3 research outputs found
Image analysis for extracapsular hip fracture surgery
PhD ThesisDuring the implant insertion phase of extracapsular hip fracture surgery, a
surgeon visually inspects digital radiographs to infer the best position for
the implant. The inference is made by “eye-balling”. This clearly leaves
room for trial and error which is not ideal for the patient.
This thesis presents an image analysis approach to estimating the ideal positioning
for the implant using a variant of the deformable templates model
known as the Constrained Local Model (CLM). The Model is a synthesis of
shape and local appearance models learned from a set of annotated landmarks
and their corresponding local patches extracted from digital femur
x-rays.
The CLM in this work highlights both Principal Component Analysis (PCA)
and Probabilistic PCA as regularisation components; the PPCA variant being
a novel adaptation of the CLM framework that accounts for landmark
annotation error which the PCA version does not account for. Our CLM
implementation is used to articulate 2 clinical metrics namely:
the Tip-Apex Distance and Parker’s Ratio (routinely used by clinicians to assess
the positioning of the surgical implant during hip fracture surgery)
within the image analysis framework. With our model, we were able to
automatically localise signi cant landmarks on the femur, which were
subsequently used to measure Parker’s Ratio directly from digital radiographs
and determine an optimal placement for the surgical implant in
87% of the instances; thereby, achieving fully automatic measurement of
Parker’s Ratio as opposed to manual measurements currently performed
in the surgical theatre during hip fracture surgery