Advances in data preprocessing for biomedical data fusion: An overview of the methods, challenges, and prospects

S Wang, ME Celebi, YD Zhang, X Yu, S Lu, X Yao… - Information …, 2021 - Elsevier
Due to the proliferation of biomedical imaging modalities, such as Photoacoustic
Tomography, Computed Tomography (CT), Optical Microscopy and Tomography, etc …

Applications of artificial intelligence in dentistry: A comprehensive review

F Carrillo‐Perez, OE Pecho, JC Morales… - Journal of Esthetic …, 2022 - Wiley Online Library
Objective To perform a comprehensive review of the use of artificial intelligence (AI) and
machine learning (ML) in dentistry, providing the community with a broad insight on the …

Vision transformers for dense prediction: A survey

S Zuo, Y Xiao, X Chang, X Wang - Knowledge-Based Systems, 2022 - Elsevier
Transformers have demonstrated impressive expressiveness and transfer capability in
computer vision fields. Dense prediction is a fundamental problem in computer vision that is …

Teeth U-Net: A segmentation model of dental panoramic X-ray images for context semantics and contrast enhancement

S Hou, T Zhou, Y Liu, P Dang, H Lu, H Shi - Computers in Biology and …, 2023 - Elsevier
Background and objective It is very significant in orthodontics and restorative dentistry that
the teeth are segmented from dental panoramic X-ray images. Nevertheless, there are some …

Collaborative deep learning model for tooth segmentation and identification using panoramic radiographs

G Chandrashekar, S AlQarni, EE Bumann… - Computers in Biology and …, 2022 - Elsevier
Panoramic radiographs are an integral part of effective dental treatment planning,
supporting dentists in identifying impacted teeth, infections, malignancies, and other dental …

Self-supervised transfer learning based on domain adaptation for benign-malignant lung nodule classification on thoracic CT

H Huang, R Wu, Y Li, C Peng - IEEE Journal of Biomedical and …, 2022 - ieeexplore.ieee.org
The spatial heterogeneity is an important indicator of the malignancy of lung nodules in lung
cancer diagnosis. Compared with 2D nodule CT images, the 3D volumes with entire nodule …

Periodontal bone loss detection based on hybrid deep learning and machine learning models with a user-friendly application

KM Sunnetci, S Ulukaya, A Alkan - Biomedical Signal Processing and …, 2022 - Elsevier
As artificial intelligence in medical imaging is used to diagnose many diseases, it can also
be employed to diagnose whether a person has periodontal bone loss or not. Accurate and …

A comprehensive review of recent advances in artificial intelligence for dentistry e-health

I Shafi, A Fatima, H Afzal, IT Díez, V Lipari, J Breñosa… - Diagnostics, 2023 - mdpi.com
Artificial intelligence has made substantial progress in medicine. Automated dental imaging
interpretation is one of the most prolific areas of research using AI. X-ray and infrared …

Analysis of deep learning techniques for dental informatics: a systematic literature review

S AbuSalim, N Zakaria, MR Islam, G Kumar, N Mokhtar… - Healthcare, 2022 - mdpi.com
Within the ever-growing healthcare industry, dental informatics is a burgeoning field of study.
One of the major obstacles to the health care system's transformation is obtaining …

Gt u-net: A u-net like group transformer network for tooth root segmentation

Y Li, S Wang, J Wang, G Zeng, W Liu, Q Zhang… - Machine Learning in …, 2021 - Springer
To achieve an accurate assessment of root canal therapy, a fundamental step is to perform
tooth root segmentation on oral X-ray images, in that the position of tooth root boundary is …