Contact

• workRoom B64 Clinical Sciences Building
  Nottingham City Hospital
  Hucknall Road
  Nottingham
  NG5 1PB
  UK
• work0115 8231895
• Yan.Chen@nottingham.ac.uk

Biography

Dr Yan Chen is Associate Professor of Cancer Screening at School of Medicine, University of Nottingham.

Her research involves exploring novel technologies and techniques that enhance screening programme, whilst minimising risk to the patient. She is recognised as a leader in researching the clinical performance in screening programmes, quality assurance of screening programmes and improving medical imaging perception.

Expertise Summary

Yan was invited to join the University of Nottingham in 2019 and since then has rapidly demonstrated expertise and leadership of multiple research programmes in health screening to increase the quality of cancer detection. She has already secured over £5 million in research funding to increase cancer detection and improve screening performance . She works directly for the National NHS Breast Screening Programme and has obtained several large research grants from WHO, EU, Public Health England, NIHR, Innovate UK and industrial partners, plus a variety of charities.

Her expertise focuses on how to evaluate and improve the medical imaging interpretation. Her research has generated societal impact by changing healthcare practice to improve patient benefit.

She was awarded the prestigious Honorary Membership of the Royal College of Radiologists in 2014 as a result of her notable contributions to clinical radiology in the UK.

Yan is internationally known and has more than 55 high-quality refereed publications in both Computer Science and Medical Sciences journals, conference proceedings and book chapters and has been invited to over 30 national and international conference presentations.

Yan's current research projects are:

• PERFORMS (Personal Performance in Mammographic Screening): UK National mandated Breast Cancer Screening External Quality Assurance scheme. UK Breast Screening Programme.
• IMPROVE: a specialist training scheme for radiographers who undergo breast screening training.
• PERFECTS (PERFormance Evaluation for CT Screening): the first national External Quality Assurance scheme for lung cancer imaging assessment. The scheme is used to ensure appropriate interpretation of lung scans which benefits patient outcome.
• DART (The Integration and Analysis of Data using Artificial Intelligence to Improve Patient Outcomes with Thoracic Diseases): an AI project aims to develop integrated diagnostics that will enable the earlier diagnosis of lung cancer for increased patient survival and large time and cost savings to the NHS.
• MyPeBS (My Personal Breast Screening): is a major ambitious European initiative. This unique international clinical study compares a personalised risk-based screening strategy (based on the individual women's risk of developing breast cancer) to standard screening among 85,000 women aged 40 to 70 in 6 countries: Belgium, France, Israel, Italy, United Kingdom and Spain.
• PROSPECTS (Prospective Randomised Trial of Digital Breast Tomosynthesis): A randomised contrail trial involving 100,000 female volunteers to compare the use of traditional 2D mammograms with the new 3D breast imaging technology. The trial will measure the efficacy and cost-effectiveness of the two technologies.

Research Summary

Her research interests chiefly concern human performance evaluations in medical imaging applications in their widest sense using visual search and computer science approaches. This currently… read more

Recent Publications

• CHEN Y, JAMES J, MICHALOPOULOU E, DARKER I and JENKINS J, 2022. Performance of Radiologists and Radiographers in Double Reading Mammograms: The UK National Health Service Breast Screening Program Radiology.
• YAN CHEN, JONATHAN JAMES, ELENI MICHALOPOULOU and IAIN DARKER, 2021. The relationship between missed breast cancers on mammography in a test-set based assessment scheme and real-life performance in a National Breast Screening Programme. European Journal of Radiology. 142, 109881
• CHEN Y, JAMES JJ, CORNFORD EJ and JENKINS J, 2020. Relationship Between Mammography Readers Real-life Performance and Performance in a Test-set Based Assessment Scheme in a National Breast Screening Programme. Radiology: Imaging Cancer.
• GALE A.G. and CHEN Y, 2020. A review of the PERFORMS scheme in breast screening The British Institite of Radiology. 93: 20190908,

• View all publications

Current Research

Her research interests chiefly concern human performance evaluations in medical imaging applications in their widest sense using visual search and computer science approaches. This currently encompasses the radiological areas of: breast screening (mammography, tomography, MRI, CESM); prostate cancer imaging (mpMRI), lung cancer imaging and chest CT as well as digital pathology and surgical areas of; orthopaedic and laparoscopic surgery, as well as dental surgical imaging.

