nmn-pandey/brain-tumour-segmentation
Code for automated brain tumor segmentation from MRI scans using CNNs with attention mechanisms, deep supervision, and Swin-Transformers. Based on my Master's dissertation project at Brunel University, it features 3 deep learning models, showcasing integration of advanced techniques in medical image analysis.
This project offers tools to automatically identify and outline brain tumors from MRI scans. It takes multi-modal MRI images (T1, T1-contrasted, T2, and FLAIR) as input and outputs precise segmentations of tumor regions. Radiologists, neuro-oncologists, and medical researchers can use this to assist in diagnosis, treatment planning, and research.
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Use this if you need to quickly and accurately segment brain tumors from a large volume of multi-modal MRI scans to aid in clinical assessment or research.
Not ideal if you require segmentation of other brain pathologies or need a solution that performs perfectly on all low-contrast or highly ambiguous tumor cases.
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Language
Python
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Last pushed
Nov 17, 2023
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