Inc0mple/3D_Brain_Tumor_Seg_V2
Using the BraTS2020 dataset, we test several approaches for brain tumour segmentation such as developing novel models we call 3D-ONet and 3D-SphereNet, our own variant of 3D-UNet with more than one encoder-decoder paths.
This project helps neuro-oncologists, radiologists, and researchers automatically identify and delineate brain tumors from MRI scans. It takes a patient's multi-modal MRI images (T1, T1c, T2, T2-FLAIR) and outputs precise 3D segmentation masks highlighting the whole tumor, peritumoral edema, and enhancing tumor regions. It is designed for those who need to quickly and accurately segment brain tumors for diagnosis, treatment planning, or research.
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Use this if you need to perform automated 3D brain tumor segmentation from MRI data, especially if you are working with limited computational resources or are looking for highly parameter-efficient models.
Not ideal if you require a production-ready, clinically validated software solution for immediate diagnostic use without further rigorous testing and integration.
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Apr 29, 2023
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