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README.md

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-license: apache-2.0
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+---
+license: apache-2.0
+tags:
+- vision
+- image-classification
+---
+
+### (Ovarian) Ovarian Carcinoma
+
+This model can additionally be run on our [pathology reports platform](https://www.pathologyreports.ai/marketplace/browse/14b2473e-17f4-4b68-b250-416f06fb20f5)
+
+Credits: Dr. Noor Alsafwani (King Fahd Hospital of the University, Saudi Arabia)
+
+### Introduction
+
+This H&E ovarian carcinoma tissue classifier was developed using transfer learning on a histology optimized version of the VGG19 CNN (DOI: 10.1038/s42256-019-0068-6) and trained to recognize ovarian serous 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) from 8 publicly available TCGA-OV H&E-stained whole slide images. Validation testing was carried out on non-overlapping cases from TCGA.
+
+### Classes
+1. Blank Space
+2. Fatty Tissue
+3. Epithelial Tumor
+4. Fibrous Tissue
+5. Mixture Of Epithelial Tumor And Fibrous Tissue
+6. Necrosis
+7. Normal Ovarian Parenchyma
+8. Tumor edge
+9. Hemorrhage
+
+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/14b2473e-17f4-4b68-b250-416f06fb20f5)