Anonymization and data transport
Generally we use the Clinical Trial Processor (CTP) for anonymization, secure data transport and allocating data to a project. CTP allows the creation of processing pipelines for DICOM scans, in which scans are received, processed and forwarded to another DICOM receiver.
Medical imaging data storage using XNAT
At the heart of the infrastructure is the storage of the medical images. For
this we use XNAT, software for a research
medical image archive created by
the Washington University in St. Louis. We host our own servers within our
institute, but also maintain the Dutch national XNAT server hosted by
CTMM-TraiT. We also created and maintain a Python library to communicate
with XNAT called xnatpy.
XNAT is used to standardize the image storage, making it easier to automate. XNAT also allows for Poject based data access management.
In medical imaging the extraction of a biomarker from an image is mostly not a single step, but an entire processing pipeline. To formalize these pipelines and help executing them in a consistent manner on compute clusters or the cloud, we created the fastr workflow software. To track the progress and status of complex pipelines our colleagues in the Leiden University Medical Center (LUMC) created the Pipeline Inspection and Monitoring (PIM) platform.
Data and workflow management services
The data and workflow management services are a collection of tools and services to manage the data flow, including manual interaction with the data, in an automated fashion. The key components are the Study Governor for automatically managing the data flow and the Task Supervisor for task based manual interaction with the data.
Manual inspection and annotation tasks
The is ViewR is a tool to interact with the data on XNAT by researchers based on the tasks served by the tasksupervisor. The layout and forms in the ViewR are determined by templates supplied by the tasksupervisor. This way the ViewR adapts itself for the task to be performed.