Use Case:

QIPCM as a sandbox for AI

QIPCM offers solutions for data management and privacy risk reduction for AI studies. All data remains within the secure platform while allowing access and tools to collaborators across the globe.

Altis Labs is an early stage company that develops imaging biomarkers using deep learning to accelerate clinical development of promising cancer therapies.

In order to build, test and validate their deep learning algorithms on datasets from public sources (such as TCIA) as well as from their customers, Altis Labs is using the QIPCM platform to ingest imaging datasets, collect labels, train algorithms on GPU enabled VMs and run testing and validation on the HPC4Health compute cluster.

Only anonymized images are sent to QIPCM, after which they are archived in our safe, secure, and backed-up PACS. Access to these images are logged and made available only to permitted personnel. Permitted personnel can thus log-in to the QIPCM platform to review trial images anytime, from anywhere with internet access.

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Requirement	QIPCM Solution
Image Anonymization and Transfer from Altis Labs customers	Custom pipeline for de-identification and secure transfer from Altis Labs customers to the QIPCM repository
Image transfer from Public data sets	Download and curation into the QIPCM repository
Image QA	Image QA by QIPCM including QA of the meta data to provide summary of adherence to acquisition protocols and anomalous cases.
Centralized Storage with Image Access Logs	Images that pass QA are forwarded to centralized PACS
Remote Connection	QIPCM Virtual Desktop Infrastructure (VMs)
GPU for deep learning	QIPCM access to HPC4health compute cluster
The software of Choice for labelling and feature extraction by Multiple Users	Installation of desired software onto user VMs

Referencing QIPCM in Your Publications

For publications resulting from our services, please acknowledge QIPCM in the Acknowledgements section of your manuscript.

Acknowledgements are an important reflection of our contributions to your published work, and help strengthen our applications for grant funding. We appreciate your acknowledgements!

In general, it is sufficient to reference qipcm.com and/or QIPCM for tracking and reporting purposes. It is not required that Individual team members be named unless they have made a direct scientific contribution to your work that warrants authorship or specific acknowledgement.
To support accurate tracking of core facility usage in publications, please include the following Research Resource Identifier (RRID)*:

– QIPCM – RRID: SCR_027527

* A Research Resource Identifier (RRID) is a unique citation code that enables transparent reporting and recognition of core facilities in published research.