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Research Paper #620

Title:Locating the Eyes in Ct Brain Scan Data
Authors:Kaggelides,K; Elliot,P; Fisher,RB
Date:Apr 1993
Presented:In proceedings of 6th Int. Conf. on Industrial Engineering and Applications of Artificial Intelligence and Expert Systems, Edinburgh, 93
Keywords:
Abstract:We describe a technique for locating the eyes in Computed Tomography brain scan data. 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 the Canny edge detector to these areas, data is further reduced to the significant edge fragments. The Hough Transform is then applied to estimate radii and centres of the CT sections through the eyes. The Converging Squares algorithm is used as an efficient and robust method to search the Hough Transform is then applied to estimate radii an centres of the CT sections through the eyes. The Converging Squares algorithm is used as an efficient and robust method to search the Hough Transform parameter space. The results are processed by the hypothesis generation stage which clusters them according to the x, y, z coordinates of the suggested centres. The ISODATA algorithm is used for clustering. The hypotheses are assessed and sorted and the most valid hypothesis is selected and refined using a second Hough Transform. 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 well on all of them.
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