AHMEDSANA/Binary-Class-Brain-Tumor-Segmentation-Using-UNET
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 our segmentation.
This project helps medical professionals analyze brain MRI scans to quickly identify and locate brain tumors. It takes 3D MRI images of a patient's brain as input and outputs a clear segmentation, highlighting the cancerous areas. This allows doctors to efficiently pinpoint the tumor's exact position.
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Use this if you are a radiologist or neurologist who needs to rapidly and accurately segment brain tumors from MRI scans for diagnosis and treatment planning.
Not ideal if you require tumor classification into specific subtypes beyond high-grade and low-grade glioma, or if you need to analyze other medical imaging modalities.
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Nov 15, 2024
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