license: cc-by-nc-sa-4.0
language:
- en
tags:
- medical
Kidney-CT-Abnormality
This Kidney-CT_Abnormality dataset consists of kidney CT scans with abnormality label. The original dataset is available at https://zenodo.org/records/8043408.
Dataset Details
Dataset Description
The kidney CT scans contained in this dataset are .mha (medical high-resolution image) files. In total, there are 986 CT scans, and each contains multiple layers. A .json file is also included, illustrating the abnormality status of each image.
Note that this dataset was reconstructed from “Dataset for: Kidney abnormality segmentation in thorax-abdomen CT scans” (https://zenodo.org/records/8014290), to fit the 2023 automated universal classification challenges (AUC2023) as stated by the authors.
Dataset Sources
- Original Homepage: https://zenodo.org/records/8043408
Uses
This dataset is intended for kidney abnormality classification.
Direct Use
Out-of-Scope Use
Dataset Structure
Dataset Creation
Curation Rationale
Kidney diseases can be challenging to detect, while identification or diagnosis is crucial for treatment. This dataset is intended to develop AI and machine learning algorithms for enhanced kidney disease recognition.
Source Data
https://zenodo.org/records/8043408
Data Collection and Processing
https://zenodo.org/records/8014290 The original dataset contains “215 thoraxabdomen CT scans with segmentations of the kidney and abnormalities in the kidney”. Note that the original datasets contains in total 38.4G image data in mha format, and there is no .json file indicating the abnormality status. Alternatively, a segmentation kidney image dataset is included.
Who are the source data producers?
Annotations
Personal and Sensitive Information
The CT scan image file names contain the study ID, indicating the differences in scans. These ids are anonymous and don’t contain any other personal information.
Bias, Risks, and Limitations
Recommendations
Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
Citation [optional]
Datasets: Alves, N., & Boulogne, L. (2023). Kidney CT Abnormality [Data set]. Zenodo. https://doi.org/10.5281/zenodo.8043408 Gabriel E. Humpire-Mamani, Luc Builtjes, Colin Jacobs, Bram van Ginneken, Mathias Prokop, & Ernst Th. Scholten. (2023). Dataset for: Kidney abnormality segmentation in thorax-abdomen CT scans [Data set]. Zenodo. https://doi.org/10.5281/zenodo.8014290