The University of Edinburgh -
Division of Informatics
Forrest Hill & 80 South Bridge

MSc Thesis #92124

Title:Locating the Eyes in Ct Brain Scan Data
Date: 1992
Abstract:In this document, a technique for locating the eyes in Computer Tomography brain scan data, is designed and implemented. The objective is to automatically localise the eyes for protection during radiotherapy planning. The image feature that is exploited is the circularity of the eyes. After data preprocessing to remove parts of the CT machinery, signature analysis is performed to locate areas of interest. By applying Canny's edge detector to these areas, data is further reduced to the significant edge fragments. The Hough Transform is then applied. The Converging Squares algorithm is used as an efficient and robust method to search the parameter space. The results are processed by the hypothesis generation stage which clusters them according with the x,y,z coordinates of the suggested centres. The ISODATA algorithm is used for clustering. The hypotheses are assessed and sorted. The most valid hypothesis is selected and refined using a second Hough Transform, this time considering spheres. After the rejection of the invalid members of the hypothesis cluster an ellipsoid is fitted to the new cluster centre and the results are drawn on the data. The method is fast and robust. The method was tested using five different data sets and it performed equally well.

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