# Deep Learning–Based Segmentation and Quantification in Experimental Kidney Histopathology

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/deep-learning-based-segmentation-and-quantification-in-experimental-kidney/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Nassim Bouteldja,Barbara M. Klinkhammer,Roman D. Bülow,Patrick Droste,Simon Otten,Saskia von Stillfried,Julia Moellmann,Susan Sheehan,Ron Korstanje,Sylvia Menzel,Peter Bankhead,Matthias Mietsch,Charis Drummer,Michael Lehrke,Rafael Kramann,Jürgen Floege,Peter Boor,Dorit Merhof |
| Citations | 182 |
| DOI | 10.1681/asn.2020050597 |
| Fields | Computer Science |
| Open Access | true |
| OA Status | green |
| OA URL | https://pure.eur.nl/en/publications/feb14945-07ac-4985-af82-3574107b91c9 |
| OpenAlex ID | https://openalex.org/W3095093830 |
| PMID | 33154175 |
| Type | article |
| Year | 2020 |

## Paper authors

- [Jürgen Floege](https://scholariq.org/researchers/jurgen-floege-2/)

## Paper journal

- [Journal of the American Society of Nephrology](https://scholariq.org/journals/journal-of-the-american-society-of-nephrology/)

## Paper primary topic

- [AI in cancer detection](https://scholariq.org/topics/ai-in-cancer-detection/)

## Paper topics

- [AI in cancer detection](https://scholariq.org/topics/ai-in-cancer-detection/)
- [Digital Imaging for Blood Diseases](https://scholariq.org/topics/digital-imaging-for-blood-diseases/)
- [Medical Image Segmentation Techniques](https://scholariq.org/topics/medical-image-segmentation-techniques/)

---
Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.