Publications
2024
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
Randomness-restricted Diffusion Model for Ocular Surface Structure Segmentation.
Guo, X., Wen, H., Hao, H., Zhao, Y., Meng, Y., Liu, J., . . . Zhao, Y. (2024). Randomness-restricted Diffusion Model for Ocular Surface Structure Segmentation.. IEEE transactions on medical imaging, PP. doi:10.1109/tmi.2024.3494762
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. (2024). 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, PP. doi:10.1109/jbhi.2024.3467256
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., Piaśnik, 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), 296. doi:10.1186/s12933-024-02367-z
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., Nguyen, A., Yang, X., & Zheng, Y. (n.d.). Dynamic Semantic-Based Spatial Graph Convolution Network for Skeleton-Based Human Action Recognition. In Proceedings of the AAAI Conference on Artificial Intelligence Vol. 38 (pp. 6225-6233). Association for the Advancement of Artificial Intelligence (AAAI). doi:10.1609/aaai.v38i6.28440
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, 1421439. doi:10.3389/fmed.2024.1421439
CLIP-DR: Textual Knowledge-Guided Diabetic Retinopathy Grading with Ranking-Aware Prompting
Yu, Q., Xie, J., Nguyen, A., Zhao, H., Zhang, J., Fu, H., . . . Meng, Y. (2024). CLIP-DR: Textual Knowledge-Guided Diabetic Retinopathy Grading with Ranking-Aware Prompting. In Lecture Notes in Computer Science (pp. 667-677). Springer Nature Switzerland. doi:10.1007/978-3-031-72378-0_62
Multi-disease Detection in Retinal Images Guided by Disease Causal Estimation
Xie, J., Chen, X., Zhao, Y., Meng, Y., Zhao, H., Nguyen, A., . . . Zheng, Y. (2024). Multi-disease Detection in Retinal Images Guided by Disease Causal Estimation. In Lecture Notes in Computer Science (pp. 743-753). Springer Nature Switzerland. 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, 1-10. 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 Proceedings of the Annual Meeting of the Association for Computational Linguistics (pp. 1830-1842).
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 Unknown Conference (pp. 98-109). Springer Nature Singapore. 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). 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. 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 Unknown Conference (pp. 49-59). Springer Nature Switzerland. doi:10.1007/978-3-031-31778-1_5
2022
Retinal Imaging Technologies in Cerebral Malaria: A Systematic Review
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). 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
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 http://arxiv.org/abs/2203.12081v1
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
Development and External Validation of a Mixed-Effects Deep Learning Model to Diagnose COVID-19 from CT Imaging
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.
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/
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
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 http://arxiv.org/abs/2110.14775v2
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
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 Proceedings of Machine Learning Research Vol. 143 (pp. 812-824).
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
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.