Progress in deep learning-based dental and maxillofacial image analysis: A systematic review
Background With the advent of deep learning in modern computing there has been
unprecedented progress in image processing and segmentation. Deep learning-based …
unprecedented progress in image processing and segmentation. Deep learning-based …
Machine learning in dentistry: a scoping review
LT Arsiwala-Scheppach, A Chaurasia… - Journal of Clinical …, 2023 - mdpi.com
Machine learning (ML) is being increasingly employed in dental research and application.
We aimed to systematically compile studies using ML in dentistry and assess their …
We aimed to systematically compile studies using ML in dentistry and assess their …
VolumeNet: A lightweight parallel network for super-resolution of MR and CT volumetric data
Deep learning-based super-resolution (SR) techniques have generally achieved excellent
performance in the computer vision field. Recently, it has been proven that three …
performance in the computer vision field. Recently, it has been proven that three …
Convolutional neural networks with intermediate loss for 3D super-resolution of CT and MRI scans
Computed Tomography (CT) scanners that are commonly-used in hospitals and medical
centers nowadays produce low-resolution images, eg one voxel in the image corresponds to …
centers nowadays produce low-resolution images, eg one voxel in the image corresponds to …
Hyperspectral super-resolution with coupled tucker approximation: Recoverability and SVD-based algorithms
We propose a novel approach for hyperspectral super-resolution, that is based on low-rank
tensor approximation for a coupled low-rank multilinear (Tucker) model. We show that the …
tensor approximation for a coupled low-rank multilinear (Tucker) model. We show that the …
Halve the dose while maintaining image quality in paediatric cone beam CT
Cone beam CT (CBCT) for dentomaxillofacial paediatric assessment has been widely used
despite the uncertainties of the risks of the low-dose radiation exposures. The aim of this …
despite the uncertainties of the risks of the low-dose radiation exposures. The aim of this …
Deep stereoscopic image super-resolution via interaction module
Deep learning-based methods have achieved remarkable performance in single image
super-resolution. However, these methods cannot be effectively applied in stereoscopic …
super-resolution. However, these methods cannot be effectively applied in stereoscopic …
Efficient computer-aided design of dental inlay restoration: a deep adversarial framework
Restoring the normal masticatory function of broken teeth is a challenging task primarily due
to the defect location and size of a patient's teeth. In recent years, although some …
to the defect location and size of a patient's teeth. In recent years, although some …
[HTML][HTML] Using super-resolution generative adversarial network models and transfer learning to obtain high resolution digital periapical radiographs
MBH Moran, MDB Faria, GA Giraldi, LF Bastos… - Computers in biology …, 2021 - Elsevier
Periapical Radiographs are commonly used to detect several anomalies, like caries,
periodontal, and periapical diseases. Even considering that digital imaging systems used …
periodontal, and periapical diseases. Even considering that digital imaging systems used …
[HTML][HTML] Application of deep learning in dentistry and implantology
DY Kang, HP Duong, JC Park - Journal of implantology and …, 2020 - implantology.or.kr
Artificial intelligence and deep learning algorithms are infiltrating various fields of medicine
and dentistry. The purpose of the current study was to review literatures applying deep …
and dentistry. The purpose of the current study was to review literatures applying deep …