024 IEEE International Conference on Bioinformatics and Biomedicine Bibm 2024 (pp. 2900-2907). doi:10.1109/BIBM62325.2024.10822671
Multi-disease Detection in Retinal Images Guided by Disease Causal Estimation
Xie, J., Chen, X., Zhao, Y., Meng, Y., Zhao, H., Anh, N., . . . Zheng, Y. (2024). Multi-disease Detection in Retinal Images Guided by Disease Causal Estimation. In Unknown Book (Vol. 15001, pp. 743-753). doi:10.1007/978-3-031-72378-0_69
Self-Guided Adversarial Network for Domain Adaptive Retinal Layer Segmentation
Zhang, J., Lu, C., Song, R., Zheng, Y., Hao, H., Meng, Y., & Zhao, Y. (2024). Self-Guided Adversarial Network for Domain Adaptive Retinal Layer Segmentation. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 73, 10 pages. doi:10.1109/TIM.2024.3440388
The Impact of Reasoning Step Length on Large Language Models
Jin, M., Yu, Q., Dong, S., Zhao, H., Hua, W., Meng, Y., . . . Du, M. (2024). The Impact of Reasoning Step Length on Large Language Models. In FINDINGS OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS: ACL 2024 (pp. 1830-1842). Retrieved from https://www.webofscience.com/
Weakly/Semi-supervised Left Ventricle Segmentation in 2D Echocardiography with Uncertain Region-Aware Contrastive Learning
Meng, Y., Zhang, Y., Xie, J., Duan, J., Zhao, Y., & Zheng, Y. (2024). Weakly/Semi-supervised Left Ventricle Segmentation in 2D Echocardiography with Uncertain Region-Aware Contrastive Learning. In PATTERN RECOGNITION AND COMPUTER VISION, PRCV 2023, PT XIII Vol. 14437 (pp. 98-109). doi:10.1007/978-981-99-8558-6_9
2023
Development and external validation of a mixed-effects deep learning model to diagnose COVID-19 from CT imaging.
Bridge, J., Meng, Y., Zhu, W., Fitzmaurice, T., McCann, C., Addison, C., . . . Zheng, Y. (2023). Development and external validation of a mixed-effects deep learning model to diagnose COVID-19 from CT imaging.. Frontiers in medicine, 10, 1113030. doi:10.3389/fmed.2023.1113030
Weakly Supervised Segmentation with Point Annotations for Histopathology Images via Contrast-Based Variational Model
Zhang, H., Burrows, L., Meng, Y., Sculthorpe, D., Mukherjee, A., Coupland, S. E., . . . Zheng, Y. (2023). Weakly Supervised Segmentation with Point Annotations for Histopathology Images via Contrast-Based Variational Model. In 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE. doi:10.1109/cvpr52729.2023.01500
Deep Learning Using Preoperative AS-OCT Predicts Graft Detachment in DMEK
Patefield, A., Meng, Y., Airaldi, M., Coco, G., Vaccaro, S., Parekh, M., . . . Romano, V. (2023). Deep Learning Using Preoperative AS-OCT Predicts Graft Detachment in DMEK. TRANSLATIONAL VISION SCIENCE & TECHNOLOGY, 12(5), 8 pages. doi:10.1167/tvst.12.5.14
Retinal imaging technologies in cerebral malaria: a systematic review.
