Beyin Bilgisayarlı Tomografi Görüntülerinde Yapay Zeka Tabanlı Beyin Damar Hastalıkları Tespiti

Author:

KARATAŞ Ali Fatih1,DOĞAN Vakkas1,KILIÇ Volkan1

Affiliation:

1. İZMİR KATİP ÇELEBİ ÜNİVERSİTESİ, MÜHENDİSLİK VE MİMARLIK FAKÜLTESİ

Abstract

Cerebrovascular disease (CVD) causes paralysis and even mortality in humans due to blockage or bleeding of brain vessels. The early diagnosis of the CVD type by the specialist can avoid these casualties with a correct course of treatment. However, it is not always possible to recruit enough specialists in hospitals or emergency services. Therefore, in this study, an artificial intelligence (AI)-based clinical decision support system for CVD detection from brain computed tomography (CT) images is proposed to improve the diagnostic results and relieve the burden of specialists. The deep learning model, a subset of AI, was implemented through a two-step process in which CVD is first detected and then classified as ischemic or hemorrhagic. Moreover, the developed system is integrated into our custom-designed desktop application that offers a user-friendly interface for CVD diagnosis. Experimental results prove that our system has great potential to improve early diagnosis and treatment for specialists, which contributes to the recovery rate of patients.

Publisher

European Journal of Science and Technology

Subject

General Earth and Planetary Sciences,General Environmental Science

Reference50 articles.

1. Alom, M. Z., Taha, T. M., Yakopcic, C., Westberg, S., Sidike, P., Nasrin, M. S., . . . Asari, V. K. (2018). The history began from alexnet: A comprehensive survey on deep learning approaches. arXiv preprint arXiv:.01164

2. Aydın, S., Çaylı, Ö., Kılıç, V., & Onan, A. (2022). Sequence-to-Sequence Video Captioning with Residual Connected Gated Recurrent Units. J Avrupa Bilim ve Teknoloji Dergisi(35), 380-386.

3. Balbay, Y., Gagnon-Arpin, I., Malhan, S., Öksüz, M. E., Sutherland, G., Dobrescu, A., . . . Habib, M. (2018). Modeling the burden of cardiovascular disease in Turkey. Anatolian Journal of Cardiology 20(4), 235.

4. Betül, U., Çaylı, Ö., Kılıç, V., & Onan, A. (2022). Resnet based Deep Gated Recurrent Unit for Image Captioning on Smartphone. J Avrupa Bilim ve Teknoloji Dergisi(35), 610-615.

5. Çaylı, Ö., Makav, B., Kılıç, V., & Onan, A. (2020). Mobile Application Based Automatic Caption Generation for Visually Impaired. Paper presented at the International Conference on Intelligent and Fuzzy Systems.

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