Four AI Workflow Trends from RSNA 2019

The Biggest Trend: Maturing Implementation of AI

Attendees who visited our booth last year were interested in learning about AI capabilities. This year they were bringing questions about implementing infrastructure needed for AI and how to scale AI research in their organizations. Scaling access to clinical data and interoperability appears to be a rising concern this year. Organizations are also gradually accepting cloud scaling as a secure option.

Radiologists are beginning to plan for AI in their standard workflows. There were many radiologists in our booth asking questions with respect to AI research in their current clinical workflows.

Data Curation for Research Still Falls Short

The focus in many workshops and presentations from radiologists was “data wrangling” and data set quality. We received many questions from attendees regarding metadata management and labelling tools. At the same time there is growing recognition that clinical systems don’t meet the needs of the research and AI development communities. Additionally, an entirely new class of solution that supports the research workflow is needed.

We recommend Dr. Paul Chang’s (University of Chicago) AuntMinnie interview during RSNA: “AI is like a great car … Most cars still need gas and roads. In the context of this analogy, gas is vetted data and the road is workflow orchestration that is AI-enabled... The only way to make a transformative technology real is to do the boring stuff, the infrastructure stuff.”

Everyone Noticed the Busy AI Showcase

The AI Showcase was very active this year. In 2018, there were roughly 70 vendors in the AI Showcase, but this year there were 129, including many international AI vendors. We noticed growth in AI development for cardiac and brain imaging.

It’s Imminent: Equipment Vendors are Integrating AI Workflows

AI is moving beyond the desktop as imaging equipment manufacturers have their eye on supporting research workflows. Leading equipment manufacturers like Philips and Canon displayed developments in their interfaces to support AI or analysis tools in a disease specific applications. Flywheel is expanding partnerships with AI vendors and equipment vendors in addition to supporting clients performing imaging and clinical research.

CEO Travis Richardson presenting at the Google Cloud Booth about Flywheel’s scalable infrastructure for machine learning.

Four Takeaways from BioData World West 2019

BioData World West wrapped up its third year! A mix of experts from industry, academia, and government mingled and mused on the data management supporting the healthcare industry.

Below are the insights from our own Chief Technology Officer, Gunnar Schaefer and Director of Sales, Marco Comianos, who attended.

Gunnar Schaefer, Co-Founder and CTO of @Flywheel_io presents on scaling medical imaging and machine learning in clinical research

Share quality data within your organization

The main focus among conversations at BioData this year was making data accessible across departments and organizations. Letting data flow freely between labs in life sciences organizations creates a feedback loop from health network partners and previously unprofitable drug trials. In health networks, data scientists can highlight opportunities where patients are underserved to create better experiences and processes that can be streamlined to cut costs.

When these different sources of data are merged, unconventional combinations of biomedical data can point to obscure patterns of disease. Scientists from organizations like GenomeAsia, Sidra Medicine, and AstraZeneca presented their findings from blending microbiome and genetic research, genotypic and phenotypic data, and imaging and text data. 

In order for machine learning to power artificial intelligence applications, data must be routed, organized, cleaned, and standardized from the moment of creation. More important than proper data storage is the ability to query a system over and over for renewed insight. Genentech introduced the need to store data so it is FAIR: findable, accessible, interoperable, and reusable. That way, data are ripe for query and can integrate together for analysis. 

However, it’s important to remember that no matter how well sources are linked together, data must be high-quality and machine learning investigations must be ethically supervised. As Faisal Khan of AstraZeneca put it: “Tortured data will confess to anything.” 

Looking forward, expect life sciences companies to adopt better data principles in their data strategies, refine what’s working already, and search for software that bridges the gaps.

Being precise about requirements for precision medicine

Much of the groundwork for precision medicine is now being laid, though mostly in oncology. At BioData, speakers gave direction for its high-value applications. 

Today’s genomics research can treat previously-untreated rare diseases. A panel addressed how data sharing must accompany public genomic projects to optimize therapeutic development for rare diseases. Presenters also reported on diversifying the pools for large genome projects. On the treatment side, analysts explained methods to match an individual’s genomic profile with one out of many pre-existing drugs, saving time for patients facing debilitating diseases. 

