Browsing by Author "Chandrasekharan, K"
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Item Early risk and predictors of cerebrovascular and cardiovascular events in transient ischemic attack and minor ischemic stroke(NEUROLOGY INDIA, 2012) Kate, M; Sylaja, PN; Chandrasekharan, K; Balakrishnan, R; Sarma, S; Pandian, JDBackground: Transient ischemic attack (TIA) and minor ischemic stroke (MIS) are associated with early recurrence and deterioration respectively. The aim of the present study was to assess the risk of new cerebrovascular and cardiovascular events in a prospective, emergently enrolled patient cohort with TIA and MIS and the predictors of risk. Materials and Methods: Patients with TIA and MIS (NIH Stroke Scale [NIHSS] <= 5) presenting within the first 48 h between July 2008-June 2009 were prospectively enrolled. The primary outcome was new-onset stroke, TIA, cardiovascular events and vascular death at 90 days and early deterioration in patients with minor stroke. The 90-day outcome was also assessed (excellent outcome; modified Rankin scale [mRS] <= 2). Results: Eighteen (15.3%) of the 118 patients enrolled developed new cerebrovascular or cardiovascular events during the 90 days of follow-up, nine (50%) of which occurred within seven days. Of the all new events 5.9% (7/118) had new stroke, 4.2% (5/118) patients developed early deterioration, 2.5% (3/118) patients had recurrent TIA and 2.5% (3/118) had cardiovascular events at 90 days. Eight (6.7%) patients had poor outcome at 90 days (mRS>2). The factors predicting new vascular events were presence of coronary artery disease (CAD), and stroke etiology being large artery atherosclerosis (LAA). Conclusion: In patients with TIA and MIS, despite urgent evaluation and aggressive management, the short-term risk of stroke and other vascular events is high. Those with CAD and LAA should be monitored closely for early deterioration.Item Partial Fourier Reconstruction Using Subspace Projection(2013 FOURTH NATIONAL CONFERENCE ON COMPUTER VISION, PATTERN RECOGNITION, IMAGE PROCESSING AND GRAPHICS (NCVPRIPG), 2013) Uma, K; Chandrasekharan, K; Paul, JSScan time reduction in MRI can be achieved by partial k-space reconstruction. Truncation of the k-space results in generation of artifacts in the reconstructed image. A subspace projection algorithm is developed for artifact-free reconstruction of sparse MRI. The algorithm is applied to a frequency weighted k-space, which fits into a signal-space model for sparse MR images. The application is illustrated using Magnetic Resonance Angiogram (MRA).