Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6333
Title: Automated Iris Localization for Radiotherapy Applications
Authors: Çavuşculu, Melih
Yetik, İmam Şamil
Yeğiner, Mete
Keywords: Image processing
learning algorithms
classification
iris localization
uveal melanoma
Issue Date: 2017
Publisher: IEEE
Source: 25th Signal Processing and Communications Applications Conference (SIU) -- MAY 15-18, 2017 -- Antalya, TURKEY
Series/Report no.: Signal Processing and Communications Applications Conference
Abstract: Uveal melanoma is a type of tumor that can cause loss of vision, loss of organ or even metastasis and loss of life. Radiotherapy is considered to be the least harmful and successful treatment type among various treatment methods. Radiotherapy should be carried out sensitively without movements of the iris. Therefore, the procedure is mostly performed by local anesthesia. Unfortunately, eye anesthesia can cause complications; therefore alternative methods are gaining importance. In this article, a method is proposed that can track the eye with a camera and automatically detect blinking so that radiotherapy can be aborted. Thus, we will be able to apply radiotherapy without anesthesia and it will he possible to stop the radiotherapy automatically so that the iris is not damaged in case of blinking. The developed method has been tested under various lighting conditions and it has been observed that the method has a very successful performance.
URI: https://hdl.handle.net/20.500.11851/6333
ISBN: 978-1-5090-6494-6
ISSN: 2165-0608
Appears in Collections:Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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