Abstract
This paper proposes a method to search for a probable tumor in magnetic resonance (MR) images of a human brain. Typically, a tumor can be found in some contiguous images of the MR sequence and positions of its appearance in such contiguous images usually have similar centroid thus their corresponding projections should be able to be detected automatically in order to support a user or a doctor for further diagnosis. Once region of a probable tumor is detected, matched checking between a pair of contiguous MR images can be done and relabeled to indicate the same area of the tumor amongst sequential images. Any regions without match between contiguous images are initially considered as irrelevant components and will not be analyzed further unless the doctor indicates otherwise. Then, ratio of tumor to brain is calculated to support as an initial diagnosis of tumors appeared in an MR image sequence .
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Acknowledgements
We would like to thank you Maharaj Nakorn Chiang Mai Hospital, Faculty of Medicine, Chiang Mai University, Thailand for example MR image sequences for this research.
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Chaisuparpsirikun, T., Chouvatut, V. (2018). Detection of Brain Tumor from MR Image Sequence Using Image Segmentation and Blob’s Centroid. In: Yang, XS., Nagar, A., Joshi, A. (eds) Smart Trends in Systems, Security and Sustainability. Lecture Notes in Networks and Systems, vol 18. Springer, Singapore. https://doi.org/10.1007/978-981-10-6916-1_11
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DOI: https://doi.org/10.1007/978-981-10-6916-1_11
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