Dr. Varut Vardhanabhuti

Dr Vince

Clinical Assistant Professor, Department of Diagnostic Radiology, HKU

  • MBBS BSc (Lond, UK), FRCR (UK), PhD(UK)
Research Interests
  • Quantitative Image Analysis using Machine Learning and Artificial Intelligence
  • Radiomics
  • Spectral CT
  • Advanced Cancer Imaging (Prostate, Liver, Nasopharyngeal and Lung Carcinoma)
  • Big Data Health Analytics

Brief Bio

Dr Vardhanabhuti completed his medical degree at Guy's, King's and St Thomas' School of Medicine in London, UK in 2005. He had subsequent training in London, Oxford, Plymouth, Exeter, and completed his Radiology training at Imperial College London, UK whilst also completing a PhD during his residency.

He has active interests in data science, machine learning, and artificial intelligence while engaging with various research projects relating to medical imaging, with the goal of early clinical translation to benefits patients. He has wide-ranging projects in the AI space including the use of quantitative radiomics in cancer prognostication, using deep learning model as a tool for automatic segmentation and cancer detection, big data using electronic patient records, etc. More recently he has been engaged in several projects applying machine learning and artificial intelligence techniques in tackling the COVID-19 pandemic.

He is passionate about using technology in education. He has previously served as a Microsoft Cloud Research Software Fellow and an Amazon Faculty Ambassador in AWS Educate Cloud Ambassador Program. He currently serves as the Vice Chair for community engagement in the International Society of Radiology.

Journal Reviewer

Current Reviewer:
European Radiology – Section Editor and Scientific Editorial Board “Computed Tomography” section

Previous/Ad Hoc Reviewer:
Investigative Radiology, European Radiology, British Journal of Radiology, Hong Kong Medical Journal, Korean Journal of Radiology, Scientific Report, npjDigital Medicine, Lancet Digital Health, Diagnostics, Clinical Radiology

