Extraction and Analysis o Hui-Fuang Dept. of C pang@asis.edu.tw Abstract—Structural characteristics of late brain medical images from CT scan can distinguishing between normal brain structu brain structure. This paper presents im algorithms for automatic segmentation and structural features of lateral ventricle in brain The effectiveness of such features on discrimination is also examined. Experimen that structural features of lateral ventricle images, including Frontal Horn Radius and V are useful for discriminating between norm brain structure. Keywords- brain medical image; feature ventricle, image processing I. INTRODUCTION In clinical medicine, doctors have long b way to extract and analyze expansion c ventricle in medical brain images in orde disease diagnosis, for instances, the diagnos hydrocephalus and brain atrophy [1]. E general, patients with brain disease posses physiological anomalies and less anatomical is believed that the structural character ventricle in brain medical images from tomography (CT) scan can be helpful fo between normal brain structure and abnorm such as obstructive hydrocephalus and brain 1 shows the schematic diagrams of imp features of lateral ventricle, including Ventri Ventricular Angle (VA), and Frontal Horn Other features, such as the expansion char third ventricle, temporal horn, or sulci mig for the task [2]. However, for a radiologist, to manua measure such features accurately on CT sca difficult and time consuming. Image proce have been successfully used in medical im Therefore, the main objectives of this study image processing algorithms for automatic s measurement of structural features of lat brain medical images, and to examine th properties of such features for distinguishing and abnormal brain structure. of Structural Features of Lateral Ventr Medical Images g Ng, Cheng-Hung Chuang, Chih-Hsueh Hsu Computer Science and Information Engineering Asia University Taichung, Taiwan w, chchuang@asia.edu.tw, sunny.boy1030@gmail.com eral ventricle in n be helpful for ure and abnormal mage processing measurement of n medical images. brain structure ntal results show in brain medical Ventricular Index, mal and abnormal extraction; lateral been looking for a characteristics of er to assist brain sis of obstructive Even though in ss more apparent l abnormalities, it ristics of lateral m computerized or distinguishing mal brain structure n atrophy [2]. Fig. portant structural icular Index (VI), n Radius (FHR). racteristics of the ght also be useful lly segment and an images is both essing techniques mage analysis [3]. y were to develop segmentation and teral ventricle in he discriminative g between normal (a) Original brain CT sc (b) Ventricular Index (VI) (c) Figure 1. Structural features of lateral ven The rest of the paper is organiz presents the algorithm and proced measuring structural features of l medical images. Section 3 contains concluding remarks are given in sec II. METHO The algorithm for segmenting a features of lateral ventricle consist First, a segmentation procedure is u ventricle region from the brain im ricle in Brain can image Ventricular Angle (VA) and Frontal Horn Radius (FHR) ntricle in brain medical image. zed as follows. Section 2 dure for segmenting and ateral ventricle in brain experimental results, and tion 4. ODS and measuring structural s of the following steps. used to extract the lateral mage. Next, each of the 2012 Sixth International Conference on Genetic and Evolutionary Computing 978-0-7695-4763-3/12 $26.00 © 2012 IEEE DOI 10.1109/ICGEC.2012.93 35 2012 Sixth International Conference on Genetic and Evolutionary Computing 978-0-7695-4763-3/12 $26.00 © 2012 IEEE DOI 10.1109/ICGEC.2012.93 35 2012 Sixth International Conference on Genetic and Evolutionary Computing 978-0-7695-4763-3/12 $26.00 © 2012 IEEE DOI 10.1109/ICGEC.2012.93 35 2012 Sixth International Conference on Genetic and Evolutionary Computing 978-0-7695-4763-3/12 $26.00 © 2012 IEEE DOI 10.1109/ICGEC.2012.93 35