Oral diseases affect nearly 3.5 billion people, and medical resources are limited, which makes access to oral health services nontrivial. Imaging-based machine learning technology is one of the most promising technologies to improve oral medical services and reduce patient costs. The development of machine learning technology requires publicly accessible datasets. However, previous public dental datasets have several limitations: a small volume of computed tomography (CT) images, a lack of multimodal data, and a lack of complexity and diversity of data. These issues are detrimental to the development of the field of dentistry. Thus, to solve these problems, this paper introduces a new dental dataset that contains 169 patients, three commonly used dental image modalities, and images of various health conditions of the oral cavity. The proposed dataset has good potential to facilitate research on oral medical services, such as reconstructing the 3D structure of assisting clinicians in diagnosis and treatment, image translation, and image segmentation.

Jaw and maxillofacial bone lesions encompass a wide variety of both neoplastic and non-neoplastic pathologies. These lesions can arise from various tissues, including bone, cartilage, and soft tissue, each presenting distinct challenges in diagnosis and treatment. While some pathologies exhibit characteristic imaging features that aid in diagnosis, many others are nonspecific. This overlap often necessitates a multimodal imaging approach, combining techniques such as radiographs, computed tomography, and magnetic resonance imaging to achieve a diagnosis or narrow the diagnostic considerations. This article provides a comprehensive review of the imaging approach to jaw and maxillofacial bone tumors, including updates on the 2022 World Health Organization classification of these tumors. The relevant anatomy of the jaw and dental structures that is important for accurate imaging interpretation is discussed.

Numerous benign cysts or solid tumors may present in the jaws. These arise from tooth-forming tissues in the dental alveolus or from nonodontogenic tissues in the basal bone of the mandible and maxilla. Radiologists provide 2 deliverables to assist in diagnosis and management: (1) appropriately formatted images demonstrating the location and extent of the lesion and (2) interpretive reports highlighting specific radiologic findings and an impression providing a radiologic differential diagnosis. This article provides guidance on essential image protocols for planning treatments, a radiologic differential diagnostic algorithm based on location and pattern recognition, and a summary of the main features of benign odontogenic lesions.

The teeth are unique in that they provide a direct pathway for spread of infection into surrounding osseous and soft tissue structures. Periodontal disease is the most common cause of tooth loss worldwide, referring to infection of the supporting structures of the tooth, principally the gingiva, periodontal ligament, cementum, and alveolar bone. Periapical disease refers to an infectious or inflammatory process centered at the root apex of the tooth, usually occurring when deep caries infect the pulp chamber and root canals. We review the pathogenesis, clinical features, and radiographic findings (emphasis on computed tomography) in periodontal and periapical disease.