Oral Radiology

Aims & Scope

As the official English-language journal of the Japanese Society for Oral and Maxillofacial Radiology and the Asian Academy of Oral and Maxillofacial Radiology, Oral Radiology is intended to be a forum for international collaboration in head and neck diagnostic imaging and all related fields.

Oral Radiology features cutting-edge research papers, review articles, case reports, and technical notes from both the clinical and experimental fields.

As membership in the Society is not a prerequisite, contributions are welcome from researchers and clinicians worldwide.

View Aims & Scope

---

Metrics & Ranking

Impact Factor

Year	Value
2025	1.7
2024	1.60

SJR (SCImago Journal Rank)

Year	Value
2024	0.589

Quartile

Year	Value
2024	Q2

h-index

Year	Value
2024	28

Journal Rank

Year	Value
2024	9859

Journal Citation Indicator

Year	Value
2024	580

---

---

Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Web of Science
• Medline
• Embase

---

Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Dentistry and Medicine, designed to support cutting-edge academic discovery.

---

Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Evaluation of an artificial intelligence system for detecting vertical root fracture on panoramic radiography

  Citation: 221

  Authors: Motoki, Kyoko, Naoki, Yoshiko, Yudai, Shota, Kazuhiko, Akitoshi, Hiroshi, Eiichiro

• Deep-learning classification using convolutional neural network for evaluation of maxillary sinusitis on panoramic radiography

  Citation: 172

  Authors: Makoto, Yoshiko, Yasufumi, Taisuke, Motoki, Takuma, Yoshitaka, Michihito, Akitoshi, Hiroshi, Eiichiro

• Tooth detection and classification on panoramic radiographs for automatic dental chart filing: improved classification by multi-sized input data

  Citation: 87

  Authors: Chisako, Takumi, Ryo, Tatsuro, Wataru, Yoshiko, Xiangrong, Takeshi, Akitoshi, Eiichiro, Hiroshi

• Deep-learning approach for caries detection and segmentation on dental bitewing radiographs

  Citation: 82

  Authors: Ibrahim Sevki, Kaan, Serdar, Özer, Samet, Adem, Yasin, Elif, Hande, Ahmet Faruk, Alper

• Trabecular structure designation using fractal analysis technique on panoramic radiographs of patients with bisphosphonate intake: a preliminary study

  Citation: 62

  Authors: Kemal Özgür, Emine Şebnem, Seval, Nihat, Cemal, Kaan

• CT evaluation of extranodal extension of cervical lymph node metastases in patients with oral squamous cell carcinoma using deep learning classification

  Citation: 61

  Authors: Yoshiko, Yoshihiko, Toru, Atsushi, Motoki, Yoshitaka, Michihito, Masako, Akitoshi, Eiichiro

• Evaluation of the mandibular trabecular bone in patients with bruxism using fractal analysis

  Citation: 60

  Authors: Melike, Melek, Sevgi, Kaan

• Deep learning object detection of maxillary cyst-like lesions on panoramic radiographs: preliminary study

  Citation: 58

  Authors: Hirofumi, Yoshiko, Motoki, Chiaki, Yoshitaka, Michihito, Yoshihiko, Eiichiro

• Quantitative analysis of metallic artifacts caused by dental metals: comparison of cone-beam and multi-detector row CT scanners

  Citation: 53

  Authors: Jira, Naoya, Shumei, Yoshinobu, Souhei

• Artificial intelligence models for clinical usage in dentistry with a focus on dentomaxillofacial CBCT: a systematic review

  Citation: 53

  Authors: Sorana, Oana, Mihaela, Laura, Cristian, Reinhilde

---