These advancements require access to large amounts of data with well-defined interoperability. Looking forward, expect the general hype around precision medicine to fade, making way for discussions about infrastructure which enable answers to disease-specific precision questions.

Machine learning shortens both ends of drug trials

Beyond the potential for drug discovery using genetic markers, algorithms were showcased which had correctly predicted the pharmacokinetics and effectiveness of drug compounds. Not only does this technology assist researchers and cut costs for developing compounds or finding targets, once therapies are in clinical trials, AI can predict the likelihood of certain subpopulations having an adverse reaction to a drug. Clinical trial pools normally miss these portions of the population, which can result in a public perception crisis. 

Looking forward, expect to see AI use with historical clinical data and patient data becoming a competitive factor in shortening the time horizon for successful drug launches. We’ll also see  which AI vendors become the most productive partners for life sciences organizations.

AI specialists come ready to partner

If data scientists hold some healthy skepticism of practically applying machine learning, AI specialists showed up with the energy to compensate. AI specialists are drawing talent from universities to specialize in anatomical regions. Companies in this vertical are also starting to partner with each other to complement their deep expertise in one region.

Many AI companies at BioData specialize in genomics and digital slide pathology, so look forward to development and consolidation in this field. Fewer imaging analysis companies were present at BioData - stay tuned for the imaging market insights yet to come out of RSNA!

At RSNA’s Annual Meeting, Flywheel will be exhibiting from December 1st to December 5th in the AI Showcase. Schedule a demo and find us at booth #11618.

Flywheel Exhibiting and Presenting at RSNA 2019: Bioinformatics Platform for AI Research

On December 1-6, 2019, Flywheel is speaking at the Annual Meeting of the Radiological Society of North America (RSNA) at McCormick Place in Chicago, Illinois. CEO Travis Richardson is presenting on Flywheel’s “Comprehensive Bioinformatics Platform for AI Research” as part of the RSNA 2019 program at 11:30 am on Thursday, Dec. 5th in the AI Theater. Throughout the week, Flywheel is welcoming visitors at Booth 11618 in the AI Showcase. To arrange for a private meeting onsite connect with us here!


[Image: CEO, Travis Richardson presenting]

Outdated imaging work processes block AI implementation

In the presentation, Richardson describes the challenges at research hospitals and life sciences organizations to prepare large volumes of imaging data for daily application and artificial intelligence (AI) research. He provides an overview of gaps in PACS, VNAs, and file server systems. Specifically, Richardson details current inabilities to efficiently access data, curate it, search by metadata, and scale large activities to the cloud, like algorithm training and computation.

Richardson reveals how Flywheel addresses these problems in a multi-modal data infrastructure platform that ingests, standardizes, validates, and searches data. Compatible data types include DICOM, FHIR, HL7, biomarker data, and tabular data like genomics through Flywheel’s partnerships with Google Cloud Healthcare API, Google Cloud AutoML, and Google Big Query.

The presentation is of interest to radiologists, imaging lab directors, principal investigators (PIs), and life science teams seeking to avoid IT bottlenecks and improve the speed of imaging AI and scientific discovery.

At RSNA 2019, Flywheel lays the groundwork for biomedical data sharing and machine learning

Flywheel provides a collaborative workflow for imaging research compliant with the requirements of the Food and Drug Administration (FDA), Institutional Review Boards (IRBs), the Health Information Privacy and Portability Act (HIPPA) and General Data Privacy Regulation (GDPR). Inside the Flywheel platform, users create specific imaging research workflows and projects from the curated data. Flywheel also automates reproducibility as required for funding by the National Institute of Health (NIH).

What is RSNA? RSNA 2019 Annual Meeting is the largest radiology conference in the world, showcasing new technologies such as applications for AI. It brings together radiologists, healthcare professionals, hospital administrators, biomedical clinical engineers, IT managers, physicians, and scientists from 115 countries. Flywheel’s presence, among other RSNA 2019 Chicago exhibitors, will facilitate conversations involving multiple disciplines.

Flywheel team members are looking forward to hearing about projects and data governance initiatives and to share their insights into solving biomedical and clinical data challenges.

