Axial CT Imaging Dataset for AI-Powered Kidney Stone Detection: A Resource for Deep Learning Research

This dataset introduces a comprehensive CT scan image dataset focused on kidney stone detection, consisting of two groups: one from individuals diagnosed with kidney stones and the other from those without the condition. The dataset has been meticulously curated, verified, and labeled by experienced medical professionals, ensuring its high quality and reliability for both research and educational applications. Collected from medical centers in Sulaimani and Rania, Kurdistan Region, Iraq, the dataset provides unique insights into the prevalence and characteristics of kidney stones in this region. With 3,364 original CT images and 35,457 augmented images, it offers a valuable resource for developing and evaluating deep learning algorithms for kidney stone detection. The augmented images further increase their applicability for algorithm training, medical research, and educational purposes. This dataset can potentially advance diagnostic tool development, enhance medical research, and serve as an educational resource for students studying kidney stone.

本数据集为一款聚焦肾结石检测的计算机断层扫描（Computed Tomography，简称CT）影像数据集，共分为两组：一组源自确诊肾结石的患者，另一组来自未罹患该病的人群。本数据集由资深医疗人员精心整理、审核核验并完成标注，保障了其高水准的质量与可靠性，可广泛应用于科研与教学场景。该数据集采集自伊拉克库尔德地区（Kurdistan Region）苏莱曼尼亚（Sulaimani）与拉尼亚（Rania）的医疗中心，可为探究该区域肾结石的患病率与临床特征提供独特的研究视角。数据集包含3364张原始CT影像与35457张增强影像，可为开发与评估用于肾结石检测的深度学习算法提供宝贵的研究资源。增强影像进一步拓展了其在算法训练、医学研究及教学场景中的应用适用性。本数据集有望推动诊断工具的研发、助力医学研究进展，并可作为研习肾结石方向学生的教学资源。