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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 10
Issue Published : 115
Article Submitted : 19456
Article Published : 8041
Total Authors : 21252
Total Reviewer : 769
Total Countries : 144
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| Paper Title: | Using CNN to Detect and Categorize Brain Tumors |
| Authors Name: | E.Chandraditya , K. Rahul Reddy , K. Rishik |
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IJRTI_189916
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| Published Paper Id: | IJRTI2405069 |
| Published In: | Volume 9 Issue 5, May-2024 |
| DOI: | |
| Abstract: | Accurately estimating a tumor's extent is a critical and challenging challenge in the context of brain tumor planning and quantitative assessment. Because magnetic resonance imaging (MRI) is non-invasive and does not involve ionizing radiation, it has become the main diagnostic method for brain malignancies. Gliomas are a particularly aggressive type of brain tumor that often only results in a few months to life expectancy when it reaches an advanced stage. In clinical settings, manual segmentation—the process of delineating tumor boundaries on MRI scans—is a tedious procedure that greatly depends on the expertise and skill of the operator. To address these challenges, our paper aims to develop an automated system leveraging Convolutional Neural Networks (CNNs) for the detection and classification of brain tumors using MRI scan images as input. This system seeks to identify and categorize tumors into specific types such as Glioma, Pituitary tumor, Meningioma, or determine the absence of a tumor altogether. By harnessing the power of CNN architectures, which excel at learning spatial features and patterns in images, we aim to streamline the tumor detection process, reduce human error, and improve diagnostic accuracy in clinical practice. |
| Keywords: | Convolutional Neural Networks (CNNs), Deep Learning, classifiers, Neural Network, layers, chatbot, flask web application, Image Classification, Watershed Algorithm, segmentation, Magnetic Resonance Imaging(MRI). |
| Cite Article: | "Using CNN to Detect and Categorize Brain Tumors ", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.9, Issue 5, page no.465 - 472, May-2024, Available :http://www.ijrti.org/papers/IJRTI2405069.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 |
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Published Paper ID: IJRTI2405069
Registration ID:189916
Published In: Volume 9 Issue 5, May-2024
DOI (Digital Object Identifier):
Page No: 465 - 472 Country: Hyderabad, Telangana, India Research Area: Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2405069 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2405069 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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