Update README.md

README.md

@@ -12,6 +12,20 @@ This dataset is the official release of the benchmark introduced in the paper
 The dataset will be released in phases. Each subset will be manually reviewed before being progressively opened to the public.<br>
 Currently released subset: <br>CHAOS (CN).
 
+---
+## Abstract
+
+Multi-turn reasoning segmentation is essential for mimicking real-world clinical workflows, 
+where anatomical structures are identified through step-by-step dialogue based on spatial, 
+functional, or pathological descriptions. However, the lack of a dedicated benchmark in this area has limited progress.
+To address this gap, we introduce the first bilingual benchmark for multi-turn medical image segmentation, supporting both Chinese and English dialogues.
+The benchmark consists of 28,904 images, 113,963 segmentation masks, and 232,188 question–answer pairs, covering major organs and anatomical systems across CT 
+and MRI modalities. Each dialogue requires the model to infer the segmentation target based on prior conversational turns 
+and previously segmented regions. We evaluate several state-of-the-art models, including MedCLIP-SAM, LISA, and LISA++, 
+and report three key findings: (1) existing models perform poorly on our benchmark, far below clinical usability standards; 
+(2) performance degrades as dialogue turns increase, reflecting limited multi-turn reasoning capabilities; and (3) general-purpose models such as LISA 
+can outperform medical-specific models, suggesting that further integration of domain knowledge is needed for specialized medical applications.
+
 ---
 
 ## 📁 Dataset Directory Structure
@@ -103,7 +117,7 @@ Each turn of QA contains the following fields (example):
 ## Citation
 
 If you find this work useful or use this dataset in your research, please cite our paper.  
-*Note: The paper has been accepted at BIBM 2025 and is to appear; final publication details (e.g., pages/DOI) will be updated upon release.*
+**Note: The paper has been accepted at BIBM 2025 and is to appear; final publication details (e.g., pages/DOI) will be updated upon release.**
 
 
 ```bibtex