We report a method measuring 3-Ddisplacement of cambered mirror for cryogenic optical system using white light speckle photography with double light sources and double cameras. Data acquiring and processing based on a digital image processing system is described. The 3-Ddisplacement and displacement vector distributions in two low-temperature ranges are measured.

Respiratory-induced cardiac deformation is a major problem for high-resolution cardiac imaging. This paper presents a new technique for predictive cardiac motion modeling and correction, which uses partial least squares regression to extract intrinsic relationships between three-dimensional (3-D) cardiac deformation due to respiration and multiple one-dimensional real-time measurable surface intensity traces at chest or abdomen. Despite the fact that these surface intensity traces can be strongly coupled with each other but poorly correlated with respiratory-induced cardiac deformation, we demonstrate how they can be used to accurately predict cardiac motion through the extraction of latent variables of both the input and output of the model. The proposed method allows cross-modality reconstruction of patient specific models for dense motion field prediction, which after initial modeling can be used for real-time prospective motion tracking or correction. Detailed numerical issues related to the technique are discussed and the effectiveness of the motion and deformation modeling is validated with 3-D magnetic resonance data sets acquired from ten asymptomatic subjects covering the entire respiratory range.

This paper presents a virtual tagging framework for measuring, as well as visualising, myocardial deformation using magnetic resonance (MR) velocity imaging. Tagging grids are allocated artificially according to the deformation gradient with varying shapes and densities. The control points are then deformed such that the difference between the induced deformation velocity and that of actually measured MR data is minimum. A full three-dimensional implementation of the technique combined with the mass conservation constraint is provided. Numerical considerations of applying the proposed framework and different optimization strategies have been investigated with both simulated and phantom experiments. The accuracy of the technique in terms of following material deformation is compared with that of conventional tagging technique. Index Terms-Finite-element analysis, magnetic resonance (MR) tagging, mass conservation, myocardial deformation, myocardial velocity mapping, strain analysis.

This paper introduces a novel approach to deformation modeling based on partial-least-squares-regression and its application to the registration of first-pass magnetic resonance perfusion image sequences. The method relies on the extraction of intrinsic correlations between the latent factors of both the input and output signals for deriving a simple yet accurate deformation model. The strength of the technique has been demonstrated with both numerically simulated data sets and a myocardial perfusion study which involves nine patients with known coronary artery disease. The method represents a step forward for the commonly used principal component analysis for salient motion feature extraction. The proposed technique should be applicable to studies that involve deformation prediction such as motion adaptive radiotherapy and imaging, where the deformation of the target organ can be predicted from externally measurable signals.

通过空彤彤态函敷的引入，将数字圈像（嵌斑）档是搜索方法进一步推广。提出丁敷字图像相是分析法在这一方击中，把对桩秽厦其各十导敷分量独立进行的相先进代变为叶变形彤态画敷的系数进行相是遗代，从而既简化丁速代过程，更妾现丁整十空彤埽的直接剥量（计算)。典型的实验蛄秉验证丁进一方法的可行性。