Exploring Machine Learning Algorithms for Automated Segmentation of Brain Tumors from MRI Scans

Sridhar, Sushmitha Vurutur (2024) Exploring Machine Learning Algorithms for Automated Segmentation of Brain Tumors from MRI Scans. Masters thesis, Dublin, National College of Ireland.

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Abstract

The paper evaluates the potential of using pre-trained Convolutional Neural Network (CNN) models for the automatic segmentation of brain tumors from MRI scans. Traditional brain tumor segmentation techniques are time-consuming and highly variable, highlighting the need for faster and more accurate methods. This study explores the performance of three transfer-learning-based pre-trained CNN models: MobileNetV2, VGG16, and ResNet50. These models were trained and tested using augmentation techniques for increasing diversity on an MRI image dataset. ResNet50 achieved the highest test accuracy at 81.48%, followed by VGG16 at 77.78%, and then MobileNetV2 at 59.26%. The result of the current study proves that pre-trained models can feasibly be used for the segmentation of brain tumors but require further optimization in order to improve their accuracy and generalization. Given the diversity of the datasets and techniques in reducing overfitting, such models can potentially improve diagnoses in neuro-oncology. Commercialization by fully automated tools that seamlessly integrate into the routine clinical workflow is foreseeable, saving time for radiologists and improving patient outcomes.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Niculescu, Hamilton UNSPECIFIED
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning Q Science > Life sciences > Medical sciences Q Science > Life sciences > Medical sciences > Pathology > Tumors
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Ciara O'Brien
Date Deposited:	26 Aug 2025 11:18
Last Modified:	26 Aug 2025 11:18
URI:	https://norma.ncirl.ie/id/eprint/8637

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