Kidney stone detection via axial CT imaging: A dataset for AI and deep learning applications

基于轴向CT成像的肾结石检测:用于人工智能和深度学习应用的数据集

阅读:1

Abstract

This article introduces a comprehensive CT scan image dataset focused on kidney stone detection, consisting of two groups: one drawn from patients with kidney stones and the other from patients without kidney stones. This dataset has been cleaned, cross-checked, and checked adequately before labeling in coordination with the medical experts from the medical field. Samples in the dataset were derived from different health facilities in Sulaimani and Rania, Iraq, which supplied crucial information about the demographics and patterns of kidney stones in the area. It holds 3364 original CT images and 35,457 augmented CT images, which can be used to create deep-learning models for kidney stone diagnosis. The enhanced images also make it possible to use them in training or developing medical practice and educational algorithms. This dataset can be an asset in developing new diagnostic tools, supporting medical research, and being used as learning material for students studying in the medical field.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。