UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
Call for Paper
Volume 11 | Issue 10 | October 2024

JETIREXPLORE- Search Thousands of research papers



WhatsApp Contact
Click Here

Published in:

Volume 10 Issue 8
August-2023
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

7.95 impact factor calculated by Google scholar

Unique Identifier

Published Paper ID:
JETIR2308325


Registration ID:
523203

Page Number

d180-d195

Share This Article


Jetir RMS

Title

Brain Tumor Detection Using Artificial Neural Network

Abstract

Brain tumors are abnormal growths or masses of brain cells that can develop from brain tissue or spread to other parts of the body. Diagnosis of brain tumors involves medical history evaluation, physical examination, imaging tests, and biopsy. In this study, an artificial neural network (ANN) model specifically Convolutional Neural Network (CNN) model was developed for brain tumor detection. The model was trained using a dataset of brain tumor images and evaluated using various performance metrics and has achieved high accuracy, precision, recall, and F1-score. The image preprocessing was done using TensorFlow (keras) to resize, augment the data and normalize it before feeding to the model. The feature extraction was performed using ReLU and then the extracted features were fed into the CNN model developed to detect whether there is tumor or not. The model successfully classifies both positive and negative cases, with detection accuracy of 0.9849, precision of 0.9846, recall data of 0.9828, and an F1-score of 0.9837. The confusion matrix analysis confirmed the model's performance, revealing low false positives and false negatives. These findings suggest that the CNN model holds promise as a valuable tool for assisting medical professionals in early detection of brain tumors.

Key Words

Brain tumor, accuracy, precision, recall, F1 score and MRI

Cite This Article

"Brain Tumor Detection Using Artificial Neural Network", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 8, page no.d180-d195, August-2023, Available :http://www.jetir.org/papers/JETIR2308325.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Brain Tumor Detection Using Artificial Neural Network", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 8, page no. ppd180-d195, August-2023, Available at : http://www.jetir.org/papers/JETIR2308325.pdf

Publication Details

Published Paper ID: JETIR2308325
Registration ID: 523203
Published In: Volume 10 | Issue 8 | Year August-2023
DOI (Digital Object Identifier):
Page No: d180-d195
Country: Gombe, Gombe, Nigeria .
Area: Science & Technology
ISSN Number: 2349-5162
Publisher: IJ Publication


Preview This Article


Downlaod

Click here for Article Preview

Download PDF

Downloads

00081

Print This Page

Current Call For Paper

Jetir RMS