Current ultrasound methods for measuring myocardial strain are often limited to measurements in one or two dimensions. Cardiac motion and deformation however are truly 3-D. With the introduction of matrix transducer technology, 3-D ultrasound imaging of the heart has become feasible but suffers from low temporal and spatial resolution, making 3-D strain estimation challenging. In this paper, it is shown that automatic intensity-based spatio-temporal elastic registration of currently available 3-D volumetric ultrasound data sets can be used to measure the full 3-D strain tensor. The method was validated using simulated 3-D ultrasound data sets of the left ventricle (LV). Three types of data sets were simulated: a normal and symmetric LV with different heart rates, a more realistic asymmetric normal LV and an infarcted LV. The absolute error in the estimated displacement was between 0.47 +/-0.23 and 1.00 +/-0.59 mm, depending on heart rate and amount of background noise. The absolute error on the estimated strain was 9%-21% for the radial strain and 1%-4% for the longitudinal and circumferential strains. No large differences were found between the different types of data sets. The shape of the strain curves was estimated properly and the position of the infarcts could be identified correctly. Preliminary results on clinical data taken in vivo from three healthy volunteers and one patient with an apical aneurism confirmed these findings in a qualitative manner as the strain curves obtained with the proposed method have an amplitude and shape similar to what could be expected.

ABSTRACT:Unmanned aerial vehicles (UAVs) are becoming increasingly popular in professional mapping for stockpile analysis, construction site monitoring, and many other applications. Due to their robustness and competitive pricing, consumer UAVs are used more and more for these applications, but they are usually equipped with rolling shutter cameras. This is a significant obstacle when it comes to extracting high accuracy measurements using available photogrammetry software packages. In this paper, we evaluate the impact of the rolling shutter cameras of typical consumer UAVs on the accuracy of a 3D reconstruction. Hereto, we use a beta-version of the Pix4Dmapper 2.1 software to compare traditional (non rolling shutter) camera models against a newly implemented rolling shutter model with respect to both the accuracy of geo-referenced validation points and to the quality of the motion estimation. Multiple datasets have been acquired using popular quadrocopters (DJI Phantom 2 Vision+, DJI Inspire 1 and 3DR Solo) following a grid flight plan. For comparison, we acquired a dataset using a professional mapping drone (senseFly eBee) equipped with a global shutter camera. The bundle block adjustment of each dataset shows a significant accuracy improvement on validation ground control points when applying the new rolling shutter camera model for flights at higher speed (8 m/s). Competitive accuracies can be obtained by using the rolling shutter model, although global shutter cameras are still superior. Furthermore, we are able to show that the speed of the drone (and its direction) can be solely estimated from the rolling shutter effect of the camera.

SUMMARYFish swimming is probably one of the most studied and best understood locomotor behaviors in vertebrates. However, many fish also actively exploit sediments. Because of their elongate body shape, anguilliform fishes are not only efficient swimmers but also very maneuverable. Consequently, many species live in complexly structured environments near the bottom and many are known to burrow into the sediment. To better understand burrowing and subsurface locomotion in anguilliform fish we provide descriptive kinematic data on subsurface locomotion in a burrowing eel (Pisodonophis boro) using videofluoroscopy. We also measured the maximal forces that can be exerted by this species during head-first and tail-first burrowing, and explored the implications of head-first burrowing on mechanical stress distribution in the skull. Our data show that P. boro uses lateral undulation to penetrate and move in sandy sediments under water. The kinematics of subsurface locomotion are different from those observed during swimming and are characterized by a very high slip factor. These observations differ considerably from recently published data in terrestrial sand-swimming lizards, and suggest that the sediment behaves like a solid rather than a frictional fluid. Finally, our finite element models show that the cranial shape and structure in the head-first burrowing P. boro is mechanically more suited for head-first burrowing than that of an obligate tail-first burrowing species, Heteroconger hassi.

Automatic quantification of regional left ventricular deformation in volumetric ultrasound data remains challenging. Many methods have been proposed to extract myocardial motion, including techniques using block matching, phase-based correlation, differential optical flow methods, and image registration. Our lab previously presented an approach based on elastic registration of subsequent volumes using a B-spline representation of the underlying transformation field. Encouraging results were obtained for the assessment of global left ventricular function, but a thorough validation on a regional level was still lacking. For this purpose, univentricular thick-walled cardiac phantoms were deformed in an experimental setup to locally assess strain accuracy against sonomicrometry as a reference method and to assess whether regions containing stiff inclusions could be detected. Our method showed good correlations against sonomicrometry: r(2) was 0.96, 0.92, and 0.84 for the radial (ε(RR)), longitudinal (ε(LL)), and circumferential (ε(CC)) strain, respectively. Absolute strain errors and strain drift were low for ε(LL) (absolute mean error: 2.42%, drift: -1.05%) and ε(CC) (error: 1.79%, drift: -1.33%) and slightly higher for ε(RR) (error: 3.37%, drift: 3.05%). The discriminative power of our methodology was adequate to resolve full transmural inclusions down to 17 mm in diameter, although the inclusion-to-surrounding tissue stiffness ratio was required to be at least 5:2 (absolute difference of 39.42 kPa). When the inclusion-to-surrounding tissue stiffness ratio was lowered to approximately 2:1 (absolute difference of 22.63 kPa), only larger inclusions down to 27 mm in diameter could still be identified. Radial strain was found not to be reliable in identifying dysfunctional regions.

When imaging the heart, good temporal resolution is beneficial for capturing the information of short-lived cardiac phases (in particular, the isovolumetric phases). To increase the frame rate, parallel beamforming is a commonly used technique for fast cardiac imaging. Conventionally, a 4 multiple-line-acquisition (4MLA) system increases the frame rate by a factor of 4, making use of a broadened transmit beam to reduce block-like artifacts. As an alternative, it has been proposed to transmit an unfocused beam (i.e., plane wave or diverging wave) for which a large number of parallel receive beams (i.e., 16) can be formed for each transmit. However, to keep the spatial resolution acceptable in these approaches, spatial compounding of overlapping successive transmits is required. As a result, the effective gain in frame rate is similar to that of a 4MLA system. To date, it remains unclear how conventional 4MLA compares to plane-wave or diverging-wave imaging when operating at similar frame rate. The goal of this study was therefore to directly contrast the performance of these beamforming methods by computer simulation. In this study, the performance of 4 different imaging systems was investigated by quantitatively evaluating the characteristics of their beam profiles. The results showed that the conventional 4MLA and plane wave imaging were very competitive imaging strategies when operating at a similar frame rate. 4MLA performed better in the near field (i.e., 10 to 50 mm), whereas plane-wave imaging had better beam profiles in the far field (i.e., 50 to 90 mm). Although diverging-wave imaging had the poorest performance in the present study, it could potentially be improved by optimizing the settings.