From 3d8236a8c6fe7622b43286b92da438d2d262ba45 Mon Sep 17 00:00:00 2001
From: Richard Osuala <47958412+RichardObi@users.noreply.github.com>
Date: Mon, 27 Nov 2023 23:37:43 +0100
Subject: [PATCH] Update README.md

Update of description of generate function with model 8
---
 README.md | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/README.md b/README.md
index 091b709..df80b7e 100644
--- a/README.md
+++ b/README.md
@@ -85,7 +85,7 @@ Documentation is available at [medigan.readthedocs.io](https://medigan.readthedo
 
 ### Generation example
 #### DCGAN 
-Create mammography masses with labels (malignant or benign) using a cDCGAN model.
+Create mammography masses with labels (malignant or benign) using a class-conditional DCGAN model.
 ```python
 # import medigan and initialize Generators
 from medigan import Generators
@@ -96,7 +96,9 @@ generators = Generators()
 generators.generate(model_id=8, num_samples=8, install_dependencies=True)
 ```
 ![sample](docs/source/_static/samples/c-dcgan/model8_samples.png)
-The generated top row samples are malignant and the bottom row samples benign masses (regions-of-interest of mammograms).
+
+The synthetic images in the top row show malignant masses (breast cancer) while the images in the bottom row show benign masses. 
+Given such images with class information, image classification models can be (pre-)trained.
 
 
 #### CYCLEGAN