Automated segmentation and deep learning classification of ductopenic parotid salivary glands in sialo cone-beam CT images

Elia Halle, Tevel Amiel, Doron J. Aframian, Tal Malik, Avital Rozenthal, Oren Shauly, Leo Joskowicz, Chen Nadler, Talia Yeshua

Abstract: This study addressed the challenge of detecting and classifying the severity of ductopenia in parotid glands, a structural abnormality characterized by a reduced number of salivary ducts, previously shown to be associated with salivary gland impairment. The aim of the study was to develop an automatic algorithm designed to improve diagnostic accuracy and efficiency in analyzing ductopenic parotid glands using sialo cone-beam CT (sialo-CBCT) images.