Wilson, K. J., Dhalla, A., Meng, Y., Tu, Z., Zheng, Y., Mhango, P., . . . Beare, N. A. V. (2023). Retinal imaging technologies in cerebral malaria: a systematic review.. Malaria journal, 22(1), 139. doi:10.1186/s12936-023-04566-7
Transportation Object Counting With Graph-Based Adaptive Auxiliary Learning
Meng, Y., Bridge, J., Zhao, Y., Joddrell, M., Qiao, Y., Yang, X., . . . Zheng, Y. (2023). Transportation Object Counting With Graph-Based Adaptive Auxiliary Learning. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 24(3), 3422-3437. doi:10.1109/TITS.2022.3226504
Artificial Intelligence Based Analysis of Corneal Confocal Microscopy Images for Diagnosing Peripheral Neuropathy: A Binary Classification Model
Meng, Y., Preston, F. G., Ferdousi, M., Azmi, S., Petropoulos, I. N., Kaye, S., . . . Zheng, Y. (2023). Artificial Intelligence Based Analysis of Corneal Confocal Microscopy Images for Diagnosing Peripheral Neuropathy: A Binary Classification Model. JOURNAL OF CLINICAL MEDICINE, 12(4). doi:10.3390/jcm12041284
Bilateral adaptive graph convolutional network on CT based Covid-19 diagnosis with uncertainty-aware consensus-assisted multiple instance learning
Meng, Y., Bridge, J., Addison, C., Wang, M., Merritt, C., Franks, S., . . . Zheng, Y. (2023). Bilateral adaptive graph convolutional network on CT based Covid-19 diagnosis with uncertainty-aware consensus-assisted multiple instance learning. MEDICAL IMAGE ANALYSIS, 84, 20 pages. doi:10.1016/j.media.2022.102722
Dual Consistency Enabled Weakly and Semi-Supervised Optic Disc and Cup Segmentation With Dual Adaptive Graph Convolutional Networks
Meng, Y., Zhang, H., Zhao, Y., Gao, D., Hamill, B., Patri, G., . . . Zheng, Y. (2023). Dual Consistency Enabled Weakly and Semi-Supervised Optic Disc and Cup Segmentation With Dual Adaptive Graph Convolutional Networks. IEEE TRANSACTIONS ON MEDICAL IMAGING, 42(2), 416-429. doi:10.1109/TMI.2022.3203318
Automatically Segment the Left Atrium and Scars from LGE-MRIs Using a Boundary-Focused nnU-Net
Zhang, Y., Meng, Y., & Zheng, Y. (2023). Automatically Segment the Left Atrium and Scars from LGE-MRIs Using a Boundary-Focused nnU-Net. In Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics Vol. 13586 LNCS (pp. 49-59). doi:10.1007/978-3-031-31778-1_5
Corneal Confocal Microscopy Based Deep Learning Algorithms Demonstrate Excellent Diagnostic Accuracy in Identifying Patients with Dementia, Multiple Sclerosis and Parkinson's Disease
2022
Graph Representation Learning for Biometric and Biomedical Images Analysis
Meng, Y. (2022, October 31). Graph Representation Learning for Biometric andBiomedical Images Analysis.
Artificial Intelligence and Corneal Confocal Microscopy: The Start of a Beautiful Relationship
Alam, U., Anson, M., Meng, Y., Preston, F., Kirthi, V., Jackson, T. L., . . . Petropoulos, I. N. (2022). Artificial Intelligence and Corneal Confocal Microscopy: The Start of a Beautiful Relationship. JOURNAL OF CLINICAL MEDICINE, 11(20), 19 pages. doi:10.3390/jcm11206199
Shape-Aware Weakly/Semi-Supervised Optic Disc and Cup Segmentation with Regional/Marginal Consistency
Meng, Y., Chen, X., Zhang, H., Zhao, Y., Gao, D., Hamill, B., . . . Zheng, Y. (2022). Shape-Aware Weakly/Semi-Supervised Optic Disc and Cup Segmentation with Regional/Marginal Consistency. In MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION, MICCAI 2022, PT IV Vol. 13434 (pp. 524-534). doi:10.1007/978-3-031-16440-8_50
Informed Consent In Facial Photograph Publishing: A Cross-sectional Pilot Study To Determine The Effectiveness Of Deidentification Methods
Preston, F. G., Meng, Y., Zheng, Y., Hsuan, J., Hamill, K. J., & McCormick, A. G. (2022). Informed Consent In Facial Photograph Publishing: A Cross-sectional Pilot Study To Determine The Effectiveness Of Deidentification Methods. JOURNAL OF EMPIRICAL RESEARCH ON HUMAN RESEARCH ETHICS, 17(3), 373-381. doi:10.1177/15562646221075459