Selected Publications
Journal Papers

  • Wu W, Hu D, Niu C, Yu H*, Vardhanabhuti V*, Wang G*. DRONE: Dual-domain Residual-based Optimization NEtwork for Sparse-view CT Reconstruction. IEEE transactions on medical imaging. 2021. [Corresponding Author.]
  • Xie CY, Hu YH, Ho JW, Han LJ, Yang H, Wen J, Lam KO, Wong IT, Law SY, Chiu KWH, Fu JH, Vardhanabhuti V*. Using Genomics Feature Selection Method in Radiomics Pipeline Improves Prognostication Performance in Locally Advanced Esophageal Squamous Cell Carcinoma-A Pilot Study. Cancers. 2021;13(9). [Corresponding Author.]
  • Dou Q, So TY, Jiang M, Liu Q, Vardhanabhuti V, Kaissis G, et al. Federated deep learning for detecting COVID-19 lung abnormalities in CT: a privacy-preserving multinational validation study. NPJ digital medicine. 2021;4(1):60.
  • Perucho JAU, Wang M, Vardhanabhuti V, Tse KY, Chan KKL, Lee EYP. Association between IVIM parameters and treatment response in locally advanced squamous cell cervical cancer treated by chemoradiotherapy. European Radiology. 2021.
  • Wu W, Shi J, Yu H, Wu W, Vardhanabhuti V*. Tensor Gradient L₀-Norm Minimization-Based Low-Dose CT and Its Application to COVID-19. IEEE Transactions on Instrumentation and Measurement. 2021;70:1-12. [Corresponding Author.]
  • So TY, Vardhanabhuti V*. Essential imaging of the nasopharyngeal space with special focus on nasopharyngeal carcinoma. Operative Techniques in Otolaryngology-Head and Neck Surgery. 2021 Feb 6. [Corresponding Author.]
  • Wu W, Shi J, Yu H, Wu W, Vardhanabhuti V*. Tensor Gradient L₀-Norm Minimization-Based Low-Dose CT and Its Application to COVID-19. IEEE Transactions on Instrumentation and Measurement. 2021 Jan 19;70:1-2. [Corresponding Author.]
  • Broeke LV, Grillon M, Yeung AW, Wu W, Tanaka R, Vardhanabhuti V*. Feasibility of photon-counting spectral CT in dental applications—a comparative qualitative analysis. BDJ open. 2021 Jan 27;7(1):1-8. [Corresponding Author.]
  • Ding J, Cao P, Chang CHC, Gao Y, Chan S, Vardhanabhuti V*. Deep learning-based thigh muscle segmentation for reproducible fat fraction quantification using fat-water decomposition MRI. Insights into Imaging, in press 2020. [Corresponding Author.]
  • Chiu WHK, Vardhanabhuti V, Poplavskiy D, Yu PLH, Du R, Yap AYH, et al. Detection of COVID-19 Using Deep Learning Algorithms on Chest Radiographs. Journal of thoracic imaging, in press 2020.
  • Hu Y, Xie C, Yang H, Ho JWK, Wen J, Han L, Chiu K, Fu J*, Vardhanabhuti V*. Assessment of Intratumoral and Peritumoral Computed Tomography Radiomics for Predicting Pathological Complete Response to Neoadjuvant Chemoradiation in Patients With Esophageal Squamous Cell Carcinoma. JAMA network open. 2020;3(9):e2015927. [Co-Corresponding Author.]
  • Hu Y, Xie C, Yang H, Ho JWK, Wen J, Han L, Lam, K. O., Wong, I. Y. H., Law, S. Y. K, Chiu, K. W. H, Vardhanabhuti V*, Fu J*. Computed tomography-based deep-learning prediction of neoadjuvant chemoradiotherapy treatment response in esophageal squamous cell carcinoma. Radiotherapy and oncology. 2020;154:6-13. [Co-Corresponding Author.]
  • Tan SZK, Du R, Perucho JAU, Chopra SS, Vardhanabhuti V*, Lim LW*. Dropout in Neural Networks Simulates the Paradoxical Effects of Deep Brain Stimulation on Memory. Frontiers in aging neuroscience. 2020;12:273. [Co-Corresponding Author.]
  • Vardhanabhuti V*. CT scan AI-aided triage for patients with COVID-19 in China. The Lancet Digital health. 2020;2(10):e494-e5. [Corresponding Author.]
  • Xie C, Ng MY, Ding J, Leung ST, Lo CSY, Wong HYF, Vardhanabhuti V. Discrimination of pulmonary ground-glass opacity changes in COVID-19 and non-COVID-19 patients using CT radiomics analysis. European journal of radiology open. 2020;7:100271. [Corresponding Author.]
