BACKGROUND: Accurate correction of x-ray scatter in dedicated breast computed tomography (bCT) imaging may result in improved visual interpretation and is crucial to achieve quantitative accuracy during image reconstruction and analysis.
INTRODUCTION: The aim of this systematic review and meta-analysis was to investigate the overall accuracy of deep learning models in detecting periapical (PA) radiolucent lesions in dental radiographs, when compared to expert clinicians.
International journal of oral and maxillofacial surgery
Dec 12, 2022
Robotic assistance can help in physically guiding the drilling trajectory during zygomatic implant positioning. A new robot-assisted strategy for a flapless zygomatic implant placement protocol is reported here. In this protocol, a preoperative compu...
BACKGROUND: Motion-compensated (MoCo) reconstruction shows great promise in improving four-dimensional cone-beam computed tomography (4D-CBCT) image quality. MoCo reconstruction for a 4D-CBCT could be more accurate using motion information at the CBC...
Lateral cephalograms and related analysis constitute representative methods for orthodontic treatment. However, since conventional cephalometric radiographs display a three-dimensional structure on a two-dimensional plane, inaccuracies may be produce...
The aim of this study was to develop an auto-segmentation algorithm for mandibular condyle using the 3D U-Net and perform a stress test to determine the optimal dataset size for achieving clinically acceptable accuracy. 234 cone-beam computed tomogra...
International journal of environmental research and public health
Nov 21, 2022
The rapid development of artificial intelligence (AI) has led to the emergence of many new technologies in the healthcare industry. In dentistry, the patient's panoramic radiographic or cone beam computed tomography (CBCT) images are used for implant...
Deep learning allows automatic segmentation of teeth on cone beam computed tomography (CBCT). However, the segmentation performance of deep learning varies among different training strategies. Our aim was to propose a 3.5D U-Net to improve the perfor...
International journal of oral and maxillofacial surgery
Nov 10, 2022
The purpose of this ambispective study was to investigate whether deep learning-based automatic segmentation and landmark detection, the SkullEngine, could be used for orthognathic surgical planning. Sixty-one sets of cone beam computed tomography (C...
PURPOSE: To simultaneously register all the longitudinal images acquired in a radiotherapy course for analyzing patients' anatomy changes for adaptive radiotherapy (ART).
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