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We segmented the Brain tumor using Brats dataset and as we know it is in 3D format we used the slicing method in which we slice the images in 2D form according to its 3 axis and then giving the model for training then combining waits to segment brain tumor. We used UNET model for training our dataset.

Python 100.00%
brain-tumor-detection brain-tumor-segmentation braintumorsegmentation brats brats-dataset brats2018 deep-learning mri-images mri-segmentation python python3 tensorflow tumor-segmentation unet-image-segmentation unet-keras unet-segmentation

four-class-brain-tumor-segmentation.'s Introduction

MasterHead

Hi 👋, I'm Ahmed Sana

A passionate AI Engineer | Machine Learning Enthusiast | Artificial Neural Network Expert

ahmedsana

  • 🔭 I’m currently working on Image Regeneration

  • 🌱 I’m currently learning Image Generation

  • 💬 Ask me about Neural Networks, Machine Learning, Computer Vision

  • 📫 How to reach me [email protected]

Languages and Tools:

arduino c git java matlab opencv pandas python scikit_learn tensorflow

ahmedsana

 ahmedsana

ahmedsana

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