| Fully automatic left atrium segmentation from late gadolinium enhanced magnetic resonance imaging using a dual fully convolutional neural network Z Xiong, VV Fedorov, X Fu, E Cheng, R Macleod, J Zhao IEEE transactions on medical imaging 38 (2), 515-524, 2018 | 150 | 2018 |
| Multimodal spatial attention module for targeting multimodal PET-CT lung tumor segmentation X Fu, L Bi, A Kumar, M Fulham, J Kim IEEE Journal of Biomedical and Health Informatics 25 (9), 3507-3516, 2021 | 124 | 2021 |
| Segmentation of histological images and fibrosis identification with a convolutional neural network X Fu, T Liu, Z Xiong, BH Smaill, MK Stiles, J Zhao Computers in biology and medicine 98, 147-158, 2018 | 49 | 2018 |
| An attention-enhanced cross-task network to analyse lung nodule attributes in CT images X Fu, L Bi, A Kumar, M Fulham, J Kim Pattern Recognition 126, 108576, 2022 | 36 | 2022 |
| BIDCell: Biologically-informed self-supervised learning for segmentation of subcellular spatial transcriptomics data X Fu, Y Lin, DM Lin, D Mechtersheimer, C Wang, F Ameen, S Ghazanfar, ... Nature Communications 15 (1), 509, 2024 | 27 | 2024 |
| Graph-based intercategory and intermodality network for multilabel classification and melanoma diagnosis of skin lesions in dermoscopy and clinical images X Fu, L Bi, A Kumar, M Fulham, J Kim IEEE Transactions on Medical Imaging 41 (11), 3266-3277, 2022 | 24 | 2022 |
| Deep multimodal graph-based network for survival prediction from highly multiplexed images and patient variables X Fu, E Patrick, JYH Yang, DD Feng, J Kim Computers in Biology and Medicine 154, 106576, 2023 | 15 | 2023 |
| Hybrid CNN-transformer network for interactive learning of challenging musculoskeletal images L Bi, U Buehner, X Fu, T Williamson, P Choong, J Kim Computer Methods and Programs in Biomedicine 243, 107875, 2024 | 4 | 2024 |
| CT-based radiogenomics framework for COVID-19 using ACE2 imaging representations T Xia, X Fu, M Fulham, Y Wang, D Feng, J Kim Journal of Digital Imaging 36 (6), 2356-2366, 2023 | 2 | 2023 |
| Benchmarking the translational potential of spatial gene expression prediction from histology AS Chan, C Wang, X Fu, S Ghazanfar, J Kim, E Patrick, JYH Yang bioRxiv, 2023.12. 12.571251, 2023 | 2 | 2023 |
| Hyper-connected transformer network for co-learning multi-modality pet-ct features L Bi, X Fu, Q Liu, S Song, DD Feng, M Fulham, J Kim arXiv, 2022 | 2 | 2022 |
| Attention-enhanced cross-task network for analysing multiple attributes of lung nodules in ct X Fu, L Bi, A Kumar, M Fulham, J Kim arXiv preprint arXiv:2103.03931, 2021 | 2 | 2021 |
| Spatial gene expression at single-cell resolution from histology using deep learning with GHIST X Fu, Y Cao, B Bian, C Wang, D Graham, N Pathmanathan, E Patrick, ... BioRxiv, 2024.07. 02.601790, 2024 | 1 | 2024 |
| A Message Passing Framework for Precise Cell State Identification with scClassify2 W Ding, Y Cao, X Fu, M Torkel, J Yang bioRxiv, 2024.06. 26.600770, 2024 | | 2024 |
| Co-Learning Multi-Modality PET-CT Features via a Cascaded CNN-Transformer Network L Bi, X Fu, Q Liu, S Song, DD Feng, M Fulham, J Kim IEEE Transactions on Radiation and Plasma Medical Sciences, 2024 | | 2024 |
| Biologically-informed self-supervised learning for segmentation of subcellular spatial transcriptomics data X Fu, Y Lin, DM Lin, D Mechtersheimer, C Wang, F Ameen, S Ghazanfar, ... bioRxiv, 2023.06. 13.544733, 2023 | | 2023 |
| Machine Learning Methods for Multimodal and Multilabel Biomedical Image Analysis X Fu University of Sydney, 2023 | | 2023 |
Jinman KimSchool of Computer Science, University of SydneyVerified email at sydney.edu.au