ISSN2320-2882
Impact Factor9.17
UGC ParametersAligned
Low Cost₹1501 / $59
CrossRefDOI
ESTD2013
Peer ReviewTransparent
AccessOpen
Submission: Always Open
Paper Title
Study on Brain Tumor Detection and classification Using Machine Learning with SIFT
Authors
Deepak Kumar , Dr Aakriti Jain , Dr Sitesh kumar Sinha
Keywords
Brain Tumor Detection, Machine Learning, SIFT, PCA, SVM, ANN, MRI Classification, Feature Extraction
Abstract
Timely and accurate diagnosis of brain tumors plays a crucial role in neurological treatment. MRI imaging is the most reliable means of identification, but manual interpretation can be time-consuming and expert-dependent, leading to errors. To address this issue, this research developed a hybrid, interpretable, and resource-efficient framework based on Scale-Invariant Feature Transform (SIFT)-based feature extraction, Principal Component Analysis (PCA)-based dimensionality reduction, and Support Vector Machine (SVM) and Artificial Neural Network (ANN)-based machine learning classification.
Experimental evaluation on the BraTS 2021 and Kaggle Brain MRI datasets showed that the proposed SIFT-PCA-ML model achieved 96-97% accuracy and 0.98-0.99 AUC, comparable to modern deep learning models, but with significantly lower computational complexity. Additionally, SIFT keypoint mapping and Grad-CAM heatmaps of the ANN clearly depicted tumor-related critical regions, enhancing the model's interpretability.
This study demonstrates that the combination of handcrafted features and machine learning, especially SIFT-PCA-ANN-based models, can provide an effective, reliable, and clinically applicable solution for brain tumor detection--especially in medical centers that lack high-end GPUs or big data resources.
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IJCRT — journal style
"Study on Brain Tumor Detection and classification Using Machine Learning with SIFT", IJCRT - International Journal of Creative Research Thoughts (www.ijcrt.org), ISSN:2320-2882, Vol.13, Issue 12, page no.b795-b798, December 2025, Available :https://ijcrt.org/papers/IJCRT2512217.pdf
APA — 7th edition
Kumar, D., Jain, A., & Sinha, S. K. (2025). Study on Brain Tumor Detection and classification Using Machine Learning with SIFT. International Journal of Creative Research Thoughts, 13(12), b795-b798. https://ijcrt.org/viewpaperforall.php?paper=IJCRT2512217
MLA — 9th edition
Kumar, Deepak, et al. "Study on Brain Tumor Detection and classification Using Machine Learning with SIFT." International Journal of Creative Research Thoughts, vol. 13, no. 12, 2025, pp. b795-b798, https://ijcrt.org/viewpaperforall.php?paper=IJCRT2512217.
Chicago — 17th, bibliography
Kumar, Deepak, Aakriti Jain, and Sitesh kumar Sinha. "Study on Brain Tumor Detection and classification Using Machine Learning with SIFT." International Journal of Creative Research Thoughts 13, no. 12 (2025): b795-b798. https://ijcrt.org/viewpaperforall.php?paper=IJCRT2512217.
Harvard — author–date
Kumar, D., Jain, A. and Sinha, S.K. (2025) 'Study on Brain Tumor Detection and classification Using Machine Learning with SIFT', International Journal of Creative Research Thoughts, 13(12), pp. b795-b798. Available at: https://ijcrt.org/viewpaperforall.php?paper=IJCRT2512217
IEEE — numbered reference
D. Kumar, A. Jain and S. K. Sinha, "Study on Brain Tumor Detection and classification Using Machine Learning with SIFT," IJCRT, vol. 13, no. 12, pp. b795-b798, Dec. 2025.
Vancouver — biomedical
Kumar D, Jain A, Sinha SK. Study on Brain Tumor Detection and classification Using Machine Learning with SIFT. IJCRT. 2025 Dec;13(12):b795-b798.
AMA — 11th edition
Kumar D, Jain A, Sinha SK. Study on Brain Tumor Detection and classification Using Machine Learning with SIFT. IJCRT. 2025;13(12):b795-b798. Accessed at https://ijcrt.org/viewpaperforall.php?paper=IJCRT2512217
BibTeX — Zotero, Mendeley, LaTeX
@article{IJCRT2512217,
author = {Deepak Kumar and Aakriti Jain and Sitesh kumar Sinha},
title = {Study on Brain Tumor Detection and classification Using Machine Learning with SIFT},
journal = {International Journal of Creative Research Thoughts},
volume = {13},
number = {12},
pages = {b795-b798},
year = {2025},
month = {December},
issn = {2320-2882},
url = {https://ijcrt.org/viewpaperforall.php?paper=IJCRT2512217}
}
RIS — EndNote, RefWorks
TY - JOUR
AU - Kumar, Deepak
AU - Jain, Aakriti
AU - Sinha, Sitesh kumar
TI - Study on Brain Tumor Detection and classification Using Machine Learning with SIFT
T2 - International Journal of Creative Research Thoughts
JA - IJCRT
VL - 13
IS - 12
PY - 2025
SN - 2320-2882
UR - https://ijcrt.org/viewpaperforall.php?paper=IJCRT2512217
SP - b795-b798
ER -
Issue
Volume 13 Issue 12,
December-2025
Pages : b795-b798
Article Information
- Published In
- International Journal of Creative Research Thoughts — Volume 13, Issue 12, December 2025
- Pages
- b795-b798
- Published
- December 2025
- Registration ID
- IJCRT_298039
- Published Paper ID
- IJCRT2512217
- Research Area
- Science and Technology
- Author Type
- Indian Author
- Location
- bhopal, Madhya Pradesh, India
- Peer Review
- Request Peer Review Report
- Licence
- CC BY 4.0 · Open Access
- ISSN & Impact Factor
- 2320-2882 · IF 9.17
- Downloads
- 219
- Permanent Link
- https://ijcrt.org/viewpaperforall.php?paper=IJCRT2512217
- Published Paper PDF
- https://ijcrt.org/papers/IJCRT2512217.pdf
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International Journal of Creative Research Thoughts
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The authors would like to thank the reviewers and the editorial board of International Journal of Creative Research Thoughts for their careful reading and constructive comments, and all colleagues who supported the preparation of this manuscript.
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