A short history of FlowSigma.
The core technology of FlowSIGMA was developed and implemented in order to assure efficient and reliable execution of image-based analytics. The system was built to enable an algorithm for identifying changes in brain patients using MRI examinations. This is much more complex than simple routing or forwarding, as it requires recognition that several specific series be present to constitute the specific examination, and it requires querying the archive to determine that a prior examination of this special type is available. It also 'time boxes' the analytic, meaning that if the analytic takes more than a pre-specified amount of time, an error-handling workflow (e.g. notify Support Services) can be executed.
Since that time, the system has been used for several other workflows, including high-throughput tools like CT de-noising. It is highly reliable and has a friendly user interface for identifying when problems arise (e.g. a target is not receiving images sent to it). It allows graphical creation of workflows, which is valuable for maintaining complex workflows that are a part of the real world, and also is friendly for non-programmers to understand. The system is very flexible and is being applied to solve a wide variety of problems. Its modular design encourages integration with other industry standard tools.
Pleased to meet you. FlowSigma is excited to introduce our founders.
Chris Hanna is a 30-year veteran in the field of clinical imaging - spanning PACS, vendor-neutral archives, and imaging informatics. Few business leaders have the experiential blend stemming from both the healthcare provider (Mayo Clinic) and the technology vendor environments co-founding A.L.I Technologies Inc. formerly McKesson Imaging now Change Healthcare and co-founding TeraMedica, Inc. now part of Fujifilm).
Chris holds BSc and MSc degrees in medicinal chemistry and a PhD in pharmacology from the University of Guelph, Ontario, Canada.
Dr. Erickson received his MD and PhD degrees from Mayo Medical & Graduate School and then did his residency in diagnostic radiology and Neuroradiology fellowship at Mayo Clinic. He went on staff at Mayo Clinic, and was heavily involved in administrative responsibilities implementing a filmless department and then a paperless practice and EMR, including being the Vice Chair for IT at Mayo. More recently, he has refocused on imaging informatics research, receiving NIH grants for brain cancer, multiple sclerosis, and polycystic kidney disease. He is a recognized world expert on the application of deep learning to medical images. He was the founding Chair of the Division of Imaging Informatics, and is currently the Associate Chair for Research in Radiology.
Dr. Steve Langer studied physics at UW-Madison, Michigan State and Oakland University, along the way transitioning from experimental nuclear physics to medical physics. His Ph.D. thesis involved the design, construction and use of several novel hyperthermia devices to augment traditional Radiation Oncology therapies. He then took a residency at Mayo Clinic in diagnostic imaging physics and is boarded in that field. Post-residency, Dr. Langer went to Seattle where co-architected the filmless transitions of both UW-Seattle and Harborview Medical Center. In 2002 he returned to Mayo where he led the transition of the Radiology department in Rochester to its filmless state.
Along with his clinical duties, Dr. Langer has had a longstanding interest in tools that allow research analytics to be brought to bear in clinical practice; this includes: performance profiling, adherence to standards required in Healthcare IT, and designing scalable architectures for workflow automation. Dr. Langer is the chair of Mayo’s Enterprise Radiology Architecture And Standards committee, co-architect of the RSNA Image Share Network (an NIH funded implementation of an IHE-XDS.i infrastructure), co-author of several DICOM and IHE profiles, and co-author of the book “Informatics in Medical Imaging”. He is also the chair of the SIIM Machine Learning Committee and co-chair of the SIIM Hackathon Committee which showcases new healthcare IT standards (i.e. FHIR and DICOMweb).
Dr. Blezek received his PhD in biomedical engineering from the Mayo Graduate School. After graduation, he worked as a senior staff scientist at GE's Global Research Center, working jointly in the Visualization & Computer Vision lab and MRI lab. His research at GE included high performance medical image rendering, automated analysis of imaging based biomarkers, MR scanner based registration for longitudinal imaging, and guiding GE through six sigma software quality practices. In 2007 he became technical director Mayo's Medical Imaging Informatics Innovation Center where he lead the translation of research projects into clinical practice.
Currently, he is the Advanced Imaging Scientist for the Department of Neuroradiology. In his past and current roles, he has brought imaging informatics algorithms to the clinical practice, including: MRA aneurysm detection, automated segmentation of brain vessels for visualization, CT denoising for low-dose CT, automated white-matter tract identification in MR tractography, registration and subtraction of MR contrast images, and several others. Dr. Blezek's interests include automating radiology workflows, application of machine learning to medical images, high performance computing, software quality, and developing highly available clinical systems.