Update README.md

README.md

@@ -26,6 +26,7 @@ Biobank-scale imaging provides a unique opportunity to characterise structural a
 ## Model Details
 
 During this research, the original [DiffAE](https://diff-ae.github.io/) model was adapted and extended for 3D to create the 3D DiffAE model, and was trained on the CINE Cardiac Long-axis 4-chamber view MRIs from UK Biobank dataset using 5 different seeds. This model can be used to infer latent representations from similar cardiac MRIs, or can also be used as pretrained models and then fine-tuned on other datasets or tasks. 
+This model can also be used to generate synthetic cardiac MRIs similar to the training set. 
 
 ### Model Description
 
@@ -33,6 +34,8 @@ During this research, the original [DiffAE](https://diff-ae.github.io/) model wa
 - **Task:** Obtaining latent representation from 3D input volumes
 - **Training dataset:** [CINE Cardiac Long-axis 4-chamber view MRIs from UK Biobank](https://biobank.ctsu.ox.ac.uk/crystal/field.cgi?id=20208)
 - **Training seed:** 1701
+- **Input:** 3D MRI (2D over time), intensity normalised (min-max, followed by z-score with 0.5 mean and std)
+- **Output:** 128 latent factors. Can also be used for generating synthetic MRIs.
 
 ### Model Sources