In these domains she has performed many eye tracking and other investigations. She is also interested in Artificial Intelligence testing and evaluation in radiology and pathology. She currently collaborates externally with the Royal College of Radiologists, U.S. Food and Drug Administration, as well as radiology/pathology and surgery various departments within Nottingham QMC and Nottingham City hospitals, University Hospitals of Leicester, University of Cambridge and University of Birmingham Dental Hospital.

Future Research

She is currently pursuing the development of a spin off company concerning implementing the PERFORMS scheme internationally and is also involved in a major European H2020 precision imaging study (MyPEBS).

• CHEN Y, JAMES J, MICHALOPOULOU E, DARKER I and JENKINS J, 2022. Performance of Radiologists and Radiographers in Double Reading Mammograms: The UK National Health Service Breast Screening Program Radiology.
• YAN CHEN, JONATHAN JAMES, ELENI MICHALOPOULOU and IAIN DARKER, 2021. The relationship between missed breast cancers on mammography in a test-set based assessment scheme and real-life performance in a National Breast Screening Programme. European Journal of Radiology. 142, 109881
• CHEN Y, JAMES JJ, CORNFORD EJ and JENKINS J, 2020. Relationship Between Mammography Readers Real-life Performance and Performance in a Test-set Based Assessment Scheme in a National Breast Screening Programme. Radiology: Imaging Cancer.
• GALE A.G. and CHEN Y, 2020. A review of the PERFORMS scheme in breast screening The British Institite of Radiology. 93: 20190908,
• MCMAHON M.A., HAIGH I., CHEN Y., MILLICAN-SLATER R.A. and SHARMA N., 2020. Role of vacuum assisted excision in minimising overtreatment of ductal atypias. European Journal of Radiology.
• CHEN Y, JAMES J, CORNFORD EJ and JENKINS J, 2020. The relationship between mammography readers real-life performance and performance in a test-set based assessment scheme in a national breast screening programme: Further analysis using Bland-Altman plots Radiology: Imaging Cancer.
• Prostate Imaging Self-assessment and Mentoring (PRISM): a prototype self-assessment scheme. 2019. At: Town and Country Resort & Convention Center San Diego, California, United States02/16/2019 00:00:00-02/21/2019 00:00:00.
• PRostate Imaging Self-assessment and Mentoring (PRISM): a prototype self-assessment scheme for radiologists. 2019. At: Austria Center Vienna02/27/2019 00:00:00-03/03/2019 00:00:00.
• N. SHARMA, M. MCMAHON, Y. CHEN and B. J. G. DALL, 2019. The Potential Impact of Digital Breast Tomosynthesis on the Benign Biopsy Rate in Women Recalled within the UK Breast Screening Programme. Radiology. 29(2), 310-317
• X.LIU, J.LOU, H.FANG, Y. CHEN, P. OUYANG, Y. WANG, B. ZOU and L. WANG, 2019. A novel robust reversible watermarking scheme for protecting authenticity and integrity of medical images IEEEXplore. (In Press.)
• Q. TANG, Y. CHEN, G. SCHAEFER and A. GALE, 2019. The wearable augmented reality (AR) approach to support mammographic training: Hololens for screener training. In: Biomedical Optics and Imaging - Proceedings of SPIE. 10954. (In Press.)
• Prostate Imaging Self-assessment and Mentoring Scheme. 2018. At: Crowne Plaza Barcelona09/13/2018 00:00:00-09/16/2018 00:00:00.
• Y. CHEN, L. DONG, E. CORNFORD and J. JENKINS, 2018. The relationship between breast screening readers' real-life performance and their associated performance on the PERFORMS scheme. BREAST CANCER RESEARCH. 20,
• R. S. BHOGAL and A.G. GALE, 2018. Medical Image Encryption using Chaotic Map Improved Advanced Encryption Standard. International Journal of Information Technology and Computer Science(IJITCS).
