Abstract
This paper developed a fully automatic method to locate the brain tumor from Magnetic resonance imaging (MRI) head scans using wavelet packet transformation (WPT) based feature set. WPT is used to extract high frequency data from all sub bands of MRI images. Modulus maximum is used to detect singularities among these high frequency features and thus isolates the hyper intense nature of tumors. These tumor areas are detected by preparing a mask of modulated images and then compared it with the original scans. This method does not require any preprocessing operations like seed selection, initialization and skull stripped scans of existing methods. Experiments were done with the sample images collected from popular hospitals and clinics. The results were visually inspected for the outputs. The quantitative validation was done with the Chi-square test. It performed significance study to identify the goodness of fit, the probability of fitness is above 0.75.
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Kalaiselvi, T., Selvi, K. (2013). An Automatic Method to Locate Tumor from MRI Brain Images Using Wavelet Packet Based Feature Set. In: Prasath, R., Kathirvalavakumar, T. (eds) Mining Intelligence and Knowledge Exploration. Lecture Notes in Computer Science(), vol 8284. Springer, Cham. https://doi.org/10.1007/978-3-319-03844-5_23
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DOI: https://doi.org/10.1007/978-3-319-03844-5_23
Publisher Name: Springer, Cham
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