In this talk, we’ll explore two medical imaging models. First, we’ll dive into NVIDIA’s Versatile Imaging SegmenTation and Annotation (VISTA) model which combines semantic segmentation with interactivity, offering high accuracy and adaptability across diverse anatomical areas for medical imaging. Finally, we’ll explore MedSAM-2, an advanced segmentation model that utilizes Meta’s SAM 2 framework to address both 2D and 3D medical image segmentation tasks.
Speaker: Daniel Gural is a seasoned Machine Learning Engineer at Voxel51 with a strong passion for empowering Data Scientists and ML Engineers to unlock the full potential of their data.
Resource links
- Schedule a FiftyOne Teams demo to see the MedSAM-2 and NVIDIA VISTA-3D models in action
- MedSam-2 dataset on Hugging Face
- Segment Anything in a CT Scan with NVIDIA VISTA-3D
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