System events: readily accessible features for surgical phase detection.

Journal: International journal of computer assisted radiology and surgery
Published Date: May 13, 2016

Abstract

PURPOSE: Surgical phase recognition using sensor data is challenging due to high variation in patient anatomy and surgeon-specific operating styles. Segmenting surgical procedures into constituent phases is of significant utility for resident training, education, self-review, and context-aware operating room technologies. Phase annotation is a highly labor-intensive task and would benefit greatly from automated solutions.

Authors

  • Anand Malpani
    Department of Computer Science, The Johns Hopkins University, 3400 N. Charles St., Malone Hall Room 340, Baltimore, MD, 21218, USA. amalpan1@jhu.edu.
  • Colin Lea
    Department of Computer Science, The Johns Hopkins University, 3400 N. Charles St., Malone Hall Room 340, Baltimore, MD, 21218, USA.
  • Chi Chiung Grace Chen
    Department of Gynecology and Obstetrics, The Johns Hopkins University, Johns Hopkins Bayview Medical Center, 301 Mason Lord Drive, Suite 3200, Baltimore, MD, 21224, USA.
  • Gregory D Hager
    Department of Computer Science, The Johns Hopkins University, 3400 N. Charles St., Malone Hall Room 340, Baltimore, MD, 21218, USA.

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