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.
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.
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
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
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
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
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