Intelligent augmented reality application for personalised rhinoplasty using machine learning

Abstract

Rhinoplasty, a common yet complex cosmetic surgery, often results in patient dissatisfaction due to the reliance on subjective surgeon evaluations. This study introduces an intelligent augmented reality (AR) application for personalised nose surgery, integrating three core innovations: (1) Preoperative 3D Modelling; (2) Machine Learning (ML) Analysis; and (3) AR Visualisation. The system employs advanced computer vision algorithms to extract precise facial measurements from high-resolution 3D scans or photographs. These measurements are analysed using ML techniques to calculate key facial ratios and recommend optimal nose shapes tailored to individual facial structures. AR further enhances the surgical process by providing real-time visualisations and guidance, enabling surgeons to implement data-driven decisions with greater precision. This novel approach addresses key challenges in rhinoplasty by automating critical steps of the surgical planning process, reducing subjectivity, and significantly improving surgical accuracy. The application’s contribution extends beyond the operating room, offering surgeons a powerful educational tool with real-time feedback and interactive visualisations to support continuous skill development. This study represents a transformative step in leveraging AR and ML for enhanced precision, patient satisfaction, and surgical outcomes in cosmetic surgery.

Keywords

Rhinoplasty / plastic surgery / 3D modelling / augmented reality / machine learning / intelligent system / 3D visualisation

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