clean up README

README.md

@@ -1,76 +1,79 @@
 # pynemaiqpet
 
-python routines to analyze NEMA image quality phantom scans
+Python routines to analyze NEMA image quality phantom scans.
 
 ## Authors
 
 Georg Schramm
 
 ## License
 
-This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details
+This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.
 
 ## Installation
 
-We recommend to use the anaconda python distribution and to create a
-conda virtual environment for pynemaiqpet.
+We recommend using the Anaconda Python distribution to create a conda virtual environment for `pynemaiqpet`.
 
 The installation consists of three steps:
 
-1. (optional, if not done) Installation of anaconda / miniforge python distribution
-   to get the conda / mamba package manager
-2. Creation of the conda virtual environment including the `pynemaiqpet`
-   python package and command line tools from `conda-forge`
+1. **(Optional)** Install the Anaconda or Miniforge Python distribution to gain access to the `conda` or `mamba` package manager.
+2. Create a conda virtual environment and install the `pynemaiqpet` Python package and command-line tools from `conda-forge`.
 
-### Installation of miniforge
+**Note:** _You can also install the package from pypi using pip install, but we recommend the
+installation from conda-forge as explained below._
 
-You can either install anaconda, or use the community driven miniforge
-distribution [here](https://github.com/conda-forge/miniforge)
+### Installation method 1: Anaconda/Miniforge and conda-forge
 
-### Creation of the virtual conda environment and installation of pynemaiqpet
+You can either install Anaconda or use the community-driven Miniforge distribution. Find more information and downloads [here](https://github.com/conda-forge/miniforge).
 
-You can create a virtual conda environment containing the `pynemaiqpet`
-python package and command line tools via:
+### Creation of the Virtual Conda Environment and Installation of pynemaiqpet
 
-```
+To create a virtual conda environment containing the `pynemaiqpet` Python package and command-line tools, run:
+
+```bash
 conda create -c conda-forge -n pynemaiqpet pynemaiqpet
 ```
 
-After installation, activate the environment via
+After installation, activate the environment by running:
 
+```bash
+conda activate pynemaiqpet
 ```
 
-conda activate pynemaiqpet
+### Installation method 2 (not recommended): pypi and pip
+
 ```
+pip install pynemaiqpet
+```
+
+### Test your installation
 
-To test your installation you can execute the following in python
+To test your installation, execute the following commands in Python:
 
 ```python
 import pynemaiqpet
 print(pynemaiqpet.__version__)
 print(pynemaiqpet.__file__)
 ```
 
-or by displaying the help of the command line tool
+Alternatively, you can check the command-line tool's help page:
 
-```
+```bash
 pynemaiqpet_wb_nema_iq -h
 ```
 
-## Run demos
+## Running Demos
 
-To analyze a PET reconstruction of the NEMA WB phantom stored in dicom in
-the folder `my_pet_recon` using the command line tool, you can execute:
+To analyze a PET reconstruction of the NEMA whole-body phantom stored in DICOM format in the folder `my_pet_recon`, use the following command:
 
-```
+```bash
 pynemaiqpet_wb_nema_iq my_pet_recon --output_dir my_pet_recon_results --show --verbose
 ```
 
-You can also apply an additional isotropic Gaussian post filter to the reconstructed
-image, before running the analysis using the `--fwhm_mm` command line argument:
+To apply an additional isotropic Gaussian post-filter to the reconstructed image before analysis, use the `--fwhm_mm` argument. For example, to apply a filter with a full width at half maximum (FWHM) of 5.0 mm:
 
-```
+```bash
 pynemaiqpet_wb_nema_iq my_pet_recon --output_dir my_pet_recon_results_5mm_fwhm_gauss --show --verbose --fwhm_mm 5.0
 ```
 
-**Note:** This github repository contains two example NEMA recons in the [data subfolder](./data).
+**Note:** This GitHub repository contains two example NEMA reconstructions in the [data subfolder](./data).