Merge pull request #173 from AustralianCancerDataNetwork/softwarex

Add SoftwareX details

Author: pchlap

CITATION.cff

@@ -4,8 +4,7 @@
 cff-version: 1.2.0
 title: PyDicer
 message: >-
-  If you use this software, please cite it using the
-  metadata from this file.
+  If you use this software, please cite our SoftwareX article.
 type: software
 authors:
   - given-names: Phillip
@@ -23,8 +22,6 @@ authors:
   - given-names: Xinyi
     family-names: Cui
     affiliation: University of New South Wales
-  - given-names: Shuchao
-    family-names: Pang
   - given-names: Shrikant
     family-names: Deshpande
     affiliation: South Western Sydney Local Health District
@@ -43,3 +40,31 @@ keywords:
 license: Apache-2.0
 version: 0.2.0
 date-released: "2023-12-20"
+preferred-citation:
+  authors:
+  - family-names: Chlap
+    given-names: Phillip
+    orcid: "https://orcid.org/0000-0002-6517-8745"
+  - given-names: Daniel
+    family-names: Al Mouiee
+  - family-names: Finnegan
+    given-names: Robert N.
+    orcid: "https://orcid.org/0000-0003-4728-8462"
+  - given-names: Janet
+    family-names: Cui
+  - given-names: Chin
+    family-names: Vicky
+  - given-names: Deshpande
+    family-names: Shrikant
+  - given-names: Holloway
+    family-names: Lois
+  date-published: "2024-12-14"
+  doi: 10.1016/j.softx.2024.102010
+  journal: SoftwareX
+  publisher:
+    name: Elsevier
+  title: "PyDicer: An open-source python library for conversion and analysis of radiotherapy DICOM data"
+  type: article
+  url: "https://doi.org/10.1016/j.softx.2024.102010"
+  volume: 29
+  year: 2025

README.md

@@ -1,5 +1,7 @@
 # PyDicer: PYthon Dicom Image ConvertER
 
+[![SoftwareX](https://img.shields.io/badge/SoftwareX-10.1016/j.softx.2024.102010-green.svg)](https://doi.org/10.1016/j.softx.2024.102010)
+
 Welcome to PyDicer, a tool to ease the process of converting Radiotherapy DICOM data objects into a format typically used for research purposes. In addition to data conversion, functionality is provided to help analyse the data. This includes computing radiomic features, radiotherapy dose metrics and auto-segmentation metrics. PyDicer uses the NIfTI format to store data is a well defined file system structure. Tracking of these data objects in CSV files, also stored on the file system, provides an easy and flexible way to work with the converted data in your research.
 
 The [PyDicer documentation](https://australiancancerdatanetwork.github.io/pydicer/index.html) provides several examples and guides to help you get started with the tool. Here are a few **PyDicer principles** to keep in mind as you get started:
@@ -38,6 +40,9 @@ PyDicer will place converted and intermediate files into a specific directory st
 - `[working]/.pydicer`: Intermediate files as well as log output will be stored in here
 - `[working]/[dataset_name]`: Clean datasets prepared using the Dataset Preparation Module will be stored in a directory with their name and will symbolically link to converted in the `[working]/data` directory
 
+![PyDicer Working Directory structure](assets/pydicer-working-directory-structure.png)
+*PyDicer working directory structure ([Chlap, P. et al. SoftwareX](https://doi.org/10.1016/j.softx.2024.102010))*
+
 ## Pipeline
 
 The pipeline handles fetching of the DICOM data to conversion and preparation of your research dataset. Here are the key steps of the pipeline:
@@ -82,6 +87,12 @@ pydicer.add_input(dicom_directory)
 pydicer.run_pipeline()
 ```
 
+## How to Cite
+
+If you make use of PyDicer within your research work, please consider citing our SoftwareX paper:
+
+**Chlap P, Al Mouiee D, Finnegan RN, et al. PyDicer: An open-source python library for conversion and analysis of radiotherapy DICOM data. *SoftwareX*. 2025;[29:102010. doi:10.1016/j.softx.2024.102010](https://doi.org/10.1016/j.softx.2024.102010)**
+
 ## Contributing
 
 PyDicer is an open-source tool and contributions are welcome! Here are some ways you might consider contributing to the project: