Brain tumor's approximate correspondence and area with interior holes filled

• Main Authors: Varin Chouvatut, Ekkarat Boonchieng
• 格式: Conference Proceeding
• 出版: 2018
• 主題: Computer Science; Agricultural and Biological Sciences
• 在線閱讀: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85031743208&origin=inward; http://cmuir.cmu.ac.th/jspui/handle/6653943832/43649
• 機構: Chiang Mai University

© 2017 IEEE. Measuring area of tumor in human's brain from only single image may provide incorrect information for further diagnosis. Generally, a doctor or an expert must examine a brain tumor from several sequential MRI images to conclude its size or the severity level of patient's illness. To imitate the way a doctor diagnosing such case in a real situation, some digital image processing techniques are proposed and applied in order to provide support for a tentative or an initial analysis to the doctor. Thus, correspondence of appearances of a tumor presented in all MRI images should be linked and considered. In image processing, a closed area can be seen as an object and based on the similarity of its interior shadings, the object's centroid can be estimated. Unfortunately, although an object's centroid may be calculated even there exists slightly different shadings which are still considered as having similarity inside the closed shape of the object, only a small hole can cause deviation of computed centroid from its expected position. Since the typical thresholding techniques still leave a hole whose area has a certain amount of different shading from the major shading of the object's area. Thus, we proposed a number of image processing techniques for the purpose of tumor area approximation. Moreover, the proposed methods include a correspondence technique would also support multiple-object detection and linking centroids of the same object, which is a brain tumor in this case, presented in a pair of contiguous images.