  • Chan SK, Chan SY, Choi HCW, Tong CC, Lam KO, Kwong DLW, Vardhanabhuti V, Leung TW, Luk MY, and Lee AWM. 2020. Prognostication of Half-Life Clearance of Plasma EBV DNA in Previously Untreated Non-metastatic Nasopharyngeal Carcinoma Treated With Radical Intensity-Modulated Radiation Therapy.  Frontiers in Oncology 2020. 10:1417.
  • Yan KK, Wang X, Lam W, Vardhanabhuti V, Lee AW, Pang HH. Radiomics analysis using stability selection supervised component analysis for right-censored survival data. Computers in biology and medicine. 2020:103959.
  • Cao P, Cui D, Vardhanabhuti V, Hui ES. Development of fast deep learning quantification for magnetic resonance fingerprinting in vivo. Magnetic resonance imaging. 2020;70:81-90.
  • Ko JM-Y, Vardhanabhuti V, Ng W-T, Lam K-O, Ngan RK-C, Kwong DL-W, et al. Clinical utility of serial analysis of circulating tumour cells for detection of minimal residual disease of metastatic nasopharyngeal carcinoma. British journal of cancer. 2020.
  • Wu W, Chen P, Wang S, Vardhanabhuti V, Liu F, Yu H. Image-domain Material Decomposition for Spectral CT using a Generalized Dictionary Learning. IEEE Transactions on Radiation and Plasma Medical Sciences. 2020:1-.
  • Xie C, Du R, Ho JWK, Pang HHM, Chiu KWH, Lee EYP, Vardhanabhuti V*. Effect of machine-learning re-sampling techniques for imbalanced datasets in 18F-FDG PET-based radiomics model on prognostication performance in cohorts of head and neck cancer patients. EJNMMI 2020.
    [Corresponding Author.]
  • Ng MY, Zhou W, Vardhanabhuti V, Lee CH, Yu EYT, Wan EYF, et al. Cardiac magnetic resonance for asymptomatic patients with type 2 diabetes and cardiovascular high risk (CATCH): a pilot study. Cardiovascular Diabetology. 2020;19:article no. 42.
  • Cheung C, Ho JD-L, Vardhanabhuti V, Chang H-C, Kwok KW*. Design and Fabrication of Wireless Multilayer Tracking Marker for Intraoperative MRI-guided Interventions. IEEE/ASME Transactions on Mechatronics. 2020.
    [IF 4.943, Rank 6/49 (Engineering, Manufacturing)]
  • Perucho JAU, Chang HCC, Vardhanabhuti V, Wang M, Becker AS, Wurnig MC, et al. B-Value Optimization in the Estimation of Intravoxel Incoherent Motion Parameters in Patients with Cervical Cancer. Korean Journal of Radiology. 2020;21(2):218-27.
  • Wu W, Chen P, Vardhanabhuti V, Wu W, Yu H. Improved Material Decomposition with a Two-step Regularization for spectral CT. IEEE Access. 2019.
  • van Lunenburg, J. T. J., Tripathi, V., Chan, V. S. H., Lee, V. K. H., Lee, E. Y., Vardhanabhuti, V., & Chiu, K. W. H. (2019). Sequence and Observer Variability in Gadoxectic Acid-Enhanced MRI Lesion Measurements in Hepatocellular Carcinoma. Acad Radiol. doi:10.1016/j.acra.2019.05.021.
  • Coiffier, B. C. A., Shen, P. C. H., Lee, E. Y. P., Kwong, T. S. P., Lai, Y. T. A., Wong, M. F. E., Vardhanabhuti V, Khong, P. L. (2019). Introducing point-of-care ultrasound through structured multifaceted ultrasound module in the undergraduate medical curriculum at the University of Hong Kong. Ultrasound. 2020;28(1):38-46.
  • Lee, V. H. F., Chan, J. Y. W., Vardhanabhuti, V., Kwong, D. L. W., Leung, T. W., Chan, S. Y., . . . Lee, W. M. A. (2019). Advancing Care for Head and Neck Cancers in a Multidisciplinary Tumour Board in the East. Clin Oncol, 31(8), 549.
  • Du, R., Lee, V. H., Yuan, H., Lam, K.-O., Pang, H. H., Chen, Y., . . . Vardhanabhuti, V*. (2019). Radiomics Model to Predict Early Progression of Nonmetastatic Nasopharyngeal Carcinoma after Intensity Modulation Radiation Therapy: A Multicenter Study. Radiology: Artificial Intelligence, 1(4), e180075. doi:10.1148/ryai.2019180075. [Corresponding Author.]
  • Au KY, Chen H, Lam WC, Chong CO, Lau A, Vardhanabhuti V, et al. Sinew acupuncture for knee osteoarthritis: study protocol for a randomized sham-controlled trial. BMC complementary and alternative medicine. 2018;18(1):133.
