Artificial Intelligence-Assisted Segmentation of a Falx Cerebri Calcification on Cone-Beam Computed Tomography: A Case Report.

Intracranial calcifications, particularly within the falx cerebri, serve as crucial diagnostic markers ranging from benign accumulations to signs of severe pathologies. The falx cerebri, a dural fold that separates the cerebral hemispheres, presents challenges in visualization due to its low contrast in standard imaging techniques. Recent advancements in artificial intelligence (AI), particularly in machine learning and deep learning, have significantly transformed radiological diagnostics.

Artificial intelligence versus semi-automatic segmentation of the inferior alveolar canal on cone-beam computed tomography scans: A pilot study.

Background: The inferior alveolar canal (IAC) is a fundamental mandibular structure. It is important to conduct a precise pre-surgical evaluation of the IAC to prevent complications. Recently, the use of artificial intelligence (AI) has demonstrated potential as a valuable tool for dentists, particularly in the field of oral and maxillofacial radiology.

Evaluation of a Vendor-Agnostic Deep Learning Model for Noise Reduction and Image Quality Improvement in Dental CBCT.

Background/objectives: To assess the impact of a vendor-agnostic deep learning model (DLM) on image quality parameters and noise reduction in dental cone-beam computed tomography (CBCT) reconstructions.

Methods: This retrospective study was conducted on CBCT scans of 93 patients (41 males and 52 females, mean age 41.2 years, SD 15.

Small Extracellular Vesicles and Oral Mucosa: The Power Couple in Regenerative Therapies?

Although ongoing debates persist over the scope of phenomena classified as regenerative processes, the most up-to-date definition of regeneration is the replacement or restoration of damaged or missing cells, tissues, organs, or body parts to full functionality. Despite extensive research on this topic, new methods in regenerative medicine are continually sought, and existing ones are being improved. Small extracellular vesicles (sEVs) have gained attention for their regenerative potential, as evidenced by existing studies conducted by independent research groups.

Accuracy of Artificial Intelligence for Cervical Vertebral Maturation Assessment-A Systematic Review.

To systematically review and summarize the existing scientific evidence on the diagnostic performance of artificial intelligence (AI) in assessing cervical vertebral maturation (CVM). This review aimed to evaluate the accuracy and reliability of AI algorithms in comparison to those of experienced clinicians. Comprehensive searches were conducted across multiple databases, including PubMed, Scopus, Web of Science, and Embase, using a combination of Boolean operators and MeSH terms.