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Prof Dean Barratt
2.04 (Malet Place Eng. Building) / 1.01 (Charles Bell House)
UCL Medical Physics & Biomedical Engineering
Floor 2, Malet Place Engineering Building, UCL Gower St. Campus
Prof Dean Barratt profile picture
  • Professor of Medical Image Computing
  • Dept of Med Phys & Biomedical Eng
  • Faculty of Engineering Science
Research Summary


I co-lead the CANDI Research Group and my academic research focuses on the development of new medical image analysis and computational modelling technologies to support the detection, diagnosis, and treatment of disease, particularly solid-organ cancers.

My research encompasses both methodological research (algorithm development) and translational research, including the development of prototype clinical software and systems, clinical evaluation studies, and negotiating regulatory and clinical pathways.

Areas of Research Interest

  • The application of emerging AI and machine learning techniques to improve the safety, efficacy, accuracy, accessibility, and cost-effectiveness of computer-assisted interventions (including minimally-invasive and image-guided surgical procedures) and non-surgical procedures such as radiotherapy;
  • The use of ultrasound imaging as a safe, low-cost, and versatile tool for localising internal tissue structures and disease during interventional procedures
  • The analysis of medical ultrasound images;
  • Automatic and semi-automatic multi-modal image registration (the spatial alignment of different types of images, such MRI, CT, x-ray, and ultrasound);
  • Automatic and semi-automatic multi-modal image segmentation (identifying clinally-important features in medical images, such as 
  • Prostate cancer, pancreatobiliary cancers, and orthopaedic surgery;
  • The analysis of longitudinal images for improved detection of disease progression and risk stratification.
  • Realtime 3D spatial tracking of medical instruments
  • Translational research related to the design, development, and clinical evaluation of software-based medical devices, with expertise in image-guided navigation systems, and regulatory compliance.
  • Pre-operative planning and simulation of computer-assisted interventional procedures.
My research has resulted in novel computer algorithms to align spatially different types of image (multi-mode image registration) with minimal use interaction, and new image-based methods for compensating for soft-tissue motion during interventional procedures that draw on advanced computational modelling techniques.

I have also led the development and commercialisation of a CE-marked and FDA-approved software-based medical device for performing tumour-targeted prostate cancer needle biopsy and minimally-invasive prostate cancer treatments.

Research Affiliations

  • Computer-assisted Navigation, Diagnosis & Intervention (CANDI) Research Group (https://www.ucl.ac.uk/medical-physics-biomedical-engineering/research/research-groups/computer-assisted-navigation-diagnosis-and-intervention-candi)
  • UCL Department of Medical Physics & Biomedical Engineering
  • UCL Department of Computer Science
  • UCL Centre for Medical Image Computing (CMIC)
  • UCL Wellcome-EPSRC Centre for Interventional & Surgical Science (WEISS)
  • UCL Institute of Healthcare Engineering (IHE)
  • UCL Hospital NHS Foundation Trust (Radiology)
Teaching Summary
I am the Director of Studies for the Department of Medical Physics & Biomedical Engineering and a member of the UCL Faculty of Engineering Sciences Teaching Committee.

I currently lead the Dragon's Den Scenario for 2nd year Biomedical Engineering undergraduates.

01-OCT-2011 Senior Lecturer Medical Physics & Bioengineering University College London, United Kingdom
Academic Background
2013   ATQ01 - Successfully completed an institutional provision in teaching in the HE sector Institute of Education
2002   Doctor of Philosophy Imperial College of Science, Technology and Medicine
1995   Master of Science Imperial College of Science, Technology and Medicine
1994   Master of Engineering (Honours) University of Oxford
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