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dc.contributor.author Gayanga, TDL
dc.contributor.author Pathirana, GPSN
dc.contributor.author Sandanayake, TC
dc.contributor.editor Sudantha, BH
dc.date.accessioned 2022-11-18T06:51:18Z
dc.date.available 2022-11-18T06:51:18Z
dc.date.issued 2019-12
dc.identifier.citation T. D. L. Gayanga, G. P. S. N. Pathirana and T. C. Sandanayake, "Detecting and Capturing the Intensity of a Brain Tumor using MRI Images," 2019 4th International Conference on Information Technology Research (ICITR), 2019, pp. 1-6, doi: 10.1109/ICITR49409.2019.9407795. en_US
dc.identifier.uri http://dl.lib.uom.lk/handle/123/19566
dc.description.abstract Mutated cells in the brain are known as tumors. There are two types of tumors present in the brain, and they are malignant and benign tumors. Benign tumors are non-cancerous tumors which reside inside a person's brain having a primitive shape and size. Malignant tumors are cancerous brain tumors which spread by transforming the cells into the cell type next to the malignant tumor and have no clearly defined edge or shape(cloudy). Treatment planning and detection is the most efficient way of treating a patient and improving the condition. Magnetic Resonance Imaging (MRI) is the established method to detect the tumors. After the detection classification of the tumor manually takes reasonable time and sometimes it is impossible to detect the type with the naked eye. This results in having to conduct a biopsy which is a risk as well as sometimes impossible. One of the main factors to be considered in segmenting the tumor is the edge intensity of the tumor. For detecting the intensity of the tumor edge a novel completely automatic and reliable detection based on CNN is proposed. Pre-processing and running the improved images through CNN to get the best possible features to be extracted from the MRI images. Canny edge detection and Wavelet transform are applied to detect the edge and finally, Hough transform is used to detect the intensity of the edge. Edge detection method that proposed in this paper will have a wide verity of surgical applications. en_US
dc.publisher Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa, Sri Lanka en_US
dc.relation.uri https://ieeexplore.ieee.org/document/9407795 en_US
dc.subject BenignTumors en_US
dc.subject Malignant Tumors en_US
dc.subject Magnetic Resonance Imaging en_US
dc.subject Convolutional Neural Networks en_US
dc.title Detecting and capturing the intensity of a brain tumor using mri images en_US
dc.type Conference-Full-text en_US
dc.identifier.faculty IT en_US
dc.identifier.department Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa. en_US
dc.identifier.conference 4th International Conference in Information Technology Research 2019 en_US
dc.identifier.place Colombo,Sri Lanka en_US
dc.identifier.proceeding Proceedings of the 4th International Conference in Information Technology Research 2019 en_US
dc.identifier.doi doi: 10.1109/ICITR49409.2019.9407795 en_US


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  • ICITR - 2019 [19]
    International Conference on Information Technology Research (ICITR)

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