Surgical workflow recognition with 3DCNN for Sleeve Gastrectomy.

Journal: International journal of computer assisted radiology and surgery
Published Date: Aug 20, 2021

Abstract

PURPOSE: Surgical workflow recognition is a crucial and challenging problem when building a computer-assisted surgery system. Current techniques focus on utilizing a convolutional neural network and a recurrent neural network (CNN-RNN) to solve the surgical workflow recognition problem. In this paper, we attempt to use a deep 3DCNN to solve this problem.

Authors

  • Bokai Zhang
    C-SATS, Inc. Johnson & Johnson, 1100 Olive Way, Suite 1100, Seattle, WA, 98101, USA. bzhang29@its.jnj.com.
  • Amer Ghanem
    C-SATS, Inc. Johnson & Johnson, 1100 Olive Way, Suite 1100, Seattle, WA, 98101, USA.
  • Alexander Simes
    C-SATS, Inc. Johnson & Johnson, 1100 Olive Way, Suite 1100, Seattle, WA, 98101, USA.
  • Henry Choi
    C-SATS, Inc. Johnson & Johnson, 1100 Olive Way, Suite 1100, Seattle, WA, 98101, USA.
  • Andrew Yoo
    C-SATS, Inc. Johnson & Johnson, 1100 Olive Way, Suite 1100, Seattle, WA, 98101, USA.

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