Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
A tumor is a growth of cells in the organs or near it. Tumors can happen in the any tissue. Nearby locations include nerves, the pituitary gland, the pineal gland, and the membranes that cover the surface of the brain. Although MRI images are a popular imaging method for evaluating these tumors, the volume of data it generates makes it difficult to manually segment the images in a reasonable amount of time, which restricts the use of precise quantitative assessments in clinical settings. The enormous spatial and structural heterogeneity among tumors makes automatic segmentation a difficult task, hence dependable and automatic segmentation methods are needed. In our project we developed deep learning models based on convolutional neural network and Edge Detection algorithms to perform the automated semantic image segmentation of the MRI images of the tumor. We explored the current state of the CNNs architecture and evaluated them on the BraTS dataset. Different regularization methods and hyperparameters are tested and optimized through a series of experiments.
Keywords:
Tumor, MRI images, Edge Detection, Deep learning, CNN.
Cite Article:
"SEMANTIC SEGMENTATION BASED CNN FOR TUMOR DETECTION", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.8, Issue 6, page no.796 - 802, June-2023, Available :http://www.ijrti.org/papers/IJRTI2306121.pdf
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ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator