Recognizing surgeon's actions during suture operations from video sequences

Ye Li, Jun Ohya, Toshio Chiba, Rong Xu, Hiromasa Yamashita

研究成果: Conference contribution

抄録

Because of the shortage of nurses in the world, the realization of a robotic nurse that can support surgeries autonomously is very important. More specifically, the robotic nurse should be able to autonomously recognize different situations of surgeries so that the robotic nurse can pass necessary surgical tools to the medical doctors in a timely manner. This paper proposes and explores methods that can classify suture and tying actions during suture operations from the video sequence that observes the surgery scene that includes the surgeon's hands. First, the proposed method uses skin pixel detection and foreground extraction to detect the hand area. Then, interest points are randomly chosen from the hand area so that their 3D SIFT descriptors are computed. A word vocabulary is built by applying hierarchical K-means to these descriptors, and the words frequency histogram, which corresponds to the feature space, is computed. Finally, to classify the actions, either SVM (Support Vector Machine), Nearest Neighbor rule (NN) for the feature space or a method that combines sliding window with NN is performed. We collect 53 suture videos and 53 tying videos to build the training set and to test the proposed method experimentally. It turns out that the NN gives higher than 90% accuracies, which are better recognition than SVM. Negative actions, which are different from either suture or tying action, are recognized with quite good accuracies, while Sliding window did not show significant improvements for suture and tying and cannot recognize negative actions.

本文言語English
ホスト出版物のタイトルMedical Imaging 2014
ホスト出版物のサブタイトルImage Processing
出版社SPIE
ISBN(印刷版)9780819498274
DOI
出版ステータスPublished - 2014 1 1
イベントMedical Imaging 2014: Image Processing - San Diego, CA, United States
継続期間: 2014 2 162014 2 18

出版物シリーズ

名前Progress in Biomedical Optics and Imaging - Proceedings of SPIE
9034
ISSN(印刷版)1605-7422

Conference

ConferenceMedical Imaging 2014: Image Processing
国/地域United States
CitySan Diego, CA
Period14/2/1614/2/18

ASJC Scopus subject areas

  • 電子材料、光学材料、および磁性材料
  • 原子分子物理学および光学
  • 生体材料
  • 放射線学、核医学およびイメージング

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