Update README.md

README.md

@@ -110,6 +110,37 @@ After extraction, the dataset can be accessed using libraries supporting OME-Zar
 * `ome-zarr-py`
 * `dask`
 
+### Example: Loading sample slices using zarr
+
+Below is a minimal example demonstrating how to load and access slices from a single sample.
+
+```python
+import zarr
+
+# Open a sample from the training split
+z = zarr.open("ome/train/Bamboo_A_bin1x1_ome_1.zarr", mode="r")
+
+# Visualize zarr store
+print(z.tree())
+
+# High-resolution slice
+img_hr = z["HR/0"][1000, :, :]
+
+# Registered low-resolution slice (4x resolution difference)
+img_reg = z["REG/0"][250, :, :]
+
+# Unregistered low-resolution slice
+img_lr = z["LR/0"][1000, :, :]
+```
+
+### Notes
+
+* Volumes are stored in (D, H, W) format, with the first dimension (`D`) corresponding to the slice index
+* Resolution scales for each scan are available via levels 0-3 (`HR/1`, `HR/2`, etc.)
+
+⚠️ Be careful with loading full volumes, as this may exceed system memory
+
+
 ## Intended Use
 
 VoDaSuRe is designed for:
@@ -120,7 +151,7 @@ VoDaSuRe is designed for:
 
 ## Dataset Creation
 
-The dataset was created using **laboratory CT (Lab-CT) imaging systems**, capturing paired high- and low-resolution volumetric scans under varying acquisition conditions.
+The dataset was created by paired high- and low-resolution volumetric acquisition using Lab-CT.
 
 Further details are available in the associated paper and project page.