A Community-Driven Validation Service for Standard Medical Imaging Objects

Digital medical imaging laboratories contain many distinct types of equipment provided by different manufacturers. Interoperability is a critical issue and the DICOM protocol is a de facto standard in those environments. However, manufacturers' implementation of the standard may have non-conformities at several levels, which will hinder systems' integration. Moreover, medical staff may be responsible for data inconsistencies when entering data. Those situations severely affect the quality of healthcare services since they can disrupt system operations. The existence of software able to confirm data quality and compliance with the DICOM standard is important for programmers, IT staff and healthcare technicians. Although there are a few solutions that try to accomplish this goal, they are unable to deal with certain situations that require user input. Furthermore, these cases usually require the setup of a working environment, which makes the sharing of validation information more difficult. This article proposes and describes the development of a Web DICOM validation service for the community. This solution requires no configuration by the user, promotes validation results share-ability in the community and preserves patient data privacy since files are de-identified on the client side.Comment: Computer Standards & Interfaces, 201

Using Dashboard Networks to Visualize Multiple Patient Histories: A Design Study on Post-operative Prostate Cancer

In this design study, we present a visualization technique that segments patients' histories instead of treating them as raw event sequences, aggregates the segments using criteria such as the whole history or treatment combinations, and then visualizes the aggregated segments as static dashboards that are arranged in a dashboard network to show longitudinal changes. The static dashboards were developed in nine iterations, to show 15 important attributes from the patients' histories. The final design was evaluated with five non-experts, five visualization experts and four medical experts, who successfully used it to gain an overview of a 2,000 patient dataset, and to make observations about longitudinal changes and differences between two cohorts. The research represents a step-change in the detail of large-scale data that may be successfully visualized using dashboards, and provides guidance about how the approach may be generalized

Visually Characterizing Source Code Changes

International audienceRevision Control Systems (e.g., SVN, Git, Mercurial) include automatic and advanced merging algorithms that help developers to merge their modifications with development repositories. While these systems can help to textually detect conflicts, they do not help to identify the semantic consequences of a change. Unfortunately, there is little support to help release masters (integrators) to take decisions about the integration of changes into the system release. Most of the time, the release master needs to read all the modified code, check the diffs to build an idea of a change, and dig for details from related unchanged code to understand the context and potential impact of some changes. As a result, such a task can be overwhelming. In this article we present a visualization tool to support integrators of object-oriented programs in comprehending changes. Our approach named Torch characterizes changes based on structural informa- tion, authors and symbolic information. It mixes text-based diff information with visual representation and metrics characterizing the changes. The current implementation of our approach analyses Smalltalk programs, and thus we de- scribe our experiments applying it to Pharo, a large open-source system. We also report on the evaluations of our approach by release masters and developers of several open-source projects