PLAYBOT: An Intelligent Visually-Guided Robot for the Disabled
Playbot is a long-term, large-scale research project, whose goal is to provide a vision-based computer controlled wheelchair that enables children and adults with mobility impairments to become more independent.
We present a framework for the analysis of short axis cardiac MRI, using statistical models of shape and appearance. The framework integrates temporal and structural constraints and avoids common optimization problems inherent in such high dimensional models. The first contribution is the introduction of an algorithm for fitting 3D active appearance models (AAMs) on short axis cardiac MRI. We observe a 44-fold increase in fitting speed and a segmentation accuracy that is on par with Gauss–Newton optimization, one of the most widely used optimization algorithms for such problems. The second contribution involves an investigation on hierarchical 2D + time active shape models (ASMs), that integrate temporal constraints and simultaneously improve the 3D AAM based segmentation. We obtain encouraging results (endocardial/epicardial error 1.43 ± 0.49 mm/1.51 ± 0.48 mm) on 7980 short axis cardiac MR images acquired from 33 subjects. We have placed our dataset online, for the community to use and build upon.
This paper presents a wavelet-based framework for enhancing the coherent structures attributable to the target organ in cardiac Magnetic Resonance (MR) images. Previous approaches focus on the Rician nature of noise in magnitude MR images. Image noise is but only one of the confounding factors that obscure the anatomical structures of the target organ. This paper models the image noise in a magnitude MR image in terms of two noise classes which occur over different ranges of signal intensity. An adaptive enhancement scheme is developed to achieve simultaneous attenuation of the effects of these factors and improvement in image contrast.
