change to latest tag

so the release number doesn't get out of date -- could have bumpversion change to every latest release, but not sure it is really necessary since the `latest` docker tag always points to the latest versioned release now anyways..

docs/getting_started/docker.md

@@ -10,20 +10,20 @@ Open your Windows Command Prompt by clicking the bottom left `Windows` button an
 
 Pull the container (this will take some time and storage space, but like an installation it only needs to be done once and can then be run on many datasets):
 
-    docker pull khanlab/hippunfold:v1.3.3
+    docker pull khanlab/hippunfold:latest
 
 Run HippUnfold without any arguments to print the short help:
 
-    docker run -it --rm khanlab/hippunfold:v1.3.3    
+    docker run -it --rm khanlab/hippunfold:latest    
 
 Use the `-h` option to get a detailed help listing:
 
-    docker run -it --rm khanlab/hippunfold:v1.3.3 -h
+    docker run -it --rm khanlab/hippunfold:latest -h
 
 Note that all the Snakemake command-line options are also available in
 HippUnfold, and can be listed with `--help-snakemake`:
 
-    docker run -it --rm khanlab/hippunfold:v1.3.3 --help-snakemake
+    docker run -it --rm khanlab/hippunfold:latest --help-snakemake
 
 ## Running an example
 
@@ -47,13 +47,13 @@ ds002168/
 
 Now let's run HippUnfold on the test dataset. Docker will need read/write access to the input and output directories, respectively. This is achieved with the `-v` flag. This 'binds' or 'mounts' a directory to a new directory inside the container.
 
-    docker run -it --rm -v c:\Users\jordan\Downloads\ds002168:/bids -v c:\Users\jordan\Downloads\ds002168_hippunfold:/output khanlab/hippunfold:v1.3.3 /bids /output participant --modality T1w -n
+    docker run -it --rm -v c:\Users\jordan\Downloads\ds002168:/bids -v c:\Users\jordan\Downloads\ds002168_hippunfold:/output khanlab/hippunfold:latest /bids /output participant --modality T1w -n
 
 Explanation: 
 
 `-v c:\Users\jordan\Downloads\ds002168:/bids` tells Docker to mount the directory `c:\Users\jordan\Downloads\ds002168` into a new directory inside the container named `/bids`. We then do the same things for our output directory named `ds002168_hippunfold`, which we mount to `/output` inside the container. These arguments are not specific to HippUnfold but rather are general ways to use Docker. You may want to familiarize yourself with [Docker options](https://docs.docker.com/engine/reference/run/).
 
-Everything after we specified the container (`khanlab/hippunfold:v1.3.3`) are arguments to HippUnfold itself. The first of these arguments (as with any BIDS App) are the input directory (`/bids`), the output directory (`/output`), and then the analysis level (`participant`). The `participant` analysis 
+Everything after we specified the container (`khanlab/hippunfold:latest`) are arguments to HippUnfold itself. The first of these arguments (as with any BIDS App) are the input directory (`/bids`), the output directory (`/output`), and then the analysis level (`participant`). The `participant` analysis 
 level is used in HippUnfold for performing the segmentation, unfolding, and any
 participant-level processing. The `group` analysis is used to combine subfield volumes
 across subjects into a single tsv file.  The `--modality` flag is also required, and describes which image we use for segmentation. Here we used the T1w image. We also used the `--dry-run/-n`  option to just print out what would run, without actually running anything.
@@ -68,7 +68,7 @@ useful if you are running multiple subjects.
 Running the following command (hippunfold on a single subject) may take ~30 minutes if you have 8 cores, shorter if you have more 
 cores, but could be much longer (several hours) if you only have a single core.
 
-    docker run -it --rm -v c:\Users\jordan\Downloads\ds002168:/bids -v c:\Users\jordan\Downloads\ds002168_hippunfold:/output khanlab/hippunfold:v1.3.3 /bids /output participant --modality T1w -p --cores all
+    docker run -it --rm -v c:\Users\jordan\Downloads\ds002168:/bids -v c:\Users\jordan\Downloads\ds002168_hippunfold:/output khanlab/hippunfold:latest /bids /output participant --modality T1w -p --cores all
 
 After this completes, you should have a `ds002168_hippunfold` directory with outputs for the one subject.
 
@@ -79,7 +79,7 @@ in the BIDS test dataset, you can use the `--modality T2w` option. In this case,
 test dataset has a limited FOV, we should also make use of the `--t1-reg-template` command-line option,
 which will make use of the T1w image for template registration, since a limited FOV T2w template does not exist.
 
-    docker run -it --rm -v c:\Users\jordan\Downloads\ds002168:/bids -v c:\Users\jordan\Downloads\ds002168_hippunfold_t2w:/output khanlab/hippunfold:v1.3.3 /bids /output participant --modality T2w --t1-reg-template -p --cores all
+    docker run -it --rm -v c:\Users\jordan\Downloads\ds002168:/bids -v c:\Users\jordan\Downloads\ds002168_hippunfold_t2w:/output khanlab/hippunfold:latest /bids /output participant --modality T2w --t1-reg-template -p --cores all
 
 Note that if you run with a different modality, you should use a separate output directory, since some of the files 
 would be overwritten if not.