Tiffany Y. So is an academic radiologist with subspecialty expertise in neuroimaging and medical image computing. She obtained her medical degree from the University of Melbourne, Australia and completed internship and basic training at the Royal Melbourne Hospital. She completed Radiology training at Alfred Health in Melbourne, training in diagnostic radiology with subspecialty training rotations in trauma imaging, neuroradiology, thoracic and lung transplant imaging and body imaging. Dr So is a Fellow of the Royal Australian and New Zealand College of Radiologists and a registered specialist in Diagnostic Radiology in Australia (AHPRA), New Zealand (MCNZ), and Hong Kong (MCHK). Her research work focuses on advanced MRI techniques, quantitative neuroimaging biomarkers, and clinically translatable artificial intelligence (AI) applications. Her work integrates multimodal imaging, clinical parameters, and molecular data to support precision neuro-oncology and computational radiology. Her research also encompasses multiple sclerosis and cerebrovascular disease, with a focus on lesion characterisation and the evaluation of prognosis and patient outcomes. She also has a particular interest in imaging of traumatic head injury, head and neck imaging development of medical healthcare technologies, and AI in education. She has completed a Master of Medicine in Radiology, with her work centred on traumatic injuries to the dural venous sinuses.

Dr So is actively involved in undergraduate teaching and postgraduate radiology resident training. She serves as a diagnostic radiologist at the Department of Imaging and Interventional Radiology at the Prince of Wales Hospital, New Territories East Cluster (NTEC), contributing to clinical services provided by the Hospital Authority. Additionally, she is a part of the neuroradiology team delivering diagnostic neuroimaging services to patients within the NTEC. She is an experienced academic editor and reviewer for clinical journals and international conferences and is actively engaged in local and international collaborations.

Dr So is a member of the European Society of Radiology (ESR), Radiological Society of North America (RSNA), The Medical Image Computing and Computer Assisted Intervention Society (MICCAI), Institution of Electrical and Electronics Engineers (IEEE), The Australian and New Zealand Society of Neuroradiology (ANZSNR), and American Roentgen Ray Society (ARRS).

Current teaching profile includes undergraduate teaching (CUHK 4th and final year medical students), postgraduate radiology resident training (FRCR trainees), and visiting students from international institutions, in the form of lectures, small group and clinical tutorials, flipped classroom teaching, on the job teaching as well as informal tutorials. Dr So plays a leading role in curriculum planning and design for the undergraduate radiology program at CUHK, integrating both conventional delivery methods and eLearning approaches. Her current educational research projects focus on the incorporation of technology, artificial intelligence, and game-based learning into medical education. These projects aim to develop innovative and readily accessible teaching materials to enhance teaching curriculums across several disciplines.

Dr So serves as the Coordinator of the MED4 Radiology Course and Coordinator of the MED6 Objective Structured Clinical Examination (OSCE) in Surgery for Radiology and is an active examiner in undergraduate assessments.

She takes an interest in quality improvement in medical education and the techniques and approaches to maintain a quality teaching and student learning experience; in the past year attending several relevant workshops and seminars related to these areas. She also supports collaborative work through actively engaging Students as Partners (SaP) in curriculum and educational material development, working together with other students and staff toward shared educational goals.

Teaching awards

• Faculty of Medicine Faculty Education Award 2024 – Early Career Faculty Members
• Faculty of Medicine Faculty Education Award 2024 – Collaborative Teams
  (Team Leader: Prof A King; Team Members: Prof JF Griffith, Prof WCW Chu, Dr TY So, Dr J Abrigo)
• People’s Choice Poster Prize, Teaching and Learning Innovation Expo 2025 (XRLiA LLM Chatbot).
• People’s Choice Poster Prize, Teaching and Learning Innovation Expo 2024 (Transient Global Amnesia App).
• Educational Technology Innovation Gold award, Teaching and Learning Innovation Expo 2022 (NasogastriX).
• Best presentation award, Tripartite Medical Education Conference – Actualising the Curriculum Continuum 2023.

