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Congress: ECR25
Poster Number: C-20900
Type: Poster: EPOS Radiologist (scientific)
Authorblock: T. Yeshua, T. Amiel, E. Halle, C. Nadler; Jerusalem/IL
Disclosures:
Talia Yeshua: Nothing to disclose
Tevel Amiel: Nothing to disclose
Elia Halle: Nothing to disclose
Chen Nadler: Nothing to disclose
Keywords: Artificial Intelligence, Head and neck, Salivary glands, Cone beam CT, CAD, Pathology
References

1. Ship JA. (2002) Diagnosing, managing, and preventing salivary gland disorders. Oral Dis 8(2):77-89.

2. Halle E, et al. (2024) Automated segmentation and deep learning classification of ductopenic parotid salivary glands in sialo cone-beam CT images. Int J Comput Assist Radiol Surg.

3. Abdalla-Aslan R, et al. (2021) Standardization of terminology, imaging features, and interpretation of CBCT sialography of major salivary glands. Quintessence Int 52(8):728-740.

4. Keshet N, et al. (2019) Novel parotid sialo-cone-beam computerized tomography features in patients with suspected Sjogren's syndrome. Oral Dis 25(1):126-132.

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