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Detection of brain tumors from MR images using fuzzy thresholding and texture feature descriptor

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Abstract

Efficient detection and classification of brain tumors using magnetic resonance images provide significant support to the neurologists. However, many approaches developed for this purpose exhibit limited accuracy due to irregular boundary pixels and intensity non-uniformity in MR images. Therefore, to minimize these issues and attain better performance, a new methodology is proposed based on the fuzzy thresholding and local texture feature descriptor. The proposed model includes four fundamental steps: noise reduction, tumor extraction, feature extraction, and classification. Anisotropic diffusion filtering is implemented to reduce the noise without losing information that is essential in the interpretation of the brain tumor images. Then, spatial fuzzy C-means thresholding and morphological operations-based image segmentation are applied to extract the tumor area of the brain. In the very next step, obtains texture features using a complete local binary pattern - based feature descriptor. These features capture inherent information from brain MR images. In the later stage, these features are concatenated using a serial-based fusion approach before classification using supervised learning approaches (decision tree, naive bayes, random forest, and LogitBoost). The above investigations are evaluated with simulations on harvard medical school and Kaggle repository data sets. The experimental outcomes support the significance of the proposed methodology which exhibited better performance compared to the state-of-the-art methods.

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No funding agencies for this research work. This work was carried out in the part of doctorate degree.

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  1. School of Electronics Engineering (SENSE), VIT-AP University, Amaravati, Andhra Pradesh, 522237, India

    K. Rasool Reddy & Ravindra Dhuli

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  1. K. Rasool Reddy
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K.R.R. contributed to conceptualization, methodology, software, formal analysis, investigation, validation, resources, and writing—original draft. R.D. contributed to supervision, review, and editing.

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Correspondence to Ravindra Dhuli.

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Reddy, K.R., Dhuli, R. Detection of brain tumors from MR images using fuzzy thresholding and texture feature descriptor. J Supercomput 79, 9288–9319 (2023). https://doi.org/10.1007/s11227-022-05033-x

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