It enhances the segmentation accuracy of detecting COVID-19 regions from CT scans. The proposed strategy leverages an ensemble technique to combine the outputs ...
Dec 23, 2022 · Abstract:The devastation caused by the coronavirus pandemic makes it imperative to design automated techniques for a fast and accurate detection ...
Dec 22, 2022 · A pre-trained deep-learning model, called DenseNet, was developed [35] for classifying 121 CT-images into COVID-19 positive and negative ...
Jan 1, 2024 · We propose a novel non-invasive tool, using deep learning and imaging, for delineating COVID-19 infection in lungs.
Dec 21, 2022 · Automated delineation of COVID-19 lesions from lung CT scans aids the diagnosis and prognosis for patients. The asymmetric shapes and ...
Methods: To address these challenges, we propose a novel self-supervised deep learning method for automated segmentation of COVID-19 infection lesions and ...
Collective Intelligent Strategy for Improved Segmentation of COVID-19 from CT · no code implementations • 23 Dec 2022 • Surochita Pal Das, Sushmita Mitra, ...
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COVID-rate: an automated framework for segmentation of COVID-19 ...
pmc.ncbi.nlm.nih.gov › PMC8881477
Based on a set of comprehensive experiments, we have evaluated performance of the proposed COVID-Rate model in segmenting COVID-19 lesions from 2D CT images and ...
Missing: strategy | Show results with:strategy
Methods: We designed a segmentation network for COVID-19-infected regions in CT images. To begin with, multilayered features were extracted by the backbone ...
Missing: Collective strategy
Collective Intelligent Strategy for Improved Segmentation of COVID-19 from CT ... An automatic COVID-19 CT segmentation network using spatial and channel ...