Publications

My work spans cervical spine imaging, medical anomaly detection, image reconstruction, and quantitative imaging.

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Author role

First- and co-first-author publications

Journal badges use 2025 JIF/JCR data and the 2025 CAS journal partition; MICCAI uses the March 2026 CCF list.

Review Figure 1 connecting cervical X-ray, CT, and MRI with six artificial-intelligence task groups — Fig. 1 · Manuscript figure

Under ReviewCo-first author

Artificial intelligence for degenerative cervical myelopathy imaging: a systematic review across tasks and modalities

Qi Zhang^†, Xiuyuan Chen^†, Zihui Wang^†, Kun Wang, Lianming Wu, Hongxing Shen, Jianqi Sun

Manuscript under review · 2026

This systematic review examines 103 studies of artificial intelligence for degenerative cervical myelopathy across MRI, CT, X-ray, and six task groups. It summarises current evidence and the recurring challenges of retrospective single-centre data and limited external validation.

Project

BibTeX

Artificial intelligence for degenerative cervical myelopathy imaging: a systematic review across tasks and modalities

@unpublished{zhang2026dcmreview,
  title={Artificial intelligence for degenerative cervical myelopathy imaging: a systematic review across tasks and modalities},
  author={Zhang, Qi and Chen, Xiuyuan and Wang, Zihui and Wang, Kun and Wu, Lianming and Shen, Hongxing and Sun, Jianqi},
  year={2026},
  note={Manuscript under review}
}

Paper Figure 1 showing the workflow from dataset construction and pathology-guided segmentation to expert-based diagnosis — Fig. 1 · Paper figure

PublishedCo-first author2025 JIF · 6.8JCR Q1CAS 2025 · Tier 2 · Top

Pathology-Guided AI System for Accurate Segmentation and Diagnosis of Cervical Spondylosis

Qi Zhang^†, Xiuyuan Chen^†, Ziyi He^†, Lianming Wu, Kun Wang, Jianqi Sun, Hongxing Shen

IEEE Journal of Biomedical and Health Informatics · 2026 · 30(2) · 1216-1229

This pathology-guided system links cervical MRI segmentation with automated calculation of clinically relevant indicators. The design emphasises interpretable measurements and validation across clinical data sources.

DOI10.1109/JBHI.2025.3598469

Paper Code Project

BibTeX

Pathology-Guided AI System for Accurate Segmentation and Diagnosis of Cervical Spondylosis

@article{zhang2026pathology,
  title={Pathology-Guided AI System for Accurate Segmentation and Diagnosis of Cervical Spondylosis},
  author={Zhang, Qi and Chen, Xiuyuan and He, Ziyi and Wu, Lianming and Wang, Kun and Sun, Jianqi and Shen, Hongxing},
  journal={IEEE Journal of Biomedical and Health Informatics},
  volume={30},
  number={2},
  pages={1216--1229},
  year={2026},
  doi={10.1109/JBHI.2025.3598469}
}

JointSR Figure 2 showing the anatomy-style decoupled hybrid implicit neural representation framework — Fig. 2 · Paper figure

PublishedCo-first authorCCF B · 2026MICCAI · Premier conference

Reconstructing Isotropic 3D Cervical MRI from Anisotropic Clinical Scans via Anatomy-Style Decoupled INRs

Qi Zhang^†, Xiuyuan Chen^†, Yibo Hu, Hongxing Shen, Jianqi Sun

Medical Image Computing and Computer Assisted Intervention - MICCAI 2026 · 2026 · 16888 · 478-487

Published online 26 September 2026. Springer lists 2027 as the citation year.

An anatomy-style decoupled hybrid implicit neural representation reconstructs an isotropic 3D cervical MRI volume from routine anisotropic multi-view scans. The method uses unified spatial coordinates, view-specific style embeddings, and stochastic view dropout without paired high-resolution supervision.

