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Scientific studies
CranioCatch in academic research
You can find current academic studies on CranioCatch here!
A Deep Learning Approach To Detection Of Oral Cancer Lesions From Intra Oral Patient Images: A Preliminary Retrospective Study
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A Deep Learning Approach to Automatic Tooth Caries Segmentation in Panoramic Radiographs of Children in Primary Dentition, Mixed Dentition, and Permanent Dentition
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Detecting White Spot Lesions On Post-Orthodontic Oral Photographs Using Deep Learning Based On The Yolov5x Algorithm A Pilot Study
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Artificial Intelligence System for Automatic Maxillary Sinus Segmentation on Cone Beam Computed Tomography Images
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Predicting Extraction Difficulty of Impacted Maxillary Third Molars Using a Deep Learning Approach
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The Detection of Pulp Stones with Automatic Deep Learning in Panoramic Radiographies: An AI Pilot Study
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Tooth Numbering And Classification On Bitewing Radiographs: An Artificial Intelligence Pilot Study
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Detection of Periodontal Bone Loss Patterns and Furcation Defects from Panoramic Radiographs Using Deep Learning Algorithm: A Retrospective Study
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Second Mesiobuccal Canal Segmentation With Yolov5 Architecture Using Cone Beam Computed Tomography Images
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Detection Of Tooth Numbering, Frenulum Attachment, Gingival Overgrowth, And Gingival Inflammation Signs On Dental Photographs Using Convolutional Neural Network Algorithms: A Retrospective Study
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Classification of Temporomandibular Joint Osteoarthritis on Cone Beam Computed Tomography Images Using Artificial Intelligence System
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Assessing the Effectiveness of Artificial Intelligence Models for Detecting Alveolar Bone Loss in Periodontal Disease
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Detecting Pulp Stones with Automatic Deep Learning in Bitewing Radiographs: A Pilot Study of Artificial Intelligence
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A Comperative Study of Use of Artificial Intelligence in Oral Radiology Education
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Deep-Learning-Based Automatic Segmentation of Parotid Gland on Computed Tomography Images
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The U-Net Approaches to Evaluation of Dental Bite-Wing Radiographs: An Artificial Intelligence Study
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A Deep Learning Approach for Masseter Muscle Segmentation on Ultrasonography
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A Deep Learning Algorithm For Classification Of Oral Lichen Planus Lesions From Photographic Images: A Retrospective Study
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Convolutional Neural Network Performance for Sella Turcica Segmentation and Classification Using CBCT Images
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A Deep Learning Model for Idiopathic Osteosclerosis Detection on Panoramic Radiographs
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Automatic Feature Segmentation in Dental Periapical Radiographs
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Performance of a Convolutional Neural NetworkBased Artificial Intelligence Algorithm for Automatic Cephalometric Landmark Detection
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Automatic Detection and Classification of Dental Restorations in Panoramic Radiographs with Artificial Intelligence Method Developed Using Deep Learning Method: Methodological Studies
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Detecting the presence of taurodont teeth on panoramic radiographs using a deep learning‐based convolutional neural network algorithm
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Automatic Detection of Dentigerous Cysts on Panoramic Radiographs: A Deep Learning Study
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Diagnostic charting of panoramic radiography using deep-learning artificial intelligence system
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A U-Net Approach to Apical Lesion Segmentation on Panoramic Radiographs
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Deep-learning approach for caries detection and segmentation on dental bitewing radiographs
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Performance of a convolutional neural network algorithm for tooth detection and numbering on periapical radiographs
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An Artifıcial Intelligence Approach To Automatic Tooth Detection And Numbering In Panoramic Radiographs
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An Artificial Intelligence Hypothetical Approach for Masseter Muscle Segmentation on Ultrasonography in Patients With Bruxism
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Artificial Intelligence System For Automatic Deciduous Tooth Detection And Numbering In Panoramic Radiographs
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Success Of Artificial Intelligence System In Determining Alveolar Bone Loss From Dental Panoramic Radiography Images
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An artificial intelligence proposal to automatic teeth detection and numbering in dental bite-wing radiographs
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