Artık evrişimli sinir ağı kullanılarak göğüs röntgeni görüntülerinde pnömoni tespiti

Yıl 2024, Cilt: 39 Sayı: 3, 1719 - 1732, 20.05.2024

İpek İnal Atik

https://doi.org/10.17341/gazimmfd.1271385

Öz

Pnömoni hastalığı akciğer dokusunun iltihaplanması neticesinde ortaya çıkan bir göğüs hastalığıdır. Pnömoni her yaşta görülebilmekle birlikte iki yaş altı ve altmış beş yaş üstü kişilerde oldukça tehlikelidir. Dünya Sağlık Örgütü verilerine göre dünyadaki tüm ölümlerin yaklaşık yüzde %7’si kadarının pnömoni nedeniyle olduğu belirtilmektedir. Hastalıktan kaynaklı ölüm oranlarının azaltılmasında hastalığın erken teşhisi ve tedavisi önemli bir etkendir. Çalışmada üç boyutlu (3D) göğüs röntgen görüntülerinden pnömoni tespiti için etkin bir evrişimli sinir ağı (ESA) modeli önerilmiştir. Önerilen model, ön eğitimli ResNet ile transfer öğrenme yaklaşımı kullanılarak tasarlanmıştır. Modelde artık blok bağlantılar ile derin öğrenme mimarisindeki bazı katmanlar atlanarak performansı arttırılmıştır. Önerilen yöntemin performansı basit bir ESA modeli, önerilen modelden artık blokların çıkarıldığı ESA modeli ve yaygın olarak kullanılan ön eğitimli ağlardan olan ResNet-18 ile karşılaştırılmıştır. Yapılan analizlere göre önerilen yöntemin doğruluk, özgüllük, hassasiyet, kesinlik ve F-1 skoru değerleri sırasıyla %98,42; %97,52; %99,35; %97,47 ve %98,90 olarak elde edilmiştir. Analizlerden elde edilen sonuçlar incelendiğinde, önerilen yöntemin göğüs röntgen görüntülerinden pnömoni tespitinde başarılı olduğunu ortaya koymaktadır.

Anahtar Kelimeler

göğüs röntgen görüntü, pnömoni, sınıflandırma, ESA, artık blok

Kaynakça

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