FRACTAL ANALYSIS AS A METHOD FOR FEATURE EXTRACTION IN DETECTING OSTEOPOROTIC BONE DESTRUCTION

Zbigniew Omiotek, Rã“å»a Dzierå»ak and Andrzej Kè¨pa
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Zbigniew Omiotek: Faculty of Electrical Engineering and Computer Science, Lublin University of Technology Nadbystrzycka 38d, 20-618 Lublin, Poland
Rã“å»a Dzierå»ak: Faculty of Electrical Engineering and Computer Science, Lublin University of Technology Nadbystrzycka 38d, 20-618 Lublin, Poland
Andrzej Kè¨pa: ��Department of Radiology and Nuclear Medicine, Independent Public Clinical Hospital No. 4, Jaczewskiego 8, 20-954 Lublin, Poland

FRACTALS (fractals), 2021, vol. 29, issue 04, 1-15

Abstract: Fractal analysis was used in the study to determine a set of feature descriptors which could be applied in the process of diagnosing bone damage caused by osteoporosis. The subject of the research was CT images of vertebrae on the thoraco-lumbar region. The dataset contained images of healthy patients and patients diagnosed with osteoporosis. On the basis of fractal analysis and feature selection by linear stepwise regression, three descriptors were obtained. These were two fractal dimensions calculated by the variation method and fractal lacunarity calculated by the box counting method. The first two descriptors were obtained as a result of the analysis of gray images, and the third was the result of analysis of binary images. The effectiveness of the descriptors was verified using six popular supervised classification methods: linear and quadratic discriminant analyses, naive Bayes classifier, decision tree, K-nearest neighbors (K-NN) and random forests. The best results were obtained using the K-NN classifier; they were as follows: overall classification accuracy: 81%, classification sensitivity: 78%, classification specificity: 90%, positive predictive value: 90% and negative predictive value: 77%. The results of the research have shown that fractal analysis can be a useful tool to extract features of spinal CT images in the diagnosis of osteoporotic bone defects.

Keywords: Fractal Analysis; Fractal Dimension; Osteoporosis; Feature Extraction; Computed Tomography; Texture Analysis; Feature Selection; Classification (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1142/S0218348X2150095X

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