Semantic Segmentation with Pixel Masks and Voxels in V7 Darwin | Tutorial
Did you know that you can use V7 Darwin for semantic segmentation tasks? Pixel masks let you create accurate training data labels or even work with voxels when dealing with medical volumetric data or other 3D views.
In the video, we explain what semantic masks are, how they differ from other annotation classes, and how they can be particularly useful in the context of medical imaging.
0:00 - Introduction
0:40 - Use cases for semantic masks
1:15 - Differences between polygon and pixel mask annotations
1:50 - Using masks in V7 Darwin
3:07 - Voxels and working with 3D views and DICOM
3:49 - Summary
The addition of mask annotations in V7 Darwin introduces another powerful feature to your computer vision toolkit. With their high precision and detail, they are poised to enhance the quality and accuracy of semantic segmentation tasks across various industries and use cases.
If you're interested in learning more about V7 Darwin masks, you can visit our documentation pages: Semantic Masks - https://docs.v7labs.com/docs/introduc...
V7 for Medical Imaging - • V7 for Medical Image Annotation & Model Tr...
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