AIMC Topic: Sinus Floor Augmentation

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Application of a semi-active robotic system for implant placement in atrophic posterior maxilla: A retrospective case series.

Journal of dentistry Jan 26, 2025
OBJECTIVE: The study aimed to evaluate the accuracy and safety of a semi-active robotic system for implant placement in atrophic posterior maxilla.
Humans Retrospective Studies Female Aged Adult Male Middle Aged Cone-Beam Computed Tomography Robotics Robotic Surgical Procedures Surgery, Computer-Assisted Dental Implants Atrophy Maxilla Dental Implantation, Endosseous Sinus Floor Augmentation
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Automated Segmentation of Graft Material in 1-Stage Sinus Lift Based on Artificial Intelligence: A Retrospective Study.

Clinical implant dentistry and related research Dec 16, 2024
OBJECTIVES: Accurate assessment of postoperative bone graft material changes after the 1-stage sinus lift is crucial for evaluating long-term implant survival. However, traditional manual labeling and segmentation of cone-beam computed tomography (CB...
Humans Artificial Intelligence Retrospective Studies Cone-Beam Computed Tomography Image Processing, Computer-Assisted Bone Transplantation Bone Substitutes Sinus Floor Augmentation
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A transcrestal sinus floor elevation strategy based on a haptic robot system: An in vitro study.

Clinical implant dentistry and related research Sep 12, 2024
OBJECTIVES: To reveal the force profiles recorded by haptic autonomous robotic force feedback during the transcrestal sinus floor elevation (TSFE) process, providing a reference for the surgery strategy during TSFE.
Humans In Vitro Techniques Printing, Three-Dimensional Robotics Robotic Surgical Procedures Sinus Floor Augmentation
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Deep learning for the identification of ridge deficiency around dental implants.

Clinical implant dentistry and related research Dec 27, 2023
OBJECTIVES: This study aimed to use a deep learning (DL) approach for the automatic identification of the ridge deficiency around dental implants based on an image slice from cone-beam computerized tomography (CBCT).
Humans Deep Learning Dental Implants Bone Transplantation Maxilla Dental Implantation, Endosseous Sinus Floor Augmentation Alveolar Ridge Augmentation
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Deep learning-based automatic segmentation of bone graft material after maxillary sinus augmentation.

Clinical oral implants research Nov 30, 2023
OBJECTIVES: To investigate the accuracy and reliability of deep learning in automatic graft material segmentation after maxillary sinus augmentation (SA) from cone-beam computed tomography (CBCT) images.
Humans Female Reproducibility of Results Male Middle Aged Deep Learning Cone-Beam Computed Tomography Bone Transplantation Maxillary Sinus Sinus Floor Augmentation
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