The complexity of contemporary neuroradiology requires neuroradiologists to extract, interpret, and communicate important content from large and complex data sets. A new paradigm for image and data management is required to intelligently utilizes the information inherent in clinical management schemes (pathways) and to determine the optimal protocols for image acquisition, organization, display, processing and objectifying patients' subjective findings; (b) providing timely anc accurate diagnosis; and (c) reducing the inefficiency of healthcare delivery by streamlining review and potentially reducing the number of tests performed. We hypothesize that these PACS technologies will facilitate rapid clinical actions and increase physician satisfaction by facilitating tools for intelligent reporting, creating new reporting, and teaching methods, and forming searchable databases for research and medical care purposes. This project's goals are twofold: [1] to implement a new strategy for customized management and presentation of imaging studies and related documents in patients with neurological disease by developing clinically driven adaptive reading protocols; and [2] to assist automatic authoring of multi-media reports containing critical images and finding sin brain tumor patients by developing intelligent adaptive report authoring protocols. These objectives will be achieved by developing object-oriented process and data models of the imaging processes, the tasks, and the data used and generated in the course of patient care, leading to the development of adaptive imaging protocols for data presentation, online quantification, and automated report creation. The technical performance of these models, protocols, and toolkits are formally evaluated. Lastly, we will evaluate the clinical impact of the resulting PACS-workstation-based system on the performance, confidence, and satisfaction of neuroradiologists and neuro-oncologists.
| Bashyam, Vijayaraghavan; Hsu, William; Watt, Emily et al. (2009) Problem-centric organization and visualization of patient imaging and clinical data. Radiographics 29:331-43 |
| Taira, Ricky K; Taira, Ricky; Bui, Alex et al. (2008) A tool for improving the longitudinal imaging characterization for neuro-oncology cases. AMIA Annu Symp Proc :712-6 |
| Son, Roderick Y; Taira, Ricky K; Kangarloo, Hooshang et al. (2008) Context-sensitive correlation of implicitly related data: an episode creation methodology. IEEE Trans Inf Technol Biomed 12:549-60 |
| Bui, Alex A T; Morioka, Craig; Dionisio, John David N et al. (2007) OpenSourcePACS: an extensible infrastructure for medical image management. IEEE Trans Inf Technol Biomed 11:94-109 |
| Taira, Ricky K; Bashyam, Vijayaraghavan; Kangarloo, Hooshang (2007) A field theoretical approach to medical natural language processing. IEEE Trans Inf Technol Biomed 11:364-75 |
| Bui, Alex A T; Aberle, Denise R; Kangarloo, Hooshang (2007) TimeLine: visualizing integrated patient records. IEEE Trans Inf Technol Biomed 11:462-73 |
| Ardekani, Siamak; Kumar, Anand; Bartzokis, George et al. (2007) Exploratory voxel-based analysis of diffusion indices and hemispheric asymmetry in normal aging. Magn Reson Imaging 25:154-67 |
| Ardekani, Siamak; Selva, Luis; Sayre, James et al. (2006) Quantitative metrics for evaluating parallel acquisition techniques in diffusion tensor imaging at 3 Tesla. Invest Radiol 41:806-14 |
| Ardekani, Siamak; Sinha, Usha (2006) Statistical representation of mean diffusivity and fractional anisotropy brain maps of normal subjects. J Magn Reson Imaging 24:1243-51 |
| Ardekani, Siamak; Sinha, Usha (2005) Geometric distortion correction of high-resolution 3 T diffusion tensor brain images. Magn Reson Med 54:1163-71 |
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