Abstract
In this paper, we present the pre-processing approaches for MRI brain scans. The magnetic bias field correction of MR images is a preliminary step and the subsequent pre-processing step of intensity normalization of MR images. Both of these pre-processing steps facilitate as promising inputs to the segmentation models, and the promising outputs from these segmentation models aid for better diagnosis and prognosis of diseases. The BRATS 2015 dataset is used in the experimental work; the intensity normalization techniques applied to this dataset yield good results in segmenting the gliomas, thus enhancing the further image analysis pertaining to gliomas.
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Poornachandra, S., Naveena, C., Aradhya, M. (2018). Intensity Normalization—A Critical Pre-processing Step for Efficient Brain Tumor Segmentation in MR Images. In: Bhateja, V., Nguyen, B., Nguyen, N., Satapathy, S., Le, DN. (eds) Information Systems Design and Intelligent Applications. Advances in Intelligent Systems and Computing, vol 672. Springer, Singapore. https://doi.org/10.1007/978-981-10-7512-4_87
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DOI: https://doi.org/10.1007/978-981-10-7512-4_87
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