- JointMMCC: joint maximum-margin classification and clustering of imaging dataRoman Filipovych
Section of Biomedical ImageAnalysis, Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
IEEE Trans Med Imaging 31:1124-40. 2012..We apply our proposed approach to an medical resonance imaging study of aging, and identify coherent subpopulations (i.e., clusters) of cognitively less stable adults...
- Semi-supervised cluster analysis of imaging dataRoman Filipovych
Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
Neuroimage 54:2185-97. 2011..e. cognitively stable) state. We analyze the clusters' structure, and show that clustering results obtained using our approach correlate well with clinical data...
- Semi-supervised pattern classification of medical images: application to mild cognitive impairment (MCI)Roman Filipovych
Section of Biomedical Image Analysis, Department of Radiology, University of Pennsylvania, 3600 Market St, Suite 380, Philadelphia, PA 19104, USA
Neuroimage 55:1109-19. 2011....
- Mild cognitive impairment: baseline and longitudinal structural MR imaging measures improve predictive prognosisLinda K McEvoy
Department of Radiology, University of California, San Diego, 9500 Gilman Dr, La Jolla, CA 92093, USA
Radiology 259:834-43. 2011..To assess whether single-time-point and longitudinal volumetric magnetic resonance (MR) imaging measures provide predictive prognostic information in patients with amnestic mild cognitive impairment (MCI)...