Zobrazeno 1 - 10
of 109
pro vyhledávání: '"QIYUAN TIAN"'
Publikováno v:
NeuroImage, Vol 298, Iss , Pp 120766- (2024)
Streamline tractography locally traces peak directions extracted from fiber orientation distribution (FOD) functions, lacking global information about the trend of the whole fiber bundle. Therefore, it is prone to producing erroneous tracks while mis
Externí odkaz:
https://doaj.org/article/39cf3b9f38944b5cb1cf8d1886bde62b
Autor:
Zihan Li, Ziyu Li, Berkin Bilgic, Hong‐Hsi Lee, Kui Ying, Susie Y. Huang, Hongen Liao, Qiyuan Tian
Publikováno v:
Advanced Science, Vol 11, Iss 24, Pp n/a-n/a (2024)
Abstract Diffusion magnetic resonance imaging is an important tool for mapping tissue microstructure and structural connectivity non‐invasively in the in vivo human brain. Numerous diffusion signal models are proposed to quantify microstructural pr
Externí odkaz:
https://doaj.org/article/7f163da8df154b27984888d8a565f0aa
Autor:
Congyu Liao, Uten Yarach, Xiaozhi Cao, Siddharth Srinivasan Iyer, Nan Wang, Tae Hyung Kim, Qiyuan Tian, Berkin Bilgic, Adam B. Kerr, Kawin Setsompop
Publikováno v:
NeuroImage, Vol 275, Iss , Pp 120168- (2023)
Purpose: To develop a high-fidelity diffusion MRI acquisition and reconstruction framework with reduced echo-train-length for less T2* image blurring compared to typical highly accelerated echo-planar imaging (EPI) acquisitions at sub-millimeter isot
Externí odkaz:
https://doaj.org/article/029ab055df1d4befbbc7cb8132c0c5ca
Autor:
Qiyuan Tian, Qiuyun Fan, Thomas Witzel, Maya N. Polackal, Ned A. Ohringer, Chanon Ngamsombat, Andrew W. Russo, Natalya Machado, Kristina Brewer, Fuyixue Wang, Kawin Setsompop, Jonathan R. Polimeni, Boris Keil, Lawrence L. Wald, Bruce R. Rosen, Eric C. Klawiter, Aapo Nummenmaa, Susie Y. Huang
Publikováno v:
Scientific Data, Vol 9, Iss 1, Pp 1-11 (2022)
Measurement(s) brain measurement Technology Type(s) diffusion magnetic resonance imaging Factor Type(s) diffusion time • gradient strength • direction Sample Characteristic - Organism Homo sapiens Machine-accessible metadata file describing the r
Externí odkaz:
https://doaj.org/article/5ee95e39c6e848d5a63171ac869f90e8
Autor:
Santiago Aja-Fernández, Carmen Martín-Martín, Álvaro Planchuelo-Gómez, Abrar Faiyaz, Md Nasir Uddin, Giovanni Schifitto, Abhishek Tiwari, Saurabh J. Shigwan, Rajeev Kumar Singh, Tianshu Zheng, Zuozhen Cao, Dan Wu, Stefano B. Blumberg, Snigdha Sen, Tobias Goodwin-Allcock, Paddy J. Slator, Mehmet Yigit Avci, Zihan Li, Berkin Bilgic, Qiyuan Tian, Xinyi Wang, Zihao Tang, Mariano Cabezas, Amelie Rauland, Dorit Merhof, Renata Manzano Maria, Vinícius Paraníba Campos, Tales Santini, Marcelo Andrade da Costa Vieira, SeyyedKazem HashemizadehKolowri, Edward DiBella, Chenxu Peng, Zhimin Shen, Zan Chen, Irfan Ullah, Merry Mani, Hesam Abdolmotalleby, Samuel Eckstrom, Steven H. Baete, Patryk Filipiak, Tanxin Dong, Qiuyun Fan, Rodrigo de Luis-García, Antonio Tristán-Vega, Tomasz Pieciak
Publikováno v:
NeuroImage: Clinical, Vol 39, Iss , Pp 103483- (2023)