Teaching grants awarded as Principal Investigator (PI)

Total of n=10 teaching education grants awarded as PI, including:

• eLearning Modules for radiographic assessment of lines and tubes and their potential complications – Implementing artificial intelligence (AI) and game-based learning, funded by the University Grants Committee (UGC)- Teaching Development and Language Enhancement Grant (TDLEG)
• Micro-modules and Game-Based Learning for the Radiological Assessment of Nasogastric Tube Positioning, funded by The Chinese University of Hong Kong Teaching and Learning Grant (CDGS)
• Curriculum development in Abdominal Ultrasound, funded by The Chinese University of Hong Kong Teaching and Learning Grant
• United College Campus Training Grants for Teaching and Education

Grant Review

• Reviewer, Teaching Development and Language Enhancement Grant (TDLEG) 2025–28 proposal review panel, CUHK

Teaching related knowledge transfer

• YouTube channel – Developed a YouTube channel featuring short videos teaching practical concepts of radiology.
• Mobile application development – developed mobile applications containing electronic modules and interactive games for iOS
• Large language model (LLM) chatbot development

Dr So provides clinical radiology service in all areas of diagnostic radiology at the Prince of Wales Hospital. She specializes in neuroimaging and has specialty interest in advanced MRI brain imaging, multiple sclerosis, stroke and cerebrovascular imaging, head and neck imaging and artificial intelligence in radiology.

Recent service

Editorial roles:

• Junior Deputy Editor – European Radiology
• Editorial board member – European Radiology (Neuro Section)
• Editorial Board Member, Scientific Reports
• Editorial Board Member, Therapeutic Advances in Neurological Disorders
• Editorial Board Member, BMC Medical Imaging
• Guest Associate Editor, Frontiers in Medicine
• Topic Editor (Artificial Intelligence), Frontiers in Radiology
• Associate Editor, IEEE EMBC 2026 (Biomedical Imaging and Image Processing)

Conference Leadership:

• Program Chair, CLINICCAI, MICCAI 2022 – 25th International Conference on Medical Image Computing and Computer Assisted Intervention, Singapore
• Program Committee, CLINICCAI, MICCAI 2023 – 25th International Conference on Medical Image Computing and Computer Assisted Intervention, Vancouver, Canada
• Program Committee, CLINICCAI, MICCAI 2024 – 26th International Conference on Medical Image Computing and Computer Assisted Intervention, Marrakesh Morocco
• Program Chair, CLINICCAI, MICCAI 2022 – 25th International Conference on Medical Image Computing and Computer Assisted Intervention, Singapore
• Program Committee, CLINICCAI, MICCAI 2023 – 25th International Conference on Medical Image Computing and Computer Assisted Intervention, Vancouver, Canada
• Program Committee, CLINICCAI, MICCAI 2024 – 26th International Conference on Medical Image Computing and Computer Assisted Intervention, Marrakesh Morocco

Ethics and Governance:

• Member, The Joint Chinese University of Hong Kong (CUHK) and New Territories East Cluster (NTEC) Clinical Research Ethics Committee (CREC), 2025–Present, contributing to the ethical and scientific review of clinical research involving human subjects

Postgraduate Supervision and Examination:

• Supervisor – MPhil/PhD students supervisor, Examiner – MPhil/PhD students

Peer Review:

• Reviewer, leading journals including European Radiology, NPJ Digital Medicine, BMJ, The Lancet Oncology, and Clinical Radiology
• Conference reviewer (e.g RSNA, MICCAI)

Dr So is actively engaged in interdisciplinary research encompassing neuroimaging, medical artificial intelligence and computer-aided diagnosis. She is particularly interested in the application of advanced imaging techniques to investigate into structural and functional changes in the brain.  Harnessing the capabilities of computational approaches, Dr So and her team focus on methods to integrate imaging, clinical and/or molecular data, and artificial intelligence and machine learning into research.

