An Intelligent Multi-Class Brain Tumor Classification System
S Jyothi
, Y Nithin Aditya , G Meghansh Rao , Radha Seelaboyina
CNN, Deep Learning, ResNet-50, OpenCV, TensorFlow.
The field of medicine is witnessing a transformative era driven by Artificial Intelligence (AI). Advancements in digital data acquisition, machine learning algorithms, and robust computing infrastructure have opened doors for AI applications in areas previously considered the exclusive domain of human experts. Brain tumors, characterized by abnormal tissue growth due to uncontrolled cellular proliferation, pose a significant health threat due to their potential malignancy. These tumors can infiltrate and consume healthy brain tissue, leading to life-threatening consequences. This project delves into the recent breakthroughs in AI technologies and their applications within the biomedical field. We identify challenges that need to be addressed for further progress in medical AI systems, and explore the economic, legal, and social ramifications of AI integration within healthcare. In response to this critical need, we propose a novel method for precise brain tumor detection and classification. Our project offers a user-friendly interface that facilitates tumor detection, classification, and severity visualization. This system leverages the power of Convolutional Neural Networks (CNNs) for robust tumor classification and incorporates cutting-edge machine learning algorithms for enhanced performance.
"An Intelligent Multi-Class Brain Tumor Classification System", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.10, Issue 1, page no.a494-a498, January-2025, Available :https://ijsdr.org/papers/IJSDR2501047.pdf
Volume 10
Issue 1,
January-2025
Pages : a494-a498
Paper Reg. ID: IJSDR_211096
Published Paper Id: IJSDR2501047
Downloads: 000347151
Research Area: Engineering
Country: Hyderabad, Telangana, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
