Features of the non-contact carotid pressure waveform: Cardiac and vascular dynamics during rebreathing

This report amplifies and extends prior descriptions of the use of laser Doppler vibrometry (LDV) as a method for assessing cardiovascular activity, on a non-contact basis. A rebreathing task (n = 35 healthy individuals) was used to elicit multiple effects associated with changes in autonomic drive as well as blood gases including hypercapnia. The LDV pulse was obtained from two sites overlying the carotid artery, separated by 40 mm. A robust pulse signal was obtained from both sites, in accord with the well-described changes in carotid diameter over the blood pressure cycle. Emphasis was placed on extracting timing measures from the LDV pulse, which could serve as surrogate measures of pulse wave velocity (PWV) and the associated arterial stiffness. For validation purposes, a standard measure of pulse transit time (PTT) to the radial artery was obtained using a tonometric sensor. Two key measures of timing were extracted from the LDV pulse. One involved the transit time along the 40 mm distance separating the two LDV measurement sites. A second measure involved the timing of a late feature of the LDV pulse contour, which was interpreted as reflection wave latency and thus a measure of round-trip travel time. Both LDV measures agreed with the conventional PTT measure, in disclosing increased PWV during periods of active rebreathing. These results thus provide additional evidence that measures based on the non-contact LDV technique might provide surrogate measures for those obtained using conventional, more obtrusive assessment methods that require attached sensors.

Representing and computing regular languages on massively parallel networks

A general method is proposed for incorporating rule-based constraints corresponding to regular languages into stochastic inference problems, thereby allowing for a unified representation of stochastic and syntactic pattern constraints. The authors' approach establishes the formal connection of rules to Chomsky grammars and generalizes the original work of Shannon on the encoding of rule-based channel sequences to Markov chains of maximum entropy. This maximum entropy probabilistic view leads to Gibbs representations with potentials which have their number of minima growing at precisely the exponential rate that the language of deterministically constrained sequences grow. These representations are coupled to stochastic diffusion algorithms, which sample the language-constrained sequences by visiting the energy minima according to the underlying Gibbs probability law. This coupling yields the result that fully parallel stochastic cellular automata can be derived to generate samples from the rule-based constraint sets. The production rules and neighborhood state structure of the language of sequences directly determine the necessary connection structures of the required parallel computing surface. Representations of this type have been mapped to the DAP-510 massively parallel processor consisting of 1024 mesh-connected bit-serial processing elements for performing automated segmentation of electron-micrograph images.

Deblurring subject to nonnegativity constraints when known functions are present with application to object-constrained computerized tomography

The reconstruction of tomographic images is often treated as a linear deblurring problem. When a high-density, man-made metal object is present somewhere in the image field, it is a deblurring problem in which the unknown function has a component that is known except for some location and orientation parameters. We first address general linear deblurring problems in which a known function having unknown parameters is present. We then show how the resulting iterative solution can be applied to tomographic imaging in the presence of man-made foreign objects, and we apply the result, in particular, to X-ray computed tomography imaging used in support of brachytherapy treatment of advanced cervical cancer.

Ovulation rate and distribution in the thoroughbred mare, as determined by ultrasonic scanning: the effect of age

Ovarian activity was monitored in 2181 oestrous cycles from 1136 thoroughbred brood mares to accurately determine overall ovulation rate, the relative distribution of ovulations between left and right ovary, whether mare age had an effect on these parameters and whether ovulation pattern in one cycle affected the pattern within the next. Ultrasonic scanning was used in preference to rectal palpation and slaughterhouse material due to its greater accuracy. Mare's ages ranged from 3 to 22 years. The results obtained indicated a similar incidence of ovulation occurring on the right (49.5% of all ovulations) or left ovary (50.5%). Multiple ovulations (MO) occurred in 22.4% of oestrous cycles. Significantly (P<0.01), more double ovulations (DO) were bilateral (57.2%) than unilateral (42.8%); 20.7% were unilateral right and 22.1% were unilateral left. There were 828 mares grouped into six age groups: A (3-5 years), B (6-8 years), C (9-11 years), D (12-14 years), E (15-18 years), F (18-22 years). The distribution of ovulation between the left and right ovary was not affected by age group, but significant association (P<0.01) was evident between age and MO. Group A had 15% of cycles resulting in MO compared to 19.4, 24.6, 25.8, 28.6 and 35.1% in groups B-F, respectively. A significant (P<0.01) association between MO in successive cycles was also demonstrated, with a greater chance (P<0.05) of successive single ovulations (SO) being on alternate ovaries. There was no significant repeatability of the classification of DO in one cycle compared to the next. We conclude that: (i) the mare is a symmetrical ovulator; (ii) 22.4% of cycles yield MO (ovulation rate 1.23); (iii) this MO incidence increased (P<0.01) with age; (iv) the exhibition of MO in one cycle was linked to an increased probability (P<0.01) of a MO occurring at the next one and (v) SO in one ovary was more likely (P<0.05) to be followed by a SO on the alternate ovary during the next cycle.

Iterative deblurring for CT metal artifact reduction

Iterative deblurring methods using the expectation maximization (EM) formulation and the algebraic reconstruction technique (ART), respectively, are adapted for metal artifact reduction in medical computed tomography (CT). In experiments with synthetic noise-free and additive noisy projection data of dental phantoms, it is found that both simultaneous iterative algorithms produce superior image quality as compared to filtered backprojection after linearly fitting projection gaps. Furthermore, the EM-type algorithm converges faster than the ART-type algorithm in terms of either the I-divergence or Euclidean distance between ideal and reprojected data in the authors' simulation. Also, for a given iteration number, the EM-type deblurring method produces better image clarity but stronger noise than the ART-type reconstruction. The computational complexity of EM- and ART-based iterative deblurring is essentially the same, dominated by reprojection and backprojection. Relevant practical and theoretical issues are discussed.

Roughness penalties on finite domains

A class of penalty functions for use in estimation and image regularization is proposed. These penalty functions are defined for vectors whose indexes are locations in a finite lattice as the discrepancy between the vector and a shifted version of itself. After motivating this class of penalty functions, their relationship to Markov random field priors is explored. One of the penalty functions proposed, a divergence roughness penalty, is shown to be a discretization of a penalty proposed by Good and Gaskins (1971) for use in density estimation. One potential use in estimation problems is explored. An iterative algorithm that takes advantage of induced neighborhood structures is proposed and convergence of the algorithm is proven under specified conditions. Examples in emission tomographic imaging and radar imaging are given.