Radu Chifor1, Mengxun Li2, Kim-Cuong T Nguyen3, Tudor Arsenescu4, Ioana Chifor5, Alexandru Florin Badea6, Mindra Eugenia Badea7, Mircea Hotoleanu8, Paul W Major9, Lawrence H Le10. 1. Department of Preventive Dentistry, University of Medicine and Pharmacy Iuliu Hatieganu, Cluj-Napoca, Romania Chifor Research SRL, Cluj-Napoca, Romania. raduchifor@yahoo.com. 2. Department of Radiology and Diagnostic Imaging, University of Alberta, Edmonton, AB, Canada Department of Implantology, School and Hospital of Stomatology, Wuhan University, Wuhan, China. mengxun1@ualberta.ca. 3. Department of Radiology and Diagnostic Imaging, University of Alberta, Edmonton, AB, Canada Department of Biomedical Engineering, University of Alberta, Edmonton, AB, Canada. cuong1@ualberta.ca. 4. Chifor Research SRL, Cluj-Napoca, Romania. arsenescu.tudor@gmail.com. 5. Department of Preventive Dentistry, University of Medicine and Pharmacy Iuliu Hatieganu, Cluj-Napoca, Romania Chifor Research SRL, Cluj-Napoca, Romania. ioana_chi@yahoo.com. 6. Anatomy and Embryology, Faculty of General Medicine, Iuliu Hatieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania. afbadea84@gmail.com. 7. Department of Preventive Dentistry, Faculty of Dental Medicine, Iuliu Hatieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania. mindrabadea@gmail.com. 8. Romanian Institute of Science and Technology, Cluj-Napoca, Romania. hotoleanu@rist.ro. 9. School of Dentistry, University of Alberta, Edmonton, AB, Canada. major@ualberta.ca. 10. Department of Radiology and Diagnostic Imaging, University of Alberta, Edmonton, AB, Canada Department of Biomedical Engineering, University of Alberta, Edmonton, AB, Canada School of Dentistry, University of Alberta, Edmonton, AB, Canada. lel@ualberta.ca.
Abstract
AIM: To demonstrate the feasibility of the 3D ultrasound periodontal tissue reconstruction of the lateral area of a porcine mandible using standard 2D ultrasound equipment and spatial positioning reading sensors. MATERIAL AND METHOD: Periodontal 3D reconstructions were performed using a free-hand prototype based on a 2D US scanner and a spatial positioning reading sensor. For automated data processing, deep learning algorithms were implemented and trained using semi-automatically seg-mented images by highly specialized imaging professionals. RESULTS: US probe movement analysis showed that non-parallel 2D frames were acquired during the scanning procedure. Comparing 3 different 3D periodontal reconstructions of the same porcine mandible, the accuracy ranged between 0.179 mm and 0.235 mm. CONCLUSION: The present study demonstrated the diagnostic potential of 3D reconstruction using a free-hand 2D US scanner with spatial positioning readings. The use of auto-mated data processing with deep learning algorithms makes the process practical in the clinical environment for assessment of periodontal soft tissues.
AIM: To demonstrate the feasibility of the 3D ultrasound periodontal tissue reconstruction of the lateral area of a porcine mandible using standard 2D ultrasound equipment and spatial positioning reading sensors. MATERIAL AND METHOD: Periodontal 3D reconstructions were performed using a free-hand prototype based on a 2D US scanner and a spatial positioning reading sensor. For automated data processing, deep learning algorithms were implemented and trained using semi-automatically seg-mented images by highly specialized imaging professionals. RESULTS: US probe movement analysis showed that non-parallel 2D frames were acquired during the scanning procedure. Comparing 3 different 3D periodontal reconstructions of the same porcine mandible, the accuracy ranged between 0.179 mm and 0.235 mm. CONCLUSION: The present study demonstrated the diagnostic potential of 3D reconstruction using a free-hand 2D US scanner with spatial positioning readings. The use of auto-mated data processing with deep learning algorithms makes the process practical in the clinical environment for assessment of periodontal soft tissues.
Authors: Radu Chifor; Mircea Hotoleanu; Tiberiu Marita; Tudor Arsenescu; Mihai Adrian Socaciu; Iulia Clara Badea; Ioana Chifor Journal: Sensors (Basel) Date: 2022-09-20 Impact factor: 3.847