Building Blocks of Imaging AI Use Case: Flywheel delivers presentation at BioData World West 2019

Oct., 10-11, 2019, Hilton San Diego Resort and Spa, San Diego, California– Flywheel Exchange, is sponsoring a demonstration in booth 14, and an imaging AI use case presentation “Scaling Medical Imaging and Machine Learning in Clinical Research: Data Management, Curation, Computational Workflows” at Bio-Data West 2019. To arrange for a private meeting onsite connect with us here!

The Imaging AI use case presentation by Flywheel CEO, Travis Richardson, describes a framework for a scientific workflow which manages imaging data.  The presentation by Richardson addresses creating standardization of imaging data and metadata from multiple, disparate data repositories. 

Specifically, the presentation walks through managing historical clinical trial imaging data sets, located in a variety of repositories, including: vendor neutral archives (VNAs), picture archiving and communication systems (PACS), file servers, cloud servers, thumbdrives, or even DVDs. Moreover, Richardson reviews the Imaging AI use case challenge of bulk upload ingest of imaging data and metadata, as well as automated validation of an organization’s unique DICOM imaging data and metadata files, structures, and formatting. Also, Richardson reviews how the ingested, standardized, and validated imaging data and metadata is then searchable enabling easy construction of new data sets and training models for future imaging AI training models and research projects. 

Imaging AI use case: compliance, automation and reproducibility

Key to the case study is the Flywheel imaging infrastructure platform. Flywheel exchange provides a collaborative workflow, compliant with the requirements of Institutional Review Boards (IRBs), the Health Information Privacy and Portability Act (HIPPA) and General Data Privacy Regulation (GDPR). Flywheel also automates reproducibility as required for funding by the National Institute of Health (NIH).   

The presentation is of interest to scientific workflow researchers, principal investigators (PIs), imaging lab and center directors, and life science teams seeking to avoid IT bottlenecks, improve the efficiency and speed of imaging AI and research scientific discovery. 

BioData West 2019, as an expo which includes biomedical imaging, data, clinical and research professionals as well as AI & big data, alongside start-ups, growth firms, and Fortune 100 life science organizations, the presentation at BioData West 2019 will facilitate conversations across disciplines.

Flywheel Exchange team members are looking forward to hearing about projects and initiatives, as well as to share their recent insights into biomedical imaging , infrastructure, and solving unique imaging AI challenges.

CMRR High Field Workshop 2017

Flywheel is happy to be a silver sponsor of the University of Minnesota's 2017 Workshop on High and Ultra-high Field Imaging and Training Workshop. This biennial event is organized and hosted by the Center for Magnetic Resonance Research (CMRR).

Under Dr. Kamil Ugurbil’s leadership, this scientific gathering brings together top researchers from top universities and academic institutions from around the world to disseminate and discuss the technical issues and applications of Magnetic Resonance Imaging (MRI)  and Magnetic Resonance Spectroscopy(MRS) conducted with high magnetic fields (≥ 3 T). Presentations from experts in the major areas of high field MR research will cover fundamental principles, methodology, and biomedical applications in the brain as well as the other organ systems in the body. The auditorium is standing-room only and simulcasted into spillover rooms in the facility.

The workshop also includes poster sessions and training courses covering topics such as Imaging Methods for the Connectome Projects, High-Field Parallel Transmission and Engineering, and MR Spectroscopy. Click here for a detailed program.

Alongside other sponsors such as Siemens Healthineers, GE Healthcare, Bruker, and skope, we take honor in providing researchers with the tools necessary to move research into the computational age.  

DockerCon 2017 Highlights

Flywheel leverages Docker heavily for software distribution and algorithm sharing and execution. I had the pleasure of attending Dockercon ‘17, and there were two presentations I’d like to highlight. One is validation that “containers” is an accepted method to achieve shared data processing goals. The other relates to progress on making the Docker image distribution story more consistent in China.

