AIMC Topic: Parotid Gland

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Classification of parotid gland tumors by using multimodal MRI and deep learning.

NMR in biomedicine Sep 4, 2020
Various MRI sequences have shown their potential to discriminate parotid gland tumors, including but not limited to T -weighted, postcontrast T -weighted, and diffusion-weighted images. In this study, we present a fully automatic system for the diagn...
Humans Female Male Multimodal Imaging Parotid Gland Parotid Neoplasms Diffusion Magnetic Resonance Imaging Middle Aged Deep Learning Magnetic Resonance Imaging
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Usefulness of a deep learning system for diagnosing Sjögren's syndrome using ultrasonography images.

Dento maxillo facial radiology Dec 11, 2019
OBJECTIVES: We evaluated the diagnostic performance of a deep learning system for the detection of Sjögren's syndrome (SjS) in ultrasonography (US) images, and compared it with the performance of inexperienced radiologists.
Submandibular Gland Ultrasonography Parotid Gland Sjogren's Syndrome Humans Deep Learning
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A Deep Learning Model for Predicting Xerostomia Due to Radiation Therapy for Head and Neck Squamous Cell Carcinoma in the RTOG 0522 Clinical Trial.

International journal of radiation oncology, biology, physics Jun 13, 2019
PURPOSE: Xerostomia commonly occurs in patients who undergo head and neck radiation therapy and can seriously affect patients' quality of life. In this study, we developed a xerostomia prediction model with radiation treatment data using a 3-dimensio...
Pharyngeal Neoplasms Oropharyngeal Neoplasms Submandibular Gland Xerostomia Hypopharyngeal Neoplasms Radiotherapy, Conformal Radiotherapy, Image-Guided Laryngeal Neoplasms Area Under Curve Parotid Gland Radiotherapy Planning, Computer-Assisted Humans Retrospective Studies Tomography, X-Ray Computed Logistic Models Squamous Cell Carcinoma of Head and Neck Deep Learning ROC Curve
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Preliminary study on the application of deep learning system to diagnosis of Sjögren's syndrome on CT images.

Dento maxillo facial radiology May 22, 2019
OBJECTIVES: This study estimated the diagnostic performance of a deep learning system for detection of Sjögren's syndrome (SjS) on CT, and compared it with the performance of radiologists.
Humans Sensitivity and Specificity Parotid Gland Tomography, X-Ray Computed Deep Learning Sjogren's Syndrome
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Deep Learning-Based Delineation of Head and Neck Organs at Risk: Geometric and Dosimetric Evaluation.

International journal of radiation oncology, biology, physics Mar 2, 2019
PURPOSE: Organ-at-risk (OAR) delineation is a key step in treatment planning but can be time consuming, resource intensive, subject to variability, and dependent on anatomical knowledge. We studied deep learning (DL) for automated delineation of mult...
Parotid Gland Organs at Risk Radiotherapy Planning, Computer-Assisted Submandibular Gland Brain Stem Pharyngeal Muscles Larynx Esophagus Benchmarking Mouth Humans Deep Learning Head and Neck Neoplasms Esophageal Sphincter, Upper
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Early prediction of radiotherapy-induced parotid shrinkage and toxicity based on CT radiomics and fuzzy classification.

Artificial intelligence in medicine Mar 18, 2017
MOTIVATION: Patients under radiotherapy for head-and-neck cancer often suffer of long-term xerostomia, and/or consistent shrinkage of parotid glands. In order to avoid these drawbacks, adaptive therapy can be planned for patients at risk, if the pred...
Fuzzy Logic Predictive Value of Tests Machine Learning Bayes Theorem Humans Tomography, X-Ray Computed Radiation Injuries Radiographic Image Interpretation, Computer-Assisted Risk Factors Parotid Gland Cranial Irradiation Radiation Exposure Time Factors Early Diagnosis Xerostomia Head and Neck Neoplasms Radiotherapy Dosage
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Efficient Descriptor-Based Segmentation of Parotid Glands With Nonlocal Means.

IEEE transactions on bio-medical engineering Sep 16, 2016
OBJECTIVE: We introduce descriptor-based segmentation that extends existing patch-based methods by combining intensities, features, and location information. Since it is unclear which image features are best suited for patch selection, we perform a b...
Parotid Gland Reproducibility of Results Pattern Recognition, Automated Sensitivity and Specificity Radiographic Image Enhancement Humans Radiographic Image Interpretation, Computer-Assisted Neural Networks, Computer Subtraction Technique Tomography, X-Ray Computed
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U-Attention-Net: a deep learning automatic delineation model for parotid glands in head and neck cancer organs at risk on radiotherapy localization computed tomography images.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) Jul 1, 2025
OBJECTIVE: This study aimed to develop a novel deep learning model, U-Attention-Net (UA-Net), for precise segmentation of parotid glands on radiotherapy localization CT images.
Humans Head and Neck Neoplasms Parotid Gland Organs at Risk Automation Tomography, X-Ray Computed Deep Learning Image Processing, Computer-Assisted
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Deep learning in the precise assessment of primary Sjögren's syndrome based on ultrasound images.

Rheumatology (Oxford, England) Apr 1, 2025
OBJECTIVES: This study aimed to investigate the value of a deep learning (DL) model based on greyscale ultrasound (US) images for precise assessment and accurate diagnosis of primary Sjögren's syndrome (pSS).
Sjogren's Syndrome Submandibular Gland Lacrimal Apparatus Deep Learning Ultrasonography Parotid Gland Prospective Studies Female Aged Middle Aged Case-Control Studies Adult Humans Male
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Radiomics and deep learning approach to the differential diagnosis of parotid gland tumors.

Current opinion in otolaryngology & head and neck surgery Apr 1, 2022
PURPOSE OF REVIEW: Advances in computer technology and growing expectations from computer-aided systems have led to the evolution of artificial intelligence into subsets, such as deep learning and radiomics, and the use of these systems is revolution...
Diagnosis, Differential Humans Parotid Gland Artificial Intelligence Parotid Neoplasms Deep Learning
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