This subproject is one of many research subprojects utilizing theresources provided by a Center grant funded by NIH/NCRR. The subproject andinvestigator (PI) may have received primary funding from another NIH source,and thus could be represented in other CRISP entries. The institution listed isfor the Center, which is not necessarily the institution for the investigator.The purpose of the Engineering Core is to provide a workable and efficient platform tointegrate NAC technology into a usable software application in support of ourcollaborations and outreach activities. This platform provides an essential link betweenthe abstract world of applied mathematics and computer science, where a proof ofconcept can serve as a powerful research result, and the applied biomedical scienceswhere robust and usable systems are needed to drive the analysis of multiple subjects in a variety of clinical research scenarios. In particular, the Engineering Core is focused on such issues as interoperability between algorithms developed by the various cores of the NAC so that, for example, an R01 that results from an fMRI activation detection analysis can be used as the seeding points for DTI tractography to identify the white matter connections that may associate the activated R01 with other cortical and subcortical regions. By providing a common platform for research by the multiple cores, the potential value and applicability of each core is multiplied.Beyond functionality, the common platform gives users a common set of interfaceconventions, file formats, and related application-level support to enhance theirproductivity. Through the history of the NAC enterprise, our efforts have evolvedincreasingly towards the 3D Slicer platform as our mechanism for linking the basiccomputational research with the biomedical applications. 3D Slicer also acts as theconduit for delivering this work to the outside world as part of our outreach activities.This effort has, in fact, been so successful that 3D Slicer has in some sense graduated from the NAC to become an important part of several large NIH sponsored efforts including the NA-MIC, BIRN, and NCIGT efforts. This gratifying development increases the scope of the development activities beyond what NAC alone could provide and at the same time strengthens the foundations of the software.
| 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 |
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