AutoCOR: Autonomous Condylar Offset Ratio Calculator on TKA-Postoperative Lateral Knee X-ray

04/06/2022
by   Gulsade Rabia Cakmak, et al.
5

The postoperative range of motion is one of the crucial factors indicating the outcome of Total Knee Arthroplasty (TKA). Although the correlation between range of knee flexion and posterior condylar offset (PCO) is controversial in the literature, PCO maintains its importance on evaluation of TKA. Due to limitations on PCO measurement, two novel parameters, posterior condylar offset ratio (PCOR) and anterior condylar offset ratio (ACOR), were introduced. Nowadays, the calculation of PCOR and ACOR on plain lateral radiographs is done manually by orthopedic surgeons. In this regard, we developed a software, AutoCOR, to calculate PCOR and ACOR autonomously, utilizing unsupervised machine learning algorithm (k-means clustering) and digital image processing techniques. The software AutoCOR is capable of detecting the anterior/posterior edge points and anterior/posterior cortex of the femoral shaft on true postoperative lateral conventional radiographs. To test the algorithm, 50 postoperative true lateral radiographs from Istanbul Kosuyolu Medipol Hospital Database were used (32 patients). The mean PCOR was 0.984 (SD 0.235) in software results and 0.972 (SD 0.164) in ground truth values. It shows strong and significant correlation between software and ground truth values (Pearson r=0.845 p<0.0001). The mean ACOR was 0.107 (SD 0.092) in software results and 0.107 (SD 0.070) in ground truth values. It shows moderate and significant correlation between software and ground truth values (Spearman's rs=0.519 p=0.0001412). We suggest that AutoCOR is a useful tool that can be used in clinical practice.

READ FULL TEXT

page 1

page 4

page 5

page 7

research
10/09/2019

Estimating regression errors without ground truth values

Regression analysis is a standard supervised machine learning method use...
research
12/19/2018

Automatic Classifiers as Scientific Instruments: One Step Further Away from Ground-Truth

Automatic detectors of facial expression, gesture, affect, etc., can ser...
research
03/25/2023

Feature Tracks are not Zero-Mean Gaussian

In state estimation algorithms that use feature tracks as input, it is c...
research
08/15/2022

A Pipeline for DNS-Based Software Fingerprinting

In this paper, we present the modular design and implementation of DONUT...
research
01/11/2023

The Berkelmans-Pries Feature Importance Method: A Generic Measure of Informativeness of Features

Over the past few years, the use of machine learning models has emerged ...
research
12/11/2020

On the Generation of Disassembly Ground Truth and the Evaluation of Disassemblers

When a software transformation or software security task needs to analyz...
research
04/22/2022

Translating Clinical Delineation of Diabetic Foot Ulcers into Machine Interpretable Segmentation

Diabetic foot ulcer is a severe condition that requires close monitoring...

Please sign up or login with your details

Forgot password? Click here to reset