formatting

Signed-off-by: Daniël Nobbe <[email protected]>

Author: DanielNobbe

auto3dseg/README.md

@@ -58,15 +58,15 @@ To further demonstrate the capabilities of **Auto3DSeg**, [here](./tasks/instanc
 
 ## Running With Your Own Data
 
-To run Auto3DSeg on your own dataset, you need to build a `datalist.json` file for your dataset, and run the AutoRunner on it.
+To run Auto3DSeg on your own dataset, you need to build a `datalist.json` file, and pass it to the AutoRunner.
 
 The datalist format is based on the datasets released by the [Medical Segmentation Decathlon](http://medicaldecathlon.com). 
 See the function `load_decathlon_datalist` in `monai/data/decathlon_datalist.py` for a description of the format.
 
 For the AutoRunner, we only need the `training` list in the JSON, it does not use any other fields.
-The `fold` key for each image is not required, as the AutoRunner will automatically create cross-validation folds.
-If you do add the cross-validation folds beforehand, these should align with the number of folds set in the configuration of the AutoRunner (by default 5, see [notebook](notebooks/auto_runner.ipynb)).
-Any other metadata, such as `modality`, `numTraining`, `name`, etc. will not be used by the AutoRunner, but we do recommend using metadata fields to keep track of names and versions of your dataset.
+The `fold` key for each image is not required, as the AutoRunner will automatically create cross-validation folds.  
+If you do add the cross-validation folds beforehand, these should align with the number of folds set in the configuration of the AutoRunner (by default 5, see [notebook](notebooks/auto_runner.ipynb)).  
+Any other metadata, such as `modality`, `numTraining`, `name`, etc. will not be used by the AutoRunner, but we do recommend using metadata fields to keep track of names and versions of your dataset.  
 In short, your `datalist.json` file should look like this:
 
 ```