Classification of long-bone fractures based on digital-geometric analysis of X-ray images

Article Type

Research Article

Publication Title

Pattern Recognition and Image Analysis

Abstract

The classification of fractured of a patient plays an important role in orthopaedic evaluation and diagnosis. It not only aids in assessing the severity of the disease or injury but also serves as a basis of treatment or surgical correction. This paper proposes a novel approach to automated classification of long-bone fractures based on the analysis of an input X-ray image. The method consists of four major steps: (i) extraction of the bone-contour from a given X-ray image, (ii) identification of fracture-points or cracks, (iii) determination of an equivalent set of geometric features in tune with the Müller-AO clinical classification of fractures, and (iv) identification and detailed assessment of the fracture-type. The decision procedure makes use of certain geometric properties of digital curves such as relaxed digital straight line segments (RDSS), arcs, discrete curvature, and concavity index. The proposed method for the analysis of fractures is applied on different types of bone-images and is observed to have produced correct classification in most of the test-cases.

First Page

742

Last Page

757

DOI

10.1134/S1054661816040027

Publication Date

10-1-2016

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