让医生边看CT边互动标注，自动生成带属性的病灶报告。
Interactive Segmentation and Report Generation for CT Images
- 医生可实时交互式标注3D病灶，系统同步生成分割图与描述。
- 在15类病灶上验证，报告内容更全面且可靠。
- 适合需动态调整评估的放射科医生使用。
自动化CT报告生成对提升诊断准确性和临床工作流效率至关重要。然而，现有方法缺乏可解释性，阻碍医患理解，且静态特性限制放射科医生在阅片过程中动态调整评估。受交互分割技术启发，我们提出一种全新的3D病灶形态学报告交互框架，可无缝生成分割掩码及全面的属性描述，使临床医生能生成详细的病灶特征档案以增强诊断评估。据我们所知，这是首个将交互分割与结构化报告整合于3D CT医学图像中的工作。在15类病灶上的实验结果表明，该方法在病灶分割与描述方面具有更强的全面性与可靠性。源代码将在论文接受后公开。
原文摘要 · Abstract (English)
Automated CT report generation plays a crucial role in improving diagnostic accuracy and clinical workflow efficiency. However, existing methods lack interpretability and impede patient-clinician understanding, while their static nature restricts radiologists from dynamically adjusting assessments during image review. Inspired by interactive segmentation techniques, we propose a novel interactive framework for 3D lesion morphology reporting that seamlessly generates segmentation masks with comprehensive attribute descriptions, enabling clinicians to generate detailed lesion profiles for enhanced diagnostic assessment. To our best knowledge, we are the first to integrate the interactive segmentation and structured reports in 3D CT medical images. Experimental results across 15 lesion types demonstrate the effectiveness of our approach in providing a more comprehensive and reliable reporting system for lesion segmentation and capturing. The source code will be made publicly available following paper acceptance.
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