Improved Methods for Brain Tumor Detection and Analysis Using MR Brain Images
Abd El Kader Isselmou1*
, Guizhi Xu2 and Shuai Zhang3
1Department of Biomedical Engineering, Hebei University of Technology, Tianjin City, China, 30030
2Dean of School of Electrical Engineering, Hebei University of Technology, Tianjin City, China, 30030
3Vice Dean of School of Electrical Engineering, Hebei University of Technology, Tianjin City, China,30030
Corresponding Author E-mail: Isselmou_kader@yahoo.com
Abstract: Medical image processing techniques play an important role in helping doctors and facilities for patient diagnosis, the aim of this paper is comparison between three improved methods to identify the brain tumor using magnetic resonance brain images and analysis of the performance of each method according to different values, accuracy, nJaccard coeff, ndice, sensitivity, specificity, recall and precision values,We used three improved methods the first method improved fuzzy c-means algorithm (IFCM), the second method is improved feed-forward neural network (IFFNN), and the third method is a hybrid self-organizing map with a fuzzy k-means algorithm,the significance of these methods is complementary among them where each one has an advantage in a certain value as shown in the paper results, the three methods gave a very good performance, generally they can identify the tumor area clearly in MR brain image with different performance of the values, each method gave better values than others according to a comparison between the performance value of three methods,Finally, the improved methods allow the development of algorithms to diagnose a tumor more accurately and for a short period of time and each method is distinguished from each other in the performance and value, this gives integrity and strength to this work, these methods can be used in pre and post radio surgical applications
Keywords: IFCM; IFFNN; ISOM-FKM algorithm; MRI; Tumor identification Back to TOC