Image Guided Stereotaxic Surgery System

Abstract

Background: Stereotaxic surgery system is minimally invasive form of surgical procedure which requires lot of precision and accuracy especially for invasive neural surgery in order to prevent maximum neurons in brain to be damaged Objective: Purpose of the thesis is to develop image-based guidance system for stereotaxic cage with ability to track the location of needle or drill on target brain region. Methodology: Stereotaxic grid system in real world was developed by using NI LabVIEW Vision software. Image acquisition was done using NI LabVIEW Acquisition. In NI Vision Assistant, image processing was done along with mapping from pixel to real world using image calibration. In pre-processing, color plane extraction and thresholding were done. In Perspective Grid Calibration; point of origin, spacing & coordinates were defined for both x and y axis in real world. OpenCV was used for real time drill tracking. For real time motion tracking, mean shift algorithm and red particle analysis were used. After doing histogram and back projection calculation, low saturation points were removed and mean shift algorithm was used for drill tracking. For red particle analysis several steps like calculation of likelihood N4 neighborhood, confidence interval for red color, state of next model estimation, window was set to be auto size, maximum number of particles to be chosen were 1000, vector dynamics & likelihood for each particle was calculated. Results: Real time drill motion tracking & calibration in real world was done for image guided Stereotaxic Surgery System. Drill bit of 2.35mm diameter was tracked all the way long. Measurements of position, distance & angle in real world were acquired Conclusion: Mean of distance calculation was 10.147 mm & standard deviation was 0.189 mm. Average inspection time for the whole process was 0.94ms.