AIMC Topic: Nasopharyngeal Carcinoma
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A pretreatment multiparametric MRI-based radiomics-clinical machine learning model for predicting radiation-induced temporal lobe injury in patients with nasopharyngeal carcinoma.
Head & neck
Jun 18, 2024
BACKGROUND: To establish and validate a machine learning model using pretreatment multiparametric magnetic resonance imaging-based radiomics data with clinical data to predict radiation-induced temporal lobe injury (RTLI) in patients with nasopharyng...
A deep learning-based method for the prediction of temporal lobe injury in patients with nasopharyngeal carcinoma.
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)
Apr 22, 2024
PURPOSE: To establish a deep learning-based model to predict radiotherapy-induced temporal lobe injury (TLI).
Radiomics and Deep Learning in Nasopharyngeal Carcinoma: A Review.
IEEE reviews in biomedical engineering
Jan 12, 2024
Nasopharyngeal carcinoma is a common head and neck malignancy with distinct clinical management compared to other types of cancer. Precision risk stratification and tailored therapeutic interventions are crucial to improving the survival outcomes. Ar...
Prognosis Forecast of Re-Irradiation for Recurrent Nasopharyngeal Carcinoma Based on Deep Learning Multi-Modal Information Fusion.
IEEE journal of biomedical and health informatics
Dec 5, 2023
Radiation therapy is the primary treatment for recurrent nasopharyngeal carcinoma. However, it may induce necrosis of the nasopharynx, leading to severe complications such as bleeding and headache. Therefore, forecasting necrosis of the nasopharynx a...
Deep learning-based recurrence detector on magnetic resonance scans in nasopharyngeal carcinoma: A multicenter study.
European journal of radiology
Sep 14, 2023
OBJECTIVES: Accuracy in the detection of recurrent nasopharyngeal carcinoma (NPC) on follow-up magnetic resonance (MR) scans needs to be improved.
Multi-task deep learning-based radiomic nomogram for prognostic prediction in locoregionally advanced nasopharyngeal carcinoma.
European journal of nuclear medicine and molecular imaging
Aug 19, 2023
PURPOSE: Prognostic prediction is crucial to guide individual treatment for locoregionally advanced nasopharyngeal carcinoma (LA-NPC) patients. Recently, multi-task deep learning was explored for joint prognostic prediction and tumor segmentation in ...
A deep learning MRI-based signature may provide risk-stratification strategies for nasopharyngeal carcinoma.
European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
Jun 26, 2023
OBJECTIVE: As the prognosis of nasopharyngeal carcinoma (NPC) is influenced by various factors, making it difficult for clinical physicians to predict the outcome, the objective of this study was to develop a deep learning-based signature for risk st...
The Detection of Nasopharyngeal Carcinomas Using a Neural Network Based on Nasopharyngoscopic Images.
The Laryngoscope
May 31, 2023
OBJECTIVE: To construct and validate a deep convolutional neural network (DCNN)-based artificial intelligence (AI) system for the detection of nasopharyngeal carcinoma (NPC) using archived nasopharyngoscopic images.
AI-assisted compressed sensing and parallel imaging sequences for MRI of patients with nasopharyngeal carcinoma: comparison of their capabilities in terms of examination time and image quality.
European radiology
May 23, 2023
OBJECTIVE: To compare examination time and image quality between artificial intelligence (AI)-assisted compressed sensing (ACS) technique and parallel imaging (PI) technique in MRI of patients with nasopharyngeal carcinoma (NPC).
Automatic detection and recognition of nasopharynx gross tumour volume (GTVnx) by deep learning for nasopharyngeal cancer radiotherapy through magnetic resonance imaging.
Radiation oncology (London, England)
May 8, 2023
BACKGROUND: In this study, we propose the deep learning model-based framework to automatically delineate nasopharynx gross tumor volume (GTVnx) in MRI images.
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