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An Human-Computer Interactive Augmented Reality System for Coronary Artery Diagnosis Planning and Training

  • Qiming Li*
  • , Chen Huang
  • , Shengqing Lv
  • , Zeyu Li
  • , Yimin Chen
  • , Lizhuang Ma
  • *Corresponding author for this work
  • Shanghai Jiao Tong University
  • Shanghai Maritime University
  • Shanghai University

Research output: Contribution to journal › Article › peer-review

Abstract

In order to let the doctor carry on the coronary artery diagnosis and preoperative planning in a more intuitive and more natural way, and to improve the training effect for interns, an augmented reality system for coronary artery diagnosis planning and training (ARS-CADPT) is designed and realized in this paper. At first, a 3D reconstruction algorithm based on computed tomographic (CT) images is proposed to model the coronary artery vessels (CAV). Secondly, the algorithms of static gesture recognition and dynamic gesture spotting and recognition are presented to realize the real-time and friendly human-computer interaction (HCI), which is the characteristic of ARS-CADPT. Thirdly, a Sort-First parallel rendering and splicing display subsystem is developed, which greatly expands the capacity of student users. The experimental results show that, with the use of ARS-CADPT, the reconstruction accuracy of CAV model is high, the HCI is natural and fluent, and the visual effect is good. In a word, the system fully meets the application requirement.

Original languageEnglish
Article number159
JournalJournal of Medical Systems
Volume41
Issue number10
DOIs
StatePublished - 1 Oct 2017
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Augmented reality
  • Coronary artery
  • Diagnosis and preoperative planning
  • Human computer interaction
  • Trainning

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