README.md

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

### (Lung) Lung Adenocarcinoma

This model can additionally be run on our [pathology reports platform](https://www.pathologyreports.ai/marketplace/browse/40e62b8e-f41b-4ff1-90d8-03940c11068a)

Credits: Dr. Assem Alrumeh

### Introduction

This H&E lung adenocarcinoma 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 lung adenocarcinoma and other surrounding tissue elements.
Annotations were carried out on batches of image tiles (dimensions: 256 x 256 um) grouped using image-based clustering [(HAVOC, DOI: 10.1126/sciadv.adg1894)](https://doi.org/10.1126/sciadv.adg1894) from 10 publicly available TCGA-LUAD H&E-stained whole slide images. Validation testing was carried out on non-overlapping cases from TCGA.


### Classes
1. Adenocarcinoma
2. Blank space
3. Fibroconnective and stromal elements
4. Lung parenchyma
5. Lymphoid tissue
6. Necrosis

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/40e62b8e-f41b-4ff1-90d8-03940c11068a)