• Y. ZENG, Y. ZHAO, S. LIAO, M. LIAO, Y. CHEN and X. LIU, 2018. Liver vessel segmentation based on centerline constraint and intensity model. Biomedical Signal Processing and Control. 45, 192-201
• Initial investigation of reading efficiency from experienced radiologists interpreting digital breast tomosynthesis (DBT) images. 2018. At: ACC Liverpool01/01/1900 00:00:00-01/01/1900 00:00:00.
• R.STANTON, D. JETHWA, K.JETHWA, Y. CHEN, L. WHISKER and S. TENNANT, 2018. The Value of Contrast Enhanced Spectral Mammography (CESM) in the Assessment of Lobular Breast Cancer. Tennant.
• Y. CHEN, Y. ZENG, S. LIAO, P. TANG, Y. ZHAO, M. LIAO and Y.X. LIANG, 2018. Automatic liver vessel segmentation using 3D region growing and hybrid active contour model. Computers in Biology and Medicine. 97, 63-73
• Discriminative and robust zero-watermarking scheme based on completed local binary pattern for authentication and copyright identification of medical images. 2018. At: Houston01/01/1900 00:00:00-01/01/1900 00:00:00.
• JAMES JJ and GIANNOTTI E, 2018. Evaluation of a computer-aided detection (CAD)-enhanced 2D synthetic mammogram: comparison with standard synthetic 2D mammograms and conventional 2D digital mammography. Clinical Radiology. 73, 886-892
• L. DONG, D. BERNADI, Q. TANG, A.G. GALE, X. LIU and Y. CHEN, 2017. Is there a difference in reading time when normal and abnormal DBT cases are examined by DBT experienced radiologists? BREAST CANCER RESEARCH. 19,
• DBT interpretation training: findings from analysis of expert visual search behaviour. 2017. At: Berlin, Germany01/01/1900 00:00:00-01/01/1900 00:00:00.
• H.NEVISI, Y. CHEN, L. DONG and A.G. GALE, 2017. How quickly do breast screeners learn their skills?. In: In SPIE Medical Imaging.
• L. DONG, Y. CHEN and A.G. GALE, 2017. Exploring the potential of analysing visual search behaviour data using FROC (free-response receiver operating characteristic) method: an initial study. In: SPIE Medical Imaging.
• Q. TANG, Y. CHEN and A.G. GALE, 2017. The implementation of an AR (augmented reality) approach to support mammographic interpretation training: an initial feasibility study.. In: SPIE Medical Imaging 2017 10136. 1013604-1-1013604-8
• Q. TANG, Y. CHEN and A.G. GALE, 2017. Rich interaction and feedback supported mammographic training: A trial of an augmented reality approach. Communications in Computer and Information Science. 723, 377-385
• Y. CHEN, J.JAMES, A.G. GALE and L. DONG, 2016. Measuring performance in the interpretation of chest radiographs: a pilot study. Clinical Radiology.
• Y. CHEN, H.NEVISI and L. DONG, 2016. How new readers perform as compared to more experienced readers on the PERFORMS scheme. BREAST CANCER RESEARCH.
• The international use of PERFORMS mammographic test sets. 2016. At: Malmö, Sweden01/01/1900 00:00:00-01/01/1900 00:00:00.
• S. TENNANT, J.JAMES, E. CORNFORD, H. BURRELL, L. HAMILTON and C. GIRO-FRAGOULAKIS, 2016. Contrast-Enhanced Spectral Mammography Improves Diagnostic Accuracy in the Symptomatic Setting. Clinical Radiology.
• Errors in Reporting Mammograms 2016. 01/01/1900 00:00:00-01/01/1900 00:00:00.
• L. DONG, Y. CHEN, A.G. GALE and P. PHILLIPS, 2016. Eye Tracking Method Compatible with Dual-screen Mammography Workstation.. In: Procedia Computer Science 90. Elsevier BV. 206-211
• A.G. GALE and Y. CHEN, 2016. Preface. In: 20th Conference on Medical Image Understanding and Analysis (MIUA) 90. Elsevier.
• E. CORNFORD, A.E. TURNBULL, J.JAMES, R. TSANG, T. AKRAM, H. BURRELL, V. JONES and Y. CHEN, 2015. Accuracy of GE digital breast tomosynthesis vs supplementary mammographic views for diagnosis of screen-detected soft-tissue breast lesions. BRITISH JOURNAL OF RADIOLOGY. 89(1058),