Current Research

Dr So has recently led and/or contributed to research projects in the following areas:  

Quantitative and Advanced MRI:

• Applications of spin-lock imaging, including quantitative T1rho assessment of normal brain and demyelination in multiple sclerosis
• Macromolecular proton fraction (MPF) mapping in multiple sclerosis
• Brain intravoxel incoherent motion (IVIM) MRI
• Evaluation of gadolinium-based contrast agent (Gd-CA) effects in brain imaging

Artificial Intelligence and Computational Imaging:

• Machine learning and radiomics for brain tumour (glioma and mengingioma) grading, classification and predictive modelling
• AI-assisted analysis and characterisation of multiple sclerosis white matter lesionss
• Large-scale federated learning (FL) in glioma
• Contribution to international large-scale brain tumour segmentation initiatives, including the Brain Tumor Segmentation (BraTS) Challenges
• Large language model (LLM) applications in radiology
• Deep learning in head and neck imaging

Research grants awarded as Principal Investigator (PI)

• Quantitative T1rho Magnetic Resonance Imaging for Evaluation of Acuity in Multiple Sclerosis (MS) Brain Lesions, funded by Research Grants Council (RGC) Early Careers Scheme (ECS)
• Identifying relationships between cognitive dysfunction and tissue alterations in the deep grey nuclei in multiple sclerosis (MS) using macromolecular proton fraction mapping based on spin-lock (MPF-SL) magnetic resonance imaging, funded by Research Grants Council (RGC) General Research Fund (GRF)
• Development of a Versatile Universal AI Model for Seamless Meningioma Analysis Across Institutions, funded by the Health and Medical Research Fund (HMRF) 2024–25

She has additionally contributed as Co-Principal Investigator (Co-PI) on further competitive research grants, including:

• Institute of Medical Intelligence and XR (Co-PI, PC: Prof PA Heng, Department of Computer Science and Engineering) funded by Theme-based Research Scheme (TRS)
• Embracing Artificial Intelligence-Assisted Upper and Lower Urinary Tract Assessment in Primary Care and Nurse Clinic Settings (Co-PI) funded by Strategic Topics Grant (STG) 2025/26

Recent Selected Publications

So TY*, Wang L, Chen W, Choi JCH, Ai QH, Yeung DKW, Wang YXJ, Abrigo J, King AD, Lau AYL. Diagnostic Performance of Quantitative T1rho MRI for the Assessment of Disease Activity in Relapsing-Remitting Multiple Sclerosis. Acad Radiol. 2026;33(7):3053-3060. doi: 10.1016/j.acra.2026.03.049. 

Wang Z, Deng Q, So TY, Chiu WH. DoKE: Domain Knowledge-Enhanced Multi-modal Large Language Model-Based Framework for Chest X-Ray Follow-up Visual Question Answering. Biomedical Signal Processing and Control. 2026;120:109908.

So TY, Chen W. Editorial for “Association Between Intermittent Fasting and Susceptibility-Weighted MRI Phase Values in Deep Gray Matter of Patients With Multiple Sclerosis: An Observational Cohort Study”. Journal of Magnetic Resonance Imaging. 2026; 0:1-2.

Wang L, So TY*, Choi JCH, Lau AYL, Yu Z, Yeung D, Abrigo J, King AD, Wang YJ, Ai QY, Chen W. Evaluation of the Perilesional Normal-Appearing White Matter (NAWM) Microenvironment in Relapsing-Remitting Multiple Sclerosis with Quantitative T1rho MRI. Quantitative Imaging in Medicine and Surgery. 2025;15(10):9479-91.

Cai Z, Wong YH, So TY*. Multisequence MRI Habitat Analysis for Pre-operative Meningioma Grade Prediction. Quantitative Imaging in Medicine and Surgery. 2025;15(9):7874.