  • Seto WK, Mak SK, Chiu K, Vardhanabhuti V, Wong HF, Leong HT, et al. Magnetic resonance cholangiogram patterns and clinical profiles of ketamine-related cholangiopathy in drug users. Journal of hepatology. 2018;69(1):121-8.
  • Au K, Chen H, Lam W, Chong C, Lau A, Vardhanabhuti V, et al. Acupuncture and TCM. Journal of the Australian Traditional-Medicine Society. 2018;24(2):112-3.
  • Li YL, Wong KH, Law MW, Fang BX, Lau VW, Vardhanabhuti V, Lee VK, Cheng AK, Ho WY, Lam WW. Opportunistic screening for osteoporosis in abdominal computed tomography for Chinese population. Arch Osteoporos. 2018 Jul 9;13(1):76.
  • Vardhanabhuti V, Kuo MD. Lung Cancer Radiogenomics: The Increasing Value of Imaging in Personalized Management of Lung Cancer Patients. Journal of thoracic imaging. 2018;33(1):17-25.
    [First Author]
  • Yuan H, Ai QY, Kwong DL, Fong DY, King AD, Vardhanabhuti V, et al. Cervical nodal volume for prognostication and risk stratification of patients with nasopharyngeal carcinoma, and implications on the TNM-staging system. Scientific reports. 2017;7(1):10387.
  • Vardhanabhuti V*, Pang C-L, Tenant S, Taylor J, Hyde C, Roobottom C. Prospective intra-individual comparison of standard dose versus reduced-dose thoracic CT using hybrid and pure iterative reconstruction in a follow-up cohort of pulmonary nodules—Effect of detectability of pulmonary nodules with lowering dose based on nodule size, type and body mass index. European Journal of Radiology. 2017;91:130-141. [First and Corresponding Author]
  • Tenant S, Pang CL, Dissanayake P, Vardhanabhuti V, Stuckey C, Gutteridge C, Hyde C, Roobottom C. Intra-patient comparison of reduced-dose model-based iterative reconstruction with standard-dose adaptive statistical iterative reconstruction in the CT diagnosis and follow-up of urolithiasis. Eur Radiol. 2017 Mar 13. doi: 10.1007/s00330-017-4783-2.
  • Lee EY, Perucho JA, Vardhanabhuti V, He J, Siu SW, Ngu SF, Mayr NA, Yuh WT, Chan Q, Khong PL. Intravoxel incoherent motion MRI assessment of chemoradiation-induced pelvic bone marrow changes in cervical cancer and correlation with hematological toxicity. J Magn Reson Imaging. 2017 Feb 22. doi: 10.1002/jmri.25680.
  • Vardhanabhuti V, Nicol E, Morgan-Hughes G, Roobottom CA, Roditi G, Hamilton MC, Bull RK, Pugliese F, Williams MC, Stirrup J, Padley S, Taylor A, Davies LC, Bury R, Harden S. Recommendations for accurate CT diagnosis of suspected acute aortic syndrome (AAS)-on behalf of the British Society of Cardiovascular Imaging (BSCI)/British Society of Cardiovascular CT (BSCCT). Br J Radiol. 2016 Apr 7:20150705. [First Author]
  • Vardhanabhuti V*, Lo AW, Lee EY, Law SY. Dual-Tracer PET/CT Using 18F-FDG and 11C-Acetate in Gastric Adenocarcinoma With Liver Metastasis. Clin Nucl Med. 2016 Nov;41(11):864-865. First and Corresponding Author]
  • Yuan H, Tong DK, Vardhanabhuti V, Law SY, Chiu KW, Khong PL. PET/CT in the evaluation of treatment response to neoadjuvant chemoradiotherapy and prognostication in patients with locally advanced esophageal squamous cell carcinoma. Nucl Med Commun. 2016 Sep;37(9):947-55.
  • Agarwal Sharma R, Lee EY, Vardhanabhuti V, Khong PL, Ngu SF. Unusual Case of Postmenopausal Diffuse Endometriosis Mimicking Metastastic Ovarian Malignancy. Clin Nucl Med. 2016 Feb;41(2):e120-2.
  • Yuan H, Tong DK, Vardhanabhuti V, Khong PL*. Factors That Affect PERCIST-Defined Test-Retest Comparability: An Exploration of Feasibility in Routine Clinical Practice. Clin Nucl Med. 2015 Dec;40(12):941-4.
  • Vardhanabhuti V*, James J, Nensey R, Hyde C, Roobottom C. Model-based iterative reconstruction in low-dose CT colonography-feasibility study in 65 patients for symptomatic investigation. Acad Radiol. 2015 May;22(5):563-71. [First and Corresponding Author]
  • Vardhanabhuti V, Pang CL, Ninan T, Adams WM, Raju V, Suresh P*. Sarcoidosis--the greatest mimic. Semin Ultrasound CT MR. 2014 Jun;35(3):215-24. [First Author]
