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ORCIDHongxiang Lin
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2020 – today
- 2024
[c20]Minghui Wu, Yangdi Xu, Yingying Xu, Guangwei Wu, Qingqing Chen, Hongxiang Lin:
Stable Optimization for Large Vision Model Based Deep Image Prior in Cone-Beam CT Reconstruction. ICASSP 2024: 1581-1585- [c19]Yingying Xu, Yinjie Wang, Qingqing Chen, Hongjie Hu, Huimin Huang, Lanfen Lin, Yen-Wei Chen, Jingsong Li, Hongxiang Lin:
FPGA Oriented Lightweight Deep Learning Inference for Liver Cancer Segmentation. ISBI 2024: 1-5 - 2023
- [j2]Syed Furqan Qadri
, Hongxiang Lin, Linlin Shen, Mubashir Ahmad, Salman Qadri, Salabat Khan, Maqbool Khan, Syeda Shamaila Zareen, Muhammad Azeem Akbar, Md Belal Bin Heyat, Saqib Qamar:
CT-Based Automatic Spine Segmentation Using Patch-Based Deep Learning. Int. J. Intell. Syst. 2023: 1-14 (2023) - [j1]Hongxiang Lin, Matteo Figini, Felice D'Arco, Godwin Ogbole, Ryutaro Tanno, Stefano B. Blumberg, Lisa Ronan, Biobele J. Brown, David W. Carmichael, Ikeoluwa Lagunju, Judith Helen Cross, Delmiro Fernandez-Reyes, Daniel C. Alexander:
Low-field magnetic resonance image enhancement via stochastic image quality transfer. Medical Image Anal. 87: 102807 (2023) - [c18]Minchong Wu, Hongxiang Lin, Xiaoqing Lyu, Chenrui Zhang, Sun Yu:
Enabling Large Language Models to Think Twice When Its Answer Is Unreliable: A Case Study In Cancer Screening. BIBM 2023: 4975-4977 - [c17]Han Liu, Hongxiang Lin, Xiaotong Zhang, Fenglong Ma, Hongyang Chen, Lei Wang, Hong Yu, Xianchao Zhang:
Boosting Meta-Learning Cold-Start Recommendation with Graph Neural Network. CIKM 2023: 4105-4109 - [c16]Changshan Han, He Huang, Zhengfeng Lan, Zeyu Zhuang, Jingsong Li, Hongxiang Lin:
Pulse Stretching Correction for Improving Ultrasound Image Resolution. EMBC 2023: 1-4 - [c15]He Huang, Zheng Li, Changshan Han, Guangwei Wu, Zeyu Zhuang, Jingsong Li, Hongxiang Lin:
Auto-tuning numerical method for acoustic wave simulation using analytical solution. EMBC 2023: 1-4 - [c14]Zhengfeng Lan, Chao Rong, Changshan Han, Xiaolei Qu, Jingsong Li, Hongxiang Lin:
A joint method of coherence factor and nonlinear beamforming for synthetic aperture imaging with a ring array. EMBC 2023: 1-4 - [c13]Yangdi Xu, Jingsong Li, Hongxiang Lin:
Deep Fusion Network Based Sparse View CT Reconstructions for Clinical Diagnostic Scanners. EMBC 2023: 1-4 - [c12]Yucheng Tang, Yipeng Hu, Jing Li, Hu Lin, Xiang Xu, Ke Huang, Hongxiang Lin:
PLD-AL: Pseudo-label Divergence-Based Active Learning in Carotid Intima-Media Segmentation for Ultrasound Images. MICCAI (2) 2023: 57-67 - [c11]Yixiao Zhou, Ruiqi Jia, Hongxiang Lin, Hefeng Quan, Yumeng Zhao, Xiaoqing Lyu:
Improving Graph Matching with Positional Reconstruction Encoder-Decoder Network. NeurIPS 2023 - [c10]Hongxiang Lin, Ruiqi Jia, Xiaoqing Lyu:
Gated Attention with Asymmetric Regularization for Transformer-based Continual Graph Learning. SIGIR 2023: 2021-2025 - [i8]Hongxiang Lin, Matteo Figini, Felice D'Arco, Godwin Ogbole, Ryutaro Tanno, Stefano B. Blumberg, Lisa Ronan, Biobele J. Brown, David W. Carmichael, Ikeoluwa Lagunju, Judith Helen Cross, Delmiro Fernandez-Reyes, Daniel C. Alexander:
Low-field magnetic resonance image enhancement via stochastic image quality transfer. CoRR abs/2304.13385 (2023) - 2022
- [c9]Zhiwei Lin, Yongtao Wang, Hongxiang Lin:
Continual Contrastive Learning for Image Classification. ICME 2022: 1-6 - [c8]Stefano B. Blumberg, Hongxiang Lin, Francesco Grussu, Yukun Zhou, Matteo Figini, Daniel C. Alexander:
Progressive Subsampling for Oversampled Data - Application to Quantitative MRI. MICCAI (6) 2022: 421-431 - [i7]Stefano B. Blumberg, Hongxiang Lin, Francesco Grussu, Yukun Zhou, Matteo Figini, Daniel C. Alexander:
