AIMC Topic: Parotid Gland
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Deep learning for differential diagnosis of parotid tumors based on 2.5D magnetic resonance imaging.
Annals of medicine
Jun 18, 2025
PURPOSE: Accurate preoperative diagnosis of parotid gland tumors (PGTs) is crucial for surgical planning since malignant tumors require more extensive excision. Though fine-needle aspiration biopsy is the diagnostic gold standard, its sensitivity in ...
Deep Learning Based on Ultrasound Images Differentiates Parotid Gland Pleomorphic Adenomas and Warthin Tumors.
Ultrasonic imaging
Mar 29, 2025
Exploring the clinical significance of employing deep learning methodologies on ultrasound images for the development of an automated model to accurately identify pleomorphic adenomas and Warthin tumors in salivary glands. A retrospective study was c...
Prediction of High-risk Capsule Characteristics for Recurrence of Pleomorphic Adenoma in the Parotid Gland Based on Habitat Imaging and Peritumoral Radiomics: A Two-center Study.
Academic radiology
Feb 10, 2025
RATIONALE AND OBJECTIVES: This study aims to develop and validate an ultrasoundbased habitat imaging and peritumoral radiomics model for predicting high-risk capsule characteristics for recurrence of pleomorphic adenoma (PA) of the parotid gland whil...
Using Machine Learning on MRI Radiomics to Diagnose Parotid Tumours Before Comparing Performance with Radiologists: A Pilot Study.
Journal of imaging informatics in medicine
Oct 10, 2024
The parotid glands are the largest of the major salivary glands. They can harbour both benign and malignant tumours. Preoperative work-up relies on MR images and fine needle aspiration biopsy, but these diagnostic tools have low sensitivity and speci...
Applying deep learning-based ensemble model to [F]-FDG-PET-radiomic features for differentiating benign from malignant parotid gland diseases.
Japanese journal of radiology
Sep 10, 2024
OBJECTIVES: To develop and identify machine learning (ML) models using pretreatment 2-deoxy-2-[F]fluoro-D-glucose ([F]-FDG)-positron emission tomography (PET)-based radiomic features to differentiate benign from malignant parotid gland diseases (PGDs...
Machine learning-assisted diagnosis of parotid tumor by using contrast-enhanced CT imaging features.
Journal of stomatology, oral and maxillofacial surgery
Sep 2, 2024
PURPOSE: This study aims to develop a machine learning diagnostic model for parotid gland tumors based on preoperative contrast-enhanced CT imaging features to assist in clinical decision-making.
Automated segmentation and deep learning classification of ductopenic parotid salivary glands in sialo cone-beam CT images.
International journal of computer assisted radiology and surgery
Jul 31, 2024
PURPOSE: 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...
Deep learning for the automatic detection and segmentation of parotid gland tumors on MRI.
Oral oncology
Apr 13, 2024
OBJECTIVES: Parotid gland tumors (PGTs) often occur as incidental findings on magnetic resonance images (MRI) that may be overlooked. This study aimed to construct and validate a deep learning model to automatically identify parotid glands (PGs) with...
An ultrasound-based ensemble machine learning model for the preoperative classification of pleomorphic adenoma and Warthin tumor in the parotid gland.
European radiology
Apr 3, 2024
OBJECTIVES: The preoperative classification of pleomorphic adenomas (PMA) and Warthin tumors (WT) in the parotid gland plays an essential role in determining therapeutic strategies. This study aims to develop and validate an ultrasound-based ensemble...
Improvement of image quality in diffusion-weighted imaging with model-based deep learning reconstruction for evaluations of the head and neck.
Magma (New York, N.Y.)
Nov 21, 2023
OBJECTIVES: To investigate the utility of deep learning (DL)-based image reconstruction using a model-based approach in head and neck diffusion-weighted imaging (DWI).
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