Brain Tumor Detection Using MobileNet model.

Prashanth G , Jyothishree K , Vyshnavi B K , Rohit kumar jha D , Vijayalaxmi R patil

MRI - Magnetic resonance imaging

Brain tumor detection is crucial for early diagnosis and effective treatment planning. Pre trained deep learning models have shown promising performance in automating the detection process from MRI images. In this research work, a brain tumor detection system is developed to detect whether input brain MRI image has tumor or not. The system uses pre trained MobileNet model for binary classification of brain MRI images and a user interface is designed to upload the brain MRI image for tumor detection. The methodology involves acquiring a dataset of brain MRI images, preprocessing the data, training pre-trained MobileNet model, testing and evaluation of Model. The system performance is evaluated by means of MobileNet model performance metrics such as accuracy, precision, recall and F1-score. The results demonstrate that proposed MobileNet- based brain tumor detection system achieves a high accuracy of 95.25 % in detecting brain tumors. This work contributes to the field of medical image analysis by providing an efficient and accurate approach for brain tumor detection, with potential applications in clinical practice and remote healthcare settings.

Published Paper   E-Certificate

"Brain Tumor Detection Using MobileNet model.", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.8, Issue 7, page no.368 - 372, July-2023, Available :https://ijsdr.org/papers/IJSDR2307049.pdf

Volume 8 Issue 7, July-2023

Pages : 368 - 372

Paper Reg. ID: IJSDR_207651

Published Paper Id: IJSDR2307049

Downloads: 000347265

Research Area: Computer Science & Technology 

Country: bangalore, karnataka, India

Published Paper PDF: https://ijsdr.org/papers/IJSDR2307049

Published Paper URL: https://ijsdr.org/viewpaperforall?paper=IJSDR2307049

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

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition