Publications by authors named "Marie Louise Slim"
Clin Oral Investig
November 2024
Article Synopsis
- A study developed and validated an AI tool for automatically segmenting the pulp cavity of mandibular molars from cone-beam CT images, dividing data into training, validation, and testing sets for evaluation.
- The AI tool demonstrated high accuracy in segmentation, with Dice similarity coefficients of 88% for first molars and 90% for second molars, while also significantly reducing time needed for segmentation compared to manual methods.
- This AI-driven method can enhance efficiency in endodontic procedures by providing quick, accurate 3D models, potentially improving patient outcomes and anticipating complications.
