| { | |
| "display_name": "Synthesis: Finetune BICMAC", | |
| "short_description": "Supervised whole-body CBCT-to-sCT model for SynthRAD Task 2.<br><br><b>Training data:</b><br>929 paired CT-CBCT cases from SynthRAD 2023+2025.<br><br><b>How to cite:</b><br><cite>V. Boussot et al., <i>Why Registration Quality Matters: Enhancing sCT Synthesis with IMPACT-Based Registration</i>, arXiv preprint arXiv:2510.21358, <a href=\"https://doi.org/10.48550/arXiv.2510.21358\">https://doi.org/10.48550/arXiv.2510.21358</a>.</cite>", | |
| "description": "<b>Description:</b><br>Supervised whole-body CBCT-to-sCT model trained using SynthRAD 2023 and SynthRAD 2025 Task 2 datasets, distributed as five validation-fold checkpoints (<code>CV_0.pt</code> to <code>CV_4.pt</code>). Training pairs are aligned with IMPACTReg. The available Task 2 data include 291 patients from SynthRAD 2023 and 638 patients from SynthRAD 2025, for 929 patients in total.<br><br><b>Architecture and loss:</b><br>2.5D UNet++ with a ResNet34 encoder, trained with KonfAI and optimized using IMPACT-Synth, a perceptual loss leveraging semantic priors from <b>SAM 2.1-s</b>.<br><br><b>Training data:</b><br>Whole-body paired CT-CBCT volumes come from SynthRAD 2023 Task 2 (<code>brain</code>, <code>pelvis</code>) and SynthRAD 2025 Task 2 (<code>AB</code>, <code>HN</code>, <code>TH</code>). Additional OOD evaluation cohorts are available for <code>AB_ood</code>, <code>HN_ood</code>, and <code>TH_ood</code>. Pairs are aligned with IMPACTReg, and the associated transform files are available at <a href=\"https://huggingface.co/datasets/VBoussot/synthrad2023-impact-registration\">synthrad2023-impact-registration</a> and <a href=\"https://huggingface.co/datasets/VBoussot/synthrad2025-impact-registration\">synthrad2025-impact-registration</a>. The files <code>CrossValidation_0.txt</code> to <code>CrossValidation_4.txt</code> correspond to validation folds for the distributed checkpoints, and <code>Validation.txt</code> contains 150 release-validation patients.<br><br><b>Release performance (CV overall, n=150):</b><br>Dice 0.758, MAE 53.55 HU, SSIM 0.939, PSNR 32.09 dB, SAM 13.70, Reg 1.04, Uncertainty 784.24.<br><br><b>Inference note:</b><br>The prediction pipeline supports test-time augmentation and writes an averaged <code>InferenceStack</code> output that can also be used for uncertainty estimation.<br><br><b>How to cite:</b><br><cite>V. Boussot et al., <i>Why Registration Quality Matters: Enhancing sCT Synthesis with IMPACT-Based Registration</i>, arXiv preprint arXiv:2510.21358, <a href=\"https://doi.org/10.48550/arXiv.2510.21358\">https://doi.org/10.48550/arXiv.2510.21358</a>.</cite>", | |
| "tta": 2, | |
| "mc_dropout": false, | |
| "models": [ | |
| "CV_0.pt", | |
| "CV_1.pt", | |
| "CV_2.pt", | |
| "CV_3.pt", | |
| "CV_4.pt" | |
| ], | |
| "inputs": { | |
| "CBCT": { | |
| "display_name": "CBCT", | |
| "volume_type": "VOLUME", | |
| "required": true | |
| } | |
| }, | |
| "outputs": { | |
| "sCT": { | |
| "display_name": "sCT", | |
| "volume_type": "VOLUME", | |
| "required": true | |
| } | |
| }, | |
| "inputs_evaluations": { | |
| "Image": { | |
| "Evaluation.yml": { | |
| "sCT": { | |
| "display_name": "sCT", | |
| "volume_type": "VOLUME", | |
| "required": true | |
| }, | |
| "CT": { | |
| "display_name": "CT", | |
| "volume_type": "VOLUME", | |
| "required": true | |
| } | |
| } | |
| } | |
| }, | |
| "vram_plan": { | |
| "8": { | |
| "patch_size": [ | |
| 1, | |
| 512, | |
| 512 | |
| ], | |
| "batch_size": 16 | |
| }, | |
| "16": { | |
| "patch_size": [ | |
| 1, | |
| 512, | |
| 512 | |
| ], | |
| "batch_size": 28 | |
| }, | |
| "24": { | |
| "patch_size": [ | |
| 1, | |
| 512, | |
| 512 | |
| ], | |
| "batch_size": 48 | |
| } | |
| } | |
| } | |