Diagnosis of Diabetic Neuropathy by Artificial Intelligence using Corneal Confocal Microscopy
Meng, Y., Ferdousi, M., Petropoulos, I. N., Malik, R. A., Zhao, Y., Alam, U., & Zheng, Y. (2022). Diagnosis of Diabetic Neuropathy by Artificial Intelligence using Corneal Confocal Microscopy. In EUROPEAN JOURNAL OF OPHTHALMOLOGY Vol. 32 (pp. 11-12). Retrieved from https://www.webofscience.com/
3D Human Pose and Shape Reconstruction from Videos via Confidence-Aware Temporal Feature Aggregation
Zhang, H., Meng, Y., Zhao, Y., Qian, X., Qiao, Y., Yang, X., & Zheng, Y. (2022). 3D Human Pose and Shape Reconstruction from Videos via Confidence-Aware Temporal Feature Aggregation. IEEE Transactions on Multimedia, 1. doi:10.1109/tmm.2022.3167887
DTFD-MIL: Double-Tier Feature Distillation Multiple Instance Learning for Histopathology Whole Slide Image Classification
Zhang, H., Meng, Y., Zhao, Y., Qiao, Y., Yang, X., Coupland, S. E., & Zheng, Y. (2022). DTFD-MIL: Double-Tier Feature Distillation Multiple Instance Learning for Histopathology Whole Slide Image Classification. Retrieved from https://arxiv.org/abs/2203.12081v1
DTFD-MIL: Double-Tier Feature Distillation Multiple Instance Learning for Histopathology Whole Slide Image Classification
Graph-Based Region and Boundary Aggregation for Biomedical Image Segmentation
Meng, Y., Zhang, H., Zhao, Y., Yang, X., Qiao, Y., MacCormick, I. J. C., . . . Zheng, Y. (2022). Graph-Based Region and Boundary Aggregation for Biomedical Image Segmentation. IEEE TRANSACTIONS ON MEDICAL IMAGING, 41(3), 690-701. doi:10.1109/TMI.2021.3123567
DTFD-MIL: Double-Tier Feature Distillation Multiple Instance Learning for Histopathology Whole Slide Image Classification
Zhang, H., Meng, Y., Zhao, Y., Qiao, Y., Yang, X., Coupland, S. E., & Zheng, Y. (2022). DTFD-MIL: Double-Tier Feature Distillation Multiple Instance Learning for Histopathology Whole Slide Image Classification. In 2022 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2022) (pp. 18780-18790). doi:10.1109/CVPR52688.2022.01824
DTFD-MIL: Double-Tier Feature Distillation Multiple Instance Learning for Histopathology Whole Slide Image Classification.
Zhang, H., Meng, Y., Zhao, Y., Qiao, Y., Yang, X., Coupland, S. E., & Zheng, Y. (2022). DTFD-MIL: Double-Tier Feature Distillation Multiple Instance Learning for Histopathology Whole Slide Image Classification.. CoRR, abs/2203.12081.
2021
Artificial intelligence utilising corneal confocal microscopy for the diagnosis of peripheral neuropathy in diabetes mellitus and prediabetes
Preston, F. G., Meng, Y., Burgess, J., Ferdousi, M., Azmi, S., Petropoulos, I. N., . . . Alam, U. (2021). Artificial intelligence utilising corneal confocal microscopy for the diagnosis of peripheral neuropathy in diabetes mellitus and prediabetes. DIABETOLOGIA. doi:10.1007/s00125-021-05617-x
BI-GCN: Boundary-Aware Input-Dependent Graph Convolution Network for Biomedical Image Segmentation
BI-GCN: Boundary-Aware Input-Dependent Graph Convolution Network for Biomedical Image Segmentation
Meng, Y., Zhang, H., Gao, D., Zhao, Y., Yang, X., Qian, X., . . . Zheng, Y. (2021). BI-GCN: Boundary-Aware Input-Dependent Graph Convolution Network for Biomedical Image Segmentation. Retrieved from https://arxiv.org/abs/2110.14775v2
Spatial Uncertainty-Aware Semi-Supervised Crowd Counting
A regularization term for slide correlation reduction in whole slide image analysis with deep learning
Zhang, H., Meng, Y., Qian, X., Yang, X., Coupland, S. E., & Zheng, Y. (2021). A regularization term for slide correlation reduction in whole slide image analysis with deep learning. In MEDICAL IMAGING WITH DEEP LEARNING, VOL 143 Vol. 143 (pp. 812-+). Retrieved from https://www.webofscience.com/
A regularization term for slide correlation reduction in whole slide image analysis with deep learning.
