Zobrazeno 1 - 10
of 3 714
pro vyhledávání: '"Laurén, J."'
Autor:
Wang, Jin, Guo, Bocheng, Li, Yijie, Wang, Junyi, Chen, Yuqian, Rushmore, Jarrett, Makris, Nikos, Rathi, Yogesh, O'Donnell, Lauren J, Zhang, Fan
Tractography fiber clustering using diffusion MRI (dMRI) is a crucial strategy for white matter (WM) parcellation. Current methods primarily use the geometric information of fibers (i.e., the spatial trajectories) to group similar fibers into cluster
Externí odkaz:
http://arxiv.org/abs/2411.01859
Autor:
Lo, Yui, Chen, Yuqian, Liu, Dongnan, Legarreta, Jon Haitz, Zekelman, Leo, Zhang, Fan, Rushmore, Jarrett, Rathi, Yogesh, Makris, Nikos, Golby, Alexandra J., Cai, Weidong, O'Donnell, Lauren J.
Brain imaging studies have demonstrated that diffusion MRI tractography geometric shape descriptors can inform the study of the brain's white matter pathways and their relationship to brain function. In this work, we investigate the possibility of ut
Externí odkaz:
http://arxiv.org/abs/2410.22099
Autor:
Cheng, Yik San, Zhao, Runkai, Wang, Heng, Peng, Hanchuan, Lo, Yui, Chen, Yuqian, O'Donnell, Lauren J., Cai, Weidong
Reconstructing neuron morphology from 3D light microscope imaging data is critical to aid neuroscientists in analyzing brain networks and neuroanatomy. With the boost from deep learning techniques, a variety of learning-based segmentation models have
Externí odkaz:
http://arxiv.org/abs/2410.22078
Autor:
Lo, Yui, Chen, Yuqian, Liu, Dongnan, Liu, Wan, Zekelman, Leo, Rushmore, Jarrett, Zhang, Fan, Rathi, Yogesh, Makris, Nikos, Golby, Alexandra J., Cai, Weidong, O'Donnell, Lauren J.
The shape of the brain's white matter connections is relatively unexplored in diffusion MRI tractography analysis. While it is known that tract shape varies in populations and across the human lifespan, it is unknown if the variability in dMRI tracto
Externí odkaz:
http://arxiv.org/abs/2410.15108
Autor:
Li, Chenjun, Yang, Dian, Yao, Shun, Wang, Shuyue, Wu, Ye, Zhang, Le, Li, Qiannuo, Cho, Kang Ik Kevin, Seitz-Holland, Johanna, Ning, Lipeng, Legarreta, Jon Haitz, Rathi, Yogesh, Westin, Carl-Fredrik, O'Donnell, Lauren J., Sochen, Nir A., Pasternak, Ofer, Zhang, Fan
In this study, we developed an Evidence-based Ensemble Neural Network, namely EVENet, for anatomical brain parcellation using diffusion MRI. The key innovation of EVENet is the design of an evidential deep learning framework to quantify predictive un
Externí odkaz:
http://arxiv.org/abs/2409.07020
When Diffusion MRI Meets Diffusion Model: A Novel Deep Generative Model for Diffusion MRI Generation
Diffusion MRI (dMRI) is an advanced imaging technique characterizing tissue microstructure and white matter structural connectivity of the human brain. The demand for high-quality dMRI data is growing, driven by the need for better resolution and imp
Externí odkaz:
http://arxiv.org/abs/2408.12897
Gaussian processes (GPs) are canonical as surrogates for computer experiments because they enjoy a degree of analytic tractability. But that breaks when the response surface is constrained, say to be monotonic. Here, we provide a mono-GP construction
Externí odkaz:
http://arxiv.org/abs/2408.01540
Autor:
Lo, Yui, Chen, Yuqian, Zhang, Fan, Liu, Dongnan, Zekelman, Leo, Cetin-Karayumak, Suheyla, Rathi, Yogesh, Cai, Weidong, O'Donnell, Lauren J.
Parcellation of white matter tractography provides anatomical features for disease prediction, anatomical tract segmentation, surgical brain mapping, and non-imaging phenotype classifications. However, parcellation does not always reach 100\% accurac
Externí odkaz:
http://arxiv.org/abs/2407.19460
Autor:
Tchetchenian, Ari, Zekelman, Leo, Chen, Yuqian, Rushmore, Jarrett, Zhang, Fan, Yeterian, Edward H., Makris, Nikos, Rathi, Yogesh, Meijering, Erik, Song, Yang, O'Donnell, Lauren J.
Parcellation of human cerebellar pathways is essential for advancing our understanding of the human brain. Existing diffusion MRI tractography parcellation methods have been successful in defining major cerebellar fibre tracts, while relying solely o
Externí odkaz:
http://arxiv.org/abs/2407.15132
Autor:
Chen, Yuqian, Zhang, Fan, Wang, Meng, Zekelman, Leo R., Cetin-Karayumak, Suheyla, Xue, Tengfei, Zhang, Chaoyi, Song, Yang, Makris, Nikos, Rathi, Yogesh, Cai, Weidong, O'Donnell, Lauren J.
The relationship between brain connections and non-imaging phenotypes is increasingly studied using deep neural networks. However, the local and global properties of the brain's white matter networks are often overlooked in convolutional network desi
Externí odkaz:
http://arxiv.org/abs/2407.08883