Alzheimer’s Disease Detection with Deep Learning Architectures Designed Using Special Block Structures

Yıl 2023, , 745 - 752, 01.09.2023

Eyup Hanbay , Ali Arı

https://doi.org/10.35234/fumbd.1313523

Öz

Alzheimer's disease, a type of dementia, is quite common in the world. The disease has different stages and there is still no cure. With current machine learning methods, different stages of the disease can be detected. Especially with deep learning-based methods, disease detection can be made sensitively. In this study, two different deep learning architectures have developed by using special block structures of ResNet and Inception architectures. These architectures have produced effective results in the detection of Alzheimer's. With the design of special block structures, the ability of different architectures to work together has been revealed. In the experimental results, it is seen that the proposed architectures produce effective results.

Anahtar Kelimeler

Alzheimers’s disease detection, Deep learning, Inception, ResNet

Özel Blok Yapıları Kullanarak Tasarlanan Derin Öğrenme Mimarileri ile Alzheimer Hastalık Tespiti

Öz

Bir demans türü olan Alzheimer hastalığı dünyada oldukça yaygın bir şekilde görülmektedir. Hastalığın farklı evreleri olup halen geçerli bir tedavisi yoktur. Güncel makine öğrenmesi yöntemleri ile hastalığın farklı evreleri tespit edilebilmektedir. Özellikle derin öğrenme tabanlı yöntemler ile hassas şekilde hastalık tespiti yapılabilmektedir. Bu çalışmada ResNet ve Inception mimarilerinin özel blok yapıları kullanılarak iki farklı derin öğrenme mimarisi geliştirilmiştir. Bu mimariler Alzheimer tespitinde etkin sonuçlar üretmiştir. Özel blok yapılarının tasarımı ile farklı mimarilerin birlikte çalışma yetenekleri ortaya çıkarılmıştır. Yapılan deneysel sonuçlarda önerilen mimarilerin etkin sonuçlar ürettiği görülmüştür.

Anahtar Kelimeler

Alzheimer hastalığı tespiti, Derin öğrenme, Inception, ResNet

Kaynakça

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