  • Vardhanabhuti V*, Riordan RD, Mitchell GR, Hyde C, Roobottom CA. Image comparative assessment using iterative reconstructions: clinical comparison of low-dose abdominal/pelvic computed tomography between adaptive statistical, model-based iterative reconstructions and traditional filtered back projection in 65 patients. Invest Radiol. 2014 Apr;49(4):209-16. [First and Corresponding Author]
  • Vardhanabhuti V*, Ilyas S, Gutteridge C, Freeman SJ, Roobottom CA. Comparison of image quality between filtered back-projection and the adaptive statistical and novel model-based iterative reconstruction techniques in abdominal CT for renal calculi. Insights Imaging. 2013 Oct;4(5):661-9. [First and Corresponding Author]
  • Olubaniyi BO, Bhatnagar G, Vardhanabhuti V, Brown SE, Gafoor A, Suresh PS*. Comprehensive musculoskeletal sonographic evaluation of the hand and wrist. J Ultrasound Med. 2013 Jun;32(6):901-14.
  • Bhatnagar G*, Vardhanabhuti V, Nensey RR, Sidhu HS, Morgan-Hughes G, Roobottom CA. The role of multidetector computed tomography coronary angiography in imaging complications post-cardiac surgery. Clin Radiol. 2013 May;68(5):e254-65.
  • Vardhanabhuti V*, Loader R, Roobottom CA. Assessment of image quality on effects of varying tube voltage and automatic tube current modulation with hybrid and pure iterative reconstruction techniques in abdominal/pelvic CT: a phantom study. Invest Radiol. 2013 Mar;48(3):167-74. [First and Corresponding Author]
  • Vardhanabhuti V*, Loader RJ, Mitchell GR, Riordan RD, Roobottom CA. Image quality assessment of standard- and low-dose chest CT using filtered back projection, adaptive statistical iterative reconstruction, and novel model-based iterative reconstruction algorithms. AJR Am J Roentgenol. 2013 Mar;200(3):545-52. [First and Corresponding Author]
  • Vardhanabhuti V*, Olubaniyi B, Loader R, Riordan RD, Williams MP and Roobottom CA. Image quality assessment in torso phantom comparing effects of varying automatic current modulation with Filtered Back Projection, Adaptive Statistical and Model-Based Iterative Reconstruction Techniques in CT. Journal of Medical Imaging and Radiation Sciences, 2012; 43:228-238. [First and Corresponding Author]
  • Bhatnagar G, Sidhu HS, Vardhanabhuti V, Venkatanarasimha N, Cantin P, Dubbins  P*. The varied sonographic appearances of focal fatty liver disease: review and diagnostic algorithm. Clin Radiol. 2012 Apr;67(4):372-9.
  • Vardhanabhuti V, Venkatanarasimha N, Bhatnagar G, Maviki M, Iyengar S, Adams WM, Suresh P*. Extra-pulmonary manifestations of sarcoidosis. Clinical Radiology. 2012 Mar; 67(3):263-76. [First Author]
  • Sidhu HS, Venkatanarasimha N, Bhatnagar G, Vardhanabhuti V, Fox BM, Suresh SP*. Imaging features of therapeutic drug-induced musculoskeletal abnormalities. Radiographics. 2012 Jan-Feb;32(1):105-27.
  • Vardhanabhuti V*, Bhatnagar G, Brown S, James J, Sidhu H, Shuen V, Thomas R, and Fox B. Value of trainees in a radiology department – a retrospective semi-quantitative analysis. Clinical Radiology 2011; 66(7): 629-638. [First and Corresponding Author]
  • Shuen W*, Vardhanabhuti V and Pearson S. The use of transvaginal ultrasound evaluation premicrowave endometrial ablation. Ultrasound 2011; 19: 36–38.
  • Tamai T.K, Vardhanabhuti V, Arthur S., Foulkes N.S and Whitmore D. Flies and Fish: Birds of a Feather. J. Neuroendocrinology. 2003; 15: 344-349.
  • Tamai T.K, Vardhanabhuti V, Foulkes NS., Whitmore D. Early embryonic light detection improves survival. Current Biology. 2004; 14: R104-R105.  
Book Publication/Chapter
  • Book Chapter: ‘Ionizing Radiation in Medical Imaging and Efforts in Dose Optimization’. V Vardhanabhuti and C Roobottom in Ionizing Radiation Book 1. InTech Publishing – Feb 2012.

