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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 |
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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