Abstract
Background Integration of novel image reconstruction and processing methods into clinical workflow has been hampered by difficulties in implementing these techniques into the vendors’ softwares. While all vendors allow modification of imaging sequences, implementation of novel reconstruction techniques is not available in any of them. Currently, the workflow includes manually exporting the data, performing the custom reconstruction using standalone Matlab or C++ implementation, and then visualizing the results on a different workstation. This process usually requires an expert user and is not feasible in common clinical workflow. In this work, we developed a simple software tool that enables researchers to rapidly integrate post-processing and reconstruction methods developed in any programming language on any type of workstation via internet connection and directly visualize the data on the scanner console and store the data via clinical PACS system. Methods
Highlights
Integration of novel image reconstruction and processing methods into clinical workflow has been hampered by difficulties in implementing these techniques into the vendors’ softwares
We developed a simple software tool that enables researchers to rapidly integrate post-processing and reconstruction methods developed in any programming language on any type of workstation via internet connection and directly visualize the data on the scanner console and store the data via clinical PACS system
The results are automatically retrieved from the remote processing unit and directly sent to the scanner database where they can be viewed and stored similar to images reconstructed by the vendor reconstruction system
Summary
Integration of novel image reconstruction and processing methods into clinical workflow has been hampered by difficulties in implementing these techniques into the vendors’ softwares. Software platform for flexible automated reconstruction of CMR data in a clinically feasible workflow Background Integration of novel image reconstruction and processing methods into clinical workflow has been hampered by difficulties in implementing these techniques into the vendors’ softwares.
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