Predictive Modelling of Bone Age through Classification and Regression of Bone Shapes

TL;DR

This paper presents a modular approach to automated bone age assessment using bone outline features, achieving accuracy comparable to experts and analyzing factors like ethnicity and sex.

Contribution

It introduces a feature-based system separating image processing from age modeling, improving flexibility, transparency, and accuracy in bone age prediction.

Findings

Models using summary features outperform outline-based models.

Three-bone models match expert accuracy.

The system quantifies ethnicity and sex effects on development.

Abstract

Bone age assessment is a task performed daily in hospitals worldwide. This involves a clinician estimating the age of a patient from a radiograph of the non-dominant hand. Our approach to automated bone age assessment is to modularise the algorithm into the following three stages: segment and verify hand outline; segment and verify bones; use the bone outlines to construct models of age. In this paper we address the final question: given outlines of bones, can we learn how to predict the bone age of the patient? We examine two alternative approaches. Firstly, we attempt to train classifiers on individual bones to predict the bone stage categories commonly used in bone ageing. Secondly, we construct regression models to directly predict patient age. We demonstrate that models built on summary features of the bone outline perform better than those built using the one dimensional representation of the outline, and also do at least as well as other automated systems. We show that models constructed on just three bones are as accurate at predicting age as expert human assessors using the standard technique. We also demonstrate the utility of the model by quantifying the importance of ethnicity and sex on age development. Our conclusion is that the feature based system of separating the image processing from the age modelling is the best approach for automated bone ageing, since it offers flexibility and transparency and produces accurate estimates.