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Authors: Marija Chuchalina ; Aleksandrs Sisojevs and Alexey Tatarinov

Affiliation: Institute of Electronics and Computer Science, 14 Dzerbenes Str., Riga, Latvia

Keyword(s): Machine Learning, Factor of Interest, Bone Model, Ultrasound, Signal Processing.

Abstract: Osteoporosis is characterized by increased bone fragility due to a decrease in thickness of the cortical layer CTh and the development of internal porosity in it. The assessment of bone models that simulate the state of osteoporosis causes difficulties due to their complex and multi-layered structure. In the present work, the possibility of using machine learning approaches to determine internal porosity using the ultrasonic data obtained by scanning bone models was researched. The bone models were represented as sets of PMMA plates with gradually varying CTh from 2 to 6 mm. A stepwise progression of porosity from 0 to 100% of CTh was set by increasing the thickness of the porous layer PTh in steps of 1 mm. The evaluation method was based on the results of the supervised multi-class classification of the raw ultrasonic signals and their magnitude of the DFT spectrum with PTh used for labeling. Ultrasonic data was split into training and testing datasets while preserving the percentag e of samples for each class. The results of the experiments demonstrated the potential effectiveness of the PTh classification, while optimization of the datasets and additional signal processing may contribute to the improvement of the results. (More)

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Paper citation in several formats:
Chuchalina, M. ; Sisojevs, A. and Tatarinov, A. (2024). Determination of Factors of Interest in Bone Models Based on Ultrasonic Data. In Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-684-2; ISSN 2184-4313, SciTePress, pages 281-287. DOI: 10.5220/0012358500003654

@conference{icpram24,
author={Marija Chuchalina and Aleksandrs Sisojevs and Alexey Tatarinov},
title={Determination of Factors of Interest in Bone Models Based on Ultrasonic Data},
booktitle={Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2024},
pages={281-287},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012358500003654},
isbn={978-989-758-684-2},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - Determination of Factors of Interest in Bone Models Based on Ultrasonic Data
SN - 978-989-758-684-2
IS - 2184-4313
AU - Chuchalina, M.
AU - Sisojevs, A.
AU - Tatarinov, A.
PY - 2024
SP - 281
EP - 287
DO - 10.5220/0012358500003654
PB - SciTePress

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