Detection of Brain Tumor from MR Images Based on Co-occurrence Matrix : Collabration Work between Ministry Of Education, Baghdad University and Al-Nahrain University. Baghdad Iraq. 2019

ISBN-13: 9786200287847 / Angielski

Kawther Ali Khalaph; Alyaa Hussein Ali; Ihssan S. Nema

Opis

The Automatic analysis of Medical images using computer analysis diagnosis is one of the most interesting field in biomedical image processing. The proposed system gives techniques related to MRI analysis. A statistical structure analysis based on tumor segmentation scheme is presented, which focuses on the structural analysis in both normal and abnormal tissues,will help doctors to avoid the human error in manual interpretation of medical content. In this study, an enhanced thresholding algorithm is applied to extract the abnormal part from the 2D MRI. Samples of different ages and cases are taken from the AL-Imammain Al-Kadhimain Medical city and the Radiology Institute.Calculating the area of the abnormal tissue (tumor), the Wavelet transformation is then applied which is a signal estimation technique that exploits the capabilities to denoising the signal. A statistical feature has been obtained; then a hybrid method is applied in which k-mean clustering is a method of cluster analysis which aims to partitioned the images into clusters. Finally,an algorithm has been created to colored images depending on the boundary. This helps to separate the abnormal part into k clusters.

O autorze

Khalaph, Kawther AliKawther Ali Khalaph: Assistant Lecturer, Msc. Physics, Ministry of Education. Alyaa Hussein Ali:Assistant Professor, College Of Science For Women, Baghdad University. Ihssan S. Nema: Professor and Consultant Neurosurgeon, Al-Immamain Alkadhimain Medical City, Head of Department of Surgery, College of Medicine, Al-Nahrain University, Baghdad, Iraq.