Legendre moments as high performance bone biomarkers: computational methods and GPU acceleration
| Autor: | Pablo Moscato, Regina Berretta, Manuel Ujaldón, José Antonio Lachiondo |
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| Rok vydání: | 2014 |
| Předmět: |
Theoretical computer science
Computational complexity theory Biomedical Engineering Computational Mechanics 020206 networking & telecommunications 02 engineering and technology Computer Science Applications Set (abstract data type) Acceleration Discriminant Principal component analysis 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Radiology Nuclear Medicine and imaging Graphics Algorithm Legendre polynomials Curse of dimensionality Mathematics |
| Zdroj: | Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization. 4:146-163 |
| ISSN: | 2168-1171 2168-1163 |
| DOI: | 10.1080/21681163.2014.922437 |
| Popis: | We investigate the use of Legendre moments as biomarkers for an efficient and accurate classification of bone tissue on images coming from stem cell regeneration studies. Legendre moments are analysed from three different perspectives: (1) their discriminant properties in a wide set of preselected vectors of features based on our clinical and computational experience, providing solutions whose accuracy exceeds 90%; (2) the amount of information to be retained when using principal component analysis to reduce the dimensionality of the problem to either 2, 3, 4, 5 or 6 dimensions and (3) the use of the -k-feature set problem to identify a k = 4 number of features which are more relevant to our analysis from a combinatorial optimisation approach. These techniques are compared in terms of computational complexity and classification accuracy to assess the strengths and limitations of the use of Legendre moments. The second contribution of this work goes to reduce the computational complexity by using graphics ... |
| Databáze: | OpenAIRE |
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