[Development of automatic navigation measuring system using template-matching software in image guided neurosurgery]

Area of Science:

• Neurosurgery
• Medical Imaging
• Image-guided surgery

Context:

• Image-guided neurosurgery relies on accurate neuronavigation systems for brain tumor resection.
• Periodic quality assurance (QA) is crucial for maintaining navigation accuracy.
• Fiducial registration error (FRE) and target registration error (TRE) are key accuracy metrics.

Purpose:

• To evaluate the reliability of TRE compared to FRE for neuronavigation accuracy.
• To develop automated software for calculating TRE to improve QA efficiency.
• To validate the accuracy of the developed software against manual TRE calculations.

Summary:

• This study highlights Target Registration Error (TRE) as a more dependable metric than Fiducial Registration Error (FRE) for assessing neuronavigation system accuracy in neurosurgery.
• A novel software solution was developed, utilizing image processing techniques like automatic template matching to automate TRE calculation.
• The software's TRE computations were compared with manual methods, demonstrating its capability to provide reliable quality assurance for image-guided neurosurgery.

Impact:

• Automated TRE calculation streamlines the quality assurance process for neuronavigation systems.
• Improved accuracy assessment enhances patient safety in image-guided brain tumor surgeries.
• The developed software offers a reliable and efficient solution for routine QA in neurosurgical navigation.