Model Overview
Description:
VISTA-3D is a specialized interactive foundation model for 3D medical imaging. It excels in providing accurate and adaptable segmentation analysis across anatomies and modalities. Utilizing a multi-head architecture, VISTA-3D adapts to varying conditions and anatomical areas, helping guide users' annotation workflow. This model is for research purposes and not for clinical usage.
- Segment everything: Enables whole body exploration, crucial for understanding complex diseases affecting multiple organs and for holistic treatment planning.
- Segment using class: Provides detailed sectional views based on specific classes, essential for targeted disease analysis or organ mapping, such as tumor identification in critical organs.
- Segment point prompts: Enhances segmentation precision through user-directed, click-based selection. This interactive approach accelerates the creation of accurate ground-truth data, essential in medical imaging analysis.
Terms of use
By using this model, you are agreeing to the terms and conditions of the license.
References(s):
Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloe Rolland, Laura Gustafson, Tete Xiao, Spencer Whitehead, Alexander C. Berg, Wan-Yen Lo, Piotr Dollár, Ross Girshick, 2023. High-resolution 3D abdominal segmentation with random patch network fusion. Segment Anything. arXiv:2304.02643
Model Architecture:
Architecture Type: Transformer
Network Architecture: SAM-like
Input:
Input Type(s): Computed Tomography (CT) Image
Input Format(s): (Neuroimaging Informatics Technology Initiative) NIfTI
Input Parameters: Three-Dimensional (3D)
Other Properties Related to Input: Array of Class/Point Information
Output:
Output Type(s): Image
Output Format: NIfTI
Output Parameters: 3D
Software Integration:
Runtime Engine(s):
MONAI Core v.1.3
Supported Hardware Microarchitecture Compatibility:
- Ampere
- Hopper
[Preferred/Supported] Operating System(s):
- Linux
Inference:
Engine: Triton
Test Hardware: A100, H100, L40
Ethical Considerations:
NVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their supporting model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse. For more detailed information on ethical considerations for this model, please see the Model Card++ Explainability, Bias, Safety & Security, and Privacy Subcards. Please report security vulnerabilities or NVIDIA AI Concerns here.