Update 'README.md'

README.md

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-<h1 align="center">3DLAND: 3D Lesion Abdominal Anomaly Localization Dataset</h1>
+# 3DLAND
+Organ-aware 3D lesion segmentation dataset and pipeline for abdominal CT analysis (ACM Multimedia 2025)
 
+# 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**. 
+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*.
 
-- 📦 **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  
+## 🌐 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/)
 
 
 
-<p align="center"><img width="90%" src="https://git.dml.ir/mehran.advand/3DLAND/src/branch/master/assets/full_pipeline.png" /></p>
-<p align="center"><img width="100%" src="https://git.dml.ir/mehran.advand/3DLAND/assets/omparison_chart.png" /></p>