DOI10.1007/978-3-032-38179-8_46

Paper Code Project

BibTeX

Reconstructing Isotropic 3D Cervical MRI from Anisotropic Clinical Scans via Anatomy-Style Decoupled INRs

@inproceedings{zhang2026jointsr,
  title={Reconstructing Isotropic 3D Cervical MRI from Anisotropic Clinical Scans via Anatomy-Style Decoupled INRs},
  author={Zhang, Qi and Chen, Xiuyuan and Hu, Yibo and Shen, Hongxing and Sun, Jianqi},
  booktitle={Medical Image Computing and Computer Assisted Intervention -- MICCAI 2026},
  series={Lecture Notes in Computer Science},
  volume={16888},
  pages={478--487},
  publisher={Springer Nature Switzerland},
  year={2027},
  doi={10.1007/978-3-032-38179-8_46}
}

U2AD Figure 2 showing preprocessing, healthy-image pretraining, and uncertainty-guided adaptation — Fig. 2 · Paper figure

PublishedCo-first author2025 JIF · 14.0JCR Q1CAS 2025 · Tier 1 · Top

U2AD: Uncertainty-based unsupervised anomaly detection framework for detecting T2 hyperintensity in MRI spinal cord

Qi Zhang^†, Xiuyuan Chen^†, Ziyi He^†, Kun Wang^†, Lianming Wu, Hongxing Shen, Jianqi Sun

Medical Image Analysis · 2026 · 109 · 103939

U2AD detects spinal-cord T2 hyperintensity without requiring abnormal-region annotations. Its uncertainty-guided masking strategy balances reconstruction of normal anatomy with sensitivity to anomalies.

DOI10.1016/j.media.2026.103939

Paper Code Project

BibTeX

U2AD: Uncertainty-based unsupervised anomaly detection framework for detecting T2 hyperintensity in MRI spinal cord

@article{zhang2026u2ad,
  title={U2AD: Uncertainty-based unsupervised anomaly detection framework for detecting T2 hyperintensity in MRI spinal cord},
  author={Zhang, Qi and Chen, Xiuyuan and He, Ziyi and Wang, Kun and Wu, Lianming and Shen, Hongxing and Sun, Jianqi},
  journal={Medical Image Analysis},
  volume={109},
  pages={103939},
  year={2026},
  doi={10.1016/j.media.2026.103939}
}

UniTransAD Figure 3 showing the training framework, cross-sequence alignment, and adaptive fusion module — Fig. 3 · Paper figure

PublishedFirst author2025 JIF · 12.4JCR Q1CAS 2025 · Tier 1 · Top

UniTransAD: Unified Translation Framework for Anomaly Detection in Brain MRI

Qi Zhang, Xia Li, Yibo Hu, Jianqi Sun

IEEE Transactions on Medical Imaging · 2026 · 45(9) · 4876-4891

A unified translation framework addresses brain MRI anomaly detection across diseases, sequences, and missing-input settings. Dynamic style prototypes and dual-level evidence support flexible inference under different combinations of MRI inputs.

DOI10.1109/TMI.2026.3711975

Paper Code Project

BibTeX

UniTransAD: Unified Translation Framework for Anomaly Detection in Brain MRI

@article{zhang2026unitransad,
  title={UniTransAD: Unified Translation Framework for Anomaly Detection in Brain MRI},
  author={Zhang, Qi and Li, Xia and Hu, Yibo and Sun, Jianqi},
  journal={IEEE Transactions on Medical Imaging},
  year={2026},
  volume={45},
  number={9},
  pages={4876--4891},
  doi={10.1109/TMI.2026.3711975}
}

HealthiVert-GAN Figure 2 showing preprocessing, coarse-to-fine generation, iterative synthesis, quantification, and grading — Fig. 2 · Paper figure

PublishedFirst author2025 JIF · 6.8JCR Q1CAS 2025 · Tier 2 · Top

HealthiVert-GAN: A Novel Framework of Pseudo-Healthy Vertebral Image Synthesis for Interpretable Compression Fracture Grading

Qi Zhang, Cheng Chuang, Shunan Zhang, Ziqi Zhao, Kun Wang, Jun Xu, Jianqi Sun

IEEE Journal of Biomedical and Health Informatics · 2025 · 29(10) · 7299-7311

HealthiVert-GAN synthesises a pseudo-healthy vertebral reference from CT to support interpretable compression-fracture assessment. Relative height loss turns image synthesis into a measurable grading workflow.

