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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (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) |
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Volume 9 | Issue 5
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| Paper Title: | Neurosentinel Prodigy |
| Authors Name: | Shaad Shaikh , Vansh Shah , Deven Randive , Saniket Kudoo |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_216777
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| Published Paper Id: | IJNRD2403622 |
| Published In: | Volume 9 Issue 3, March-2024 |
| DOI: | |
| Abstract: | Brain tumor detection is a crucial task in the realm of medical diagnostics, bearing significant implications for patient care and outcomes. This research paper embarks on a comprehensive exploration of the development and deployment of an advanced brain tumor detection system. The methodological framework is multifaceted, commencing with the assembly of a diverse and extensive dataset of brain imaging scans. Subsequently, the data undergoes rigorous preprocessing, including noise reduction and image enhancement, to optimize the quality and fidelity of the scans. The heart of the system lies in the utilization of deep learning, particularly a convolutional neural network (CNN), which leverages the robust features extracted from the preprocessed data to distinguish between brain scans indicative of tumors and those that are not. Model training is augmented by the introduction of a validation set, allowing for finetuning to achieve optimal performance. Testing the trained model on an entirely separate and previously unseen dataset substantiates its real-world utility, providing critical insights into its robustness and accuracy. The practical implementation of the system involves seamless integration into a real-time processing platform, enabling rapid analysis of incoming brain imaging data. This operational phase includes the establishment of predefined thresholds, effectively reducing false alarms and ensuring that only the most probable cases are flagged for review by medical professionals. |
| Keywords: | Brain Tumor, CNN, VGG16, Medical. |
| Cite Article: | "Neurosentinel Prodigy", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 3, page no.g188-g199, March-2024, Available :http://www.ijnrd.org/papers/IJNRD2403622.pdf |
| Downloads: | 00066 |
| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 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:IJNRD2403622 Registration ID: 216777 Published In: Volume 9 Issue 3, March-2024 DOI (Digital Object Identifier): Page No: g188-g199 Country: Virar (East), Maharashtra, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2403622 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2403622 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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