Added link to preprocessing script to readme

README.md

@@ -60,7 +60,7 @@ We included csv tables with metadata for all images we used in this repo (`data/
 
 ### Images
 
-To download the corresponding images, log in on the ADNI page, go to "Download" -> "Image Collections" -> "Data Collections". In the box on the left, select "Other shared collections" -> "ADNI" -> "ADNI1:Annual 2 Yr 1.5T" (or the corresponding collection for 3T) and download all images. We preprocessed all images by non-linear registration to a 1 mm isotropic ICBM template via ANTs (http://stnava.github.io/ANTs/) with default parameters. 
+To download the corresponding images, log in on the ADNI page, go to "Download" -> "Image Collections" -> "Data Collections". In the box on the left, select "Other shared collections" -> "ADNI" -> "ADNI1:Annual 2 Yr 1.5T" (or the corresponding collection for 3T) and download all images. We preprocessed all images by non-linear registration to a 1 mm isotropic ICBM template via [ANTs](http://stnava.github.io/ANTs/) with default parameters, using the quick registration script from [here](https://github.com/ANTsX/ANTs/blob/master/Scripts/antsRegistrationSyNQuick.sh). 
 
 To be consistent with the codebase, put the images into the folders `data/ADNI/ADNI_2Yr_15T_quick_preprocessed` (for the 1.5 Tesla images) or `data/ADNI/ADNI_2Yr_3T_preprocessed` (for the 3 Tesla images). Within these folders, each image should have the following path: `<PTID>/<Visit (spaces removed)>/<PTID>_<Scan.Date (/ replaced by -)>_<Visit (spaces removed)>_<Image.ID>_<DX>_Warped.nii.gz`. If you want to use a different directory structure, you need to change the method `get_image_filepath` and/or the filenames in `datasets.py`.