Publications by authors named "Avital Rozenthal"
Article Synopsis
- The study aimed to create an automatic algorithm for detecting and classifying ductopenia in parotid glands, which is linked to salivary gland impairment, using sialo cone-beam CT (sialo-CBCT) images.
- The research involved an automated pipeline with three steps: computing regions of interest (ROIs), segmenting the parotid gland using a Frangi filter, and classifying ductopenia severity with a residual neural network (RNN) enhanced by maximum intensity projection (MIP) images.
- Evaluation of the algorithm on 126 scans showed excellent accuracy in ROI computation (100%) and gland segmentation (89%), with significant improvements in the detection of ductopenia severity, indicating its potential