This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. The goal of the White Matter Architecture core (WMA) is to pursue technological developments that improve current understanding of white matter anatomy in the brain. Given the small dimension of the neural pathways in relation to current imaging resolution, these technologies are vital to analyzing and visualizing the neural anatomy in normal and diseased states. The clinical objective is to analyze abnormalities in white matter architecture that underlie schizophrenia, by using techniques in diffusion tensor magnetic resonance imaging (DT-MRI) and post-process imaging. The expectation is that new knowledge acquired from these studies not only will benefit the understanding and treatment of schizophrenia, but also a broad range of other white matter diseases.
| Saito, Yukiko; Kubicki, Marek; Koerte, Inga et al. (2018) Impaired white matter connectivity between regions containing mirror neurons, and relationship to negative symptoms and social cognition, in patients with first-episode schizophrenia. Brain Imaging Behav 12:229-237 |
| Gallardo, Guillermo; Wells 3rd, William; Deriche, Rachid et al. (2018) Groupwise structural parcellation of the whole cortex: A logistic random effects model based approach. Neuroimage 170:307-320 |
| Ratner, Vadim; Gao, Yi; Lee, Hedok et al. (2017) Cerebrospinal and interstitial fluid transport via the glymphatic pathway modeled by optimal mass transport. Neuroimage 152:530-537 |
| Sastry, Rahul; Bi, Wenya Linda; Pieper, Steve et al. (2017) Applications of Ultrasound in the Resection of Brain Tumors. J Neuroimaging 27:5-15 |
| Chen, Yongxin; Georgiou, Tryphon T; Ning, Lipeng et al. (2017) Matricial Wasserstein-1 Distance. IEEE Control Syst Lett 1:14-19 |
| Niethammer, Marc; Pohl, Kilian M; Janoos, Firdaus et al. (2017) ACTIVE MEAN FIELDS FOR PROBABILISTIC IMAGE SEGMENTATION: CONNECTIONS WITH CHAN-VESE AND RUDIN-OSHER-FATEMI MODELS. SIAM J Imaging Sci 10:1069-1103 |
| Chen, Yongxin; Cruz, Filemon Dela; Sandhu, Romeil et al. (2017) Pediatric Sarcoma Data Forms a Unique Cluster Measured via the Earth Mover's Distance. Sci Rep 7:7035 |
| Schabdach, Jenna; Wells 3rd, William M; Cho, Michael et al. (2017) A Likelihood-Free Approach for Characterizing Heterogeneous Diseases in Large-Scale Studies. Inf Process Med Imaging 10265:170-183 |
| Wachinger, Christian; Brennan, Matthew; Sharp, Greg C et al. (2017) Efficient Descriptor-Based Segmentation of Parotid Glands With Nonlocal Means. IEEE Trans Biomed Eng 64:1492-1502 |
| Chen, Yongxin; Georgiou, Tryphon; Pavon, Michele et al. (2017) Robust transport over networks. IEEE Trans Automat Contr 62:4675-4682 |
Showing the most recent 10 out of 507 publications
