Deep Learning-based Medical Augmented Reality for Surgical Navigation
PDF

Keywords

Deep Learning
Surgical Outcomes

How to Cite

[1]
Dr. Thomas Dupont, “Deep Learning-based Medical Augmented Reality for Surgical Navigation”, Journal of AI in Healthcare and Medicine, vol. 4, no. 2, pp. 57–64, Sep. 2024, Accessed: Sep. 18, 2024. [Online]. Available: https://healthsciencepub.com/index.php/jaihm/article/view/86

Abstract

Medical augmented reality (AR) is revolutionizing surgical navigation by providing real-time, interactive visualizations that enhance surgical precision and decision-making. This paper explores the integration of deep learning techniques with medical AR for surgical navigation. Deep learning enables AR systems to interpret complex surgical environments, improve image registration, and enhance the overlay of digital information onto the surgical field. This paper reviews recent advancements in deep learning-based medical AR, discusses challenges and future directions, and highlights the potential impact of these technologies on surgical outcomes.

PDF

References

Saeed, A., Zahoor, A., Husnain, A., & Gondal, R. M. (2024). Enhancing E-commerce furniture shopping with AR and AI-driven 3D modeling. International Journal of Science and Research Archive, 12(2), 040-046.

N. Pushadapu, “AI-Driven Solutions for Seamless Integration of FHIR in Healthcare Systems: Techniques, Tools, and Best Practices ”, Journal of AI in Healthcare and Medicine, vol. 3, no. 1, pp. 234–277, Jun. 2023

Chen, Jan-Jo, Ali Husnain, and Wei-Wei Cheng. "Exploring the Trade-Off Between Performance and Cost in Facial Recognition: Deep Learning Versus Traditional Computer Vision." Proceedings of SAI Intelligent Systems Conference. Cham: Springer Nature Switzerland, 2023.

Alomari, Ghaith, et al. “AI-Driven Integrated Hardware and Software Solution for EEG-Based Detection of Depression and Anxiety.” International Journal for Multidisciplinary Research, vol. 6, no. 3, May 2024, pp. 1–24.

Saeed, Ayesha, et al. "A Comparative Study of Cat Swarm Algorithm for Graph Coloring Problem: Convergence Analysis and Performance Evaluation." International Journal of Innovative Research in Computer Science & Technology 12.4 (2024): 1-9.

Downloads

Download data is not yet available.