Mar 9, 2021 · This study uses the four classic pretraining models of VGG16, InceptionV3, ResNet and DenseNet to classify parotid CT images using transfer learning methods.
Mar 9, 2021 · The experimental results show that the improved CNN model achieves an accuracy of 97.78%, and its classification performance is better than ...
This study uses the four classic pretraining models of VGG16, InceptionV3, ResNet and DenseNet to classify parotid CT images using transfer learning methods and ...
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Evaluating the diagnostic efficiency of deep-learning models to distinguish malignant from benign parotid tumors on plain computed tomography (CT) images.
Deep Learning for Differentiating Benign From Malignant Parotid ...
pmc.ncbi.nlm.nih.gov › PMC8262843
This study focuses on two types of benign tumors (pleomorphic adenoma and Warthin tumor) and one type of malignant tumors (adenocarcinoma). The MRI scan ...
May 12, 2024 · This study aims to construct and compare the performance of clinical models, traditional radiomics models, deep learning (DL) models, and deep learning ...
Oct 24, 2024 · Research on the Classification of Benign and Malignant Parotid Tumors Based on Transfer Learning and a Convolutional Neural Network. Article.
Apr 23, 2024 · The DL model based on ultrasound images demonstrates exceptional capability in distinguishing between benign and malignant PTs.
ResNet50 presented high sensitivity in distinguishing malignant from benign parotid tumors on plain CT images; this made it a promising auxiliary diagnostic ...
May 16, 2022 · To design a deep learning model based on multimodal magnetic resonance image (MRI) sequences for automatic parotid neoplasm classification.