State of the Practice for Medical Imaging Software

TL;DR

This study evaluates the current state of medical imaging software, ranking top tools, identifying gaps in practices like testing and documentation, and proposing strategies for improvement based on developer interviews.

Contribution

It provides a comprehensive assessment of medical imaging software practices, ranking tools, and offering actionable recommendations to enhance software quality and development processes.

Findings

Top-ranked software: 3D Slicer, ImageJ, Fiji, OHIF Viewer

High documentation compliance (88%) and version control usage (100%)

Low adoption of continuous integration (17%) and unit testing (50%)

Abstract

We selected 29 medical imaging projects from 48 candidates, assessed 10 software qualities by answering 108 questions for each software project, and interviewed 8 of the 29 development teams. Based on the quantitative data, we ranked the MI software with the Analytic Hierarchy Process (AHP). The four top-ranked software products are 3D Slicer, ImageJ, Fiji, and OHIF Viewer. Generally, MI software is in a healthy state as shown by the following: we observed 88% of the documentation artifacts recommended by research software development guidelines, 100% of MI projects use version control tools, and developers appear to use the common quasi-agile research software development process. However, the current state of the practice deviates from the existing guidelines because of the rarity of some recommended artifacts, low usage of continuous integration (17% of the projects), low use of unit testing (about 50% of projects), and room for improvement with documentation (six of nine developers felt their documentation was not clear enough). From interviewing the developers, we identified five pain points and two qualities of potential concern: lack of development time, lack of funding, technology hurdles, ensuring correctness, usability, maintainability, and reproducibility. The interviewees proposed strategies to improve the state of the practice, to address the identified pain points, and to improve software quality. Combining their ideas with ours, we have the following list of recommendations: increase documentation, increase testing by enriching datasets, increase continuous integration usage, move to web applications, employ linters, use peer reviews, design for change, add assurance cases, and incorporate a "Generate All Things" approach.