About the Project
Breast cancer is one of the most common and life-threatening diseases worldwide, hence, early detection plays a crucial role in improving survival rates. Digital breast tomosynthesis (DBT) has made significant advancements in breast imaging by providing clearer, more detailed 3D-like scans in comparison to traditional techniques such as mammograms. However, analysing these scans is still a complex and time-consuming task, often leading to inconsistencies in diagnosis.
The proposed research aims to develop a Computer-Aided Detection (CAD) system utilising Artificial Intelligence (AI) techniques to help radiologists in identifying and classifying abnormalities in Digital Breast Tomosynthesis (DBT) scans while providing greater accuracy and efficiency. The CAD system will help in detecting suspicious areas, differentiating between benign and malignant tumours, and reducing the chances of false positives and false negatives results. By doing this, the system can help radiologists focus on the most critical cases, reducing their workload while improving overall diagnostic confidence and reducing the need to expose the patients to unnecessary radiation waves. This study will improve the existing work by exploring different methods to refine image interpretation, assess the system’s reliability using clinical performance metrics, and evaluate its potential impact on real-world screening processes. The aim is to create CAD systems that can seamlessly integrate into medical workflows, making breast cancer screening more accurate, accessible, and efficient.
How to apply:
For further information please contact: Professor Abdel Hamid Soliman – [contact details available in the full listing]
The applications should consist of a cover letter or personal statement of interest, and a CV.
Professor Abdel Hamid Soliman
Department of Engineering
School of Digital, Technology, Innovation & Business
University of Staffordshire
College Road
Stoke-on-Trent
ST4 2DE
The expected start dates are January and April 2026.
Entry Requirements:
Essential:
- Bachelor's/Master's degree in Engineering, Computing, or a related field.
- Experience with MATLAB and its toolboxes, such as the Deep Learning, Computer Vision, and Signal and Image Processing Toolboxes.
- The standard minimum IELTS Academic requirement is 6.5 overall with no less than 6.0 in each band. Some International students are also required to meet UKVI requirements for the appropriate study visa. A valid ATAS certificate (where required) must be secured as a prerequisite to enrolment.
Desirable:
- Experience in AI (ML/DL) model development for medical imaging.
- Experience with Computer-Aided Models for Tumour Detection.
- Strong problem-solving and analytical skills.
- Experience in scientific writing, including publishing journal and/or conference papers (an advantage).
