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Faculty Members have conducted research related to the Comparative Analysis of Deep Learning Algorithms for Dental Caries Detection and Prediction From Radiographic Images: A Comprehensive Umbrella Review

Haniye Kaviani

Assistant Professor of Oral & Maxillofacial Radiology

Department Oral and Maxillofacial Radiology

School of Dentistry

Tehran University of Medical Sciences

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1. Correction To: Assessment of the Diagnostic Accuracy of Strip and Furcal Perforations in Different Sizes by Cone Beam Computed Tomography (Oral Radiology, (2023), 39, 4, (654-660), 10.1007/S11282-023-00681-Y), Oral Radiology (2025)

2. Dental Caries Diagnosis Using Neural Networks and Deep Learning: A Systematic Review, Multimedia Tools and Applications (2024)

3. Assessment of the Diagnostic Accuracy of Strip and Furcal Perforations in Different Sizes by Cone Beam Computed Tomography, Oral Radiology (2023)

4. Effect of Cone-Beam Computed Tomography Voxel Size on Detection of Vertical Periodontal Bone Defects, ORAL and Implantology (2022)

5. Effect of Voxel Size on Detection of Fenestration, Dehiscence and Furcation Defects Using Cone-Beam Computed Tomography, Oral Radiology (2021)

6. Effects of Denoising and Sharpening on Detection of Secondary Caries Under Amalgam and Composite Proximal Restorations on Digital Periapical Radiographs, International Journal of Dentistry and Oral Science (2021)

7. How Does Voxel Size of Cone-Beam Computed Tomography Effect Accurate Detection of Root Strip Perforations, Iranian Endodontic Journal (2021)

8. A Case of Covid-19 Lung Infection First Detected by [18F]Fdg Pet-Ct, European Journal of Nuclear Medicine and Molecular Imaging (2020)

9. Knowledge and Attitude of Iranian Dentists Towards Cone-Beam Computed Tomography, Frontiers in Dentistry (2019)

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Haniye Kaviani

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