| # 3DLAND | # 3DLAND | ||||
| Organ-aware 3D lesion segmentation dataset and pipeline for abdominal CT analysis (ACM Multimedia 2025) | Organ-aware 3D lesion segmentation dataset and pipeline for abdominal CT analysis (ACM Multimedia 2025) | ||||
| # 3DLAND: 3D Lesion Abdominal Anomaly Localization Dataset | |||||
| This repository contains the code and dataset instructions for **3DLAND**, the first large-scale, organ-aware 3D lesion segmentation benchmark for abdominal CT scans, introduced at *ACM Multimedia 2025*. | |||||
| ## ๐ Overview | |||||
| - 6,000+ contrast-enhanced CT studies | |||||
| - 3D lesion masks aligned with 7 abdominal organs | |||||
| - Prompt-based annotation and propagation pipeline | |||||
| - Applications: anomaly detection, lesion retrieval, organ-aware analysis | |||||
| ## ๐ง Pipeline | |||||
| The lesion segmentation pipeline includes: | |||||
| 1. Organ segmentation via MONAI | |||||
| 2. Lesion-to-organ assignment | |||||
| 3. 2D mask generation using SAM prompts | |||||
| 4. 3D mask propagation using MedSAM2 | |||||
| ## ๐ฆ Dataset | |||||
| The dataset (metadata + mask annotations) is hosted at: | |||||
| ๐ [Download via Zenodo](https://zenodo.org/...) *(or your link)* | |||||
| ## ๐ License | |||||
| The dataset and outputs are licensed under **CC BY 4.0**. | |||||
| See the full license in the [LICENSE](LICENSE) file or at [creativecommons.org/licenses/by/4.0](https://creativecommons.org/licenses/by/4.0/) | |||||
| ## ๐ Getting Started | |||||
| ```bash | |||||
| git clone https://github.com/yourusername/3DLAND.git | |||||
| cd 3DLAND | |||||
| pip install -r requirements.txt | |||||