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

3DLAND: 3D Lesion Abdominal Anomaly Localization 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.