Update README.md

Author: mvdoc

README.md

@@ -1,53 +1,71 @@
-# CaseForge automated pipeline
+# An automated pipeline to create subject-specific headcases for fMRI scanning
 
-## Requirements
+This repository contains an automated pipeline to create subject-specific headcases for fMRI scanning. Headcases reduce subject motion ([Power et al., 2019](https://pubmed.ncbi.nlm.nih.gov/30639840/)), increase subject's comfort, and facilitate consistent head positioning across multiple scanning sessions. 
 
-Python requirements are listed under `requirements.txt`. You can install them with
+The pipeline takes as an input a 3D model of the participant's head and generates STL files of the headcases for 3D printing. This pipeline has been  tested only with a [Structure Sensor](https://structure.io/structure-sensor-pro), but we think other sensors may be used.
 
-```bash
-pip install -r requirements.txt
-```
-
-We also provide a conda environment file that you can try to use. The
-environment was created on Ubuntu, so it will likely not work on other
-operating systems. You can install the environment from the conda environment
-file with
+Headcases can be generated for the following head coils: 
+- Siemens 32 channel
+- Siemens 64 channel
+- Nova 32 channel
 
-```bash
-conda env create -f conda-environment.yml --name headcase
-```
+The pipeline is written in Python and uses [MeshLab](https://www.meshlab.net/) and [Blender](https://www.blender.org/). 
 
-In addition, the code requires
-
-- Blender 2.7.9. **Do not use newer versions of Blender. The code will not work.**
-- Meshlab (the code works with meshlab 1.3.2 and it has not been tested with other versions)
 
 ## Usage
 
-You need to use a structure sensor to generate a head model of the subject. Use the iOS app to send the model over email. Save the `Model.zip` file, then use `make_headcase.py` as
+The basic [Structure Scanner iOS app](https://apps.apple.com/us/app/scanner-structure-sdk/id891169722) can be used to scan a 3D model of the participant's head. For recommendations on how to scan the participant's head, see [this document](docs/glab_headcase_pipeline.md). From the Scanner app, the 3D model file (`Model.zip`) will need to be sent to an email address.
+
+The pipeline can then be used to generate a headcase with
 
 ```bash
 python make_headcase.py Model.zip Headcase.zip --headcoil s32
 ```
 
-This will generate a headcase model split into four parts and zipped in `Headcase.zip`. It is possible to generate headcases for the Siemens 32ch head-coil (`--headcoil s32`), Siemens 64ch head-coil (`--headcoil s64`), or Nova 32ch head-coil (`--headcoil n32`).
+Several options are available, including whether the headcase should be split in two parts (front and back) or in four parts (front-top, front-bottom, back-top, back-bottom). Four parts (the default) can be printed more easily on most 3D printers, but they might require gluing together the top and bottom parts. To see all options, run
+
+```bash
+python make_headcases.py --help
+```
+
+## Running with Docker
 
-### Running with docker
+We recommend running the pipeline with the Dockerfile provided in this repository.
 
-We provide a Dockerfile to generate an image with all dependencies. Create the image with
+First, the docker image needs to be built.
 
 ```bash
 docker build --tag caseforge .
 ```
 
-then you can run the pipeline as
+Then, the pipeline can be run with
 
 ```bash
 docker run --rm caseforge:latest --help
 ```
 
-To let docker see the folder with the head model, you will have to bind the folder inside the container. For example, if the head model is in `/tmp/test-headcase/model.zip`, you would run the following command
+To let docker see the folder containing the head 3D model, you will have to bind the folder inside the container. For example, if the head model is in `/tmp/test-headcase/model.zip`, the following command should be run
 
 ```bash
 docker run -v /tmp:/tmp --rm caseforge:latest /tmp/test-headcase/model.zip /tmp/test-headcase/case.zip
 ```
+
+## Manual installation
+
+Python requirements are listed under `requirements.txt`, and can be installed with
+
+```bash
+pip install -r requirements.txt
+```
+
+We also provide a conda environment file. The environment was created on Ubuntu, so it might not work on other operating systems. 
+The environment can be installed with 
+
+```bash
+conda env create -f conda-environment.yml --name headcase
+```
+
+The pipeline also requires
+
+- Blender 2.7.9 (**Do not use newer versions of Blender, or the pipeline won't work.**)
+- MeshLab 1.3.2 (**The pipeline has been tested only with this version.**)