[HTML][HTML] Surgical data science–from concepts toward clinical translation

L Maier-Hein, M Eisenmann, D Sarikaya, K März… - Medical image …, 2022 - Elsevier
Recent developments in data science in general and machine learning in particular have
transformed the way experts envision the future of surgery. Surgical Data Science (SDS) is a …

Clinical applications of artificial intelligence in robotic surgery

JE Knudsen, U Ghaffar, R Ma, AJ Hung - Journal of Robotic Surgery, 2024 - Springer
Artificial intelligence (AI) is revolutionizing nearly every aspect of modern life. In the medical
field, robotic surgery is the sector with some of the most innovative and impactful …

Towards holistic surgical scene understanding

N Valderrama, P Ruiz Puentes, I Hernández… - … conference on medical …, 2022 - Springer
Most benchmarks for studying surgical interventions focus on a specific challenge instead of
leveraging the intrinsic complementarity among different tasks. In this work, we present a …

CholecTriplet2022: Show me a tool and tell me the triplet—An endoscopic vision challenge for surgical action triplet detection

CI Nwoye, T Yu, S Sharma, A Murali, D Alapatt… - Medical Image …, 2023 - Elsevier
Formalizing surgical activities as triplets of the used instruments, actions performed, and
target anatomies is becoming a gold standard approach for surgical activity modeling. The …

Surgical tool datasets for machine learning research: a survey

M Rodrigues, M Mayo, P Patros - International Journal of Computer Vision, 2022 - Springer
This paper is a comprehensive survey of datasets for surgical tool detection and related
surgical data science and machine learning techniques and algorithms. The survey offers a …

A large-scale study of spatiotemporal representation learning with a new benchmark on action recognition

A Deng, T Yang, C Chen - Proceedings of the IEEE/CVF …, 2023 - openaccess.thecvf.com
The goal of building a benchmark (suite of datasets) is to provide a unified protocol for fair
evaluation and thus facilitate the evolution of a specific area. Nonetheless, we point out that …

CPR-Coach: Recognizing composite error actions based on single-class training

S Wang, S Wang, D Yang, M Li… - Proceedings of the …, 2024 - openaccess.thecvf.com
Fine-grained medical action analysis plays a vital role in improving medical skill training
efficiency but it faces the problems of data and algorithm shortage. Cardiopulmonary …

Evaluating the task generalization of temporal convolutional networks for surgical gesture and motion recognition using kinematic data

K Hutchinson, I Reyes, Z Li… - IEEE Robotics and …, 2023 - ieeexplore.ieee.org
Fine-grained activity recognition enables explainable analysis of procedures for skill
assessment, autonomy, and error detection in robot-assisted surgery. However, existing …

Artificial intelligence for biomedical video generation

L Li, J Qiu, A Saha, L Li, P Li, M He, Z Guo… - arXiv preprint arXiv …, 2024 - arxiv.org
As a prominent subfield of Artificial Intelligence Generated Content (AIGC), video generation
has achieved notable advancements in recent years. The introduction of Sora-alike models …

Integrating artificial intelligence and augmented reality in robotic surgery: An initial dvrk study using a surgical education scenario

Y Long, J Cao, A Deguet, RH Taylor… - … Symposium on Medical …, 2022 - ieeexplore.ieee.org
Robot-assisted surgery has become progressively more and more popular due to its clinical
advantages. In the meanwhile, the artificial intelligence and augmented reality in robotic …