A beginner's guide to arterial spin labeling (ASL) image processing

Arterial spin labeling (ASL) is a non-invasive and cost-effective MRI technique for brain perfusion measurements. While it has developed into a robust technique for scientific and clinical use, its image processing can still be daunting. The 2019 Ann Arbor ISMRM ASL working group established that education is one of the main areas that can accelerate the use of ASL in research and clinical practice. Specifically, the post-acquisition processing of ASL images and their preparation for region-of-interest or voxel-wise statistical analyses is a topic that has not yet received much educational attention. This educational review is aimed at those with an interest in ASL image processing and analysis. We provide summaries of all typical ASL processing steps on both single-subject and group levels. The readers are assumed to have a basic understanding of cerebral perfusion (patho) physiology; a basic level of programming or image analysis is not required. Starting with an introduction of the physiology and MRI technique behind ASL, and how they interact with the image processing, we present an overview of processing pipelines and explain the specific ASL processing steps. Example video and image illustrations of ASL studies of different cases, as well as model calculations, help the reader develop an understanding of which processing steps to check for their own analyses. Some of the educational content can be extrapolated to the processing of other MRI data. We anticipate that this educational review will help accelerate the application of ASL MRI for clinical brain research

Database of Byzantine Book Epigrams

This dataset is an sqldump from the database (PostgreSQL version 12.5) that is used to power the open access platform https://www.dbbe.ugent.be/. Contents The database consists of 3 schemas: data - contains the actual data logic - contains other information required to run the database (user roles, revision information, feedback information, ...) migration - contains information on the mapping between the previous data platform and the current one The database dump contains the schema and table creation instruction for all 3 schemas, but only contains the data for the data schema. It can be used to create and populate a database that can be used to run the code hosted on https://github.com/GhentCDH/dbbe. Acknowledgements Acknowledgements can be reconstructed by mapping the acknowledgement to the document table using the document_acknowledgement join table. For translations, the source of a translation can be reconstructed by mapping the translation table with one of the bibliography tables (article, book, bookchapter, online_source, blog_post, phd, bib_varia) using the reference join table