Few-Shot Medical Segmentation Using Deep Learning

We are seeking a highly motivated and talented candidate for a self-funded PhD position in the field of Few-Shot Medical Segmentation using Deep Learning. This opportunity is ideal for individuals with a strong background in computer vision, machine learning, and a passion for advancing medical image analysis.Medical image segmentation plays a crucial role in disease diagnosis, treatment planning, and medical research. In this project, the selected PhD candidate will work on developing cutting-edge deep learning techniques for few-shot medical image segmentation. Few-shot learning enables models to accurately segment medical images with minimal annotated data, a critical aspect in the medical field where data acquisition and labeling can be expensive and time-consuming.The project will involve:- Investigating state-of-the-art few-shot learning algorithms and adapting them to the medical imaging domain.- Developing novel neural network architectures for robust and accurate medical image segmentation..- Evaluating and benchmarking the developed methods on diverse medical imaging datasets.This research project offers a unique opportunity to make a significant impact on the healthcare industry by advancing the state-of-the-art in medical image analysis.

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)

Alina Miron - Alina is a lecturer in the Computer Science department and a member of the Intelligent Data Analysis (IDA). Alina has a PhD in machine learning in the field of autonomous vehicles and is an artificial intelligence researcher, developer and educator.  She has excellent understanding of data, especially real-time data and a strong background in computer vision, natural language processing and data science.