Computed tomography texture analysis
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Computed Computed tomography texture analysis (or CTTA) is a method to obtain new useful biomarkerbiomarkers that provides anprovide objective and quantitative assessment of tumour heterogeneity by analysing the differences inand patterns within the pixel values of an image. CTs can be worked with as a matrix of numbers, corresponding to Hounsfield Units. Algorithms that perform mathematical operations on these matrixes can reveal patterns and characteristics. There are over twenty texture analysis parameters which are standardized in radiomics.
Parameters assessed may include
- gray-level frequency distribution: pixel intensity histograms
- mean intensity, threshold (percentage of pixels within a specified range)
- entropy (irregularity)
- standard deviation
- skewness (asymmetry)
- kurtosis (peakedness/flatness of pixel histogram)
Applications
Oncological applications
- lesion characterisation
- pretreatment tumour assessment
- response evaluation for tumours
Non-oncological applications
- assessment of hepatic fibrosis and pulmonary fibrosis
-<p><strong>Computed tomography texture analysis</strong> (or <strong>CTTA</strong>) is a new useful biomarker that provides an objective and quantitative assessment of tumour heterogeneity by analysing the differences in the pixel values of an image.</p><h4>Parameters assessed </h4><ol>- +<p><strong> Computed tomography texture analysis</strong> (or <strong>CTTA</strong>) is a method to obtain new useful biomarkers that provide objective and quantitative assessment of tumour heterogeneity by analysing the differences and patterns within the pixel values of an image. CTs can be worked with as a matrix of numbers, corresponding to Hounsfield Units. Algorithms that perform mathematical operations on these matrixes can reveal patterns and characteristics. There are over twenty texture analysis parameters which are standardized in radiomics. </p><h4>Parameters assessed may include</h4><ol>
References changed:
- 2. Zwanenburg, A., Leger, S., Valli`eres, M. & L¨ock, S. Image biomarker standardisation initiative. eprint arXiv:1612.07003 [cs.CV] (2016).
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