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. This study aims to explore the application of AI in the segmentation and detection of falx cerebri calcifications using Cone-Beam Computed Tomography (CBCT) images through a comprehensive literature review and a detailed case report. The case report presents a 59-year-old patient diagnosed with falx cerebri calcifications whose CBCT images were analyzed using a cloud-based AI platform, demonstrating effectiveness in segmenting these calcifications, although challenges persist in distinguishing these from other cranial structures. A specific search strategy was employed to search electronic databases, yielding four studies exploring AI-based segmentation of the falx cerebri. The review detailed various AI models and their accuracy across different imaging modalities in identifying and segmenting falx cerebri calcifications, also highlighting the gap in publications in this area. In conclusion, further research is needed to improve AI-driven methods for accurately identifying and measuring intracranial calcifications. Advancing AI applications in radiology, particularly for detecting falx cerebri calcifications, could significantly enhance diagnostic precision, support disease monitoring, and inform treatment planning.

Center of Assisted Reproduction Department of Obstetrics and Gynecology University Hospital and Masaryk University 601 77 Brno Czech Republic

Chair of Practical Clinical Dentistry Department of Diagnostics Poznan University of Medical Sciences Bukowska 70 60 812 Poznan Poland

Department of Gerostomatology and Pathology of Oral Cavity Poznan University of Medical Sciences Bukowska 70 60 812 Poznan Poland

Department of Human Morphology and Embryology Head of Division of Anatomy Wrocław Medical University 50 367 Wrocław Poland

Department of Veterinary Surgery Institute of Veterinary Medicine Nicolaus Copernicus University in Torun 87 100 Torun Poland

Doctoral School Poznań University of Medical Sciences Bukowska 70 60 812 Poznan Poland

Faculty of Medical Sciences Poznan University of Medical Sciences Fredry 10 61 701 Poznan Poland

Physiology Graduate Program North Carolina State University Raleigh NC 27695 USA

Prestage Department of Poultry Sciences North Carolina State University Raleigh NC 27695 USA

Citace poskytuje Crossref.org