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README.md

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 # Endometrical cancer segmentation
 
-This repository contains trained weigts and exported learner for a residual U-Net trained on the data from the study [Automated segmentation of endometrial cancer on MR images using deep learning](https://link.springer.com/content/pdf/10.1038/s41598-020-80068-9.pdf) with the objective of reproducing the reported results.
+This repository contains weights and exported learner (encapsulates both the model architecture and its trained parameters) for a deep learning model designed to automate the segmentation of endometrial cancer on MR images. 
+Our model utilizes a Residual U-Net architecture, trained on data derived from the study [Automated segmentation of endometrial cancer on MR images using deep learning](https://link.springer.com/content/pdf/10.1038/s41598-020-80068-9.pdf).
+The primary objective of this repository is to reproduce the results reported in the study.
 
 The source code for training and running inference on your own data is available at: https://github.com/MMIV-ML/fastMONAI/tree/master/research/endometrical_cancer.