DOI10.1109/JBHI.2025.3572458

Paper Code Project

BibTeX

HealthiVert-GAN: A Novel Framework of Pseudo-Healthy Vertebral Image Synthesis for Interpretable Compression Fracture Grading

@article{zhang2025healthivert,
  title={HealthiVert-GAN: A Novel Framework of Pseudo-Healthy Vertebral Image Synthesis for Interpretable Compression Fracture Grading},
  author={Zhang, Qi and Chuang, Cheng and Zhang, Shunan and Zhao, Ziqi and Wang, Kun and Xu, Jun and Sun, Jianqi},
  journal={IEEE Journal of Biomedical and Health Informatics},
  volume={29},
  number={10},
  pages={7299--7311},
  year={2025},
  doi={10.1109/JBHI.2025.3572458}
}

MultiTransAD Figure 1 showing cross-sequence translation, feature alignment, adaptive fusion, and image generation — Fig. 1 · Paper figure

PublishedFirst authorCCF B · 2026MICCAI · Premier conference

MultiTransAD: Cross-Sequence Translation-Driven Anomaly Detection in Multi-sequence Brain MRI

Qi Zhang, Yibo Hu, Jianqi Sun

Medical Image Computing and Computer Assisted Intervention - MICCAI 2025 · 2025 · LNCS 15961 · 389-398

MultiTransAD uses translation between MRI sequences to expose anomalies as cross-sequence inconsistencies. Content-style disentanglement and dual-level evidence combine anatomical structure with contrast information.

DOI10.1007/978-3-032-04937-7_37

Paper Code Project

BibTeX

MultiTransAD: Cross-Sequence Translation-Driven Anomaly Detection in Multi-sequence Brain MRI

@inproceedings{zhang2025multitransad,
  title={MultiTransAD: Cross-Sequence Translation-Driven Anomaly Detection in Multi-sequence Brain MRI},
  author={Zhang, Qi and Hu, Yibo and Sun, Jianqi},
  booktitle={Medical Image Computing and Computer Assisted Intervention -- MICCAI 2025},
  series={Lecture Notes in Computer Science},
  volume={15961},
  pages={389--398},
  publisher={Springer Nature Switzerland},
  year={2025},
  doi={10.1007/978-3-032-04937-7_37}
}

Paper Figure 2 showing knee MRI input, automatic cartilage segmentation, quantitative parameter calculation, and validation — Fig. 2 · Paper figure

PublishedFirst author2025 JIF · 2.8JCR Q2CAS 2025 · Tier 3

Cartilage morphometry and magnetic susceptibility measurement for knee osteoarthritis with automatic cartilage segmentation

Qi Zhang, Jiaolun Geng, Ming Zhang, Tianyou Kan, Liao Wang, Songtao Ai, Hongjiang Wei, Lichi Zhang, Chenglei Liu

Quantitative Imaging in Medicine and Surgery · 2023 · 13(6) · 3508-3521

This study combines automatic cartilage segmentation with morphometric and magnetic-susceptibility measurements in knee MRI. It links image analysis to reproducible quantitative assessment of osteoarthritis-related cartilage changes.

DOI10.21037/qims-22-1245

Paper

BibTeX

Cartilage morphometry and magnetic susceptibility measurement for knee osteoarthritis with automatic cartilage segmentation

@article{zhang2023cartilage,
  title={Cartilage morphometry and magnetic susceptibility measurement for knee osteoarthritis with automatic cartilage segmentation},
  author={Zhang, Qi and Geng, Jiaolun and Zhang, Ming and Kan, Tianyou and Wang, Liao and Ai, Songtao and Wei, Hongjiang and Zhang, Lichi and Liu, Chenglei},
  journal={Quantitative Imaging in Medicine and Surgery},
  volume={13},
  number={6},
  pages={3508--3521},
  year={2023},
  doi={10.21037/qims-22-1245}
}

Complete record

Publications and manuscripts

Fig. 2 · Paper figure2026

Published2025 JIF · 14.0JCR Q1CAS 2025 · Tier 1 · Top

ARDMR: Adaptive recursive inference and representation disentanglement for multimodal large deformation registration

Yibo Hu, Qi Zhang, Ziqi Zhao, Xiaoyi Ding, Wentao Li, Jijin Yang, Jianqi Sun, Lisa X. Xu

