Suitability of DNN-based vessel segmentation for SIRT planning.

Journal: International journal of computer assisted radiology and surgery
Published Date: Aug 3, 2023

Abstract

PURPOSE: The segmentation of the hepatic arteries (HA) is essential for state-of-the-art pre-interventional planning of selective internal radiation therapy (SIRT), a treatment option for malignant tumors in the liver. In SIRT a catheter is placed through the aorta into the tumor-feeding hepatic arteries, injecting small beads filled with radiation emitting material for local radioembolization. In this study, we evaluate the suitability of a deep neural network (DNN) based vessel segmentation for SIRT planning.

Authors

  • Farina Kock
    Fraunhofer Institute for Digital Medicine MEVIS, Max-von-Laue-Str. 2, Bremen, 28359, Germany. farina.kock@mevis.fraunhofer.de.
  • Felix Thielke
    Fraunhofer Institute for Digital Medicine MEVIS, Max-von-Laue-Str. 2, 28359, Bremen, Germany.
  • Nasreddin Abolmaali
    Department of Radiology, Städtisches Klinikum Dresden, Dresden, Germany.
  • Hans Meine
    Fraunhofer Institute for Medical Image Computing MEVIS, Bremen, Germany.
  • Andrea Schenk
    Fraunhofer Institute for Medical Image Computing MEVIS, Bremen, Germany.

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