Spleen Segmentation on CT Using Convolutional Neural Network

Tulum G., Osman O., DANDİN Ö., YILMAZ V. T., KISAOĞLU A., DEMİRYILMAZ İ., ...More

Medical Technologies Congress (TIPTEKNO), İzmir, Turkey, 3 - 05 October 2019, pp.259-262, (Full Text) identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/tiptekno.2019.8895117
  • City: İzmir
  • Country: Turkey
  • Page Numbers: pp.259-262
  • Keywords: Computed tomography, spleen segmentation, convolutional neural network, MULTIORGAN SEGMENTATION, 4D GRAPHS, ATLAS, ENHANCEMENT
  • Akdeniz University Affiliated: Yes

Abstract

The automated segmentation systems have been evolving from experimental to clinical applications in radiology. By taking advantage of these, radiologists can increase diagnostic accuracy in their interpretations. In this work we proposed a convolutional neural network based spleen segmentation system. Automatically segmented spleen had an 76.7% sensitivity, 99.8% specificity, 94.7% positive prediction value, 99.9% negative prediction value and 99.8% accuracy.