Data for glomeruli characterization in histopathological images.

Data Brief

VISILAB, Universidad de Castilla-La Mancha, Ciudad Real, Spain.

Published: April 2020

The data presented in this article is part of the whole slide imaging (WSI) datasets generated in European project AIDPATH This data is also related to the research paper entitle "Glomerulosclerosis Identification in Whole Slide Images using Semantic Segmentation", published in Computer Methods and Programs in Biomedicine Journal [1]. In that article, different methods based on deep learning for glomeruli segmentation and their classification into normal and sclerotic glomerulous are presented and discussed. The raw data used is described and provided here. In addition, the detected glomeruli are also provided as individual image files. These data will encourage research on artificial intelligence (AI) methods, create and compare fresh algorithms, and measure their usability in quantitative nephropathology.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7058889PMC
http://dx.doi.org/10.1016/j.dib.2020.105314DOI Listing

Publication Analysis

Top Keywords

data
5
data glomeruli
4
glomeruli characterization
4
characterization histopathological
4
histopathological images
4
images data
4
data presented
4
presented article
4
article slide
4
slide imaging
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!