  • ‘MCQs for the First FRCR Examination’. V Vardhanabhuti, J James, R Nensey, T Ninan, R Gray and V Shuen. Oxford University Press – August 2010.

  • Yuan H, Vardhanabhuti V, Khong P-L. Imaging of Nasopharyngeal Carcinoma.  Nasopharyngeal Carcinoma: Academic Press; 2019. p. 155-78.

Invited Speaker
  • Vardhanabhuti V, editor Radiomics Applications in NPC. The 4th Hong Kong Radiographers and Radiation Therapists Conference cum The First Greater Bay Area Forum on Radiological Imaging and Technology; 2019.

  • Vardhanabhuti V, editor PSMA PET-CT imaging in Prostate Cancer–Pearls and Pitfalls.

  • Radiology Asia Conference 2019; 2019.

  • Vardhanabhuti V, editor Radiomics-Superficial Learning about Data Science and AI: What Radiologists Should Know. Radiology Asia Conference 2019; 2019.

  • Vardhanabhuti V, editor Mri Radiomics For Pre-treatment Prognostication In Patients With Npc Treated With Intensity-modulated Radiation Therapy. Mini-Symposium on MRI in Radiation Therapy, HTI Symposium, The Hong Kong Polytechnic University; 2018.

  • Vardhanabhuti V, editor Medical imaging perspectives of radiomics/radiogenomics in the era of precision oncology. Sanming Project of Medicine-The 2nd International Symposium on Specialist Education and Advances in Radiation Oncology; 2018.

  • ‘Low dose CT using iterative reconstruction - Implications for liver imaging.’ STAR Symposium Xiamen, China (14th May 2015)

  • “Update of Liver Imaging” Liver Disease Conference – Shenzhen 3rd People’s Hospital, China (19th December 2014)

  • Thoracic Aortic Imaging – Evidence for CT Protocols – British Society of Cardiovascular Imaging (BSCI) Spring Meeting, Glasgow, United Kingdom (24th–25th April 2014).

  • Use of Low Dose CT scanning using model-based iterative reconstruction – Preliminary Experience – British Institute of Radiology (BIR) Radiation Protection in CT meeting, London, UK (6th November 2012).