Medical Image Analysis · 107(Pt B) · 103844

DOI10.1016/j.media.2025.103844

Paper Code

BibTeX

ARDMR: Adaptive recursive inference and representation disentanglement for multimodal large deformation registration

@article{hu2026ardmr,
  title={ARDMR: Adaptive recursive inference and representation disentanglement for multimodal large deformation registration},
  author={Hu, Yibo and Zhang, Qi and Zhao, Ziqi and Ding, Xiaoyi and Li, Wentao and Yang, Jijin and Sun, Jianqi and Xu, Lisa X.},
  journal={Medical Image Analysis},
  volume={107},
  pages={103844},
  year={2026},
  doi={10.1016/j.media.2025.103844}
}

Fig. 1 · Manuscript figure2026

Under ReviewCo-first author

Artificial intelligence for degenerative cervical myelopathy imaging: a systematic review across tasks and modalities

Qi Zhang^†, Xiuyuan Chen^†, Zihui Wang^†, Kun Wang, Lianming Wu, Hongxing Shen, Jianqi Sun

Manuscript under review

Project

BibTeX

Artificial intelligence for degenerative cervical myelopathy imaging: a systematic review across tasks and modalities

@unpublished{zhang2026dcmreview,
  title={Artificial intelligence for degenerative cervical myelopathy imaging: a systematic review across tasks and modalities},
  author={Zhang, Qi and Chen, Xiuyuan and Wang, Zihui and Wang, Kun and Wu, Lianming and Shen, Hongxing and Sun, Jianqi},
  year={2026},
  note={Manuscript under review}
}

Fig. 1 · Paper figure2026

PublishedCo-first author2025 JIF · 6.8JCR Q1CAS 2025 · Tier 2 · Top

Pathology-Guided AI System for Accurate Segmentation and Diagnosis of Cervical Spondylosis

Qi Zhang^†, Xiuyuan Chen^†, Ziyi He^†, Lianming Wu, Kun Wang, Jianqi Sun, Hongxing Shen

IEEE Journal of Biomedical and Health Informatics · 30(2) · 1216-1229

DOI10.1109/JBHI.2025.3598469

Paper Code Project

BibTeX

Pathology-Guided AI System for Accurate Segmentation and Diagnosis of Cervical Spondylosis

@article{zhang2026pathology,
  title={Pathology-Guided AI System for Accurate Segmentation and Diagnosis of Cervical Spondylosis},
  author={Zhang, Qi and Chen, Xiuyuan and He, Ziyi and Wu, Lianming and Wang, Kun and Sun, Jianqi and Shen, Hongxing},
  journal={IEEE Journal of Biomedical and Health Informatics},
  volume={30},
  number={2},
  pages={1216--1229},
  year={2026},
  doi={10.1109/JBHI.2025.3598469}
}

Fig. 2 · Paper figure2026

PublishedCo-first authorCCF B · 2026MICCAI · Premier conference

Reconstructing Isotropic 3D Cervical MRI from Anisotropic Clinical Scans via Anatomy-Style Decoupled INRs

Qi Zhang^†, Xiuyuan Chen^†, Yibo Hu, Hongxing Shen, Jianqi Sun

Medical Image Computing and Computer Assisted Intervention - MICCAI 2026 · 16888 · 478-487

Published online 26 September 2026. Springer lists 2027 as the citation year.

DOI10.1007/978-3-032-38179-8_46

Paper Code Project

BibTeX

Reconstructing Isotropic 3D Cervical MRI from Anisotropic Clinical Scans via Anatomy-Style Decoupled INRs

@inproceedings{zhang2026jointsr,
  title={Reconstructing Isotropic 3D Cervical MRI from Anisotropic Clinical Scans via Anatomy-Style Decoupled INRs},
  author={Zhang, Qi and Chen, Xiuyuan and Hu, Yibo and Shen, Hongxing and Sun, Jianqi},
  booktitle={Medical Image Computing and Computer Assisted Intervention -- MICCAI 2026},
  series={Lecture Notes in Computer Science},
  volume={16888},
  pages={478--487},
  publisher={Springer Nature Switzerland},
  year={2027},
  doi={10.1007/978-3-032-38179-8_46}
}

