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Enhanced artificial intelligence breast MRI scanning system

IntelliScan: Enhanced artificial intelligence breast MRI scanning system


Breast cancer is the most common cancer in women worldwide, with nearly 1.7 million new cases diagnosed in 2012 (second most common cancer overall). This represents about 12% of all new cancer cases and 25% of all cancers in women. According to the World Health Organisation (Global Heath Estimates 2013, over 50% of breast cancer cases and 42% of deaths occur in developed countries. This includes the UK, where for every five (5) women newly diagnosed with breast cancer, one (1) of them will die.

This project therefore seeks to develop INTELLISCAN (an Artificial Intelligence, machine learning enhanced breast MRI scanning system for use as a highly efficient, more accurate breast cancer screening tool). Our technology applies computer based image interpretation to deliver improved detection, and diagnostic doctor/patient experience. This innovative project will be based on an enhanced software application. The successful exploitation of the technology will result in cumulative revenue of £18.5m after 6 years in the market.

This project offers a technological solution that addresses a significant healthcare challenge in the UK – breast cancer. INTELLISCAN aims to apply both advanced image processing and deep machine learning in order to develop a national platform for assisting doctors in the interpretation of data coming from breast MRI scans. The platform will be continuously fed by the data coming from all the MRI systems used in UK and will use the data and the models in order to detect anomalies and to categorise them by severity. The algorithms will also assess treatment efficiency by comparing successive MRI scans of the same patient.


INTELLISCAN represents a cutting-edge attempt to digitalise breast cancer MRI interpretation and reporting. This project aims to achieve this game-changing innovation by combining specialist “image processing” technologies and disruptive “digital” technologies (data analytics and machine learning) with advances in artificial intelligence (processing algorithms) and the internet of things (cloud hosting and image remote data transmission). It will achieve this by developing a Breast Image Interpretation and Transmission Model, linked to MRI scanners across the country that integrates a series of visualisation, data processing, communication, and decision-support systems and dramatically improves access to breast healthcare and cancer treatment compliance.


INTELLISCAN will “disrupt existing markets” by changing completely the way that breast cancer MRI is done, reported, and actioned. Hospital radiographers will be presented with digitally advanced ad highly reliable reports, allowing them to focus on other aspects of information for doctors. This thereby improves patient outcomes (currently 20% of UK cancer deaths are from missed/late diagnosis) and transforms healthcare delivery in the UK. This will also dramatically disrupt the training requirements for radiographers.

With the UK currently having the worst cancer survival rates in Western Europe, this INTELLISCAN project will therefore speed up the development of a new digital solution to the UK’s healthcare challenges as required by the competition scope.

Project Partners

  • First Option Software
  • Teesside University
  • Brunel University London

Meet the Principal Investigator(s) for the project

Professor Tat-Hean Gan
Professor Tat-Hean Gan - Professional Qualifications CEng. IntPE (UK), Eur Ing BEng (Hons) Electrical and Electronics Engg (Uni of Nottingham) MSc in Advanced Mechanical Engineering (University of Warwick) MBA in International Business (University of Birmingham) PhD in Engineering (University of Warwick) Languages English, Malaysian, Mandarin, Cantonese Professional Bodies Fellow of the British Institute of NDT Fellow of the Institute of Engineering and Technology Tat-Hean Gan has 10 years of experience in Non-Destructive Testing (NDT), Structural Health Monitoring (SHM) and Condition Monitoring of rotating machineries in various industries namely nuclear, renewable energy (eg Wind, Wave ad Tidal), Oil and Gas, Petrochemical, Construction and Infrastructure, Aerospace and Automotive. He is the Director of BIC, leading activities varying from Research and development to commercialisation in the areas of novel technique development, sensor applications, signal and image processing, numerical modelling and electronics hardware. His experience is also in Collaborative funding (EC FP7 and UK TSB), project management and technology commercialisation.

Related Research Group(s)

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Project last modified 12/10/2023