Combined Treatment With Exenatide and Cyclosporine A or Parstatin 1-26 Results in Enhanced Reduction of Infarct Size in a Rabbit Model.

Exenatide and cyclosporine A have been shown to moderately protect against myocardial reperfusion injury leading to reduction of infarct size in patients. Our objective was to investigate whether the combined treatment with exenatide (glucagon-like peptide 1 receptor agonist) and cyclosporine A or parstatin 1-26 (inhibitors of mitochondrial permeability transition pore and/or inflammation) is more beneficial than either agent alone. Rabbits underwent 40 minutes of ischemia and 120 minutes of reperfusion. Intravenous bolus administration of exenatide or cyclosporine A, 10 minutes before reperfusion, reduced infarct size by 38% (P < 0.05) and 40% (P < 0.05), and cardiac troponin I (cTnI) plasma levels by 48% (P < 0.05) and 36% (P < 0.05), respectively, compared with control. The combined administration of both agents resulted in an additive decrease of infarct size by 55% (P < 0.05) and cTnI release by 61% (P < 0.05). Also, combined treatment of exenatide and parstatin 1-26 enhanced infarct size reduction (62%, P < 0.05), compared with monotherapies (41% for parstatin 1-26, P < 0.05; 43% for exenatide, P < 0.05). In contrast, the combined administration of parstatin 1-26 and cyclosporine A canceled out the cardioprotective effects observed by monotherapies. These results suggest that, for the therapy of myocardial reperfusion injury the combined administration of exenatide and cyclosporine A or parstatin 1-26 is more effective than monotherapies and may provide advantageous clinical outcome.

Video Normals from Colored Lights.

We present an algorithm and the associated single-view capture methodology to acquire the detailed 3D shape, bends, and wrinkles of deforming surfaces. Moving 3D data has been difficult to obtain by methods that rely on known surface features, structured light, or silhouettes. Multispectral photometric stereo is an attractive alternative because it can recover a dense normal field from an untextured surface. We show how to capture such data, which in turn allows us to demonstrate the strengths and limitations of our simple frame-to-frame registration over time. Experiments were performed on monocular video sequences of untextured cloth and faces with and without white makeup. Subjects were filmed under spatially separated red, green, and blue lights. Our first finding is that the color photometric stereo setup is able to produce smoothly varying per-frame reconstructions with high detail. Second, when these 3D reconstructions are augmented with 2D tracking results, one can register both the surfaces and relax the homogenous-color restriction of the single-hue subject. Quantitative and qualitative experiments explore both the practicality and limitations of this simple multispectral capture system.

Overcoming shadows in 3-source photometric stereo.

Light occlusions are one of the most significant difficulties of photometric stereo methods. When three or more images are available without occlusion, the local surface orientation is overdetermined so that shape can be computed and the shadowed pixels can be discarded. In this paper, we look at the challenging case when only two images are available without occlusion, leading to a one degree of freedom ambiguity per pixel in the local orientation. We show that, in the presence of noise, integrability alone cannot resolve this ambiguity and reconstruct the geometry in the shadowed regions. As the problem is ill-posed in the presence of noise, we describe two regularization schemes that improve the numerical performance of the algorithm while preserving the data. Finally, the paper describes how this theory applies in the framework of color photometric stereo where one is restricted to only three images and light occlusions are common. Experiments on synthetic and real image sequences are presented.

Multiview photometric stereo.

This paper addresses the problem of obtaining complete, detailed reconstructions of textureless shiny objects. We present an algorithm which uses silhouettes of the object, as well as images obtained under changing illumination conditions. In contrast with previous photometric stereo techniques, ours is not limited to a single viewpoint but produces accurate reconstructions in full 3D. A number of images of the object are obtained from multiple viewpoints, under varying lighting conditions. Starting from the silhouettes, the algorithm recovers camera motion and constructs the object's visual hull. This is then used to recover the illumination and initialise a multi-view photometric stereo scheme to obtain a closed surface reconstruction. There are two main contributions in this paper: Firstly we describe a robust technique to estimate light directions and intensities and secondly, we introduce a novel formulation of photometric stereo which combines multiple viewpoints and hence allows closed surface reconstructions. The algorithm has been implemented as a practical model acquisition system. Here, a quantitative evaluation of the algorithm on synthetic data is presented together with complete reconstructions of challenging real objects. Finally, we show experimentally how even in the case of highly textured objects, this technique can greatly improve on correspondence-based multi-view stereo results.

Multiview stereo via volumetric Graph-Cuts and occlusion robust photo-consistency.

This paper presents a volumetric formulation for the multi-view stereo problem which is amenable to a computationally tractable global optimisation using Graph-cuts. Our approach is to seek the optimal partitioning of 3D space into two regions labelled as "object" and "empty" under a cost functional consisting of the following two terms: (1) A term that forces the boundary between the two regions to pass through photo-consistent locations and (2) a ballooning term that inflates the "object" region. To take account of the effect of occlusion on the first term we use an occlusion robust photo-consistency metric based on Normalised Cross Correlation, which does not assume any geometric knowledge about the reconstructed object. The globally optimal 3D partitioning can be obtained as the minimum cut solution of a weighted graph.