Zhang, H., Meng, Y., Qian, X., Yang, X., Coupland, S. E., & Zheng, Y. (2021). A regularization term for slide correlation reduction in whole slide image analysis with deep learning.. In M. P. Heinrich, Q. Dou, M. D. Bruijne, J. Lellmann, A. Schlaefer, & F. Ernst (Eds.), MIDL Vol. 143 (pp. 842-854). PMLR. Retrieved from http://proceedings.mlr.press/v143/
BI-GCN: Boundary-Aware Input-Dependent Graph Convolution Network for Biomedical Image Segmentation
Meng, Y., Zhang, H., Gao, D., Zhao, Y., Yang, X., Qian, X., . . . Zheng, Y. (2021). BI-GCN: Boundary-Aware Input-Dependent Graph Convolution Network for Biomedical Image Segmentation. In 32nd British Machine Vision Conference Bmvc 2021.
Learning Unsupervised Parameter-Specific Affine Transformation for Medical Images Registration
Chen, X., Meng, Y., Zhao, Y., Williams, R., Vallabhaneni, S. R., & Zheng, Y. (2021). Learning Unsupervised Parameter-Specific Affine Transformation for Medical Images Registration. In MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION - MICCAI 2021, PT IV Vol. 12904 (pp. 24-34). doi:10.1007/978-3-030-87202-1_3
Spatial Uncertainty-Aware Semi-Supervised Crowd Counting
Meng, Y., Zhang, H., Zhao, Y., Yang, X., Qian, X., Huang, X., & Zheng, Y. (2021). Spatial Uncertainty-Aware Semi-Supervised Crowd Counting. In 2021 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV 2021) (pp. 15529-15539). doi:10.1109/ICCV48922.2021.01526
TransBridge: A Lightweight Transformer for Left Ventricle Segmentation in Echocardiography
Deng, K., Meng, Y., Gao, D., Bridge, J., Shen, Y., Lip, G., . . . Zheng, Y. (2021). TransBridge: A Lightweight Transformer for Left Ventricle Segmentation in Echocardiography. In SIMPLIFYING MEDICAL ULTRASOUND Vol. 12967 (pp. 63-72). doi:10.1007/978-3-030-87583-1_7
2020
Introducing the GEV Activation Function for Highly Unbalanced Data to Develop COVID-19 Diagnostic Models
Bridge, J., Meng, Y., Zhao, Y., Du, Y., Zhao, M., Sun, R., & Zheng, Y. (2020). Introducing the GEV Activation Function for Highly Unbalanced Data to Develop COVID-19 Diagnostic Models. IEEE Journal of Biomedical and Health Informatics, 1. doi:10.1109/jbhi.2020.3012383
Undated
Corneal Confocal Microscopy Based Deep Learning Algorithms Demonstrate Excellent Diagnostic Accuracy in Identifying Patients with Dementia, Multiple Sclerosis and Parkinson's Disease
Meng, Y., Anson, M., Preston, F., Burgess, J., Ferdousi, M., Silverdale, M., . . . Alam, U. (n.d.). Corneal Confocal Microscopy Based Deep Learning Algorithms Demonstrate Excellent Diagnostic Accuracy in Identifying Patients with Dementia, Multiple Sclerosis and Parkinson's Disease.