 |
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
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (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)
|
Issue: March 2026
Volume 11 | Issue 3
Review Result and Publication of Paper within : 2-3 days
Click Here For more DetailsFor Authors
Forms / Download
Published Issue Details
Editorial Board
Other IMP Links
Facts & Figure
Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 118
Article Submitted : 21508
Article Published : 8513
Total Authors : 22399
Total Reviewer : 805
Total Countries : 158
Indexing Partner
Licence
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
|
Published Paper Details
|
|
| Paper Title: | BRAIN TUMOR DETECTION IN MRI IMAGES USING DEEP LEARNING MODELS |
| Authors Name: | E.J SATVIK VARA SIDDHARDH , KRISHNA ANAND , V.AMIT RAJ , S.Koushik sai |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_186088
|
| Published Paper Id: | IJRTI2304132 |
| Published In: | Volume 8 Issue 4, April-2023 |
| DOI: | |
| Abstract: | This study focuses on the use of deep learning (DL) models to diagnose brain tumors through Magnetic Resonance Imaging (MRI) images. Brain tumors are caused by the growth of abnormal cells, and their survival rate is difficult to determine due to their various forms. Manual detection is time-consuming and prone to errors, making computer-assisted approaches crucial in overcoming these limitations. In this study, a deep convolutional neural network (CNN) EfficientNet-B0 base model is fine-tuned with proposed layers to efficiently classify and detect brain tumor images. The proposed model employs image enhancement techniques and data augmentation methods to improve the quality of images and increase data samples for better training. Results show that the fine-tuned EfficientNet-B0 outperforms other CNN models, achieving the highest accuracy, precision, recall, and area under curve values, with an overall accuracy of 98.87%. Comparative analysis is also conducted with other DL algorithms, such as VGG16 and InceptionResNetV2. |
| Keywords: | deep learning,medical resonance images,brain tumor,computer aided diagnostics |
| Cite Article: | "BRAIN TUMOR DETECTION IN MRI IMAGES USING DEEP LEARNING MODELS", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.8, Issue 4, page no.795 - 801, April-2023, Available :http://www.ijrti.org/papers/IJRTI2304132.pdf |
| Downloads: | 000205373 |
| 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 |
| Publication Details: |
Published Paper ID: IJRTI2304132
Registration ID:186088
Published In: Volume 8 Issue 4, April-2023
DOI (Digital Object Identifier):
Page No: 795 - 801 Country: HYDERABAD, TELANGANA, INDIA Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2304132 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2304132 |
| Share Article: | |
|
Click Here to Download This Article |
|
| Article Preview | |
|
|
|
Major Indexing from www.ijrti.org
| Google Scholar | ResearcherID Thomson Reuters | Mendeley : reference manager | Academia.edu |
| arXiv.org : cornell university library | Research Gate | CiteSeerX | DOAJ : Directory of Open Access Journals |
| DRJI | Index Copernicus International | Scribd | DocStoc |
ISSN Details
 |
 |
|
ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
DOI (A digital object identifier)
| Providing A digital object identifier by DOI.ONE How to Get DOI? |
Conference
Open Access License Policy
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Important Details
Join RMS/Earn 300
WhatsApp
Click Here
Click Here
Indexing Partner |
|||
| Copyright © 2026 - All Rights Reserved - IJRTI | |||