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Applying AI to quantifying gait and joint loading in a mouse model for knee osteoarthritis using biplanar X-Ray videography, machine learning and force recordings
The aims of this project are two-fold. Firstly, it will develop a tool to automatically extract usable kinematic data from mouse X-Ray recordings with minimal manual input, allowing for a detailed analysis of large data sets. Secondly, it will quantify normal (knee) joint function as well as impaired function as a result of OA which will help to understand the disease much better, from a biomechanical point of view than we do to date.
For informal queries, please contact kristiaan.daout@liverpool.ac.uk.
The application deadline is 12 April 2019.
You can apply here:
https://www.liverpool.ac.uk/study/postgraduate-research/studentships/ai-videography-machine-learning-force-readings/
The aims of this project are two-fold. Firstly, it will develop a tool to automatically extract usable kinematic data from mouse X-Ray recordings with minimal manual input, allowing for a detailed analysis of large data sets. Secondly, it will quantify normal (knee) joint function as well as impaired function as a result of OA which will help to understand the disease much better, from a biomechanical point of view than we do to date.
For informal queries, please contact kristiaan.daout@liverpool.ac.uk.
The application deadline is 12 April 2019.
You can apply here:
https://www.liverpool.ac.uk/study/postgraduate-research/studentships/ai-videography-machine-learning-force-readings/