Update README.md

README.md

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-# Segmentation Model Project
-
-**_AI template: Nog invullen_**
+# 5ARIP10 Interdisciplinary team project
 
 ## Introduction
-
-This project is focused on developing a segmentation model. The goal of this model is to classify each pixel in an image into a set of categories.
+This project, conducted in collaboration between Eindhoven University of Technology (TU/e) and Philips, is focused on .......... for the Image Guided Therapy Challenge on Transarterial Chemoembolization (TACE) procedures. The goal of this project ..........
 
 ## Getting Started
 
@@ -20,14 +17,21 @@ Provide step by step series of examples that tell you how to get a development e
 
 Explain how to use your project. Provide examples.
 
-## Contributing
-
-If you would like to contribute, please fork the project, make your changes, and submit a pull request. We will review your changes and approve them if they are of benefit.
-
 ## License
 
-Include information about the license.
+This project is licensed under the MIT License - see the [LICENSE](https://github.com/LucianoDeben/5ARIP10-ITP-T3G3/blob/main/LICENSE) file for details.
 
 ## Acknowledgments
 
-List of people or resources you want to thank or acknowledge.
+We would like to thank the following resources and individuals:
+
+- Our project mentor, Danny Ruijters, for their guidance.
+- Philips, for their collaboration and support in this project.
+- Gopalakrishnan, Vivek, and Golland, Polina for their work on [fast auto-differentiable digitally reconstructed radiographs](https://link.springer.com/chapter/10.1007/978-3-031-23179-7_1). We utilized their [`DiffDRR`](https://github.com/eigenvivek/DiffDRR?tab=readme-ov-file#user-content-fn-1-aa759ff9097582506ce05933e125ab0a): Auto-differentiable DRR rendering and optimization in PyTorch in our project.
+
+## Authors
+This project was developed by:
+
+- Author 1: Crapels, Dhani - [email protected]
+- Author 2: Deben, Luciano - [email protected]
+- Author 3: Bierenbroodspot, Sven - [email protected]