The objective of this study is to evaluate the efficacy of deep learning (DL) techniques in improving the quality of diffusion MRI (dMRI) data in clinical applications. The study aims to determine whether the use of artificial intelligence (AI) metho
Externí odkaz:
https://doaj.org/article/59576c43e92943cc8ee0c017cb32d811
Autor:
Amy FD Howard, Michiel Cottaar, Mark Drakesmith, Qiuyun Fan, Susie Y. Huang, Derek K. Jones, Frederik J. Lange, Jeroen Mollink, Suryanarayana Umesh Rudrapatna, Qiyuan Tian, Karla L Miller, Saad Jbabdi
Publikováno v:
NeuroImage, Vol 262, Iss , Pp 119535- (2022)
To estimate microstructure-related parameters from diffusion MRI data, biophysical models make strong, simplifying assumptions about the underlying tissue. The extent to which many of these assumptions are valid remains an open research question. Thi
Externí odkaz:
https://doaj.org/article/60ebccdea499425c9fe378949fbeeb2e
Autor:
Qiuyun Fan, Cornelius Eichner, Maryam Afzali, Lars Mueller, Chantal M.W. Tax, Mathias Davids, Mirsad Mahmutovic, Boris Keil, Berkin Bilgic, Kawin Setsompop, Hong-Hsi Lee, Qiyuan Tian, Chiara Maffei, Gabriel Ramos-Llordén, Aapo Nummenmaa, Thomas Witzel, Anastasia Yendiki, Yi-Qiao Song, Chu-Chung Huang, Ching-Po Lin, Nikolaus Weiskopf, Alfred Anwander, Derek K. Jones, Bruce R. Rosen, Lawrence L. Wald, Susie Y. Huang
Publikováno v:
NeuroImage, Vol 254, Iss , Pp 118958- (2022)
Tremendous efforts have been made in the last decade to advance cutting-edge MRI technology in pursuit of mapping structural connectivity in the living human brain with unprecedented sensitivity and speed. The first Connectom 3T MRI scanner equipped
Externí odkaz:
https://doaj.org/article/aeaaabbb2052475aa9761e6aff40f5b4
Autor:
Fuyixue Wang, Zijing Dong, Qiyuan Tian, Congyu Liao, Qiuyun Fan, W. Scott Hoge, Boris Keil, Jonathan R. Polimeni, Lawrence L. Wald, Susie Y. Huang, Kawin Setsompop
Publikováno v:
Scientific Data, Vol 8, Iss 1, Pp 1-12 (2021)
Measurement(s) brain measurement Technology Type(s) magnetic resonance imaging Sample Characteristic - Organism Homo sapiens Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.14058443
Externí odkaz:
https://doaj.org/article/2314dea9b3da47c68b493b0860e8db32
Autor:
Qiyuan Tian, Ziyu Li, Qiuyun Fan, Jonathan R. Polimeni, Berkin Bilgic, David H. Salat, Susie Y. Huang
Publikováno v:
NeuroImage, Vol 253, Iss , Pp 119033- (2022)
Diffusion tensor magnetic resonance imaging (DTI) is a widely adopted neuroimaging method for the in vivo mapping of brain tissue microstructure and white matter tracts. Nonetheless, the noise in the diffusion-weighted images (DWIs) decreases the acc
Externí odkaz:
https://doaj.org/article/b316eb41bd404e5faccb8c07aafb63ff
Autor:
Shasha Li, Marziye Eshghi, Sheraz Khan, Qiyuan Tian, Juho Joutsa, Yangming Ou, Qing Mei Wang, Jian Kong, Bruce Robert Rosen, Jyrki Ahveninen, Aapo Nummenmaa
Publikováno v:
Brain Stimulation, Vol 13, Iss 5, Pp 1207-1210 (2020)
Externí odkaz:
https://doaj.org/article/fe7dc997377d461fbcc9da0b5b87b095