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MA-Net: Mutex Attention Network for COVID-19 Diagnosis on CT Images
COVID-19 is an infectious pneumonia caused by 2019-nCoV. The number of newly confirmed cases and confirmed deaths continues to remain …
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MA-Net: Mutex Attention Network for COVID-19 Diagnosis on CT Images
MXT: A New Variant of Pyramid Vision Transformer for Multi-label Chest X-ray Image Classification
Nowadays, the global COVID-19 situation is still serious, and the new mutant virus Delta has already spread all over the world. The …
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MXT: A New Variant of Pyramid Vision Transformer for Multi-label Chest X-ray Image Classification
3D gray density coding feature for benign-malignant pulmonary nodule classification on chest CT
Early detection is significant to reduce lung cancer-related death. Computer-aided detection system (CADs) can help radiologists to …
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3D gray density coding feature for benign-malignant pulmonary nodule classification on chest CT
A multi-class COVID-19 segmentation network with pyramid attention and edge loss in CT images
At the end of 2019, a novel coronavirus COVID-19 broke out. Due to its high contagiousness, more than 74 million people have been …
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A multi-class COVID-19 segmentation network with pyramid attention and edge loss in CT images
COVID-19 lesion discrimination and localization network based on multi-receptive field attention module on CT images
Since discovered in Hubei, China in December 2019, Corona Virus Disease 2019 named COVID-19 has lasted more than one year, and the …
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COVID-19 lesion discrimination and localization network based on multi-receptive field attention module on CT images
Pulmonary Nodule Risk Classification in Adenocarcinoma from CT Images Using Deep CNN with Scale Transfer Module
Pulmonary nodules risk classification in adenocarcinoma is essential for early detection of lung cancer and clinical treatment …
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Pulmonary Nodule Risk Classification in Adenocarcinoma from CT Images Using Deep CNN with Scale Transfer Module
Quantitative CT analysis of pulmonary nodules for lung adenocarcinoma risk classification based on an exponential weighted grey scale angular density distribution feature
To improve lung nodule classification efficiency, we propose a lung nodule CT image characterization method. We propose a …
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Quantitative CT analysis of pulmonary nodules for lung adenocarcinoma risk classification based on an exponential weighted grey scale angular density distribution feature