@inproceedings{c0aeca4735244a2988be889745e3b7ca,
title = "Extracting myofibre orientation from micro-CT images: An optimisation study",
abstract = "Recent studies introduced intensity based structure tensor analysis to extract the myocardium structure from micro X-ray computed tomography (micro-CT) images. The implementation of this method is empirical and encounters difficulties in validating the results. In this study, we performed series of tests using structure tensor analysis on synthetic tissue wedges with predefined fibre orientations, optimised the parameters of the method and applied it to the micro-CT images of a rabbit ventricular tissue. The accuracy of the method with several derivative filters and various parameters was investigated by quantifying the error in estimation in inclination angles. A measure of coherence was implemented to assess the coherence and reliability of the extracted orientations. We introduced Gaussian noise to investigate the robustness of this method. Our results suggest that the derivative of Gaussian and optimised Sobel derivative filter have better and balanced performances with overall mean error around 4°. The scale parameters play an important role in securing the accuracy. The algorithm is resistant to Gaussian noise. Using this method the myofibre orientation was successfully extracted from the ventricular tissue wedge images of the rabbit heart.",
author = "Haibo Ni and Castro, {Simon J.} and Stephenson, {Robert S.} and Jarvis, {Jonathan C.} and Tristan Lowe and George Hart and Boyett, {Mark R.} and Henggui Zhang",
year = "2013",
month = dec,
day = "1",
language = "English",
isbn = "9781479908844",
series = "Computing in Cardiology",
pages = "823--826",
booktitle = "Computing in Cardiology 2013, CinC 2013",
note = "2013 40th Computing in Cardiology Conference, CinC 2013 ; Conference date: 22-09-2013 Through 25-09-2013",
}