dc.description.abstract |
This study aims to develop an efficient and accurate system for the early detection of brain tumors
using machine learning algorithms applied to magnetic resonance imaging (MRI) medical images.
Brain tumor occurs because of anomalous development of cells. It is one of the major causes of
death in adults around the globe. Millions of deaths can be prevented through early detection of
brain tumors. Earlier brain tumor detection using Magnetic Resonance Imaging (MRI) may
increase a patient's survival rate.machine learning) has gained prominence in almost every field
where decision-making is involved in recent years, spanning economics, health care, marketing,
and sales. In the field of healthcare, machine learning & deep learning have shown promising
results in a variety of fields, namely disease diagnosis with medical imaging, surgical robots, and
boosting hospital performance. One such application of deep learning to detect brain tumors from
MRI scan images. In MRI, tumor is shown more clearly that helps in the process of further
treatment. This work aims to detect tumors at an early phase. A comprehensive dataset of MRI
scans, encompassing both tumor and non-tumor cases, is utilized to train and validate the proposed
machine learning models. Preprocessing techniques, including image enhancement and
normalization, are applied to standardize the input data. Various machine learning algorithms, such
as convolutional neural networks (CNNs), MobileNet model with ImageNet weights from keras
and decision trees, are implemented and compared to identify the most effective approach for brain
tumor detection.In this research of brain tumor classification, using machine learning, and built a
binary classifier to detect brain tumors from MRI scan images. The classifier used transfer
learning and obtained an accuracy of 96.5% and visualized the model’s overall performance.The
presents a model which is based on machine learning algorithms to detect brain tumors from
magnetic resonance images with high accuracy. A Convolutional Neural Network (CNN) has been
used as the algorithm for feature extraction, and segmentation. The dataset used has been acquired
from kaggle. |
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