Λεπτομέρειες βιβλιογραφικής εγγραφής
| Τίτλος: |
Surgical Suturing Skill Assessment Using Estimated Hand Roll Angle from a Deep-learning Computer Vision Algorithm. |
| Συγγραφείς: |
Gao J, Shayan AM, Singh SP, Bible J, Singapogu R, Groff RE |
| Πηγή: |
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference [Annu Int Conf IEEE Eng Med Biol Soc] 2024 Jul; Vol. 2024, pp. 1-6. |
| Τύπος έκδοσης: |
Journal Article |
| Γλώσσα: |
English |
| Στοιχεία περιοδικού: |
Publisher: [IEEE] Country of Publication: United States NLM ID: 101763872 Publication Model: Print Cited Medium: Internet ISSN: 2694-0604 (Electronic) Linking ISSN: 23757477 NLM ISO Abbreviation: Annu Int Conf IEEE Eng Med Biol Soc Subsets: MEDLINE |
| Imprint Name(s): |
Original Publication: [Piscataway, NJ] : [IEEE], [2007]- |
| Ιατρικοί όροι (MeSH): |
Hand*/physiology , Deep Learning* , Algorithms* , Suture Techniques*, Humans ; Clinical Competence |
| Περίληψη: |
This paper proposes a deep-learning computer vision algorithm to estimate hand roll angles for metric-based assessment of surgical suturing skills. The number of rolls metric, previously calculated directly from IMU data, counts the number of hand roll reversals during a single suture. To calculate this metric using computer vision, we apply a deep-learning algorithm that can reliably estimate hand roll angles after training on suturing videos collected on the SutureCoach simulator. Results show that the estimation accuracy of the deep-learning algorithm is robust to different video backgrounds. The number of rolls metrics were used to analyze suturing performance in the SutureCoach dataset, which includes attending and resident surgeons and novices. The means of number of rolls based on computer vision differs between most skill levels at both surface and depth conditions, a pattern which holds for number of rolls based on the IMU as well. The proposed algorithm provides a solution for non-contact hand roll angle estimation, which opens up the possibility of inter-operative surgical skill assessment. The code is available at https://github.com/axin233/hand_roll_estimation. |
| Entry Date(s): |
Date Created: 20250305 Date Completed: 20250510 Latest Revision: 20250510 |
| Update Code: |
20260130 |
| DOI: |
10.1109/EMBC53108.2024.10782514 |
| PMID: |
40039188 |
| Βάση Δεδομένων: |
MEDLINE |