Automatic Angle Recognition in Hallux Valgus
Pablo Izquierdo, Ana Calderon, Glenn L Jenkins, Simon Thorne and Ian Mathieson (Cardiff Metropolitan University, United Kingdom (Great Britain))
This paper describes a novel approach to modelling a specific orthopaedic condition, Hallux Valgus; it is a complex deformity resulting in more than 140 possible surgical correction procedures, each focusing on different components of the deformity. Modelling it involves a level of complexity that cannot be readily tackled by techniques traditionally available in the medical domain. It was, therefore, appropriate for us to utilise machine learning techniques; namely through neural network detection and isolation, complemented by angle detection. We present results of running a machine learning algorithm to detect the deformity and end with recommendations as to how it may be utilised in judging successful surgical outcomes.
Conference: UKSim-AMSS 22nd International Conference on Computer Modelling and Simulation, UKSim2020
Published: Mar 25, 2020