# Workflow Details

This section describes the Autoafids workflow (i.e. steps taken to produce 
intermediate and final files). Autoafids is a 
[Snakemake](https://snakemake.readthedocs.io/en/stable/) workflow, and thus a 
directed acyclic graph (DAG) that is automatically configured based on a set of 
rules.

## Overall workflow

Below is an image exhibiting the workflow DAG. Each rounded rectangle underneath the modality input row (T1w, T2w, FLAIR, ct) in 
the DAG represents a rule (i.e. some code or script that produces an output), 
with arrows representing the connections (i.e. inputs / outputs) to these rules.

![workflow](../images/dag.png)

### Processing landmark data (AFIDs)
1. Extract fiducial points from the landmark files (.fcsv is supported)
2. Generate a landmark Euclidean distance/probability map with each voxel communicating distance to an AFID of interest

## Train
Currently, we support generating your own models (i.e., training) in a sperate workflow (i.e., afids-cnn: https://github.com/afids/afids-CNN). For more details, see [Known Issues](#known-issues).

## Apply
Use the classic BIDS App syntax to genereate output AFID .fcsv files. For other derivative outputs, the following flags will be supported: 

`--fidqc`: for quality control of landmark prediction in the form of (*html) format

`--regqc`: for quality control of registration on a BIDS dataset and its derivatives (e.g., fMRIPrep or LeadDBS derivative outputs) 

`--stereotaxy`: predicts a .fcsv file with stereotactic targets (e.g., subthalamaic nucelus) also providing AC-PC transform files in the process 

`--charing`: to make use of AFID charting analysis on a given dataset