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README.md
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# 🥞 *PanTrack*: Longitudinal Pancreatic Cancer Tracking Benchmark
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PanTrack is a longitudinal CT benchmark for tumor lesion tracking and segmentation, introduced alongside the paper:
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> **Exploiting Longitudinal Context in Clinician-Verified Interactive Lesion Tracking**
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> Yannick Kirchhoff\*, Maximilian Rokuss\*, et al. — *MICCAI 2026*
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> [\[Paper\]](https://
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This dataset was used **exclusively as a held-out out-of-distribution (OOD) test set**. It was never used for training or model selection in any experiments reported in the paper. It serves as a rigorous cross-domain generalization benchmark for lesion tracking models trained on other data (e.g., autoPET/CT IV).
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## Citation
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If you use *PanTrack*, please cite:
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# 🥞 *PanTrack*: Longitudinal Pancreatic Cancer Tracking Benchmark
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<div align="center">
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[](https://huggingface.co/datasets/mrokuss/PanTrack)
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[](https://arxiv.org/abs/2605.23118) 
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[](https://github.com/MIC-DKFZ/LongiSeg) 
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</div>
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<img src="https://huggingface.co/datasets/mrokuss/PanTrack/resolve/main/PanTrack.jpg" alt="PanTrack Logo"/>
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PanTrack is a longitudinal CT benchmark for tumor lesion tracking and segmentation, introduced alongside the paper:
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> **Exploiting Longitudinal Context in Clinician-Verified Interactive Lesion Tracking**
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> Yannick Kirchhoff\*, Maximilian Rokuss\*, et al. — *MICCAI 2026*
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> [\[Paper\]](https://arxiv.org/abs/2605.23118) [\[Code & Models\]](https://github.com/MIC-DKFZ/LongiSeg)
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This dataset was used **exclusively as a held-out out-of-distribution (OOD) test set**. It was never used for training or model selection in any experiments reported in the paper. It serves as a rigorous cross-domain generalization benchmark for lesion tracking models trained on other data (e.g., autoPET/CT IV).
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---
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## 🔗 Also Interesting
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Related work on longitudinal medical image analysis and lesion tracking:
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**LesionLocator: Zero-Shot Universal Tumor Segmentation and Tracking in 3D Whole-Body Imaging** *(CVPR 2025)*
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A framework for zero-shot lesion segmentation and longitudinal tumor tracking in 3D full-body imaging, combining a large-scale lesion dataset, promptable segmentation, and deep-learning-based image registration.
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[](https://openaccess.thecvf.com/content/CVPR2025/html/Rokuss_LesionLocator_Zero-Shot_Universal_Tumor_Segmentation_and_Tracking_in_3D_Whole-Body_CVPR_2025_paper.html) [\[GitHub\]](https://github.com/MIC-DKFZ/LesionLocator)
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**Longitudinal Segmentation of MS Lesions via Temporal Difference Weighting** *(MICCAI 2024)*
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Introduces a Difference Weighting Block that explicitly incorporates temporal differences between baseline and follow-up MRI scans for superior MS lesion segmentation and detection.
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[](https://arxiv.org/abs/2409.13416) [\[GitHub\]](https://github.com/MIC-DKFZ/Longitudinal-Difference-Weighting)
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---
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## Citation
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If you use *PanTrack*, please cite:
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