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

### (GI) Gastrointestinal Adenocarcinoma

This model can additionally be run on our [pathology reports platform](https://www.pathologyreports.ai/marketplace/browse/a7d3b949-d1dd-4a5c-bfa7-a9fe3cb8d79a)

Credits: Dr. Mohamed Al-Yousef (King Fahd Hospital of the University, Saudi Arabia)

### Introduction

This H&E colorectal 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 colorectal adenocarcinoma 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 8 publicly available TCGA-COAD H&E-stained whole slide images. Validation testing was carried out on non-overlapping image tiles from the same cases.


### Classes

1. Connective tissue
2. Edge of Tumor
3. Edge Of Tumor And Inflammtory Cells
4. Epithelial Pattern
5. Neoplastic epithelial pattern
6. Inflammatory Cells
7. Mucin
8. Smooth muscle
9. Acute hemorrhage
10. Blank space
11. Necrosis
12. Neoplastic Epithelial Pattern - Signet Ring
14. Non-neoplastic epithelial pattern

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/a7d3b949-d1dd-4a5c-bfa7-a9fe3cb8d79a)