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Related Experiment Video

Updated: Dec 26, 2025

Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities
07:13

Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities

Published on: October 27, 2023

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Robust marker detection and high precision measurement for real-time anatomical registration using Taguchi method.

Abhishek Kaushik1, T A Dwarakanath1,2, Gaurav Bhutani2

  • 1Department of Engineering Sciences, Homi Bhabha National Institute, Mumbai, India.

The International Journal of Medical Robotics + Computer Assisted Surgery : MRCAS
|March 13, 2020
PubMed
Summary

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This study presents a robust real-time algorithm for autonomous marker detection and coordinate measurement, crucial for precise robot-assisted surgery. The algorithm ensures accuracy even under challenging operating room conditions.

Area of Science:

  • Computer Vision
  • Robotics
  • Medical Imaging

Background:

  • Accurate autonomous marker detection and measurement are critical for high-precision anatomical registration in surgery.
  • Real-time, accurate, and robust measurements are essential despite varied operating theatre conditions.

Purpose of the Study:

  • To design and implement a robust, real-time algorithm for measuring marker coordinates.
  • To enable robot-based autonomous registration and surgery through precise marker localization.

Main Methods:

  • Algorithm developed in two parts using the recursive Taguchi method.
  • Part one focuses on marker detection.
  • Part two locates the marker's center and measures coordinates via concentric ellipse fitting.
Keywords:
Taguchi methodanatomical registrationautonomous neuro-registrationfiducial marker detection

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Related Experiment Videos

Last Updated: Dec 26, 2025

Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities
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Main Results:

  • Algorithm tested under extreme conditions: uneven lighting, distorted color, surface distortions, and random marker orientation.
  • Demonstrated robustness in real-time marker detection and measurement.

Conclusions:

  • The developed algorithm is successfully implemented for real-time marker detection and coordinate measurement.
  • The system provides a reliable solution for autonomous registration in robotic surgery.