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

• Published in: Informatics in medicine unlocked Vol. 13; pp. 139 - 150
• Main Authors: Roy, Sudipta, Bhattacharyya, Debnath, Bandyopadhyay, Samir Kumar, Kim, Tai-Hoon
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 2018; Elsevier
• Subjects: Abnormality detection; Accuracy estimation; Brain tumor; Heterogeneity; Magnetic resonance imaging; Segmentation; Brain tumor; Heterogeneity; Accuracy estimation; Abnormality detection; Segmentation; Magnetic resonance imaging
• ISSN: 2352-9148; 2352-9148
• DOI: 10.1016/j.imu.2018.02.006

Accurate identification of brain tumor and its 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 its extent. This paper presents a computerized approach to brain tumor-edema detection and analysis from the MRI of brain sequences. 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 its location findings using statistical and unsupervised clustering prediction method. 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 context to accuracy and error metrics. 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.