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Performance Evaluation of Hardhat Image Classification Using Deep Learning and Grad-CAM2023 6th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)10.1109/ISRITI60336.2023.10467745
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Dual-path parallel hierarchical diagnostic model of glioma based on pathomorphological featureBiomedical Signal Processing and Control10.1016/j.bspc.2023.105559

Study on Brain Tumor Classification Through MRI Images Using a Deep Convolutional Neural Network

Kirti Sharma, Ketna Khanna, Sapna Gambhir, Mohit Gambhir

Source Title: International Journal of Information Retrieval Research (IJIRR)12(1)

ISSN: 2155-6377|EISSN: 2155-6385|EISBN13: 9781683182085|DOI: 10.4018/IJIRR.289610

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MLA

Sharma, Kirti, et al. "Study on Brain Tumor Classification Through MRI Images Using a Deep Convolutional Neural Network." IJIRR vol.12, no.1 2022: pp.1-19. http://doi.org/10.4018/IJIRR.289610

APA

Sharma, K., Khanna, K., Gambhir, S., & Gambhir, M. (2022). Study on Brain Tumor Classification Through MRI Images Using a Deep Convolutional Neural Network. International Journal of Information Retrieval Research (IJIRR), 12(1), 1-19. http://doi.org/10.4018/IJIRR.289610

Chicago

Sharma, Kirti, et al. "Study on Brain Tumor Classification Through MRI Images Using a Deep Convolutional Neural Network," International Journal of Information Retrieval Research (IJIRR) 12, no.1: 1-19. http://doi.org/10.4018/IJIRR.289610

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Abstract

Brain tumor (Glioma) is one of the deadliest diseases that attack humans, now even men or women aged 20-30 are suffering from this disease. To cure tumor in a person, doctors use MRI machine, because the results of MRI images are proven to provide better image results than CT-Scan images, but sometimes it is difficult to distinguish between the MRI images having tumors with that images not having tumor from MRI image results. It is because of resulting contrast is like any other normal organ. However, using features of image processing techniques like scaling, contrast enhancement and thresh-holding based in Deep Neural Networks the scheme can classify the results more appropriately and with high accuracy. In this paper, this study reveals the nitty-gritty of Brain tumor (Gliomas) and Deep Learning techniques for better inception in the field of computer-vision.