How I Use nnUNet for Medical Image Segmentation: A Comprehensive Guide
Guide to nnUNet for segmentation.
November 7, 2024
We Help you add AI to your Medical Device
We take care of your data from start to finish. From annotation guidance and anonymization to handling various file formats, we ensure your data is ready for analysis and model training.
We select the optimal model configurations tailored to your specific tasks. Our team handles the entire training process, including evaluation, to deliver high-performance models.
We deploy your trained models or those created by your team. Whether it’s deploying as APIs on GCP or AWS or creating an MVP UI, we ensure your models are ready for use.
PYCAD is a company dedicated to medical imaging and computer vision. We have over three years of experience in medical imaging and six years in computer vision. Our company was founded in 2023, and since then, we’ve successfully completed more than 10 projects, both long and short-term.
At PYCAD, we work closely with our clients to understand their needs and provide solutions that help them achieve their goals. We are passionate about using the latest technologies to improve medical imaging and make a positive impact.
If you want to learn more about what we do or see examples of our work, feel free to contact us or check out our portfolio.
At PYCAD, data security and privacy are our top priorities. We ensure that all data remains confidential and is never shared with any third parties. Your data will be handled securely and will be deleted immediately after the completion of the project to maintain privacy.
PYCAD primarily works with startups developing AI solutions for medical imaging. However, we also collaborate with larger companies and radiology centers to provide our expertise and services.
Yes, PYCAD offers post-deployment support to ensure the seamless integration and operation of our solutions. As most of our projects are long-term, ongoing support is typically included as part of our services to assist with any needs that arise after deployment.
Guide to nnUNet for segmentation.
Add custom metadata to NIfTI/NRRD using SimpleITK and Nibabel.
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