IAD Index of Academic Documents
  • Home Page
  • About
    • About Izmir Academy Association
    • About IAD Index
    • IAD Team
    • IAD Logos and Links
    • Policies
    • Contact
  • Submit A Journal
  • Submit A Conference
  • Submit Paper/Book
    • Submit a Preprint
    • Submit a Book
  • Contact
  • Avrupa Bilim ve Teknoloji Dergisi
  • Issue:40 Special Issue
  • Pancreas Segmentation Using U-Net Based Segmentation Networks in CT Modality: A Comparative Analysis

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

Authors : Alperen DERİN, Caglar GURKAN, Abdulkadir BUDAK, Hakan KARATAŞ
Pages : 94-98
Doi:10.31590/ejosat.1171803
View : 18 | Download : 9
Publication Date : 2022-09-30
Article Type : Research Paper
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 insert ignore into journalissuearticles values(AI); supported decision support system was created for pancreas segmentation.
Keywords : Pankreas, Segmentasyon, Derin öğrenme, U Net, Residual U Net

ORIGINAL ARTICLE URL
VIEW PAPER (PDF)

* There may have been changes in the journal, article,conference, book, preprint etc. informations. Therefore, it would be appropriate to follow the information on the official page of the source. The information here is shared for informational purposes. IAD is not responsible for incorrect or missing information.


Index of Academic Documents
İzmir Academy Association
CopyRight © 2023-2025