• Common mammography reading errors in real life and PERFORMS. 2015. At: East Midlands Conference Centre, Nottingham01/01/1900 00:00:00-01/01/1900 00:00:00.
• S. TENNANT, E. CORNFORD, J.JAMES, H. BURRELL, L. HAMILTON and Y. CHEN, 2015. Contrast enhanced spectral mammography (CESM) - What is the "Added Value" in a symptomatic setting?: Initial findings from a UK centre BREAST CANCER RESEARCH. 17(Suppl 1), 14
• E. CORNFORD, A.E. TURNBULL, J.JAMES, R. TSANG, T. AKRAM, H. BURRELL and Y. CHEN, 2015. Accuracy of GE digital breast tomosynthesis versus supplementary mammographic views for diagnosis of screen-detected soft tissue breast lesions. Breast Cancer Research. 17,
• A. SELVAN, Y. CHEN and A.G. GALE, 2015. A perceptual aid to delineating the extent of potential mammographic abnormalities. BREAST CANCER RESEARCH. 17(Suppl 1), 19
• Challenge to detection in screening mammography and feedback from mini-PERFORMS lab. 2015. At: Annual Meeting, London01/01/1900 00:00:00-01/01/1900 00:00:00.
• Performance Testing for Radiologists Interpreting Chest Radiographs. 2015. At: McCormick Place, Chicago, USA01/01/1900 00:00:00-01/01/1900 00:00:00.
• Y. CHEN, J.JAMES, A.E. TURNBULL and A.G. GALE, 2015. The use of lower resolution viewing devices for mammographic interpretation: implications for education and training. European Radiology. 25(10), 3003-3008
• L. DONG, Y. CHEN, A.G. GALE, B. REES and C. MAXWELL-ARMSTRONG, 2014. Visual search behaviour during laparoscopic cadaveric procedures. In: Proc. SPIE 9037, Medical Imaging 2014: Image Perception, Observer Performance, and Technology Assessment. 903719.
• Y. CHEN, L. DONG, A.G. GALE, B. REES and C. MAXWELL-ARMSTRONG, 2014. Laparoscopic surgical skills training: an investigation of the potential of using surgeons' visual search behaviour as a performance indicator.. In: C. MELLO-THOMS and M. KUPINSKI, eds., Proc. SPIE 9037, Medical Imaging 2014: Image Perception, Observer Performance, and Technology Assessment 903704.
• Y. CHEN, L. DONG and A.G. GALE, 2014. Are abnormalities missed in the PERFORMS self-assessment scheme due to visual or cognitive factors? Breast Cancer Research. 16,
• J. YOUNGS, C. MAXWELL-ARMSTRONG, H. PARK, A.G. GALE and Y. CHEN, 2013. Can an eye tracker be used as a marker of surgical progress? International Journal of Surgery. 11(8), 695
• L. DONG, Y. CHEN and A.G. GALE, 2013. Breast screening: understanding case difficulty and the nature of errors.. In: C. ABBEY, ed., Proc. SPIE 8673, Medical Imaging 2013: Image Perception, Observer Performance, and Technology Assessment
• Y. CHEN and A.G. GALE, 2013. Does routine breast screening practice over-ride display quality in reporting enriched test sets?. In: C. ABBEY and C. MELLO-THOMS, eds., Medical Imaging 2013: Image Perception, Observer Performance, and Technology Assessment.
• A.G. GALE and Y. CHEN, 2012. Radiological informatics in breast screening: Towards improved radiologists' performance. BMEI. 1104-1107
• Y. CHEN, A.G. GALE and M. EVANOFF, 2012. Performance differences across the Atlantic when UK and USA radiologists read the same set of test screening cases In: Medical Imaging 2012: Image Perception, Observer Performance, and Technology Assessment.
• L. DONG, Y. CHEN, A.G. GALE and D. CHAKRABORTY, 2012. A potential method to identify poor breast screening performance. In: In Medical Imaging 2012: Image Perception, Observer Performance, and Technology Assessment. SPIE.
• Y. CHEN, A.G. GALE, A.E. TURNBULL and J.JAMES, 2011. Is image manipulation necessary to interpret digital mammographic images efficiently? In: Progress in Biomedical Optics and Imaging - Proceedings of SPIE. 7966.
