Abstract #1808

Implementation of the academic image processing pipeline ExploreASL in an outpatient center using IntelliSpace Discovery

Sandeep Ganji¹, Nandor Pinter², Jan Petr3³, Bela Ajtai², Joseph V Fritz², Laszlo Mechtler², Shahrukh Husain², Alexander Fischer⁴, Frederik Barkhof^5,6, and Henri‌ Mutsaerts^5,7

¹Philips, Gainesville, FL, United States, ²Dent Neurologic Institute, Amherst, NY, United States, ³Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany, ⁴Philips Research, Aachen, Germany, ⁵Dept of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam, Netherlands, ⁶Institute of Biomedical Engineering and Neurology, University College London, London, United Kingdom, ⁷Ghent Institute for Functional and Metabolic Imaging, Ghent, Belgium

The use of standardized image processing pipelines is continuously increasing in radiological research with developments in computing power, image processing, and machine learning techniques. Early integration of academic processing methods into clinical research workflow would accelerate the translation of promising novel MRI techniques into the clinic. However, the integration of such tools is both resource and time consuming. While most of neurological imaging takes place in outpatient centers, resource and workflow limitations of such clinics do not allow for the application of advanced image analysis. Here, we present the integration the “ExploreASL” into the PACS-connected research platform IntelliSpace Discovery.

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