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Python Deep Learning 2026 ID: 1CP0633

Brain Tumor Prediction and Segmentation Using CNN

Keywords: Brain Tumor Prediction, Brain Tumor Segmentation, CNN, Deep Learning, Artificial Intelligence, MRI Image Analysis, Medical Image Processing, U-Net, Image Classification, Image Segmentation, Tumor Dete

Project Synopsis & Overview

This project aims to develop an automated deep learning system for brain tumor prediction and segmentation from MRI images using Convolutional Neural Networks (CNN). The system processes MRI brain images through image processing and preprocessing techniques such as resizing, grayscale conversion, noise reduction, normalization, histogram equalization, and skull stripping. CNN or U-Net-based segmentation is used to identify and localize the tumor region. The segmented tumor region is then analyzed for classification and severity prediction. A Python-based GUI using Tkinter can be used to provide the prediction results. The system is designed to assist medical professionals by reducing manual analysis time and supporting brain tumor diagnosis and treatment planning.

Complete Technical Specifications

Project ID 1CP0633 (DB ID: 633)
Project Title Brain Tumor Prediction and Segmentation Using CNN
Domain Division Python
Sub-Domain / Tech Deep Learning
IEEE Year 2026
Package Price ₹6500
Created Date Sep 17, 2026
Project Price
₹6500 ₹8000 20% OFF
100% Executable Source Code & DB
IEEE Journal Paper Synopsis & PPT
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