> This page is for VISTA-3D, version 1.0.0 (Latest) (default). > For other versions, use one of these documentation indexes: > - 1.0.0 (Latest) (default): https://docs.nvidia.com/nim/medical/vista3d/1.0.0/llms.txt > For clean Markdown of any page, append .md to the page URL. > For a complete documentation index, see https://docs.nvidia.com/nim/medical/llms.txt. > For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.nvidia.com/nim/medical/_mcp/server. # Performance ## Accuracy Performance The accuracy performance is measured by calculating the dice score on ground truth and inference results on 7 images. The following table shows the dice score for each class and the mean dice score for each case. | Case | Image | Class | Dice Score | Mean Dice | | ---- | -------------------------------------------------------------------------------------------------------------------------- | ---------------------- | ---------- | --------- | | 1 | [spleen_2_image.nii.gz](https://vista3d-nim-test-images.s3.amazonaws.com/test-vista3d-nim-image-url/spleen_2_image.nii.gz) | spleen | 0.9652 | 0.9652 | | 2 | [s0996.nii](https://vista3d-nim-test-images.s3.amazonaws.com/test-vista3d-nim-image-url/s0996.nii) | aorta | 0.9682 | 0.9682 | | 3 | [liver_129.nii.gz](https://vista3d-nim-test-images.s3.amazonaws.com/test-vista3d-nim-image-url/liver_129.nii.gz) | liver | 0.9177 | 0.8008 | | | | hepatic tumor | 0.6840 | | | 4 | [lung_034.nii.gz](https://vista3d-nim-test-images.s3.amazonaws.com/test-vista3d-nim-image-url/lung_034.nii.gz) | lung tumor | 0.8779 | 0.8779 | | 5 | [colon_203.nii](https://vista3d-nim-test-images.s3.amazonaws.com/test-vista3d-nim-image-url/colon_203.nii) | colon cancer primaries | 0.8421 | 0.8421 | | 6 | [s0459.nii](https://vista3d-nim-test-images.s3.amazonaws.com/test-vista3d-nim-image-url/s0459.nii) | stomach | 0.9360 | 0.9004 | | | | inferior vena cava | 0.9087 | | | | | pancreas | 0.7810 | | | | | vertebrae L1 | 0.9793 | | | | | vertebrae T8 | 0.9769 | | | | | brain | 0.8203 | | | 7 | [s0675.nii](https://vista3d-nim-test-images.s3.amazonaws.com/test-vista3d-nim-image-url/s0675.nii) | left rib 8 | 0.8731 | 0.9165 | | | | right rib 3 | 0.9463 | | | | | right rib 12 | 0.9498 | | | | | right iliopsoas | 0.8696 | | | | | heart | 0.9439 | | ## Speed Performance The speed performance is measured by calculating the time cost on 6 images with different GPUs. The following tables show the results for both PyTorch and TensorRT models for each case. ### Case 1 **Image:** [256cubic.nii.gz](https://vista3d-nim-test-images.s3.amazonaws.com/test-vista3d-nim-image-url/256cubic.nii.gz) **Classes:** [] **Size:** 256 x 256 x 256 | GPU | Model | Mean Speed (s) | Median Speed (s) | | ------------ | -------- | -------------- | ---------------- | | H100 | PyTorch | 3.028 | 2.968 | | | TensorRT | 2.702 | 2.710 | | A100 | PyTorch | 7.126 | 7.147 | | | TensorRT | 5.856 | 5.674 | | RTX 6000 Ada | PyTorch | 6.757 | 6.763 | | | TensorRT | 6.539 | 6.237 | | L40s | PyTorch | 8.767 | 8.823 | | | TensorRT | 8.543 | 8.720 | ### Case 2 **Image:** [256cubic.nii.gz](https://vista3d-nim-test-images.s3.amazonaws.com/test-vista3d-nim-image-url/256cubic.nii.gz) **Classes:** [spleen] **Size:** 256 x 256 x 256 | GPU | Model | Mean Speed (s) | Median Speed (s) | | ------------ | -------- | -------------- | ---------------- | | H100 | PyTorch | 2.511 | 2.521 | | | TensorRT | 2.287 | 2.298 | | A100 | PyTorch | 6.117 | 6.125 | | | TensorRT | 4.0935 | 4.086 | | RTX 6000 Ada | PyTorch | 5.514 | 5.593 | | | TensorRT | 5.169 | 5.168 | | L40s | PyTorch | 6.903 | 6.944 | | | TensorRT | 6.597 | 6.594 | ### Case 3 **Image:** [512cubic.nii.gz](https://vista3d-nim-test-images.s3.amazonaws.com/test-vista3d-nim-image-url/512cubic.nii.gz) **Classes:** [] **Size:** 512 x 512 x 512 | GPU | Model | Mean Speed (s) | Median Speed (s) | | ------------ | -------- | -------------- | ---------------- | | H100 | PyTorch | 16.308 | 16.294 | | | TensorRT | 15.235 | 15.226 | | A100 | PyTorch | 91.567 | 92.848 | | | TensorRT | 87.108 | 84.881 | | RTX 6000 Ada | PyTorch | 109.338 | 109.405 | | | TensorRT | 103.284 | 103.386 | | L40s | PyTorch | 96.068 | 97.135 | | | TensorRT | 95.064 | 91.982 | ### Case 4 **Image:** [512cubic.nii.gz](https://vista3d-nim-test-images.s3.amazonaws.com/test-vista3d-nim-image-url/512cubic.nii.gz) **Classes:** [liver] **Size:** 512 x 512 x 512 | GPU | Model | Mean Speed (s) | Median Speed (s) | | ------------ | -------- | -------------- | ---------------- | | H100 | PyTorch | 14.156 | 14.147 | | | TensorRT | 13.079 | 13.066 | | A100 | PyTorch | 37.947 | 37.963 | | | TensorRT | 34.156 | 33.852 | | RTX 6000 Ada | PyTorch | 32.242 | 32.256 | | | TensorRT | 31.434 | 31.149 | | L40s | PyTorch | 33.164 | 34.715 | | | TensorRT | 33.244 | 33.151 | ### Case 5 **Image:** [512-768.nii.gz](https://vista3d-nim-test-images.s3.amazonaws.com/test-vista3d-nim-image-url/512-768.nii.gz) **Classes:** [] **Size:** 512 x 512 x 768 | GPU | Model | Mean Speed (s) | Median Speed (s) | | ------------ | -------- | -------------- | ---------------- | | H100 | PyTorch | 89.312 | 88.864 | | | TensorRT | 87.692 | 87.501 | | A100 | PyTorch | 144.568 | 143.292 | | | TensorRT | 140.919 | 140.490 | | RTX 6000 Ada | PyTorch | 160.502 | 160.697 | | | TensorRT | 151.359 | 144.844 | | L40s | PyTorch | 146.684 | 150.386 | | | TensorRT | 147.603 | 144.717 | ### Case 6 **Image:** [512-768.nii.gz](https://vista3d-nim-test-images.s3.amazonaws.com/test-vista3d-nim-image-url/512-768.nii.gz) **Classes:** [heart] **Size:** 512 x 512 x 768 | GPU | Model | Mean Speed (s) | Median Speed (s) | | ------------ | -------- | -------------- | ---------------- | | H100 | PyTorch | 22.957 | 22.991 | | | TensorRT | 21.499 | 21.515 | | A100 | PyTorch | 58.676 | 58.831 | | | TensorRT | 55.636 | 54.910 | | RTX 6000 Ada | PyTorch | 49.822 | 50.126 | | | TensorRT | 33.956 | 33.831 | | L40s | PyTorch | 49.225 | 51.239 | | | TensorRT | 48.805 | 49.690 |