3DLAND: 3D Lesion Abdominal Anomaly Localization Dataset

![visitors](https://visitor-badge.laobi.icu/badge?page_id=mehran.advand/3DLAND&left_color=%234CAF50&right_color=%23FFC107) [![GitHub Repo stars](https://img.shields.io/github/stars/mehran.advand/3DLAND?style=social)](https://git.dml.ir/mehran.advand/3DLAND/stargazers) Follow on Twitter
**Subscribe for updates: [3DLAND Google Group](https://groups.google.com/g/3dland-dataset)**
We introduce **3DLAND**, the first large-scale, **organ-aware** 3D lesion segmentation dataset for contrast-enhanced **abdominal CT scans**. - 📦 **6,000+** CT volumes - 🧠 3D Lesions labeled across **7 abdominal organs**: liver, kidneys, spleen, pancreas, stomach, gallbladder - 🤖 Built using a **prompt-driven**, expert-verified segmentation pipeline - ⚙️ Designed for tasks such as anomaly detection, lesion retrieval, and multimedia-driven clinical AI This level of structured annotation would traditionally take **25+ years** of expert effort — 3DLAND accomplishes it in weeks using automated reasoning and deep learning.