Please use this identifier to cite or link to this item: http://earchive.tpu.ru/handle/11683/46959
Title: Detection of fibrosis regions in the lungs based on CT scans
Authors: Natzina Juanita Francis
metadata.dc.contributor.advisor: Aksenov, Sergey Vladimirovich
Keywords: электронные ресурсы; images; neural network; томографические изображения; нейронные сети; методы обработки; фиброз; легкие
Issue Date: 2017
Publisher: Изд-во ТПУ
Citation: Natzina Juanita Francis. Detection of fibrosis regions in the lungs based on CT scans / Natzina Juanita Francis ; sci. adv. S. V. Aksenov // Информационные технологии в науке, управлении, социальной сфере и медицине : сборник научных трудов IV Международной научной конференции, 5-8 декабря 2017 г., Томск : в 2 ч. — Томск : Изд-во ТПУ, 2017. — Ч. 2. — [С. 4-9].
Abstract: The main aim in the article was to provide an accurate, simple and fast algorithm that can increase the performance of the system and thereby the efficiency. Accurate results for lung images have not been accurate as the edges form in many diverse ways. Thereby, a universally applicable edge detection algorithm cannot comply with the purpose of detecting fibrosis. Thus by considering and furthermore introducing a deep convolutional neural network with pixel manipulation, the detection of fibrosis can be made easy, efficient and even accurate unlike the traditional learning structures. By implementing this we are free from extraction of features or even computation of multiple channels and thus suggesting a very straight forward method in terms of the detection and output accuracy.
URI: http://earchive.tpu.ru/handle/11683/46959
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