Litcius/Paper detail

Classification of Brain Tumor Area for MRI images

Ameer Hussian Morad, Hadeel Moutaz Al-Dabbas

2020Journal of Physics Conference Series14 citationsDOIOpen Access PDF

Abstract

The technical merit of the proposed method is using multiple techniques that fused in each processing part of filtering, segmentation, and features. The originality is to select the best technique depending on some measurements for implementation. Aiming for better enhancement of selected MRI of AlKindy Hospital Patients, as case study, to get efficient diagnose process is the purpose of the current technique using MATLAB that include smoothing, segmentation, feature extraction and classification. The method uses two filters (Median and Slantlet) and two segmentation methods are used (K-mean cluster and Morphological operation) and the area size is used in feature extraction. The experimental results classification is indicating that 50% of the used images are medium cases of brain tumor and 10% low stage both can be treated, while 40% is of high cases of brain tumor reflected that the treatment is difficult.

Topics & Concepts

SegmentationArtificial intelligenceComputer scienceSmoothingPattern recognition (psychology)Stage (stratigraphy)Feature (linguistics)Feature extractionProcess (computing)Image segmentationComputer visionOperating systemBiologyPaleontologyLinguisticsPhilosophyBrain Tumor Detection and Classification