A Few-Shot U-Net Deep Learning Model for COVID-19 Infected Area Segmentation in CT Images

A Few-Shot U-Net Deep Learning Model for COVID-19 Infected Area Segmentation in CT Images

Recent studies indicate that detecting radiographic patterns on CT chest scans can yield high sensitivity and specificity for COVID-19 identification. In this paper, we scrutinize the effectiveness of deep learning models for semantic segmentation of pneumonia-infected area segmentation in CT images...

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Bibliographic Details
Main Authors: Athanasios Voulodimos, Eftychios Protopapadakis, Iason Katsamenis, Anastasios Doulamis, Nikolaos Doulamis
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Sensors
Subjects:
deep learning
few-shot learning
semantic segmentation
CT images
COVID-19
Online Access:https://www.mdpi.com/1424-8220/21/6/2215

Internet

https://www.mdpi.com/1424-8220/21/6/2215

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