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Projects/AI & ML/Deep Learning Brain Tumor MRI Segmentation using U-Net
Artificial Intelligence & Machine LearningMajor Final Year Project

Deep Learning Brain Tumor MRI Segmentation using U-Net

Deep Learning Brain Tumor MRI Segmentation using U-Net

Project Overview & Abstract

Medical AI project utilizing a custom U-Net architecture implemented in PyTorch. Achieves a 92.8% Dice Similarity Coefficient across BraTS multimodal MRI datasets. Highlights necrotic, enhancing, and edema tissue contours with an interactive slice-by-slice diagnostic viewer.

Technologies & Tools Used

PythonPyTorchU-NetOpenCVFastAPIReact

Deliverable Package File Contents

Source Code ZIP Archive

Complete executable project folder with all scripts & configuration.

IEEE Project Report (.docx & PDF)

Includes Abstract, Literature Survey, System Design, Data Flow, Test Cases, and References.

PPT Presentation Deck (.pptx)

Ready 15-20 slide presentation deck formatted for university viva evaluation.

Complete Deliverables PackageVERIFIED

Source Code, IEEE Report & PPT

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Verified Source Code (ZIP)
Formatted IEEE Project Report (.docx/PDF)
Seminar PPT Presentation
Execution Video & Setup Guide
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