Abstract
Recently, a large number of inspection methods are implemented to examine the brain MRI slices recorded using Flair/T2 modality. The Flair/T2 modality provides more visible brain abnormalities than other modalities. This work implemented a heuristic algorithm based examination procedure. In this, the Bat Algorithm (BA) is used to improve the visibility of the tumor-pixels using the Kapur’s Entropy (KE). The improved tumor section is then collected using the Watershed Segmentation Method (WSM). Later, a comparison linking the tumor portion and available Ground-Truth Image (GTI) is executed and the Quality Measures (QM) is computed individually for Flair and T2. During this investigation, the MRI slices with 240 × 240 × 1 pixel resolution are considered and this technique is implemented on 400 MRI slices (Flair = 200 + T2 = 200). The average result of QM confirmed that the BA-based technique helped to get superior result (Accuracy >95% for Flair/T2 modality slices). In future, this methodology can be implemented to analyze the MRI slices obtained from the hospitals.
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Sindhu, V., Singaravelan, M., Ramadevi, J., Vinitha, S., Hemapriyaa, S. (2021). Bat Algorithm Aided System to Extract Tumor in Flair/T2 Modality Brain MRI Slices. In: Dey, N., Rajinikanth, V. (eds) Applications of Bat Algorithm and its Variants. Springer Tracts in Nature-Inspired Computing. Springer, Singapore. https://doi.org/10.1007/978-981-15-5097-3_9
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