Detection of location-specific intra-cranial brain tumors

Shola Usharani, Rama Parvathy Lakshmanan, Gayathri Rajakumaran, Aritra Basu, Anjana Devi Nandam, Sivakumar Depuru

Abstract


Mutations or abnormalities in genes can occasionally cause cells to grow uncontrolled, resulting in a tumor, which is very dangerous. These are the most prevalent cancer causes. They are caused by significant damage to genes in a specific cell during a person's existence. Brain tumors are increasing rapidly, majorly brain tumor cases in the US are projected to rise from 27,000 in 2020 to 31,000 in 2023 at an annual growth rate of 1.5%, all the cases are rising because of the detection of the tumors in the late phase. Thus, it needs the hour to create something which can solve this anomaly and help us detect the tumor rapidly and efficiently. While major research papers on brain tumor detection mainly focus on the detection and classification of the tumors, the presented research aims to first detect the tumor using pre-recognized photos using machine learning object detection models. Then after successful detection of the tumor, the study team plans to determine its precise coordinates and display the tumor and its location in the picture.


Keywords


Brain tumor; Convolutional neural network; EfficientNet; Genes; Machine learning models; MobileNet v2

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DOI: http://doi.org/10.11591/ijai.v14.i1.pp428-438

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IAES International Journal of Artificial Intelligence (IJ-AI)
ISSN/e-ISSN 2089-4872/2252-8938 
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

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