Abstract
It has been shown that it is possible to differentiate viable amniotic membrane towards osteogenic lineage, i.e. bony tissue. This process of mineralization may take several weeks and can show different manifestations per sample. The tissue can only be used, when the mineralization process is advanced in a certain degree. Therefore, a forecast of the development of mineralization would be helpful to save time and resources. This paper shows how a prediction on the development of mineralization can be made by using several image processing techniques, machine learning methods, and hybrid ensembles of machine learning algorithms.
Original language | English |
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Title of host publication | Computer Aided Systems Theory – EUROCAST 2015 - 15th International Conference, Revised Selected Papers |
Editors | Franz Pichler, Roberto Moreno-Díaz, Alexis Quesada-Arencibia |
Publisher | Springer |
Pages | 318-325 |
Number of pages | 8 |
ISBN (Print) | 9783319273396 |
DOIs | |
Publication status | Published - 2015 |
Event | 15th International Conference on Computer Aided Systems Theory, Eurocast 2015 - Las Palmas, Gran Canaria, Spain Duration: 8 Feb 2015 → 13 Feb 2015 http://eurocast2015.fulp.ulpgc.es/ |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 9520 |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | 15th International Conference on Computer Aided Systems Theory, Eurocast 2015 |
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Country/Territory | Spain |
City | Las Palmas, Gran Canaria |
Period | 08.02.2015 → 13.02.2015 |
Internet address |
Keywords
- Hybride machine learning ensembles
- Image processing
- Osteogenic tissue engineering