Developing an Artificial Intelligence Solution to Autosegment the Edentulous Mandibular Bone for Implant Planning.
Mohammad-Adel MouftiNuha TrabulsiMarah GhoushehTala FattalAli AshiraSabalan DaneshvarPublished in: European journal of dentistry (2023)
Segmentation of the edentulous spans on CBCT images was successfully conducted by machine learning with good accuracy compared to manual segmentation. Unlike traditional AI object detection models that identify objects present in the image, this model identifies missing objects. Finally, challenges in data collection and labeling are discussed, together with an outlook at the prospective stages of a larger project for a complete AI solution for automated implant planning.
Keyphrases
- artificial intelligence
- deep learning
- big data
- machine learning
- soft tissue
- convolutional neural network
- cone beam computed tomography
- quality improvement
- working memory
- genome wide
- electronic health record
- body composition
- solid state
- real time pcr
- magnetic resonance imaging
- dna methylation
- contrast enhanced
- bone loss
- bone regeneration