Heads and Tails - Tracking the sperm's beating flagellum

Infertility affects 1 in 6 couples, is emotionally devastating, and requires expensive and invasive treatments. Importantly, we place a significant and unequal burden on women, who often require risk-bearing procedures to address what is caused by, in 50% of cases, a male factor. Despite major progress in IVF and other assisted reproduction technologies, the analysis and treatment of male factor infertility lags behind. By taking an interdisciplinary approach - integrating computational mathematics and experimental imaging with clinical data - we are working to improving understanding of these widespread problems and ultimately develop new diagnostics and treatments for male infertility.

This project involves the development of both model-based and deep learning approaches for the analysis of microscopy videos of sperm swimming, with particular interest paid to the rapidly beating tail. How sperm use their tail to swim forms the strongest selection mechanism in natural reproduction. However, existing tools can’t measure how sperm tails move, leading to poor diagnostic and treatment success. By tracking sperm more efficiently from videos, and then using that information in mathematical models to quantify e.g. the efficiency of swimming, we will look to understand: how we can identify the best sperm in a population; how this links to clinical outcomes (such as pregnancy or live birth); and how such insights can be packaged into clinically-usable tools for real-world impact.

While having a base in the School of Mathematics, for this PhD project you will be working within an interdisciplinary Centre that bridges the gaps between computational, experimental and healthcare research. This will give you a unique opportunity to understand the clinical need through interactions with the Fertility Centre at Birmingham Women’s Hospital. This work will build naturally on the research expertise of the supervisor, who has significant experience creating computational and image analysis tools to develop the next generation of diagnostics and treatments for male-factor infertility.

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