Deep learning-based autonomous diagnosis of gastrointestinal tract cancers

Gastrointestinal (GI) tract cancer is the leading cause of all cancer deaths. Deep learning-based diagnosis of GI tract diseases has the potential to revolutionise diagnostic speed, accuracy, and cost.

This research will design and develop a deep machine learning-based AI system for polyp detection and classification in the GI tract. This project will develop a holistic dataset for GI tract diseases including endoscopy (CE and PE) images in collaboration with a clinical partner.

How to apply

If you are interested in applying for the above PhD topic please follow the steps below:

1. Contact the supervisor by email or phone to discuss your interest and find out if you would be suitable. Supervisor details can be found on this topic page. The supervisor will guide you in developing the topic-specific research proposal, which will form part of your application.
2. Click on the 'Apply here' button on this page and you will be taken to the relevant PhD course page, where you can apply using an online application.
3. Complete the online application indicating your selected supervisor and include the research proposal for the topic you have selected.

Good luck!

This is a self funded topic

Brunel offers a number of funding options to research students that help cover the cost of their tuition fees, contribute to living expenses or both. See more information here: https://www.brunel.ac.uk/research/Research-degrees/Research-degree-funding. The UK Government is also offering Doctoral Student Loans for eligible students, and there is some funding available through the Research Councils. Many of our international students benefit from funding provided by their governments or employers. Brunel alumni enjoy tuition fee discounts of 15%.

Meet the Supervisor(s)

Md Nazmul Huda - Dr M Nazmul Huda received his BSc (Hons) degree in Electrical and Electronic Engineering from Bangladesh University of Engineering and Technology, Bangladesh in 2008, his MSc by Research degree in Computing Science from Staffordshire University, UK in 2011 and his Ph.D. degree in Robotics and Control from Bournemouth University, UK in 2016.  At present, he is a Senior Lecturer in Electronic and Electrical Engineering at Brunel University London and supervising several PhD students in robotics, artificial intelligence and renewable energy. Before joining at Brunel University London, he has held several academic/research positions at Coventry University, Cranfield University, Bournemouth University, Staffordshire University and Bangladesh. He has more than ten years of experience in performing research and leading research projects in robotics, control and machine learning funded by various funding bodies including EPSRC and Innovate UK. He has filed a patent and published papers on flagship journals and conferences. He is a member of IET, IEEE, IEEE RAS and EPSRC associate peer review college. He has been nominated as a regular reviewer for EPSRC grants applications. He has been collaborating with internal and external academic and industrial partners and actively developing research proposals as a PI and Co-PI for internal and external funding calls including Horizon 2020, Wellcome Trust and High-Volume Transport. He also serves as a reviewer for many flagship journals and conferences in robotics, control and artificial intelligence including IEEE ICRA, IEEE IROS, IEEE SSRR, IEEE/ASME Transactions on Mechatronics, IEEE Robotics and Automation Letters (RA-L) etc.

Related Research Group(s)

Electronic Systems - Investigating processes and mechanisms found in nature to inspire alternative approaches to the design and implementation of intelligent electronic systems.