Literature DB >> 24323973

Fiberfox: facilitating the creation of realistic white matter software phantoms.

Peter F Neher1, Frederik B Laun, Bram Stieltjes, Klaus H Maier-Hein.   

Abstract

PURPOSE: Phantom-based validation of diffusion-weighted image processing techniques is an important key to innovation in the field and is widely used. Openly available and user friendly tools for the flexible generation of tailor-made datasets for the specific tasks at hand can greatly facilitate the work of researchers around the world.
METHODS: We present an open-source framework, Fiberfox, that enables (1) the intuitive definition of arbitrary artificial white matter fiber tracts, (2) signal generation from those fibers by means of the most recent multi-compartment modeling techniques, and (3) simulation of the actual MR acquisition that allows for the introduction of realistic MRI-related effects into the final image.
RESULTS: We show that real acquisitions can be closely approximated by simulating the acquisition of the well-known FiberCup phantom. We further demonstrate the advantages of our framework by evaluating the effects of imaging artifacts and acquisition settings on the outcome of 12 tractography algorithms.
CONCLUSION: Our findings suggest that experiments on a realistic software phantom might change the conclusions drawn from earlier hardware phantom experiments. Fiberfox may find application in validating and further developing methods such as tractography, super-resolution, diffusion modeling or artifact correction.
Copyright © 2013 Wiley Periodicals, Inc.

Keywords:  artifact simulation; diffusion-weighted imaging; open-source software; software phantoms; synthetic white matter fibers

Mesh:

Year:  2013        PMID: 24323973     DOI: 10.1002/mrm.25045

Source DB:  PubMed          Journal:  Magn Reson Med        ISSN: 0740-3194            Impact factor:   4.668


  24 in total

Review 1.  Challenges in diffusion MRI tractography - Lessons learned from international benchmark competitions.

Authors:  Kurt G Schilling; Alessandro Daducci; Klaus Maier-Hein; Cyril Poupon; Jean-Christophe Houde; Vishwesh Nath; Adam W Anderson; Bennett A Landman; Maxime Descoteaux
Journal:  Magn Reson Imaging       Date:  2018-11-29       Impact factor: 2.546

2.  Tractography reproducibility challenge with empirical data (TraCED): The 2017 ISMRM diffusion study group challenge.

Authors:  Vishwesh Nath; Kurt G Schilling; Prasanna Parvathaneni; Yuankai Huo; Justin A Blaber; Allison E Hainline; Muhamed Barakovic; David Romascano; Jonathan Rafael-Patino; Matteo Frigo; Gabriel Girard; Jean-Philippe Thiran; Alessandro Daducci; Matt Rowe; Paulo Rodrigues; Vesna Prčkovska; Dogu B Aydogan; Wei Sun; Yonggang Shi; William A Parker; Abdol A Ould Ismail; Ragini Verma; Ryan P Cabeen; Arthur W Toga; Allen T Newton; Jakob Wasserthal; Peter Neher; Klaus Maier-Hein; Giovanni Savini; Fulvia Palesi; Enrico Kaden; Ye Wu; Jianzhong He; Yuanjing Feng; Michael Paquette; Francois Rheault; Jasmeen Sidhu; Catherine Lebel; Alexander Leemans; Maxime Descoteaux; Tim B Dyrby; Hakmook Kang; Bennett A Landman
Journal:  J Magn Reson Imaging       Date:  2019-06-09       Impact factor: 4.813

Review 3.  Advances in computational and statistical diffusion MRI.

Authors:  Lauren J O'Donnell; Alessandro Daducci; Demian Wassermann; Christophe Lenglet
Journal:  NMR Biomed       Date:  2017-11-14       Impact factor: 4.044

4.  Brain connections derived from diffusion MRI tractography can be highly anatomically accurate-if we know where white matter pathways start, where they end, and where they do not go.

Authors:  Kurt G Schilling; Laurent Petit; Francois Rheault; Samuel Remedios; Carlo Pierpaoli; Adam W Anderson; Bennett A Landman; Maxime Descoteaux
Journal:  Brain Struct Funct       Date:  2020-08-20       Impact factor: 3.270

5.  Limits to anatomical accuracy of diffusion tractography using modern approaches.

Authors:  Kurt G Schilling; Vishwesh Nath; Colin Hansen; Prasanna Parvathaneni; Justin Blaber; Yurui Gao; Peter Neher; Dogu Baran Aydogan; Yonggang Shi; Mario Ocampo-Pineda; Simona Schiavi; Alessandro Daducci; Gabriel Girard; Muhamed Barakovic; Jonathan Rafael-Patino; David Romascano; Gaëtan Rensonnet; Marco Pizzolato; Alice Bates; Elda Fischi; Jean-Philippe Thiran; Erick J Canales-Rodríguez; Chao Huang; Hongtu Zhu; Liming Zhong; Ryan Cabeen; Arthur W Toga; Francois Rheault; Guillaume Theaud; Jean-Christophe Houde; Jasmeen Sidhu; Maxime Chamberland; Carl-Fredrik Westin; Tim B Dyrby; Ragini Verma; Yogesh Rathi; M Okan Irfanoglu; Cibu Thomas; Carlo Pierpaoli; Maxime Descoteaux; Adam W Anderson; Bennett A Landman
Journal:  Neuroimage       Date:  2018-10-11       Impact factor: 6.556

6.  Tracking and validation techniques for topographically organized tractography.

Authors:  Dogu Baran Aydogan; Yonggang Shi
Journal:  Neuroimage       Date:  2018-07-02       Impact factor: 6.556

7.  When tractography meets tracer injections: a systematic study of trends and variation sources of diffusion-based connectivity.

Authors:  Dogu Baran Aydogan; Russell Jacobs; Stephanie Dulawa; Summer L Thompson; Maite Christi Francois; Arthur W Toga; Hongwei Dong; James A Knowles; Yonggang Shi
Journal:  Brain Struct Funct       Date:  2018-04-16       Impact factor: 3.270

8.  A 3D model-based simulation of demyelination to understand its effects on diffusion tensor imaging.

Authors:  Teddy Salan; Eddie L Jacobs; Wilburn E Reddick
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2017-07

9.  Modeling topographic regularity in structural brain connectivity with application to tractogram filtering.

Authors:  Junyan Wang; Dogu Baran Aydogan; Rohit Varma; Arthur W Toga; Yonggang Shi
Journal:  Neuroimage       Date:  2018-08-04       Impact factor: 6.556

10.  Parallel Transport Tractography.

Authors:  Dogu Baran Aydogan; Yonggang Shi
Journal:  IEEE Trans Med Imaging       Date:  2021-02-02       Impact factor: 10.048

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