DC Field | Value | Language |
dc.contributor.author | Asipovich, V. S. | - |
dc.contributor.author | Dudich, O. N. | - |
dc.contributor.author | Krasilnikova, V. L. | - |
dc.contributor.author | Karakulko, A. A. | - |
dc.contributor.author | Radnionok, A. L. | - |
dc.contributor.author | Moroz, P. A. | - |
dc.contributor.author | Nikolaev, A. Y. | - |
dc.contributor.author | Konovalova, M. A. | - |
dc.contributor.author | Yashin, K. D. | - |
dc.date.accessioned | 2020-03-03T09:41:19Z | - |
dc.date.available | 2020-03-03T09:41:19Z | - |
dc.date.issued | 2019 | - |
dc.identifier.citation | Deep Learning in Processing Medical Images and Calculating the Orbit Volume / V. S. Asipovich [and other] // 4-th International Conference on Nanotechnologies and Biomedical Engineering : Proceedings of ICNBME-2019, Chisinau, Moldova, September 18-21, 2019 / editors : Ion Tiginyanu, Victor Sontea, Serghei Railean. – Switzerland : Springer Nature Switzerland, 2019. – Vol. 77. – P. 519-522. – (IFMBE Proceedings). | ru_RU |
dc.identifier.uri | https://libeldoc.bsuir.by/handle/123456789/38635 | - |
dc.description.abstract | A software tool for calculating the volume of a soft-tissue eye orbit using the deep learning of neural network Mask R-CNN has been developed and tested. The result of the development will be in demand when evaluating the results of surgical intervention for the reconstruction of the thin bones of the orbit. It was established that the inaccuracy in constructing the contour of a soft-tissue orbit is 4–8%. | ru_RU |
dc.language.iso | en | ru_RU |
dc.publisher | Springer | ru_RU |
dc.subject | публикации ученых | ru_RU |
dc.subject | Orbit | ru_RU |
dc.subject | Orbit volume | ru_RU |
dc.subject | Deep learning | ru_RU |
dc.subject | Neural network | ru_RU |
dc.subject | Biomedical images | ru_RU |
dc.title | Deep Learning in Processing Medical Images and Calculating the Orbit Volume | ru_RU |
dc.type | Статья | ru_RU |
Appears in Collections: | Публикации в зарубежных изданиях
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