Current applications of deep learning and radiomics on CT and CBCT for maxillofacial diseases
The increasing use of computed tomography (CT) and cone beam computed tomography
(CBCT) in oral and maxillofacial imaging has driven the development of deep learning and …
(CBCT) in oral and maxillofacial imaging has driven the development of deep learning and …
A review on AI-based medical image computing in head and neck surgery
Head and neck surgery is a fine surgical procedure with a complex anatomical space,
difficult operation and high risk. Medical image computing (MIC) that enables accurate and …
difficult operation and high risk. Medical image computing (MIC) that enables accurate and …
Accuracy and precision of mandible segmentation and its clinical implications: virtual reality, desktop screen and artificial intelligence
Objective 3D modeling is a major challenge in computer-assisted surgery (CAS). Manual
segmentation, as the gold standard, is tedious, time consuming, and particularly challenging …
segmentation, as the gold standard, is tedious, time consuming, and particularly challenging …
Organ segmentation from computed tomography images using the 3D convolutional neural network: a systematic review
AE Ilesanmi, T Ilesanmi, OP Idowu, DA Torigian… - International Journal of …, 2022 - Springer
Computed tomography images are scans that combine a series of X-rays with computer
processing techniques to display organs in the body. Recently, 3D CNN models have …
processing techniques to display organs in the body. Recently, 3D CNN models have …
Automatic segmentation of teeth, crown–bridge restorations, dental implants, restorative fillings, dental caries, residual roots, and root canal fillings on …
Background: The aim of our study is to provide successful automatic segmentation of various
objects on orthopantomographs (OPGs). Methods: 8138 OPGs obtained from the archives of …
objects on orthopantomographs (OPGs). Methods: 8138 OPGs obtained from the archives of …
Deep learning‐based automatic segmentation of bone graft material after maxillary sinus augmentation
B Tao, J Xu, J Gao, S He, S Jiang… - Clinical Oral …, 2023 - Wiley Online Library
Objectives To investigate the accuracy and reliability of deep learning in automatic graft
material segmentation after maxillary sinus augmentation (SA) from cone‐beam computed …
material segmentation after maxillary sinus augmentation (SA) from cone‐beam computed …
A deep learning-based automatic segmentation of zygomatic bones from cone-beam computed tomography images: A proof of concept
Objectives To investigate the efficiency and accuracy of a deep learning-based automatic
segmentation method for zygomatic bones from cone-beam computed tomography (CBCT) …
segmentation method for zygomatic bones from cone-beam computed tomography (CBCT) …
Multi-organ segmentation: a progressive exploration of learning paradigms under scarce annotation
Precise delineation of multiple organs or abnormal regions in the human body from medical
images plays an essential role in computer-aided diagnosis, surgical simulation, image …
images plays an essential role in computer-aided diagnosis, surgical simulation, image …
Development and model form assessment of an automatic subject-specific vertebra reconstruction method
D Zhang, A Aoude, M Driscoll - Computers in Biology and Medicine, 2022 - Elsevier
Background: Current spine models for analog bench models, surgical navigation and
training platforms are conventionally based on 3D models from anatomical human body …
training platforms are conventionally based on 3D models from anatomical human body …
Design and implementation of a surgical planning system for robotic assisted mandible reconstruction with fibula free flap
Purpose Free fibula flap is the gold standard for the treatment of mandibular defects.
However, the existing preoperative planning protocol is cumbersome to execute, costly to …
However, the existing preoperative planning protocol is cumbersome to execute, costly to …