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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 Barkhof5,6, and Henri‌ Mutsaerts5,7
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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