3DLAND

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 (or your link)

🚀 Getting Started

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