Title: A novel feature extraction scheme for visualisation of 3D anatomical structures

Authors: R. Menaka; R. Karthik

Addresses: School of Electronics Engineering, VIT University, Vellore, India ' School of Electronics Engineering, VIT University, Vellore, India

Abstract: The purpose of this research is to analyse various algorithms for feature extraction in CT images and thereby developing an efficient scheme for feature extraction that supports effective visualisation of three-dimensional (3D) bony structures. An extensive study has been made on the single-scale and multi-scale spatial domain feature extraction algorithms. In order to overcome the issues associated with spatial domain feature extraction algorithms, a frequency domain-based scheme involving curvelet transform has been introduced. The significant features are extracted by designing a filter based on the statistical parameters of the curvelet coefficients across multiple scales. The slices with significant features are stacked along the z-plane to generate a point cloud. The effectiveness of the proposed curvelet-based algorithm is proved by comparing it with other methods based on Feature Similarity Index Measure (FSIM). Feature similarity was found to be between 85% and 90% for the curvelet-based feature extraction scheme.

Keywords: computed tomography; Harris corner features; SIFT features; SURF features; curvelet transform; FSIM; feature similarity index measure; feature extraction; visualisation; 3D anatomical structures; CT images; medical images; bony structures.

DOI: 10.1504/IJBET.2016.076732

International Journal of Biomedical Engineering and Technology, 2016 Vol.21 No.1, pp.49 - 66

Received: 27 Jul 2015
Accepted: 04 Oct 2015

Published online: 24 May 2016 *

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