NV-Generate-CT is a state-of-the-art three-dimensional (3D) Latent Diffusion Model designed for generating high-quality synthetic CT images with or without anatomical annotations. This AI model excels in data augmentation and creating realistic medical imaging data to supplement limited datasets due to privacy concerns or rare conditions. It can also significantly enhance the performance of other medical imaging AI models by generating diverse and realistic training data.
MAISI offers several key features:
Generates high-resolution 3D CT images up to 512 × 512 × 768 voxels
Supports variable voxel sizes ranging from 0.5mm to 5.0mm
Capable of annotating up to 127 anatomical classes, including organs and tumors
Allows controllable anatomy size for 10 specific classes
Produces paired segmentation masks
By providing these capabilities, MAISI is a valuable tool for researchers advancing AI applications in healthcare. However, it is important to note that this model is intended for research purposes only and not for clinical usage.
The current demo showcases only a subset of the model’s capabilities. For full functionality and advanced usage, please refer to the GitHub repository.
[1] Zhao, Can, et al. "Maisi-v2: Accelerated 3d high-resolution medical image synthesis with rectified flow and region-specific contrastive loss." arXiv preprint arXiv:2508.05772 (2025).
[2] Guo, Pengfei, et al. "Maisi: Medical ai for synthetic imaging." 2025 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). IEEE, 2025.
Input Type: Integer
Input Format: Single integer value
Input Parameters: Required input indicates the number of synthetic images the model will generate.
body_region
Input Type: List
Input Format: Array of Strings
Input Parameters: Required input indicates the region of body the generated CT will focus on
Input Type: List
Input Format: Array of Strings
Input Parameters: Optional list of 127 anatomical classes (listed in the Additional Information section)
output_size
Input Type: List
Input Format: Array of 3 Integers
Input Parameters: Optional list of 3 numbers that indicate the x, y, and z size of the CT image. They must be one of 128, 256, 384, 512 for x- and y-axes, 128, 256, 384, 512, 640, 768 for the z-axis.
spacing
Input Type: List
Input Format: Array of 3 Floats
Input Parameters: Optional list of 3 floats that indicate the spacing of the CT image
Each element must be in the range: 0.5 to 5.0
controllable_anatomy_size
Input Type: List
Input Format: Array of Tuples (String, Float)
Input Parameters: Optional list of tuples for up to 10 different anatomies. Each tuple consists of an (organ_name, size_value) pair.
size_value range: 0.0 to 1.0, or -1 (means not exist/delete this organ)
Output:
Output Type(s): Image(s) Output Format: (Neuroimaging Informatics Technology Initiative) NIfTI, (Digital Imaging and Communications in Medicine) DICOM, and (Nearly Raw Raster Data) Nrrd Output Parameters: Three-Dimensional (3D) Output Description: Synthetic CT image with dimensions up to 512x512x768 and spacing between 0.5mm and 5.0mm, reflecting controllable anatomy sizes as specified. If requested in input parameters, an additional NIfTI file containing the corresponding label map for the anatomy_list is also provided.
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