Cool Genes: The Search for a Cure Using Genomics, Big Data and Docker

James Lowey, CIO at Translational Genomics Research Institute (TGEN), presented the system they designed based upon their needs to effectively deal with the genetic data they process to provide more effective treatments for patients

Data Management

One of James’  starting slides reminds me of one we use. A ceiling-high pyramid of storage media that looks like it is about to topple. Everyone agrees there is value in these troves of unmanaged data. In many cases, the cost of using it is too high due to:

  • Low confidence of finding the data of interest, and that the contents match our memory.
  • Loss of institutional knowledge of what data is available, or how to access it.
  • Effort to retrieve a small bit of data across the whole set for broad analysis
  • Changing standards over time for file formats, organization, compression.

Once you have Data Management, you are able to leverage the Docker ecosystem for the benefit of healthcare and research. Specifically, TGEN has developed a number of data processing pipelines, and have constructed a system to execute them


The existing ecosystem of Docker orchestration and cluster solutions and patterns mean TGEN, and other institutions can invest less into software engineering, and more into new ways to analyze the genetic data to improve patient outcomes.

Docker Images provide a platform to ensure execution environments match development/test environments. In the case of TGEN, it is easy to imagine how this creates confidence that the treatment prescribed will not be compromised by such differences. This is one of the core reasons Flywheel has chosen containerization technology from the very start in the pursuit of Reproducible Research.


How do you bootstrap a collaboration network for data scientists to share not just ideas, but data conversion and analysis building blocks? Similar to the automation story, the Docker platform handles many of the packaging/distribution/execution concerns. Now the primary concern becomes establishing a standard way to represent inputs, outputs, execution semantics, and domain-specific variables. Once that is in place, others can contribute new tools that can easily be executed by your data execution engine.

Flywheel has an open specification fitting this mold (Flywheel Gears and manages the Flywheel Exchange where contributors can publish their gears for use across Flywheel environments.

Docker in China

Docker Hub is still coming to China! I had been concerned with the silence on this front since the initial partnership with Alibaba Cloud was announced last October. As a stakeholder in Flywheel’s software distribution strategy, I am excited at the prospect of unifying our process to lower complexity and risk to achieve higher customer satisfaction.

The project for offering Dockerhub in China is nearing completion, with expected availability this summer. The free service will be limited to public Docker Hub repositories and replicated from the existing Dockerhub. The details were missing for 1) how separate this China Docker Hub would be, and 2) whether there would be additional hurdles for use by Docker Image authors/publishers, or consumers.

JFrog reps said they would be offering private Docker Registry service within China that will not require a Mainland China business entity. I’m taking that lowered bar to entry with some skepticism. If JFrog can pull that off, and make it easy to use, it will be something I recommend to colleagues.


Flywheel's ISMRM 2017 Recap

The annual ISMRM meeting is now over and most of us are back home debriefing with colleagues and sharing stories of the largest MR-focused gathering of scientists, educators, and industry.

Topics presented and discussed covered a wide range, such as understanding neural circuits, neural imaging, dynamic real-time imaging, theranostic MRI in precision medicine, and sports medicine. Other important topics included reproducibility in MR research and advancements in multi-modality research.  The call for late-breaking abstracts generated an impressive 100+ submissions on machine learning.

A very well deserved thank you to the ISMRM team and all the volunteers that made this event a success. Coordinating over 5,700 members, attendees, and exhibitors who worked hard on poster sessions, electronic posters, oral sessions, power pitches, plenary and educational sessions, and technical exhibits is nothing short of a logistics miracle.

Flywheel had a successful week discussing content management challenges and solutions. We very much appreciate all the booth visitors and detailed conversations. The MRI research community continues to generate large amounts of complex data and processing algorithms, and the feedback to our platform and approach was extremely positive.  We delivered over 100 product demonstrations and had a wonderful evening with customers and friends during our annual “ISMRM Flywheel Night.”

Our latest release contained data validation and rules-based automation features that greatly resonated with our audience. We also showed an early preview of our EEG viewer based on collaboration with Brain Products; stay tuned for more information. We are back at the office collating and prioritizing feature requests and product enhancement ideas so we can continue to deliver on our promise to help researchers “Do Science, Not IT.”   

See you next at the next tradeshow!

