Evidence map›Paper›PMID 39085681›Full record

ArticleInternational journal of computer assisted radiology and surgery2025

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

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In one paragraph

Article in International journal of computer assisted radiology and surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Elia HalleDepartment of Data Mining, Jerusalem College of Technology, Jerusalem, Israel.
Tevel AmielOral Maxillofacial Imaging Unit, Department of Oral Medicine, Sedation and Imaging, Faculty of Dental Medicine, The Hebrew University of Jerusalem, Hadassah Medical Center, Jerusalem, Israel.
Doron J AframianDepartment of Oral Medicine, Sedation and Imaging, Faculty of Dental Medicine, The Hebrew University of Jerusalem, Hadassah Medical Center, Jerusalem, Israel.
Tal MalikDepartment of Data Mining, Jerusalem College of Technology, Jerusalem, Israel.
Avital RozenthalDepartment of Data Mining, Jerusalem College of Technology, Jerusalem, Israel.
Oren ShaulySchool of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel.
Leo JoskowiczSchool of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel.
Chen NadlerOral Maxillofacial Imaging Unit, Department of Oral Medicine, Sedation and Imaging, Faculty of Dental Medicine, The Hebrew University of Jerusalem, Hadassah Medical Center, Jerusalem, Israel.
Talia YeshuaDepartment of Data Mining, Jerusalem College of Technology, Jerusalem, Israel. yeshua@g.jct.ac.il.ORCID http://orcid.org/0000-0002-0772-0356

Funding

Ministry of Science, Technology and Space 5007
6 · The paper itself

Abstract

purposeThis 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.

methodsWe developed an end-to-end automatic pipeline consisting of three main steps: (1) region of interest (ROI) computation, (2) parotid gland segmentation using the Frangi filter, and (3) ductopenia case classification with a residual neural network (RNN) augmented by multidirectional maximum intensity projection (MIP) images. To explore the impact of the first two steps, the RNN was trained on three datasets: (1) original MIP images, (2) MIP images with predefined ROIs, and (3) MIP images after segmentation.

resultsEvaluation was conducted on 126 parotid sialo-CBCT scans of normal, moderate, and severe ductopenic cases, yielding a high performance of 100% for the ROI computation and 89% for the gland segmentation. Improvements in accuracy and F1 score were noted among the original MIP images (accuracy: 0.73, F1 score: 0.53), ROI-predefined images (accuracy: 0.78, F1 score: 0.56), and segmented images (accuracy: 0.95, F1 score: 0.90). Notably, ductopenic detection sensitivity was 0.99 in the segmented dataset, highlighting the capabilities of the algorithm in detecting ductopenic cases.

conclusionsOur method, which combines classical image processing and deep learning techniques, offers a promising solution for automatic detection of parotid glands ductopenia in sialo-CBCT scans. This may be used for further research aimed at understanding the role of presence and severity of ductopenia in salivary gland dysfunction.

Indexed as

Cone-Beam Computed TomographyDeep LearningImage Interpretation, Computer-AssistedSalivary Gland DiseasesSialographyContrast MediaHumansIopamidolParotid GlandRetrospective StudiesSeverity of Illness IndexSjogren's SyndromeContrast MediaiomeprolIopamidolClassificationDeep LearningDuctopeniaParotid salivary gland imagingSegmentationSialo cone-beam CT scans

Identifiers

PMID39085681

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