REAL-TIME SURGICAL NAVIGATION IN ORAL MAXILLOFACIAL SURGERY USING AUGMENTED AI AND DEEP CNNs - Balasaheb Balkhande (ShodhKosh: Journal of Visual and Performing Arts, 2024)
Real-time intraoperative navigation during Oral and maxillofacial surgery (OMS) is essential for achieving accuracy and for a safe operation. In this paper, we show a modified artificial intelligence (AI) framework based on deep CNNs that can automatically execute segmentation, registration, and visualization for intricate maxillofacial structures. The platform combines a deep learning model with an AR interface that displays key anatomy on the operative field as the procedure is being performed. Results shown that the proposed method can obtain high segment accuracy and robust tool tracking to enhance the intra-operative decision and improve the surgery outcome. The result of this work makes it possible to combine deep CNNs and AR technologies toward intelligent, real-time surgical navigation in OMS.