Heterogeneity of human brain tumor with lesion identification, localization, and analysis from MRI

Objective: Accurate identification of brain tumors and their heterogeneity is a critical task in planning for proper therapy. A reliable fully automatic detection and analysis method for the brain tumor is necessary for an efficient measurement of the tumors and their extent. This paper presents a computerized approach to brain tumor-edema detection and analysis from the MRI of brain sequences. Method: Computer-aided diagnosis systems are focused on several research activities, and the ideas of the study of brain images with the diverse modality of heterogeneity by applying better image analysis algorithms. The proposed automated modern approach includes several stages of image segmentation, area and volume calculation, and locational findings using statistical and an unsupervised clustering prediction method. Result: The outcome of the proposed computerized method is compared with reference images and gives very promising results. Performance of our proposed methodology is also assessed with the gold standard recent comparable method, and our method gives better results in the context of accuracy and error metrics. Conclusion: The proposed method is capable of improving the overall detection, segmentation, and quantification of a variety of tumors for different cases from multiple standard datasets. Keywords: Abnormality detection, Brain tumor, Segmentation, Heterogeneity, Magnetic resonance imaging, Accuracy estimation