ISMRM - Open Science Initiative for Perfusion Imaging (OSIPI): The multi-delay Arterial Spin Labeling Challenge

Motivation: The OSIPI ASL Challenge is a community initiative motivated by open science principles that aim to establish good practices in ASL image analysis and Cerebral Blood Flow (CBF) quantification. Goal(s): The second ASL challenge's main goal is to provide a thorough comparison of existing post-processing pipelines focusing on Multi-PLD methodology. Approach: The second roadmap will provide different datasets; a population dataset which will bring real variability to the challenge and synthetic data which allows straightforward ground truth comparison. Results: The second edition of the ASL Challenge will contribute to gaining new insights into the potential sources of variability within the multi-PLD analysis pipeline. Impact: Through the second edition of the ASL Challenge, we seek to enhance our understanding of multi-PLD analysis in the ASL community. Its success could establish a consensus on the processing of multi-PLD ASL data, positively influencing clinical and scientific practices.

Authors

Publication Details

Journal
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Published
2024-11-26
DOI
https://doi.org/10.58530/2024/4869
Primary Topic
Advanced MRI Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

ISMRM - Open Science Initiative for Perfusion Imaging (OSIPI): The multi-delay Arterial Spin Labeling Challenge

Moss Zhao, Sriranga Kashyap, Joseph G. Woods, Henk J. M. M. Mutsaerts et al.
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Advanced MRI Techniques and Applications
article

ISMRM - Open Science Initiative for Perfusion Imaging (OSIPI): The multi-delay Arterial Spin Labeling Challenge

Moss Zhao, Sriranga Kashyap, Joseph G. Woods, Henk J. M. M. Mutsaerts, Joana Pinto, Jan Petr, André Monteiro Paschoal, Ícaro Oliveira
article en

Abstract

Motivation: The OSIPI ASL Challenge is a community initiative motivated by open science principles that aim to establish good practices in ASL image analysis and Cerebral Blood Flow (CBF) quantification. Goal(s): The second ASL challenge's main goal is to provide a thorough comparison of existing post-processing pipelines focusing on Multi-PLD methodology. Approach: The second roadmap will provide different datasets; a population dataset which will bring real variability to the challenge and synthetic data which allows straightforward ground truth comparison. Results: The second edition of the ASL Challenge will contribute to gaining new insights into the potential sources of variability within the multi-PLD analysis pipeline. Impact: Through the second edition of the ASL Challenge, we seek to enhance our understanding of multi-PLD analysis in the ASL community. Its success could establish a consensus on the processing of multi-PLD ASL data, positively influencing clinical and scientific practices.

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Openalex Percentile: Top 64%
Advanced MRI Techniques and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.