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Automatic Masseter Thickness Measurement and Ideal Point Localization for Botulinum Toxin Injection
Summary
This study introduces an AI-driven method for precise botulinum toxin injection point localization in masseter muscle hypertrophy. The system uses 3D imaging and AI to improve accuracy and reduce risks associated with manual methods.
Area of Science:
- Medical Imaging
- Artificial Intelligence
- Anatomy
Background:
- Botulinum toxin injections are effective for masseter muscle hypertrophy.
- Manual injection point localization is subjective and carries risks.
- Objective, quantitative methods are needed for safer, more effective treatment.
Purpose of the Study:
- To develop an automated system for precise botulinum toxin injection point localization.
- To improve upon subjective, experience-based manual localization methods.
- To enhance safety and efficacy in treating masseter muscle hypertrophy.
Main Methods:
- A novel 3D fully convolutional neural network was developed for automatic segmentation of mandible and masseter regions from CT images.
- Ray casting and automatic thickness measurement were employed for ideal injection point identification.
- The system was evaluated on CT images from 53 patients.
Main Results:
- The proposed segmentation framework significantly outperformed existing state-of-the-art methods.
- The localization system demonstrated reliable injection point decisions.
- An intuitive, interactive user interface was provided.
Conclusions:
- The automated system offers a quantitative and reliable approach to masseter botulinum toxin injection point localization.
- This AI-driven methodology enhances precision and potentially reduces side effects.
- The system represents a significant advancement over traditional manual techniques.
