COVID-19 Lung Radiography Segmentation by Means of Multiphase Transfer Learning
نویسندگان
چکیده
COVID-19 is characterized by its impact on the respiratory system and, during global outbreak of 2020, specific protocols had to be designed contain spread within hospitals. This required use portable X-ray devices that allow for a greater flexibility in terms their arrangement rooms not specifically such purpose. However, poor image quality, together with subjectivity expert, can hinder diagnosis process. Therefore, automatic methodologies advised. Even so, development challenging due scarcity available samples. For this reason, we present COVID-19-specific methodology able segment these chest radiographs reduced number samples via multiple transfer learning phases. allows us extract knowledge from two related fields and obtain robust limited data target domain. Our proposal aims help both experts other computer-aided systems focus attention region interest, ignoring unrelated information.
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ژورنال
عنوان ژورنال: Engineering proceedings
سال: 2021
ISSN: ['2673-4591']
DOI: https://doi.org/10.3390/engproc2021007005