Unleashing hidden canines: a novel fast R-CNN based technique for automatic auxiliary canine impaction

The field of orthodontics has witnessed rapid advancements in diagnostic technologies, enabling early identification and targeted treatment of various dental anomalies.Canine impaction, being one of the most common malocclusions, requires precise and prompt detection to ensure optimal outcomes [1].The objective of using artificial intelligence (AI) in the context of maxillary canine impactions is to enhance diagnostic accuracy, treatment planning, and overall outcomes in dental and orthodontic procedures.AI can analyze complex datasets, including radiographic images and patient records, to identify patterns and provide valuable insights for clinicians.*Author for correspondence By leveraging AI, healthcare professionals can achieve a more precise understanding of maxillary canine impactions, leading to improved decisionmaking, personalized treatment strategies, and ultimately, better patient care.Traditional methods of diagnosing impactions are labor-intensive and prone to human error.In this context, it proposes a cutting-edge convolutional neural network (CNN)based technique that promises to revolutionize the way orthodontists identify and manage auxiliary canine impactions [2].The motivation behind AI-based auxiliary canine impaction diagnosis and management is to enhance the quality of dental care, improve patient outcomes, and leverage the capabilities of AI to provide more precise and efficient solutions in the field of dentistry like Research