| dc.contributor.author | Kurachka, K. | |
| dc.contributor.author | Wang, X. | |
| dc.contributor.author | Ren, H. | |
| dc.coverage.spatial | Симферополь | ru_RU |
| dc.date.accessioned | 2026-04-13T11:03:21Z | |
| dc.date.available | 2026-04-13T11:03:21Z | |
| dc.date.issued | 2025 | |
| dc.identifier.citation | Kurachka, K. A Python-implemented algorithm for three-dimensional reconstruction of the human lumbar spine from DICOM CT data / K. Kurachka, X. Wang, H. Ren // Автоматизация, телекоммуникации, информационные технологии и программное обеспечение 2025 (ATITS 2025) : материалы международной научно-практической конференции, Ялта, 28-31 октября 2025 г. / Крымский федеральный университет имени В. И. Вернадского. – Симферополь, 2025. – С. 70–72. | ru_RU |
| dc.identifier.uri | https://elib.gstu.by/handle/220612/47684 | |
| dc.description.abstract | Degenerative disc disease is one of the leading causes of low back pain. Computed
tomography (CT) provides high-resolution images of the spine, but a three-dimensional (3D) model
is crucial for biomechanical analysis and surgical planning. This paper presents an open-source,
fully automated Python algorithm for reconstructing the human lumbar spine from DICOM CT
data. This method utilizes Hounsfield unit-based bone segmentation, morphological optimization,
and the marching cubes algorithm for surface extraction, ultimately generating an STL mesh. | ru_RU |
| dc.language.iso | en | ru_RU |
| dc.publisher | КФУ им. В.И. Вернадского | ru_RU |
| dc.title | A Python-implemented algorithm for three-dimensional reconstruction of the human lumbar spine from DICOM CT data | ru_RU |
| dc.type | Article | ru_RU |
