Abstract
With an expansion in the demand for automated medical imaging, the field is getting importance, fast, reliable and efficient diagnosis which can provide insight to the picture image better than human eyes. Brain tumor is the second leading cause of cancer-related deaths in men age 20–40 and 5th leading cause cancer among women in the same group. A diagnosis of tumor is a very important part in its treatment. Identification of a tumor is very important part in its treatment. To obtain the background, this paper covers noise elimination and image sharpening and also morphological functions, erosion and dilation. Plotting contour and c-label of the tumor and its boundary provides us identifying the size, shape and position of the tumor, it helps the medical employee as well as the patient to understand the seriousness of the tumor with the help of different labeling for different levels of elevation.
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Acknowledgements
We would like to thank the GIET University and MRIET College for the immense support for our research work to implement.
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Mekala, B., Kiran Kumar Reddy, P. (2023). Detecting Brain Tumors in Medical Image Technology Using Machine Learning. In: Kumar, R., Pattnaik, P.K., R. S. Tavares, J.M. (eds) Next Generation of Internet of Things. Lecture Notes in Networks and Systems, vol 445. Springer, Singapore. https://doi.org/10.1007/978-981-19-1412-6_56
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DOI: https://doi.org/10.1007/978-981-19-1412-6_56
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