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Dr Joseph Jacob
Dr Joseph Jacob profile picture
  • Principle Research Fellow
  • Respiratory Medicine
  • Div of Medicine
  • Faculty of Medical Sciences

I qualified in medicine from Imperial College London, and following early training years in London and the South East, I worked for Medecins sans Frontieres for 2 years in Darfur, Sudan and India. My radiology training encompassed work at Kings College  Hospital, London and Auckland City Hospital, New Zealand prior to completion of an MD Research with Imperial College London under Professor David Hansell at the Royal Brompton Hospital in 2016.

My primary research interest has been in the use of computer tools to quantify lung damage. I was awarded a 5-year Wellcome Trust Clinical Research Career Development Fellowship in 2018 at University College London, to evaluate the role of computer analysis of CT imaging to detect damage in lung cancer screening populations. Other research interests, based at the Centre for Medical Image Computing at University College London relate to the use of computer-analysis of CT imaging in fibrosing lung diseases and airways diseases. I have co-authored over 100 papers, won national and international awards for my work and was awarded the 2017 best thesis prize by the National Heart and Lung Institute.

I am currently the Research lead for the British Society of Thoracic Imaging and was the Royal College of Radiologist Roentgen Professor for the year 2021.

Research Groups
Research Summary

I have been evaluating computer analyses of lung damage on CT imaging for over 5 years with an emphasis on lung fibrosis and its evolution over time. I work at the Centre for Medical Image Computing, University College London, with a talented team of computer scientists where advanced machine learning and deep learning techniques are used to identify and quantify lung damage.

Teaching Summary

I have delivered over 85 invited lectures around the world including as a keynote speaker. As well as discussing contemporary research topics I also lecture on the fundamentals of image interpretation across a variety of lung diseases. 

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