BACKGROUND: Pathological maxillary sinus would affect implant treatment and even result in failure of maxillary sinus lift and implant surgery. However, the maxillary sinus abnormalities are challenging to be diagnosed through CBCT images, especially...
OBJECTIVES: To investigate the accuracy and reliability of deep learning in automatic graft material segmentation after maxillary sinus augmentation (SA) from cone-beam computed tomography (CBCT) images.
INTRODUCTION: The determination of identity factors such as age and sex has gained significance in both criminal and civil cases. Paranasal sinuses like frontal and maxillary sinuses, are resistant to trauma and can aid profiling. We developed a deep...
Accurate paranasal sinus segmentation is essential for reducing surgical complications through surgical guidance systems. This study introduces a multiclass Convolutional Neural Network (CNN) segmentation model by comparing four 3D U-Net variations-n...
OBJECTIVES: The study aims to develop an artificial intelligence (AI) model based on nnU-Net v2 for automatic maxillary sinus (MS) segmentation in cone beam computed tomography (CBCT) volumes and to evaluate the performance of this model.
BACKGROUND: Panoramic radiography (PR) is available to determine the contact relationship between maxillary molar teeth (MMT) and the maxillary sinus floor (MSF). However, as PRs do not provide clear and detailed anatomical information, advanced imag...
BACKGROUND & OBJECTIVE: Sex estimation is a critical aspect of forensic expertise. Some special anatomical structures, such as the maxillary sinus, can still maintain integrity in harsh environmental conditions and may be served as a basis for sex es...
Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
38922721
OBJECTIVE: Segmentation, the partitioning of patient imaging into multiple, labeled segments, has several potential clinical benefits but when performed manually is tedious and resource intensive. Automated deep learning (DL)-based segmentation metho...
Clinical implant dentistry and related research
38863306
Cone-beam computed tomography (CBCT) imaging of the maxillary sinus is indispensable for implantologists, offering three-dimensional anatomical visualization, morphological variation detection, and abnormality identification, all critical for diagnos...
International journal of computer assisted radiology and surgery
38850438
PURPOSE: Paranasal anomalies, frequently identified in routine radiological screenings, exhibit diverse morphological characteristics. Due to the diversity of anomalies, supervised learning methods require large labelled dataset exhibiting diverse an...