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

3DLAND

<<<<<<< HEAD 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:

Organ segmentation via MONAI
Lesion-to-organ assignment
2D mask generation using SAM prompts
3D mask propagation using MedSAM2

📦 Dataset

The dataset (metadata + mask annotations) is hosted at:
👉 Download via Zenodo (or your link)

📄 License

The dataset and outputs are licensed under CC BY 4.0.
See the full license in the LICENSE file or at 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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