Erdal BAŞARAN, Zafer CÖMERT, Yuksel CELIK

Timpanik Membran Görüntü Özellikleri Kullanılarak Sınıflandırılması

Orta kulak inflamasyonu olarak bilinen otitis media rahatsızlığının teşhis edilmesi için otoskop cihazı ile zar bölgesine bakılarak karar verilmektedir. Dokusal özellik çıkarma algoritmaları, görüntüler üzerinde bölge tespiti ve görüntüye ait özelliklerin elde edilmesinde yaygın olarak kullanılmaktadır. Bu çalışmada gerekli yasal izinler alındıktan sonra elde edilen orta kulak görüntülerinde normal ve otitis media görüntülerinin ayırt edilmesi için literatürde yaygın olarak kullanılan gri seviyeli eş-oluşum matrisi, yerel ikili örüntüler, yönlü gradyanların histogram algoritmaları kullanılmıştır. Bu dokusal özellik çıkarma algoritmalarının görüntüleri sınıflandırma üzerinde başarıları incelendikten sonra her bir özellik setine görüntülere ait renk kanallarının ortalamaları da eklenerek bu özelliğin sınıflandırma başarısına etkisi incelenmiştir. Sonuç olarak tek başına bir dokusal özellik çıkarma algoritması kullanıldığında en iyi sonuçlar yerel ikili örüntü algoritması ile elde edilmiştir. Bu algoritmaya renk kanallarının ortalaması da eklendiği zaman sınıflandırma başarısını olumlu yönde etkilediği sonucuna varılmıştır. Sınıflandırma sonucunda % 78.67 doğruluk oranı elde edilmiştir.

Anahtar Kelimeler:

Biyomedikal işaret işleme, yapay öğrenme, özellik çıkarımı, sınıflandırma

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