AIMC Topic: Molar
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Age estimation based on 3D pulp chamber segmentation of first molars from cone-beam-computed tomography by integrated deep learning and level set.
International journal of legal medicine
Nov 13, 2020
OBJECTIVES: To develop an automatic segmentation method to segment the pulp chamber of first molars from 3D cone-beam-computed tomography (CBCT) images, and to estimate ages by calculated pulp volumes.
Artificial intelligence-driven novel tool for tooth detection and segmentation on panoramic radiographs.
Clinical oral investigations
Aug 26, 2020
OBJECTIVE: To evaluate the performance of a new artificial intelligence (AI)-driven tool for tooth detection and segmentation on panoramic radiographs.
Artificial Intelligence (AI)-Driven Molar Angulation Measurements to Predict Third Molar Eruption on Panoramic Radiographs.
International journal of environmental research and public health
May 25, 2020
The purpose of the presented Artificial Intelligence (AI)-tool was to automatically segment the mandibular molars on panoramic radiographs and extract the molar orientations in order to predict the third molars' eruption potential. In total, 838 pano...
Comparison of 3 deep learning neural networks for classifying the relationship between the mandibular third molar and the mandibular canal on panoramic radiographs.
Oral surgery, oral medicine, oral pathology and oral radiology
May 20, 2020
OBJECTIVE: The aim of this study was to compare time and storage space requirements, diagnostic performance, and consistency among 3 image recognition convolutional neural networks (CNNs) in the evaluation of the relationships between the mandibular ...
A deep-learning artificial intelligence system for assessment of root morphology of the mandibular first molar on panoramic radiography.
Dento maxillo facial radiology
Nov 9, 2018
OBJECTIVES:: The distal root of the mandibular first molar occasionally has an extra root, which can directly affect the outcome of endodontic therapy. In this study, we examined the diagnostic performance of a deep learning system for classification...
Anesthetic Efficacy of Gow-Gates Nerve Block, Inferior Alveolar Nerve Block, and Their Combination in Mandibular Molars with Symptomatic Irreversible Pulpitis: A Prospective, Randomized Clinical Trial.
Journal of endodontics
Dec 19, 2017
INTRODUCTION: The purpose of this prospective, randomized clinical trial was to evaluate the anesthetic efficacy of the Gow-Gates nerve block (GGNB), the inferior alveolar nerve block (IANB), and their combination for mandibular molars in patients wi...
A segmentation and classification scheme for single tooth in MicroCT images based on 3D level set and k-means+.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
May 31, 2016
Accurate classification of different anatomical structures of teeth from medical images provides crucial information for the stress analysis in dentistry. Usually, the anatomical structures of teeth are manually labeled by experienced clinical doctor...
Morphological effects of input data quantity in AI-powered dental crown design.
Journal of dentistry
Aug 1, 2025
OBJECTIVES: This retrospective in vitro study evaluated the impact of input data quantity on the morphology of dental crowns generated by AI-based software. The hypothesis suggests that increased input data quantity improves the quality of generated ...
Machine Learning Models in the Detection of MB2 Canal Orifice in CBCT Images.
International dental journal
Jun 1, 2025
OBJECTIVES: The objective of the present study was to determine the accuracy of machine learning (ML) models in the detection of mesiobuccal (MB2) canals in axial cone-beam computed tomography (CBCT) sections.
[A deep learning segmentation model for detecting caries in molar teeth].
Zhonghua yi xue za zhi
Aug 30, 2022
This study aimed to build a home use deep learning segmentation model to identify the scope of caries lesions. A total of 494 caries photographs of molars and premolars collected via endoscopy were selected. Subsequently, these photographs were label...
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