Progressive Subsampling for Oversampled Data - Application to Quantitative MRI. CoRR abs/2203.09268 (2022) - [i6]Minghui Wu, Yangdi Xu, Yingying Xu, Guangwei Wu, Qingqing Chen, Hongxiang Lin:
Adaptively Re-weighting Multi-Loss Untrained Transformer for Sparse-View Cone-Beam CT Reconstruction. CoRR abs/2203.12476 (2022) - [i5]Stefano B. Blumberg, Hongxiang Lin, Yukun Zhou, Paddy Slator, Daniel C. Alexander:
An Experiment Design Paradigm using Joint Feature Selection and Task Optimization. CoRR abs/2210.06891 (2022) - 2021
- [c7]Wen Youpeng, Hongxiang Lin, Guo Yiju, Zhao Liang:
AMVAE: Asymmetric Multimodal Variational Autoencoder for Multi-view Representation. ICANN (1) 2021: 391-402 - [c6]Hongxiang Lin, Yukun Zhou, Paddy J. Slator, Daniel C. Alexander:
Generalised Super Resolution for Quantitative MRI Using Self-supervised Mixture of Experts. MICCAI (6) 2021: 44-54 - [c5]Yukun Zhou, Moucheng Xu, Yipeng Hu, Hongxiang Lin, Joseph Jacob, Pearse A. Keane, Daniel C. Alexander:
Learning to Address Intra-segment Misclassification in Retinal Imaging. MICCAI (1) 2021: 482-492 - [i4]Yukun Zhou, Moucheng Xu, Yipeng Hu, Hongxiang Lin, Joseph Jacob, Pearse A. Keane, Daniel C. Alexander:
Learning to Address Intra-segment Misclassification in Retinal Imaging. CoRR abs/2104.12138 (2021) - [i3]Zhiwei Lin, Yongtao Wang, Hongxiang Lin:
Continual Contrastive Self-supervised Learning for Image Classification. CoRR abs/2107.01776 (2021) - 2020
- [i2]Matteo Figini, Hongxiang Lin, Godwin Ogbole, Felice D'Arco, Stefano B. Blumberg, David W. Carmichael, Ryutaro Tanno, Enrico Kaden, Biobele J. Brown, Ikeoluwa Lagunju, Helen J. Cross, Delmiro Fernandez-Reyes, Daniel C. Alexander:
Image Quality Transfer Enhances Contrast and Resolution of Low-Field Brain MRI in African Paediatric Epilepsy Patients. CoRR abs/2003.07216 (2020)
2010 – 2019
- 2019
- [c4]Hongxiang Lin, Matteo Figini, Ryutaro Tanno, Stefano B. Blumberg, Enrico Kaden, Godwin Ogbole, Biobele J. Brown, Felice D'Arco, David W. Carmichael, Ikeoluwa Lagunju, Helen J. Cross, Delmiro Fernandez-Reyes, Daniel C. Alexander:
Deep Learning for Low-Field to High-Field MR: Image Quality Transfer with Probabilistic Decimation Simulator. MLMIR@MICCAI 2019: 58-70 - [c3]Neil P. Oxtoby, Fabio S. Ferreira, Ágoston Mihalik, Tong Wu, Mikael Brudfors, Hongxiang Lin, Anita Rau, Stefano B. Blumberg, Maria Robu, Cemre Zor, Maira Tariq, Mar Estarellas Garcia, Baris Kanber, Daniil I. Nikitichev, Janaina Mourão Miranda:
ABCD Neurocognitive Prediction Challenge 2019: Predicting Individual Residual Fluid Intelligence Scores from Cortical Grey Matter Morphology. ABCD-NP@MICCAI 2019: 114-123 - [c2]Ágoston Mihalik, Mikael Brudfors, Maria Robu, Fabio S. Ferreira, Hongxiang Lin, Anita Rau, Tong Wu, Stefano B. Blumberg, Baris Kanber, Maira Tariq, Mar Estarellas Garcia, Cemre Zor, Daniil I. Nikitichev, Janaina Mourão Miranda, Neil P. Oxtoby:
ABCD Neurocognitive Prediction Challenge 2019: Predicting Individual Fluid Intelligence Scores from Structural MRI Using Probabilistic Segmentation and Kernel Ridge Regression. ABCD-NP@MICCAI 2019: 133-142 - [i1]Hongxiang Lin, Matteo Figini, Ryutaro Tanno, Stefano B. Blumberg, Enrico Kaden, Godwin Ogbole, Biobele J. Brown, Felice D'Arco, David W. Carmichael, Ikeoluwa Lagunju, Helen J. Cross, Delmiro Fernandez-Reyes, Daniel C. Alexander:
Deep Learning for Low-Field to High-Field MR: Image Quality Transfer with Probabilistic Decimation Simulator. CoRR abs/1909.06763 (2019) - 2018
- [c1]Hongxiang Lin, Takashi Azuma, Mehmet Burcin Unlu, Shu Takagi:
Evaluation of Adjoint Methods in Photoacoustic Tomography with Under-Sampled Sensors. MICCAI (1) 2018: 73-81
Coauthor Index
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