Fig. 2 · Paper figure2026

PublishedCo-first author2025 JIF · 14.0JCR Q1CAS 2025 · Tier 1 · Top

U2AD: Uncertainty-based unsupervised anomaly detection framework for detecting T2 hyperintensity in MRI spinal cord

Qi Zhang^†, Xiuyuan Chen^†, Ziyi He^†, Kun Wang^†, Lianming Wu, Hongxing Shen, Jianqi Sun

Medical Image Analysis · 109 · 103939

DOI10.1016/j.media.2026.103939

Paper Code Project

BibTeX

U2AD: Uncertainty-based unsupervised anomaly detection framework for detecting T2 hyperintensity in MRI spinal cord

@article{zhang2026u2ad,
  title={U2AD: Uncertainty-based unsupervised anomaly detection framework for detecting T2 hyperintensity in MRI spinal cord},
  author={Zhang, Qi and Chen, Xiuyuan and He, Ziyi and Wang, Kun and Wu, Lianming and Shen, Hongxing and Sun, Jianqi},
  journal={Medical Image Analysis},
  volume={109},
  pages={103939},
  year={2026},
  doi={10.1016/j.media.2026.103939}
}

Fig. 3 · Paper figure2026

PublishedFirst author2025 JIF · 12.4JCR Q1CAS 2025 · Tier 1 · Top

UniTransAD: Unified Translation Framework for Anomaly Detection in Brain MRI

Qi Zhang, Xia Li, Yibo Hu, Jianqi Sun

IEEE Transactions on Medical Imaging · 45(9) · 4876-4891

DOI10.1109/TMI.2026.3711975

Paper Code Project

BibTeX

UniTransAD: Unified Translation Framework for Anomaly Detection in Brain MRI

@article{zhang2026unitransad,
  title={UniTransAD: Unified Translation Framework for Anomaly Detection in Brain MRI},
  author={Zhang, Qi and Li, Xia and Hu, Yibo and Sun, Jianqi},
  journal={IEEE Transactions on Medical Imaging},
  year={2026},
  volume={45},
  number={9},
  pages={4876--4891},
  doi={10.1109/TMI.2026.3711975}
}

Fig. 2 · Paper figure2025

PublishedFirst author2025 JIF · 6.8JCR Q1CAS 2025 · Tier 2 · Top

HealthiVert-GAN: A Novel Framework of Pseudo-Healthy Vertebral Image Synthesis for Interpretable Compression Fracture Grading

Qi Zhang, Cheng Chuang, Shunan Zhang, Ziqi Zhao, Kun Wang, Jun Xu, Jianqi Sun

IEEE Journal of Biomedical and Health Informatics · 29(10) · 7299-7311

DOI10.1109/JBHI.2025.3572458

Paper Code Project

BibTeX

HealthiVert-GAN: A Novel Framework of Pseudo-Healthy Vertebral Image Synthesis for Interpretable Compression Fracture Grading

@article{zhang2025healthivert,
  title={HealthiVert-GAN: A Novel Framework of Pseudo-Healthy Vertebral Image Synthesis for Interpretable Compression Fracture Grading},
  author={Zhang, Qi and Chuang, Cheng and Zhang, Shunan and Zhao, Ziqi and Wang, Kun and Xu, Jun and Sun, Jianqi},
  journal={IEEE Journal of Biomedical and Health Informatics},
  volume={29},
  number={10},
  pages={7299--7311},
  year={2025},
  doi={10.1109/JBHI.2025.3572458}
}

Fig. 1 · Paper figure2025

PublishedFirst authorCCF B · 2026MICCAI · Premier conference

MultiTransAD: Cross-Sequence Translation-Driven Anomaly Detection in Multi-sequence Brain MRI

Qi Zhang, Yibo Hu, Jianqi Sun

Medical Image Computing and Computer Assisted Intervention - MICCAI 2025 · LNCS 15961 · 389-398

DOI10.1007/978-3-032-04937-7_37

Paper Code Project

BibTeX

MultiTransAD: Cross-Sequence Translation-Driven Anomaly Detection in Multi-sequence Brain MRI

