An Automated Approach of CT Scan Image Processing for Brain Tumor Identification and Evaluation

Abstract

Brain Tumor identification and evaluation requires Computed Tomography (CT) scan and image processing in medical diagnosis. The Manual methods for the detection of abnormal cell growths in brain tissue is both time consuming and non-reliable. This paper initiates with a discussion of a clinical diagnosis case of normal brain tissue and other with tumor affected images. The affected area is identified first with manual approach and further an automated approach is discussed using NI Lab VIEW software for locating the exact position and its evaluation. The described method provides a better way of diagnosing brain tumor in a quick and reliable automated manner. In the view of this, an automatic segmentation of brain MR images is needed to correctly segment White Matter (WM), Cerebrospinal fluid (CSF) and Gray Matter (GM) tissues of brain in a shorter span of time. The manual segmentation of brain tumor is abstruse job and may provide erroneous results.