* denotes equal contribution; ^ denotes corresponding authorship.
2022
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Unsupervised Anomaly Detection in Medical Images with a Memory-augmented Multi-level Cross-attentional Masked Autoencoder
Yu Tian, Guansong Pang, Yuyuan Liu, Chong Wang, Yuanhong Chen, Fengbei Liu, Rajvinder Singh, Johan W Verjans, and Gustavo Carneiro
arXiv preprint 2022
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Self-supervised Multi-class Pre-training for Unsupervised Anomaly Detection and Segmentation in Medical Images
Yu Tian*, Fengbei Liu*, Guansong Pang, Yuanhong Chen, Yuyuan Liu, Johan W Verjans, Rajvinder Singh, and Gustavo Carneiro
arXiv preprint 2022
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Translation Consistent Semi-supervised Segmentation for 3D Medical Images
Yuyuan Liu, Yu Tian, Chong Wang, Yuanhong Chen, Fengbei Liu, Vasileios Belagiannis, and Gustavo Carneiro
arXiv preprint 2022
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Semantic-guided Image Virtual Attribute Learning for Noisy Multi-label Chest X-ray Classification
Yuanhong Chen*, Fengbei Liu*, Yu Tian, Yuyuan Liu, and Gustavo Carneiro
arXiv preprint 2022
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Artifact-Tolerant Clustering-Guided Contrastive Embedding Learning for Ophthalmic Images
Min Shi, Anagha Lokhande, Mojtaba S Fazli, Vishal Sharma, Yu Tian, Yan Luo, Louis R Pasquale, Tobias Elze, Michael V Boland, Nazlee Zebardast, and others
arXiv preprint 2022
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Pixel-wise Energy-biased Abstention Learning for Anomaly Segmentation on Complex Urban Driving Scenes
Yu Tian*, Yuyuan Liu*, Guansong Pang, Fengbei Liu, Yuanhong Chen, and Gustavo Carneiro
European Conference on Computer Vision (ECCV Oral) 2022
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Contrastive Transformer-based Multiple Instance Learning for Weakly Supervised Polyp Frame Detection
Yu Tian, Guansong Pang, Fengbei Liu, Yuyuan Liu, Chong Wang, Yuanhong Chen, Johan W Verjans, and Gustavo Carneiro
International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI Early Accept) 2022
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NVUM: Non-Volatile Unbiased Memory for Robust Medical Image Classification
Fengbei Liu, Yuanhong Chen, Yu Tian, Yuyuan Liu, Chong Wang, Vasileios Belagiannis, and Gustavo Carneiro
International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI Early Accept) 2022
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Multi-view Local Co-occurrence and Global Consistency Learning Improve Mammogram Classification Generalisation
Yuanhong Chen, Wang Hu, Chong Wang, Yu Tian, Fengbei Liu, Yuyuan Liu, Michael Elliott, Davis McCarthy, Helen Frazer, and Gustavo Carneiro
International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI Early Accept) 2022
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Knowledge Distillation to Ensemble Global and Interpretable Prototype-based Mammogram Classification Models
Chong Wang, Yuanhong Chen, Yuyuan Liu, Yu Tian, Fengbei Liu, Davis McCarthy, Michael Elliott, Helen Frazer, and Gustavo Carneiro
International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI Early Accept) 2022
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ACPL: Anti-curriculum Pseudo-labelling for Semi-supervised Medical Image Classification
Fengbei Liu*, Yu Tian*, Yuanhong Chen, Yuyuan Liu, Vasileios Belagiannis, and Gustavo Carneiro
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2022
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Perturbed and Strict Mean Teachers for Semi-supervised Semantic Segmentation
Yuyuan Liu, Yu Tian, Yuanhong Chen, Fengbei Liu, Vasileios Belagiannis, and Gustavo Carneiro
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2022
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Deep One-Class Classification via Interpolated Gaussian Descriptor
Yuanhong Chen*, Yu Tian*^, Guansong Pang, and Gustavo Carneiro
In Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI Oral) 2022
2021
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Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learning
Yu Tian, Guansong Pang, Yuanhong Chen, Rajvinder Singh, Johan W Verjans, and Gustavo Carneiro
In Proceedings of the IEEE/CVF international conference on computer vision (ICCV) 2021
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Constrained Contrastive Distribution Learning for Unsupervised Anomaly Detection and Localisation in Medical Images
Yu Tian, Guansong Pang, Fengbei Liu, Seon Ho Shin, Johan W Verjans, Rajvinder Singh, Gustavo Carneiro, and others
In International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2021
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Self-supervised Mean Teacher for Semi-supervised Chest X-ray Classification
Fengbei Liu*, Yu Tian*, Filipe R Cordeiro, Vasileios Belagiannis, Ian Reid, and Gustavo Carneiro
In International Workshop on Machine Learning in Medical Imaging (MICCAI-MLMI) 2021
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Detecting, Localising and Classifying Polyps from Colonoscopy Videos using Deep Learning
Yu Tian, Leonardo Zorron Cheng Tao Pu, Yuyuan Liu, Gabriel Maicas, Johan W Verjans, Alastair D Burt, Seon Ho Shin, Rajvinder Singh, and Gustavo Carneiro
Deep Learning for Medical Image Analysis (second edition) 2021
2020
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Few-shot anomaly detection for polyp frames from colonoscopy
Yu Tian, Gabriel Maicas, Leonardo Zorron Cheng Tao Pu, Rajvinder Singh, Johan W Verjans, and Gustavo Carneiro
In International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2020
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Computer-aided diagnosis for characterization of colorectal lesions: comprehensive software that includes differentiation of serrated lesions
Leonardo Zorron Cheng Tao Pu, Gabriel Maicas, Yu Tian, Takeshi Yamamura, Masanao Nakamura, Hiroto Suzuki, Gurfarmaan Singh, Khizar Rana, Yoshiki Hirooka, Alastair D Burt, and others
Gastrointestinal endoscopy (GIE) 2020
2019
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One-stage five-class polyp detection and classification
Yu Tian, Leonardo ZCT Pu, Rajvinder Singh, Alastair D Burt, and Gustavo Carneiro
In IEEE 16th International Symposium on Biomedical Imaging (ISBI) 2019
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Prospective study assessing a comprehensive computer-aided diagnosis for characterization of colorectal lesions: results from different centers and imaging technologies
Leonardo Zorron Cheng Tao Pu, Gabriel Maicas, Yu Tian, Takeshi Yamamura, Gurfarmaan Singh, Khizar Rana, Hiroto Suzuki, Masanao Nakamura, Yoshiki Hirooka, and others
Journal of Gastroenterology and Hepatology (JGH) 2019
Semantic-guided Image Virtual Attribute Learning for Noisy Multi-label Chest X-ray ClassificationarXiv preprint 2022
Artifact-Tolerant Clustering-Guided Contrastive Embedding Learning for Ophthalmic ImagesarXiv preprint 2022
Multi-view Local Co-occurrence and Global Consistency Learning Improve Mammogram Classification GeneralisationInternational Conference on Medical Image Computing and Computer-Assisted Intervention (
Knowledge Distillation to Ensemble Global and Interpretable Prototype-based Mammogram Classification ModelsInternational Conference on Medical Image Computing and Computer-Assisted Intervention (
Detecting, Localising and Classifying Polyps from Colonoscopy Videos using Deep LearningDeep Learning for Medical Image Analysis (second edition) 2021
Photoshopping colonoscopy video framesIn IEEE 17th International Symposium on Biomedical Imaging (
Computer-aided diagnosis for characterization of colorectal lesions: comprehensive software that includes differentiation of serrated lesionsGastrointestinal endoscopy (
One-stage five-class polyp detection and classificationIn IEEE 16th International Symposium on Biomedical Imaging (