International Conference Presentations (n = 61). 
Selected Published Proceedings (most recent):
  • Lee VHF, Chan ASY, Kwong DLW, Leung TW, Ng SCY, Tong CC, Lam KO, Vardhanabhuti V, Chan SK, and Choi CW. 2020. Phase II study of consolidative intensity-modulated radiation therapy following first-line palliative systemic chemotherapy for de novo previously untreated metastatic (M1) nasopharyngeal carcinoma. In ASCO, abstract published in  Journal Clinical Oncology. 2020
  • V Vardhanabhuti, HT Au, J Ding, EYP Lee, P Cao, E Hui. Repeatability of Magnetic Resonance Fingerprinting using ISMRM/NIST MRI Phantom in Philips 3T MRI Scanner. In International Society of Magnetic Resonance Imaging (ISMRM) 2020.
  • F Huang, V Vardhanabhuti, PL Khong, M-Y Ng, P Cao. A level-set reformulated as deep recurrent network for left/right ventricle segmentation on cardiac cine MRI. In International Society of Magnetic Resonance Imaging (ISMRM) 2020.
  • J Ding, V Vardhanabhuti, E Lai, Y Gao, S Chan, P Cao. Deep learning-based thigh muscle segmentation for reproducible fat fraction quantification using fat-water decomposition MRI. In International Society of Magnetic Resonance Imaging (ISMRM) 2020.
  • Du R, Vardhanabhuti V. 3D-RADNet: Extracting labels from DICOM metadata for training general medical domain deep 3D convolution neural networks. In Medical Imaging Deep Learning (MIDL) 2020.
  • C. Xie ,Y. Hu, L. Han, J. Fu, V. Vardhanabhuti, K. Chiu. Deep learning CT-based radiomics for prediction of treatment response to neoadjuvant chemoradiation in oesophageal squamous cell carcinoma. In European Congress of Radiology (ECR) 2020.
  • C. Xie, J. Ho, H. Pang, R. Du, K. Chiu, E. Lee, V. Vardhanabhuti. Machine learning re-sampling techniques in imbalanced datasets improve prognostication performance in a multicentre cohort of head and neck cancer patients using a PET-based radiomics model. In European Congress of Radiology (ECR) 2020.
  • C Xie, Y Chen, V Vardhanabhuti. Primary tumour and lymph node radiomics assessment in PET-CT in non-metastatic nasopharyngeal carcinoma patients. In European Congress of Radiology. Vienna, European Society of Radiology, 2020.
  • Vardhanabhuti V. Simulation and Clinical Multi-Reader Study using Clinically-Led Deep Learning Automated Radiograph Triaging System. In European Society of Radiology. Vienna, European Congress of Radiology, 2020. http://dx.doi.org/10.26044/ecr2020/C-05006
  • Tsougenis E, Onder OF, Lai C, Tang T, Lee C, Du R, Vardhanabhuti V. Clinically-Led Automated Radiograph Triaging System Based on Convolution Neural Networks -- A Simulation Study. In 8th Joint Scientific Meeting of RCR & HKCR and 27th Annual Scientific Meeting of HKCR; 2019.
  • Xie C, Du R, Vardhanabhuti V. Prediction of disease early progression in patients with locoregionally advanced nasopharyngeal carcinoma using PET radiomics-based model. In 8th Joint Scientific Meeting of RCR & HKCR and 27th Annual Scientific Meeting of HKCR; 2019.
  • Liu, Z., Jiang, W., Lee, K. H., Lo, Y. L., Ng, Y. L., Dou, Q., Vardhanabhuti V, Kwok, K. W. (2019). A Two-Stage Approach for Automated Prostate Lesion Detection and Classification with Mask R-CNN and Weakly Supervised Deep Neural Network. In Medical Image Computing and Computer-Assisted Intervention (MICCAI) Workshop – Modelling and Monitoring of Computer Assisted Intervention, 2019.
  • Du R, Cao P, Han L, Ai Q, King AD, Vardhanabhuti V. Deep convolution neural network model for automatic risk assessment of patients with non-metastatic nasopharyngeal carcinoma. MIDL, London, UK, 2019.
Current Lab Members
  • Richard Du – FT PhD candidate
  • Chenyi Xie – FT PhD candidate

  • Fan Huang – Post-doctoral Fellow

  • Kei Shing Douglas Ng – Post-doctoral Fellow

  • Jie Lian – Research Assistant, to be PhD candidate (Presidential Scholarship)

  • Vivian Ip – Research Assistant

  • Felix Yung – Research Assistant

Previous Lab Members
  • Jie Dingformer post-doctoral fellow, Aug 2019-May 2020 (now at the Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin 53226, USA)

  • Lieza Vanden Broekeformer post-doctoral fellow, Oct 2019-Sept 2020 (now at MARS Bioimaging Ltd, Christchurch, New Zealand)

  • Weiwen Wuformer post-doctoral fellow, Sept 2019 – Dec 2020 (now at the Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, N.Y. USA)