Convolutional Neural Network Ensemble Segmentation With Ratio-Based Sampling for the Arteries and Veins in Abdominal CT Scans.

Journal: IEEE transactions on bio-medical engineering
Published Date: Apr 21, 2021

Abstract

OBJECTIVE: Three-dimensional (3D) blood vessel structure information is important for diagnosis and treatment in various clinical scenarios. We present a fully automatic method for the extraction and differentiation of the arterial and venous vessel trees from abdominal contrast enhanced computed tomography (CE-CT) volumes using convolutional neural networks (CNNs).

Authors

  • Alena-Kathrin Golla
    Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
  • Dominik F Bauer
    Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
  • Ralf Schmidt
    Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
  • Tom Russ
    Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Theodor Kutzer Ufer 1-3, 68167 Mannheim, Germany.
  • Dominik Norenberg
  • Khanlian Chung
    Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Theodor Kutzer Ufer 1-3, 68167 Mannheim, Germany.
  • Christian Tonnes
  • Lothar R Schad
  • Frank G Zöllner

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