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@@ -14,11 +14,21 @@ pretty_name: PanTrack
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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://github.com/MIC-DKFZ/LongiSeg) [\[Code & Models\]](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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  ## 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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+ [![Hugging Face Dataset](https://img.shields.io/badge/🤗%20Hugging%20Face-PanTrack-yellow.svg)](https://huggingface.co/datasets/mrokuss/PanTrack)
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+ [![arXiv](https://img.shields.io/badge/arXiv-2605.23118-B31B1B.svg)](https://arxiv.org/abs/2605.23118)&#160;
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+ [![GitHub](https://img.shields.io/badge/GitHub-LongiSeg-181717?logo=github&logoColor=white)](https://github.com/MIC-DKFZ/LongiSeg)&#160;
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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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+ [![CVPR](https://img.shields.io/badge/%20CVPR%202025%20-open%20access-blue.svg)](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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+ [![arXiv](https://img.shields.io/badge/arXiv-2409.13416-B31B1B.svg)](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: