scholarly journals Ranking diffusion-MRI models with in-vivo human brain data

Author(s):  
Uran Ferizi ◽  
Torben Schneider ◽  
Eleftheria Panagiotaki ◽  
Gemma Nedjati-Gilani ◽  
Hui Zhang ◽  
...  
Keyword(s):  
2013 ◽  
Vol 72 (6) ◽  
pp. 1785-1792 ◽  
Author(s):  
Uran Ferizi ◽  
Torben Schneider ◽  
Eleftheria Panagiotaki ◽  
Gemma Nedjati-Gilani ◽  
Hui Zhang ◽  
...  

Author(s):  
Uran Ferizi ◽  
Torben Schneider ◽  
Maira Tariq ◽  
Claudia A. M. Wheeler-Kingshott ◽  
Hui Zhang ◽  
...  
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2017 ◽  
Vol 30 (9) ◽  
pp. e3734 ◽  
Author(s):  
Uran Ferizi ◽  
Benoit Scherrer ◽  
Torben Schneider ◽  
Mohammad Alipoor ◽  
Odin Eufracio ◽  
...  

2020 ◽  
Vol 6 (31) ◽  
pp. eaba8245 ◽  
Author(s):  
Simona Schiavi ◽  
Mario Ocampo-Pineda ◽  
Muhamed Barakovic ◽  
Laurent Petit ◽  
Maxime Descoteaux ◽  
...  

Diffusion magnetic resonance imaging is a noninvasive imaging modality that has been extensively used in the literature to study the neuronal architecture of the brain in a wide range of neurological conditions using tractography. However, recent studies highlighted that the anatomical accuracy of the reconstructions is inherently limited and challenged its appropriateness. Several solutions have been proposed to tackle this issue, but none of them proved effective to overcome this fundamental limitation. In this work, we present a novel processing framework to inject into the reconstruction problem basic prior knowledge about brain anatomy and its organization and evaluate its effectiveness using both simulated and real human brain data. Our results indicate that our proposed method dramatically increases the accuracy of the estimated brain networks and, thus, represents a major step forward for the study of connectivity.


2019 ◽  
Vol 225 (4) ◽  
pp. 1277-1291 ◽  
Author(s):  
Susie Y. Huang ◽  
Qiyuan Tian ◽  
Qiuyun Fan ◽  
Thomas Witzel ◽  
Barbara Wichtmann ◽  
...  

1994 ◽  
Vol 31 (2) ◽  
pp. 185
Author(s):  
Yong Whee Bahk ◽  
Kyung Sub Shinn ◽  
Tae Suk Suh ◽  
Bo Young Choe ◽  
Kyo Ho Choi

Author(s):  
Y Liu ◽  
D Gebrezgiabhier ◽  
J Arturo Larco ◽  
S Madhani ◽  
A Shahid ◽  
...  

Cells ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 914
Author(s):  
Melanie V. Brady ◽  
Flora M. Vaccarino

The complexities of human neurodevelopment have historically been challenging to decipher but continue to be of great interest in the contexts of healthy neurobiology and disease. The classic animal models and monolayer in vitro systems have limited the types of questions scientists can strive to answer in addition to the technical ability to answer them. However, the tridimensional human stem cell-derived organoid system provides the unique opportunity to model human development and mimic the diverse cellular composition of human organs. This strategy is adaptable and malleable, and these neural organoids possess the morphogenic sensitivity to be patterned in various ways to generate the different regions of the human brain. Furthermore, recapitulating human development provides a platform for disease modeling. One master regulator of human neurodevelopment in many regions of the human brain is sonic hedgehog (SHH), whose expression gradient and pathway activation are responsible for conferring ventral identity and shaping cellular phenotypes throughout the neural axis. This review first discusses the benefits, challenges, and limitations of using organoids for studying human neurodevelopment and disease, comparing advantages and disadvantages with other in vivo and in vitro model systems. Next, we explore the range of control that SHH exhibits on human neurodevelopment, and the application of SHH to various stem cell methodologies, including organoids, to expand our understanding of human development and disease. We outline how this strategy will eventually bring us much closer to uncovering the intricacies of human neurodevelopment and biology.


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