• Y. CHEN, A.G. GALE, A.E. TURNBULL and J.JAMES, 2011. Is image manipulation necessary to interpret digital mammographic images efficiently? In: Medical Imaging 2011: Image Perception, Observer Performance, and Technology Assessment. SPIE.
• I.T. DARKER, Y. CHEN and A.G. GALE, 2011. Health professionals' agreement on density judgements and successful abnormality identification within the UK Breast Screening Programme. In: Progress in Biomedical Optics and Imaging - Proceedings of SPIE. 7966.
• L. DONG, Y. CHEN and A.G. GALE, 2011. Early identification of substandard breast screening performers. Breast Cancer Research. 13,
• Y. CHEN, A.G. GALE, M. EVANOFF and U. ZAKIR, 2011. Cross-Atlantic differences in reading the same breast screening cases. Breast Cancer Research.
• Y. CHEN, J.JAMES, A. EVANS, A.E. TURNBULL and A.G. GALE, 2010. An investigation of workstation image manipulation usage when examining FFDM images. Breast Cancer Research. 12(Suppl 3), 9
• I.T. DARKER, A.G. GALE and Y. CHEN, 2010. Variability in film reader estimates of breast density in the PERFORMS scheme. Breast Cancer Research. 12(Suppl 3), 42
• Y. CHEN and Y. CHEN, 2010. Using eye gaze in intelligent interactive imaging training In: Proceedings of the 2010 workshop on Eye gaze in intelligent human machine interaction - EGIHMI '10..
• Y. CHEN and A.G. GALE, 2010. Intelligent Computing Applications Based on Eye Gaze: Their Role in Medical Image Interpretation. 320-325
• Y. CHEN, A.E. TURNBULL, J.JAMES, A.G. GALE and H. SCOTT, 2010. Breast screening: visual search as an aid for digital mammographic interpretation training. In: Medical Imaging 2010: Image Perception, Observer Performance, and Technology Assessment. SPIE.
• Y. CHEN, A.G. GALE and A. EVANS, 2009. The feasibility of vision-supported computer-based training in digital mammography. Breast Cancer Research. 11, 29
• Y. CHEN, A.G. GALE, H. SCOTT, A. EVANS and J.JAMES, 2009. Computer-Based Learning to Improve Breast Cancer Detection Skills.. In: J.A. JACKO, ed., Proceedings of the 13th International Conference on Human-Computer Interaction, Part IV: Interacting in Various Application Domains 5613. 49-57
• Y. CHEN, A.G. GALE and H. SCOTT, 2008. Mammographic interpretation training: what exactly do film-readers want? Breast Cancer Research. 10(S3),
• Y. CHEN, A.G. GALE and H. SCOTT, 2008. Anytime, Anywhere Mammographic Interpretation Training. Contemporary Ergonomics. 375-380
• Analysis of visual search behaviour from experienced radiologists interpreting digital breast tomosynthesis (DBT) images: a pilot study. At: Houston01/01/1900 00:00:00-01/01/1900 00:00:00.
• Q. TANG, Y. CHEN, G.SCHAEFER and A.G. GALE, The development of an augmented reality (AR) approach to mammographic training: overcoming some real world challenges.. In: Medical Imaging 2018: Image-Guided Procedures, Robotic Interventions, and Modeling.: International Society for Optics and Photonics 10576.
• Y. CHEN, J.JAMES and A.G. GALE, How important is mammographic image manipulation when examining digital screening cases? Breast Cancer Research. 11(7),
• Y. CHEN, A.G. GALE and H. SCOTT, Mammographic interpretation training in the UK: current difficulties and future outlook.. In: B. SAHINER and D.J. MANNING, eds., Medical Imaging 2009: Image Perception, Oberver Performance and Technology Assessment 7263.
• Y. CHEN, A.G. GALE and H. SCOTT, Mammographic interpretation training: how useful is handhled technology? Progress in biomedical and optical imaging. 9,
• Y. CHEN, T. ROSS and V. MITCHELL, The need for technology to support creative information sharing whilst mobile: Identified activities and relationship groups. Lecture Notes in Computer Science. 4564, 50-59