NicklasVraa/VAE_based_segmentation
Exploring variational-autoencoder-based semantic segmentation for analyzing CT-scans.
This project offers a method for precisely identifying and outlining tumors in medical CT scans. It takes raw CT scan data as input and produces segmented images where tumors are highlighted, making it easier for medical professionals to review and analyze scans. Radiologists, oncologists, and other medical imaging specialists would find this useful for diagnostic support and treatment planning.
No commits in the last 6 months.
Use this if you need an automated way to accurately segment and identify tumorous regions within CT scan images.
Not ideal if you require a solution for non-medical image segmentation or need to work with imaging modalities other than CT scans.
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21
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1
Language
Jupyter Notebook
License
GPL-3.0
Last pushed
Dec 06, 2023
Commits (30d)
0
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