# 3DLAND
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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*.

## 🌐 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

## 🧠 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

## 📦 Dataset

The dataset (metadata + mask annotations) is hosted at:  
👉 [Download via Zenodo](https://zenodo.org/...) *(or your link)*

## 📄 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/)

## 🚀 Getting Started

```bash
git clone https://github.com/yourusername/3DLAND.git
cd 3DLAND
pip install -r requirements.txt

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Organ-aware 3D lesion segmentation dataset and pipeline for abdominal CT analysis (ACM Multimedia 2025 candidate)
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