Abstract
Analysis of brain MRI is of utmost importance as it reveals the underlying details of the main controlling portion of human body. In this paper, we have proposed a fully automated approach to differentiate abnormal brain images from healthy MRI. The proposed method segments out the tumor region from the abnormal MRI by analyzing the energy profile of the image pixels. After tumor segmentation, the tumor features are analyzed to classify the degree of malignancy. This approach can be applied to segment both high grade and low grade tumors.
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Acknowledgement
Authors would like to acknowledge Department of Science & Technology, Government of India, for financial support vide ref. no. SR/WOS-A/ET-1022/2014 under Woman Scientist Scheme to carry out this work.
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Mukherjee, S., Bandyopadhyay, O., Biswas, A. (2017). Automated Brain Tumor Diagnosis and Severity Analysis from Brain MRI. In: Barneva, R., Brimkov, V., Tavares, J. (eds) Computational Modeling of Objects Presented in Images. Fundamentals, Methods, and Applications. CompIMAGE 2016. Lecture Notes in Computer Science(), vol 10149. Springer, Cham. https://doi.org/10.1007/978-3-319-54609-4_14
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DOI: https://doi.org/10.1007/978-3-319-54609-4_14
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