journal article·2024-09-12Open access

Special Issue “Advanced Imaging in Orthopedic Biomechanics”

Claudio Belvedere, Sorin Siegler

Applied Sciences· Volume 14· Issue 18

Abstract

Continued advances in medical imaging are increasingly resulting in promising developments, for example in producing high-resolution visualization of musculoskeletal systems and thus having a high impact in clinical assessments [...]
Only a short abstract or summary was supplied by the source.
Source: crossref · Quality: short

Research context

OpenAlex topics: Medical Imaging and Analysis · Advanced X-ray and CT Imaging · Dental Radiography and Imaging

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Movement Analysis Laboratory, IRCCS Istituto Ortopedico Rizzoli, 40136 Bologna, Italy

Department of Mechanical Engineering, Drexel University, Philadelphia, PA 19104, USA

References (24)

Show source-provided references
1. Advances in imaging-the changing environment for the imaging specialist10.7812/TPP/05-118 ↗
2. Advances in medical imaging10.7326/0003-4819-112-3-203 ↗
3. Recent Developments in SPECT/CT10.1053/j.semnuclmed.2022.01.004 ↗
4. Advancing Research on Medical Image Perception by Strengthening Multidisciplinary Collaboration10.1093/jncics/pkab099 ↗
5. The past, present and future role of artificial intelligence in imaging10.1016/j.ejrad.2018.06.020 ↗
6. Impact of new technologies on dose reduction in CT10.1016/j.ejrad.2010.06.036 ↗
7. Dose Reduction While Preserving Diagnostic Quality in Head CT: Advancing the Application of Iterative Reconstruction Using a Live Animal Model
8. Cost-effectiveness modelling in diagnostic imaging: A stepwise approach10.1007/s00330-015-3770-8 ↗
9. Ergonomics in Radiology: Improving the Work Environment for Radiologists10.1067/j.cpradiol.2022.03.001 ↗
10. van der Velden, B.H.M., Kuijf, H.J., Gilhuijs, K.G.A., and Viergever, M.A. (2022). Explainable artificial intelligence (XAI) in deep learning-based medical image analysis. Med. Image Anal., 79.10.1016/j.media.2022.102470 ↗
11. Bucking, T.M., Hill, E.R., Robertson, J.L., Maneas, E., Plumb, A.A., and Nikitichev, D.I. (2017). From medical imaging data to 3D printed anatomical models. PLoS ONE, 12.10.1371/journal.pone.0178540 ↗
12. AI in Medical Imaging Informatics: Current Challenges and Future Directions10.1109/JBHI.2020.2991043 ↗
13. Gargiulo, P., Helgason, T., Ramon, C., Jonsson, H., and Carraro, U. (2014). CT and MRI Assessment and Characterization Using Segmentation and 3D Modeling Techniques: Applications to Muscle, Bone and Brain. Eur. J. Transl. Myol., 24.10.4081/bam.2014.1.55 ↗
14. Accuracy of linear measurements on CBCT images related to presurgical implant treatment planning: A systematic review10.1111/clr.13142 ↗
15. Weightbearing Computed Tomography of the Foot and Ankle: Emerging Technology Topical Review10.1177/1071100717740330 ↗
16. Maxillofacial cone beam computed tomography: Essence, elements and steps to interpretation10.1111/j.1834-7819.2011.01657.x ↗
17. Imaging and Biomechanics10.1177/0363546518817315 ↗
18. Galbusera, F., Cina, A., Panico, M., Albano, D., and Messina, C. (2020). Image-based biomechanical models of the musculoskeletal system. Eur. Radiol. Exp., 4.10.1186/s41747-020-00172-3 ↗
19. Wang, L., Chen, K.C., Gao, Y., Shi, F., Liao, S., Li, G., Shen, S.G., Yan, J., Lee, P.K., and Chow, B. (2014). Automated bone segmentation from dental CBCT images using patch-based sparse representation and convex optimization. Med. Phys., 41.10.1118/1.4868455 ↗
20. Hussain, S., Mubeen, I., Ullah, N., Shah, S., Khan, B.A., Zahoor, M., Ullah, R., Khan, F.A., and Sultan, M.A. (2022). Modern Diagnostic Imaging Technique Applications and Risk Factors in the Medical Field: A Review. BioMed Res. Int., 2022.10.1155/2022/5164970 ↗
21. Clinical applications of cone-beam computed tomography in dental practice
22. Quantification of the accuracy of MRI generated 3D models of long bones compared to CT generated 3D models10.1016/j.medengphy.2011.07.027 ↗
23. 3D representation of the surface topography of normal and dysplastic trochlea using MRI10.1016/j.knee.2010.07.006 ↗
24. Inoue, A., Ohnishi, T., Kohno, S., Nishida, N., Nakamura, Y., Ohtsuka, Y., Matsumoto, S., and Ohue, S. (2015). Usefulness of an Image Fusion Model Using Three-Dimensional CT and MRI with Indocyanine Green Fluorescence Endoscopy as a Multimodal Assistant System in Endoscopic Transsphenoidal Surgery. Int. J. Endocrinol., 2015.10.1155/2015/694273 ↗