肺癌 CT 影像数据集|医学影像数据集|肺癌检测数据集

RIDER Lung CT Dataset 是一个用于评估非小细胞肺癌患者CT扫描中肿瘤测量变异性的数据集，包含32名患者在短时间内重复进行的胸部CT扫描，共计15419张图像。每位患者的两次扫描均在15分钟内完成，采用相同扫描方案，确保条件一致性。数据集中放射科医生手动测量肿瘤最大直径，并结合计算机软件辅助分析，利用一致性相关系数和Bland-Altman图评估测量重复性。该数据集适用于医学影像分析、肿瘤进展评估、算法可靠性验证及人工智能模型训练等场景，具有高临床价值和研究意义。

The RIDER Lung CT Dataset is a dedicated dataset for evaluating tumor measurement variability in CT scans of patients with non-small cell lung cancer. It contains repeated chest CT scans from 32 patients conducted within a short interval, with a total of 15,419 images. For each patient, the two scans were completed within 15 minutes using the same scanning protocol to ensure consistent scanning conditions. Radiologists manually measured the maximum diameter of the tumors with the assistance of computer-aided analysis software, and the measurement reproducibility was assessed using the concordance correlation coefficient and Bland-Altman plots. This dataset features high clinical value and research significance, and is applicable to scenarios including medical image analysis, tumor progression evaluation, algorithm reliability validation, and artificial intelligence model training.

搜集汇总

背景与挑战

背景概述

该数据集是RIDER Lung CT Dataset，专注于非小细胞肺癌的CT影像分析，用于评估肿瘤测量变异性。它包含32名患者的15419张图像，每位患者进行两次快速重复扫描以确保数据一致性，总容量达40.06GB，适用于医学影像研究和肺癌检测算法开发。