@inproceedings{zhang2025multitransad,
  title={MultiTransAD: Cross-Sequence Translation-Driven Anomaly Detection in Multi-sequence Brain MRI},
  author={Zhang, Qi and Hu, Yibo and Sun, Jianqi},
  booktitle={Medical Image Computing and Computer Assisted Intervention -- MICCAI 2025},
  series={Lecture Notes in Computer Science},
  volume={15961},
  pages={389--398},
  publisher={Springer Nature Switzerland},
  year={2025},
  doi={10.1007/978-3-032-04937-7_37}
}

Fig. 1 · Paper figure2025

PublishedCCF B · 2026MICCAI · Premier conference

RDMR: Recursive Inference and Representation Disentanglement for Multimodal Large Deformation Registration

Yibo Hu, Ziqi Zhao, Qi Zhang, Lisa X. Xu, Jianqi Sun

Medical Image Computing and Computer Assisted Intervention - MICCAI 2025 · LNCS 15962 · 512-522

DOI10.1007/978-3-032-04947-6_49

Paper Code

BibTeX

RDMR: Recursive Inference and Representation Disentanglement for Multimodal Large Deformation Registration

@inproceedings{hu2025rdmr,
  title={RDMR: Recursive Inference and Representation Disentanglement for Multimodal Large Deformation Registration},
  author={Hu, Yibo and Zhao, Ziqi and Zhang, Qi and Xu, Lisa X. and Sun, Jianqi},
  booktitle={Medical Image Computing and Computer Assisted Intervention -- MICCAI 2025},
  series={Lecture Notes in Computer Science},
  volume={15962},
  pages={512--522},
  publisher={Springer Nature Switzerland},
  year={2025},
  doi={10.1007/978-3-032-04947-6_49}
}

Fig. 1 · Paper figure2024

Published2025 JIF · 3.2JCR Q2CAS 2025 · Tier 3

The applications of CT with artificial intelligence in the prognostic model of idiopathic pulmonary fibrosis

Zeyu Chen^†, Zheng Lin^†, Zihan Lin, Qi Zhang, Haoyun Zhang, Haiwen Li, Qing Chang, Jianqi Sun, Feng Li

Therapeutic Advances in Respiratory Disease · 18 · 17534666241282538

DOI10.1177/17534666241282538

Paper

BibTeX

The applications of CT with artificial intelligence in the prognostic model of idiopathic pulmonary fibrosis

@article{chen2024ipf,
  title={The applications of CT with artificial intelligence in the prognostic model of idiopathic pulmonary fibrosis},
  author={Chen, Zeyu and Lin, Zheng and Lin, Zihan and Zhang, Qi and Zhang, Haoyun and Li, Haiwen and Chang, Qing and Sun, Jianqi and Li, Feng},
  journal={Therapeutic Advances in Respiratory Disease},
  volume={18},
  pages={17534666241282538},
  year={2024},
  doi={10.1177/17534666241282538}
}

Fig. 2 · Paper figure2023

PublishedFirst author2025 JIF · 2.8JCR Q2CAS 2025 · Tier 3

Cartilage morphometry and magnetic susceptibility measurement for knee osteoarthritis with automatic cartilage segmentation

Qi Zhang, Jiaolun Geng, Ming Zhang, Tianyou Kan, Liao Wang, Songtao Ai, Hongjiang Wei, Lichi Zhang, Chenglei Liu

Quantitative Imaging in Medicine and Surgery · 13(6) · 3508-3521

DOI10.21037/qims-22-1245

Paper

BibTeX

Cartilage morphometry and magnetic susceptibility measurement for knee osteoarthritis with automatic cartilage segmentation

@article{zhang2023cartilage,
  title={Cartilage morphometry and magnetic susceptibility measurement for knee osteoarthritis with automatic cartilage segmentation},
  author={Zhang, Qi and Geng, Jiaolun and Zhang, Ming and Kan, Tianyou and Wang, Liao and Ai, Songtao and Wei, Hongjiang and Zhang, Lichi and Liu, Chenglei},
  journal={Quantitative Imaging in Medicine and Surgery},
  volume={13},
  number={6},
  pages={3508--3521},
  year={2023},
  doi={10.21037/qims-22-1245}
}