MRI Brain Tumor Detection with Computer Vision

• URL: http://arxiv.org/abs/2510.10250v1
• Date: Sat, 11 Oct 2025 15:07:52 GMT
• Title: MRI Brain Tumor Detection with Computer Vision
• Authors: Jack Krolik, Jake Lynn, John Henry Rudden, Dmytro Vremenko,
• Abstract summary: This study explores the application of deep learning techniques in the automated detection and segmentation of brain tumors from MRI scans.<n>We employ several machine learning models, including basic logistic regression, Convolutional Neural Networks (CNNs), and Residual Networks (ResNet) to classify brain tumors effectively.
• Score: 0.0
• License: http://creativecommons.org/publicdomain/zero/1.0/
• Abstract: This study explores the application of deep learning techniques in the automated detection and segmentation of brain tumors from MRI scans. We employ several machine learning models, including basic logistic regression, Convolutional Neural Networks (CNNs), and Residual Networks (ResNet) to classify brain tumors effectively. Additionally, we investigate the use of U-Net for semantic segmentation and EfficientDet for anchor-based object detection to enhance the localization and identification of tumors. Our results demonstrate promising improvements in the accuracy and efficiency of brain tumor diagnostics, underscoring the potential of deep learning in medical imaging and its significance in improving clinical outcomes.

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