Please use this identifier to cite or link to this item:
Title: Classification of Ultrasonographic Thyroid Tumor Images to TIRADS Categories via Texture Analysis Methods
Authors: Tüzüner, Aslan Berk
Eroğul, Osman
Ataç, Gökçe Kaan
Er, Hale Çolakoğlu
Keywords: TIRADS
Ultrasonographic Thyroid Images
Texture Analysis
Issue Date: 2020
Publisher: IEEE
Source: Medical Technologies National Congress (TIPTEKNO) -- NOV 19-20, 2020 -- ELECTR NETWORK
Abstract: Thyroid tumors frequently observed disease by using medical imaging methods. Ultrasonography is the most frequently performed method for diagnosis. To determine, tumor is benign or malign, experienced doctors use various techniques. Fine needle aspiration biopsy and follow-up checking are used for determining type of tumor. However, these methods are time consuming and increasing work load of doctors. So, they created a risk stratification system which has called as ACR-TIRADS. Downside of this system is being subjective and for multiple tumors, it will be time consuming due to analyzing multiple features. To ease, doctors work load and help them to obtain more objective classification, on this study we worked thyroid tumors with texture analysis methods and tried to classify them, to their TIRADS classes. As the result of this study, sensitivity found up %82.8, precision %85 and accuracy found up %73.0.
ISBN: 978-1-7281-8073-1
Appears in Collections:Biyomedikal Mühendisliği Bölümü / Department of Biomedical Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

Show full item record

CORE Recommender

Page view(s)

checked on Dec 26, 2022

Google ScholarTM



Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.