Wang L, Ai QY, Chen W, Cai Z, Yu Z, Abrigo JM, So TY*. Effect of gadolinium-based contrast media on intravoxel incoherent motion (IVIM) MRI parameters in brain imaging. Physica Medica. 2025 Nov 1;139:105172.

Gao Z, Zhou Z, Yu Z, Shan Q, Lee J, Abrigo J, Hui E, So T, Chen W. Orientation-independent magnetization transfer imaging of brain white matter. Neuroimage. 2025 Sep 11;320:121456. 

Wong LM, So TY.  Towards accessible stroke services: how can AI assist NCCT interpretation for subarachnoid haemorrhage management? European Radiology. 2025;35(11):6773-4.

Zheng S, Ma W, Mu L, He K, Cao J, So TY, Zhang L, Li M, Zhai Y, Liu F, Guo S, Yin L, Zhao L, Wang L, Lee HHC, Jiang W, Niu J, Gao P, Dou Q, Zhang H. CT-based artificial intelligence system complementing deep learning model and radiologist for liver fibrosis staging. iScience. 2025;18;28(4).

Wang Z, Deng Q, So TY, Chiu WH, Lee K, Hui ES. Disease probability-enhanced follow-up chest X-ray radiology report summary generation. Scientific Reports. 2025;15(1):26930. 

Wong LM, Ai QY, Leung HS, So TY, Hung KF. Decoding the Rotation Effect: A Retrospective Study on Lesion Orientation and Wavelet Decomposition in Radiomics. Journal of Imaging Informatics in Medicine. 2025 May 6:1-2.

Moawad AW, Janas A, Baid U, Ramakrishnan D, Jekel L, Krantchev K, et al. The Brain Tumor Segmentation (BraTS-METS) Challenge 2023: Brain Metastasis Segmentation on Pre-treatment MRI. Machine Learning for Biomedical Imaging. 2025:011. 

Hou J, Cai Z, Chen W, So TY*. Spin-lock based fast whole-brain 3D macromolecular proton fraction mapping of relapsing–remitting multiple sclerosis. Scientific Reports. 2024 Aug 2;14(1):17943.

Barzegar M, Schweitzer M, So TY, Chen Y, Ertürk ŞM. Quantitative neuroradiology methods. Frontiers in Radiology. 2024 Feb 12;4:1366704.

King AD, Ai QY, Lam WJ, Tse IO, So TY, Wong LM, Tsang JY, Leung HS, Zee BC, Hui EP, Ma BB. Early detection of nasopharyngeal carcinoma: performance of a short contrast-free screening magnetic resonance imaging. JNCI: Journal of the National Cancer Institute. 2024 Jan 4:djad260

Cai Z, Wong LM, Wong YH, Lee HL, Li KY, So TY*. Dual-Level Augmentation Radiomics Analysis for Multisequence MRI Meningioma Grading. Cancers. 2023 Nov 17;15(22):5459

Wang L, Chen W, Qian Y, So TY*. Repeatability of quantitative T1rho magnetic resonance imaging in normal brain tissues at 3.0 T. Physica Medica. 2023 Aug 1;112:102641

Pati S, Baid U, Edwards B, Sheller M, Wang SH, Reina GA, et al. Federated learning enables big data for rare cancer boundary detection. Nat Commun. 2022 Dec;13(1):7346.
So TY*. Editorial Comment: Iron-sensitive MR imaging of the primary motor cortex to differentiate hereditary spastic paraplegia from other motor neuron diseases. European Radiology. 2022 Dec;32(12):8055-7.

Dou Q, So TY†, Jiang M, Liu Q, Vardhanabhuti V, Kaissis G, Li Z, Si W, Lee HH, Yu K, Feng Z. Federated deep learning for detecting COVID-19 lung abnormalities in CT: a privacy-preserving multinational validation study. NPJ digital medicine. 2021 Mar 29;4(1):60.