Krishna Subramanyan

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OBJECTIVE The treatment of craniofacial reconstructive surgery patients may benefit from comparison to average referent three-dimensional landmark data. These data may be useful for diagnosis, treatment planning, prosthetic design, or outcomes assessment. With regard to subadult patients, we hypothesize that the pattern of ontogenetic shape change of same(More)
OBJECTIVE To evaluate automatic vessel tracking techniques in the course of preoperative planning prior to transluminal aortic endograft implantation by comparing accuracy, reproducibility, and postprocessing time with source image and volume-rendered analysis methods. METHODS Multislice computed tomography datasets of 5 patients with abdominal aortic(More)
Creating a feature-preserving average of three dimensional anatomical surfaces extracted from volume image data is a complex task. Unlike individual images, averages present right-left symmetry and smooth surfaces which give insight into typical proportions. Averaging multiple biological surface images requires careful superimposition and sampling of(More)
One of the main challenges in computational modeling of neurons is to reproduce the realistic behaviour of the neurons of the brain under different behavioural conditions. Fitting electrophysiological data to computational models is required to validate model function and test predictions. Various tools and algorithms exist to fit the spike train recorded(More)
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