ISMRM 2017

Dear Friends in Research

Flywheel is heading to ISMRM 25th Annual Meeting, and we couldn't be more excited to sponsor the exhibit and engage with the community.

If you're looking towards your next grant, now is a great time to learn how Flywheel can help reduce your IT burden by providing a single place to capture, manage, analyze, and collaborate with others. To provide you with as much information as possible, we have created template language to add directly to your grant application. We can also provide a personalized letter of support. All you need to do is talk to us at booth 219 or fill out our letter of support contact form.

There are new platform features we've developed to allow researchers even more time to focus on research and not IT. Here is a snapshot on some of them.

  • Project Gear Rules:  Flywheel is introducing Project Level Gear Rules. Project administrators can set up automated tasks that will run when meeting certain criteria. For example, you can run a DICOM to NIfTI conversion Gear every time you upload data to the project with a type of DICOM.
  • Run Gear Configure: Flywheel supports Gears that require configuration parameters at runtime. The platform will render the required fields from the Gear manifest, including recommended default, and allow users to modify the parameters. The values are stored with the analysis after executing the Gear to support provenance and reproducibility.
  • ISMRM-RD: The Flywheel platform now supports the ISMRM-RD format for capturing raw data. Sharing of MRI reconstruction algorithms and code requires a common raw data format. Flywheel accomplishes this with a combination of modality-specific Connectors and converter Gears. For more on ISMRM-RD, visit GitHub.
  • Authentication: Flywheel expanded external authentication providers to include LDAP and WeChat. This feature is in addition to the Google login as the Flywheel default authentication provider.  The platform can be configured to authenticate strictly with a single authentication provider or allow for mixed-mode authentication.
  • Project Dashboard: Reading about it won't do it justice. Come and see the new and improved dashboard at booth 219.
Schedule time to discuss the platform in-depth.

When you stop by our booth, don't forget to inquire about our annual Flywheel Night. All you need for admittance is a ticket from our team. This year we will be hosting free drinks and appetizers at the MW Restaurant which is only a nine-minute walk from the convention center.

See you in Honolulu!

2017 Tradeshows


Dates: April 22-27, 2017
Location: Honolulu, HI

About the show
The International Society for Magnetic Resonance in Medicine is a multi-disciplinary nonprofit association that promotes innovation, development, and application of magnetic resonance techniques in medicine and biology throughout the world.

ISMRM is a community made up of clinicians, physicists, engineers, biochemists, and technologists-professionals united by a common interest in the ongoing dialogue between the scientific and clinical communities.

Why we’re going
This will be Flywheel’s second visit to ISMRM. Having traveled to Singapore last year, we’re very excited to show off our newest features including parallel computing, and support for ISMRMRD. If you’d like to set some time to talk with our show representatives, please contact us at We will be throwing a happy hour during the show at a local bar so stay tuned for more information or stop by our booth, #219.


Dates: June 25-29
Location: Vancouver, Canada

About the show
OHBM 2017 is the annual meeting of the Organization for Human Brain Mapping. The organization was created in 1995 and has since evolved in response to the explosion in the field of human functional neuroimaging and its movement into the scientific mainstream. OHBM provides an educational forum for the exchange of up-to-the-minute and groundbreaking research across modalities exploring Human Brain Mapping.

Why we’re going
We will be attending OHBM for the second straight year. Having created a platform specifically for Neuroimaging, we feel this conference offers a lot for attendees in the field. Within Flywheel we offer neuro-specific gears, or algorithms, that allow researchers to complete research faster and easier.


Dates: November 11-15
Location: Washington D.C.

About the show
SfN’s 47th annual meeting is the world’s largest neuroscience conference for scientists and physicians devoted to understanding the brain and nervous system. There will be more than 30,000 colleagues from more than 80 countries at the world’s largest marketplace of ideas and tools for global neuroscience.

Why we’re going
Flywheel will attend for the second year, and we’re looking to go big! Stay tuned for information on being a part of the meeting with Flywheel.

OHBM 2016

Flywheel at OHBM 2016
Flywheel will exhibit at the Organization for Human Brain Mapping in Geneva, Switzerland, June 26th to June 30th 2016. Booth # 31.