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.

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.

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。

本文应用数字图像测量系统．对砼试件在成形早期最初26小时的变形场进行了非接触的定量测量，得到了砼成形早期收缩应变随时间变化的曲线。整个测量过程简便直接，表明数字图像测量方法完全可用来对砼结构的位移场进行非接触的精密测量，在配备了相应的光学观察仪器后，也可用来测量一般的应变场，从而特为土建结构的定量测试提供新的有力手段。

This paper presents a new method for 3D shape reconstruction in computer-aided dental prosthetics. A specklegram is projected onto the tooth to be measured. This shadow speckle image is recorded and then processed by a digital image correlation method, which enables the computation of 2D shapes based on the similar principle of shadow moire method. By repeating the procedure for all the sides, i.e., one crown and several side surfaces, local 2D shapes can be measured precisely. Afterwards, these local 2D profiles are merged to form a 3D model, during which certain constraints such as the widths along perpendicular directions are introduced to guide the process. As the height information within an entire image field is recorded instantly, it has the potential to be employed in an intra-oral environment, which would make the patient feel more comfortable during the restoration process. In vitro experiments were carried out on gypsum teeth models and the results proved the effectiveness of the proposed method.