Contour - Marker Based Segmentation For Tumorous And Non-Tumorous Brain Mri Detection

Brain Tumor is a serious concern and can be a cause of death if not diagnosed properly. The fatal rate can be avoided by early detection and treatment. Computer vision technique helps to analyze brain tumors automatically and effectively. In this paper, we propose a marker-based image segmentation t...

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Published in2021 10th International Conference on Internet of Everything, Microwave Engineering, Communication and Networks (IEMECON) pp. 01 - 06
Main Authors Chowdhury, Debkumar, Mishra, Sanjukta, Mondal, Sayantika, Singh, Anjali, Guha, Koustav, Aziz, Md. Tarik, Sen, Rahul, Chowdhury, Subhankar Bhanja, Porey, Sayan, Sau, Kartik
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2021
Subjects
Brain modeling
Brain Tumor
Computational modeling
Computer vision
Filtering
Image segmentation
Magnetic resonance imaging
marker-based image segmentation
Prediction algorithms
Predictive models
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DOI10.1109/IEMECON53809.2021.9689131

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Summary:Brain Tumor is a serious concern and can be a cause of death if not diagnosed properly. The fatal rate can be avoided by early detection and treatment. Computer vision technique helps to analyze brain tumors automatically and effectively. In this paper, we propose a marker-based image segmentation technique to find the presence or absence of tumors in brain MRI images. We use a standard dataset to build the model. The model is based on the comparisons among different filtering, thresholding, and segmentation techniques to find out the best method which predicts the result with great accuracy. We evaluate the filtering methods using PSNR, SNR, MSE, RMSE Values. Finally, a marker-based algorithm has been used for detection. The Experimental result shows that our attempts are promising, and the model performs well in detecting the abnormal image.
DOI:10.1109/IEMECON53809.2021.9689131