---
license: apache-2.0
tags:
- vision
- image-classification
---

### (Kidney) Clear Cell Renal Carcinoma

This model can additionally be run on our [pathology reports platform](https://www.pathologyreports.ai/marketplace/browse/030d4c12-609d-457c-b3ba-d70d3caf129d)

Credits: Dr. Phedias Diamandis (University of Toronto, Canada)

### Introduction

This H&E clear cell carcinoma tissue classifier was developed using transfer learning on a histology optimized version of the VGG19 CNN [(DOI: 10.1038/s42256-019-0068-6)](https://doi.org/10.1038/s42256-019-0068-6) and trained to recognize clear cell and papillary renal cell carcinoma and other surrounding tissue elements.

Annotations were carried out on batches of image tiles (dimensions: 512 x 512 px) grouped using image-based clustering [(HAVOC, DOI: 10.1126/sciadv.adg1894)](https://doi.org/10.1126/sciadv.adg1894) from 5 publicly available TCGA-KIRP and 27 publicly available TCGA-KIRC H&E-stained whole slide images. The validation was carried out on non-overlapping cases from TCGA.

### Classes

1. Adipose Tissue
2. Blank space
3. Clear Cell Renal Cell Carcinoma
4. Cyst Content
5. Fibrocollagenous Tissue
6. Hemorrhage
7. Inflammation
8. Marker
9. Necrosis
10. Renal Parenchyma

This information can be found in the inference.json file

### Evaluation Metrics

Classifier validation can be found on the [pathology reports platform](https://www.pathologyreports.ai/marketplace/browse/030d4c12-609d-457c-b3ba-d70d3caf129d)