Georges Hattab bio photo


Kidney Boundary Data 2017

The Kidney Boundary Data 2017 focuses on the detection of kidney boundaries in medical imaging, providing a dataset for training and evaluating segmentation algorithms. This data was initially shared as part of the EndoVis Sub-Challenge 2017.

Kidney Boundary Data 2017

Data Set Description

  • Type: Medical Imaging
  • Number of Instances: 100 annotated images
  • Number of Variables: Not applicable (image data)
  • Attribute Characteristics: Quantitative (pixel values)
  • Date Published: 2017
  • Associated Tasks: Segmentation, Boundary Detection

Source code and data are available for download under appropriate licensing.

Data Set Characteristics

Characteristic Details
Type Medical Imaging
Number of Instances 100 annotated images
Number of Variables Not applicable
Attribute Characteristics Pixel values (quantitative)
Date Published 2017
Associated Tasks Segmentation, Edge Detection

Publications

Arnold, M., Speidel, S., & Hattab, G. (2021). Towards improving edge quality using combinatorial optimization and a novel skeletonize algorithm. BMC Medical Imaging, 21, 1-9.

Hattab, G., Arnold, M., Strenger, L., Allan, M., Arsentjeva, D., Gold, O., … & Speidel, S. (2020). Kidney edge detection in laparoscopic image data for computer-assisted surgery: Kidney edge detection. International journal of computer assisted radiology and surgery, 15, 379-387.

Data Variables

  • Image Data: Pixel values representing kidney boundaries.
  • Annotations: Ground truth segmentation masks.

Licensing

Original data available under the appropriate licensing terms provided on the EndoVis Sub-Challenge 2017 website. All source code and label data are open-source and available for modification under the Creative Commons License CC BY 4.0.