A Deep Learning Approach for Osteoporosis Identification using Cone-beam Computed Tomography
Aim
Description
Cone-beam Computed Tomography (CBCT) examination is a non-invasive x-ray technology which produces 3D images. Using a Deep Learning (DL) approach, a Computer Vision method will be elaborated which can identify more quickly and accurately the risk of osteoporosis in women. Consequently, it facilitates the early treatment of the disease as well as prevents osteoporotic fractures. The project will aim for the expansion of personalized medicine, medical and ICT sectors. The project will be conducted by the medical experts from the Rīga Stradiņš University (RSU) and DL researchers from the Institute of Electronics and Computer Sciences (EDI). The patient`s dataset will be collected by RSU researchers, in which CBCT and osteodensitometry studies are planned for 220 patients. The various measurements of the quality and quantity of the bone and radiological bone density in the maxilla and cervical vertebrae will be performed. The results will be used by EDI to develop a computer-based method of semantic segmentation, classification and explainability of osteoporosis. The project will result in 3 scientific articles, 3 presentations for international conferences and developing guidelines for dentists to determine the risk of osteoporosis by using CBCT.
Activities
- March 2023
25 March, meeting of the Latvian Dental Association, Dr Laura Nemaine (pictured) gave an oral presentation on identifying the risk of osteoporosis in images from dental, facial and jaw radiological examinations. Dr Neimane highlighted the factors in everyday practice that requires closer attention to identify the risk of osteoporosis in post-menopausal women.
- October 2022
6–8 October, in the yearly meeting of the European Society of Head and Neck Radiology, oral presentations were given by two fifth-year students from the Faculty of Dentistry, Anastasija Beibakova and Laura Jakaite.
ESHNR 2022 Book of Abstracts. Insights Imaging 13 (Suppl 3), 157 (2022)
https://doi.org/10.1186/s13244-022-01285-6- June 2022
3–4 June the 16th Joint Symposium Riga-Rostock and the 10th Congress of Baltic Association of Maxillofacial and Plastic Surgery titled Emerging Technologies in Oral and Maxillofacial Surgery took place in Rīga. RSU associated professor Dr Laura Neimane (pictured) gave an oral presentation titled 'A Deep Learning Approach for Osteoporosis Identification Using Cone-Beam Computed Tomography'.
https://pdfhost.io/v/PNkkCSPRa_RigaRostock_2022_abstracts_01062022
- May 2022
A project group meeting was held at the RSU Institute of Stomatolgy.
Left to right: Ivars Namatēvs, Oskars Radziņš, Anda Slaidiņa, Laura Neimane, Kaspars Sudars
- February 2022
A project group meeting was held at the RSU Institute of Stomatolgy.
Left to right: Oskars Radziņš, Ivars Namatēvs, Laura Neimane, Kaspars Sudars, Anda Slaidiņa
