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

### (Breast) Breast Invasive Carcinoma

This model can additionally be run on our [pathology reports platform](https://www.pathologyreports.ai/marketplace/browse/ccbc6666-c7c1-45c4-9a62-e8165603c613)

Credits: Dr. Kiran Jakate

### Introduction

This H&E breast invasive 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 breast invasive 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-BRCA H&E-stained whole slide images. The validation was carried out on non-overlapping cases from TCGA.

### Classes

1. Adipose Tissue
2. Adipose Tissue Interfaced With Another Tissue Type
3. Blank Space
4. Blood Vessel
5. Fibroconnective Tissue
6. Fibrosis
7. Lymph Node Capsule
8. Lymph Node Cortex
9. Lymph node hilum area
10. Nodal Metastatic Carcinoma

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/ccbc6666-c7c1-45c4-9a62-e8165603c613)