Please use this identifier to cite or link to this item: http://earchive.tpu.ru/handle/11683/68021
Title: Identification of bronchopulmonary segment containing COVID abrasions using EG-CNN and Segnet
Authors: Aksenov, Sergey Vladimirovich
Samuel Ragland Francis, Nadine Susanne
Samuel Ragland Francis, Natzina Juanita
Keywords: идентификация; томографические изображения; компьютерные изображения; сегментация; диагностика; COVID-19
Issue Date: 2021
Publisher: Томский политехнический университет
Citation: Aksenov, S. V. Identification of bronchopulmonary segment containing COVID abrasions using EG-CNN and Segnet / S. V. Aksenov, N. S. Samuel Ragland Francis, N. J. Samuel Ragland Francis // Молодежь и современные информационные технологии : сборник трудов XVIII Международной научно-практической конференции студентов, аспирантов и молодых учёных, 22-26 марта 2021 г., г. Томск. — Томск : Изд-во ТПУ, 2021. — [С. 96-98].
Abstract: As the current COVID pandemic is a huge concern, more effective methods are required for treatment and analysis of this disease. If COVID analysis is aided by automated detection of the disease, this will reduce time and also speed up treatment. In this research, the particular bronchopulmonary segment containing COVID is detected to narrow and segregate the treatment area. Computer Tomographic Images are passed through EG-CNN which is modelled with Segnet to detect COVID-19 abrasions. The output of the two CNNs are gated to develop the final result with high accuracy.
URI: http://earchive.tpu.ru/handle/11683/68021
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