CT Modalitesinde U-Net Tabanlı Segmentasyon Ağlarını Kullanarak Pankreas Segmentasyonu: Karşılaştırmalı Bir Analiz

Öz

Pankreas, karın içindeki küçük boyutlu organlardan biridir. Ayrıca anatomik farklılıklar, pankreasın tespit edilmesini oldukça zorlaştırmaktadır. Bu proje pankreasın otomatik olarak segmentasyonunu amaçlamaktadır. Bu amaçla 82 hastanın bilgisayarlı tomografi (BT) görüntülerini içeren NIH-CT82 veri seti kullanılmıştır. Son teknoloji bir model olan U-Net ve farklı versiyonları olan Attention U-Net, Residual U-Net, Attention Residual U-Net ve Residual U-Net++ test edilmiştir. En iyi tahmin performansı, 0.903 zar skoru, 0.823 IoU, 0.898 duyarlılık, 1.000 özgülüllük, 0.908 kesinlik ve 0.999 doğruluk ile Residual U-Net tarafından elde edilmiştir. Sonuç olarak pankreas segmentasyonu için yapay zeka (YZ) destekli bir karar destek sistemi oluşturulmuştur.

Anahtar Kelimeler

• Pankreas
• Segmentasyon
• Derin öğrenme
• U-Net
• Residual U-Net++

Pancreas Segmentation Using U-Net Based Segmentation Networks in CT Modality: A Comparative Analysis

Abstract

The pancreas is one of the small size organs in the abdomen. Moreover, anatomical differences make it difficult to detect the pancreas. This project aims to automatically segmentation of pancreas. For this purpose, NIH-CT82 data set, which includes CT images from 82 patients was used. U-Net which is state-of-the-art model and its different versions, namely Attention U-Net, Residual U-Net, Attention Residual U-Net, and Residual U-Net++ were tested. Best predict performance was achieved by Residual U-Net with the dice of 0.903, IoU of 0.823, sensitivity of 0.898, specificity of 1.000, precision of 0.908, and accuracy of 0.999. Consequently, an artificial intelligence (AI) supported decision support system was created for pancreas segmentation.

Keywords

• Pancreas
• Segmentation
• Deep learning
• U-Net
• Residual U-Net++

Kaynakça

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