Search

A toroidal high-intensity focused ultrasound (HIFU) transducer was used to expose normal bladder wall tissues non-invasively in vivo in a porcine model in order to investigate the potential to treat bladder tumors. The transducer was divided into 32 concentric rings with equal surface areas, operating at 2.5 MHz. Eight animals were split into two groups of 4. In the first group, post-mortem evaluation was performed immediately after ultrasound exposure. In the second group, animals survived for up to seven days before post-mortem evaluation. The ultrasound imaging guided HIFU device was hand-held during the procedure using optical tracking to ensure correct targeting. One thermal lesion in each animal was created using a 40 s exposure at 80 acoustic Watts (free-field) in the trigone region of the bladder wall. The average ($\pm$Standard Deviation) abdominal wall and bladder wall thicknesses were 10.3 $\pm$ 1.4 mm and 1.1 $\pm$ 0.4 mm respectively. The longest and shortest axes of the HIFU ablations were 7.7 $\pm$ 2.9 mm and 6.0 $\pm$ 1.8 mm, respectively, resulting in an ablation of the whole thickness of the bladder wall in most cases. Ablation were performed at an average depth (distance from the skin surface to the centre of the HIFU lesion) of 42.5 $\pm$ 3.8 mm and extended throughout the thickness of the bladder. There were two cases of injury to tissues immediately adjacent to the bladder wall but without signs of perforation, as confirmed by histological analysis. Non-invasive HIFU ablation using a hand-held toroidal transducer was successfully performed to destroy regions of the bladder wall in vivo.

We have conducted fully relativistic simulations in a class of scalar-tensor theories with derivative self-interactions and screening of local scales. By using high-resolution shock-capturing methods and a non-vanishing shift vector, we have managed to avoid issues plaguing similar attempts in the past. We have first confirmed recent results by ourselves in spherical symmetry, obtained with an approximate approach and pointing at a partial breakdown of the screening in black-hole collapse. Then, we considered the late inspiral and merger of binary neutron stars. We found that screening tends to suppress the (subdominant) dipole scalar emission, but not the (dominant) quadrupole scalar mode. Our results point at quadrupole scalar signals as large as (or even larger than) in Fierz-Jordan-Brans-Dicke theories with the same conformal coupling, for strong-coupling scales in the MeV range that we can simulate., Comment: 9 pages, 6 figures. PRL version (includes Supplemental Material as Appendix)

We consider k-essence, a scalar-tensor theory with first-order derivative self-interactions that can screen local scales from scalar fifth forces, while allowing for sizeable deviations from General Relativity on cosmological scales. We construct fully nonlinear static stellar solutions that show the presence of this screening mechanism, and we use them as initial data for simulations of stellar oscillations and gravitational collapse in spherical symmetry. We find that for k-essence theories of relevance for cosmology, the screening mechanism works in the case of stellar oscillation and suppresses the monopole scalar emission to undetectable levels. In collapsing stars, we find that the Cauchy problem, although locally well posed, can lead to diverging characteristic speeds for the scalar field. By introducing a ''fixing equation'' in the spirit of J. Cayuso, N. Ortiz, and L. Lehner [Phys. Rev. D 96, 084043 (2017)], inspired in turn by dissipative relativistic hydrodynamics, we manage to evolve collapsing neutron stars past the divergence of the characteristic speeds. We show that, in these systems, the screening mechanism is less efficient than for oscillating and static stars, because the collapsing star must shed away all of its scalar hair before forming a black hole. For k-essence theories of relevance for cosmology, the characteristic frequency of the resulting scalar monopole signal is too low for terrestrial detectors, but we conjecture that space-borne interferometers such as LISA might detect it if a supernova explodes in the Galaxy., Comment: 17 pages, 11 figures. Minor changes, matches version published in PRD

Horava gravity breaks Lorentz symmetry by introducing a dynamical timelike scalar field (the khronon), which can be used as a preferred time coordinate (thus selecting a preferred space-time foliation). Adopting the khronon as the time coordinate, the theory is invariant only under time reparametrizations and spatial diffeomorphisms. In the infrared limit, this theory is sometimes referred to as khronometric theory. Here, we explicitly construct a generalization of khronometric theory, which avoids the propagation of Ostrogradski modes as a result of a suitable degeneracy condition (although stability of the latter under radiative corrections remains an open question). While this new theory does not have a general-relativistic limit and does not yield a Friedmann-Robertson-Walker-like cosmology on large scales, it still passes, for suitable choices of its coupling constants, local tests on Earth and in the solar system, as well as gravitational-wave tests. We also comment on the possible usefulness of this theory as a toy model of quantum gravity, as it could be completed in the ultraviolet into a 'degenerate Horava gravity' theory that could be perturbatively renormalizable without imposing any projectability condition., Comment: 19 pages, no figures; Comments on the stability under quantum corrections amended in v2; CQG version

Gravitational theories differing from General Relativity may explain the accelerated expansion of the Universe without a cosmological constant. However, to pass local gravitational tests, a "screening mechanism" is needed to suppress, on small scales, the fifth force driving the cosmological acceleration. We consider the simplest of these theories, i.e. a scalar-tensor theory with first-order derivative self-interactions, and study isolated (static and spherically symmetric) non-relativistic and relativistic stars. We produce screened solutions and use them as initial data for non-linear numerical evolutions in spherical symmetry. We find that these solutions are stable under large initial perturbations, as long as they do not cause gravitational collapse. When gravitational collapse is triggered, the characteristic speeds of the scalar evolution equation diverge, even before apparent black-hole or sound horizons form. This casts doubts on whether the dynamical evolution of screened stars may be predicted in these effective field theories., Comment: 6 pages, 3 figures; PRL version

We compute the quasi-bound state spectra of ultralight scalar and vector fields around rotating black holes. These spectra are determined by the gravitational fine structure constant $\alpha$, which is the ratio of the size of the black hole to the Compton wavelength of the field. When $\alpha$ is small, the energy eigenvalues and instability rates can be computed analytically. Since the solutions vary rapidly near the black hole horizon, ordinary perturbative approximations fail and we must use matched asymptotic expansions to determine the spectra. Our analytical treatment relies on the separability of the equations of motion, and is therefore only applicable to the scalar field and the electric modes of the vector field. However, for slowly-rotating black holes, the equations for the magnetic modes can be written in a separable form, which we exploit to derive their energy eigenvalues and conjecture an analytic form for their instability rates. To check our conjecture, and to extend all results to large values of $\alpha$, we solve for the spectra numerically. We explain how to accurately and efficiently compute these spectra, without relying on separability. This allows us to obtain reliable results for any $\alpha \gtrsim 0.001$ and black holes of arbitrary spin. Our results provide an essential input to the phenomenology of boson clouds around black holes, especially when these are part of binary systems., Comment: 47+25 pages, 16 figures

Retinal microaneurysms are the earliest clinical sign of diabetic retinopathy disease. Detection of microaneurysms is crucial for the early diagnosis of diabetic retinopathy and prevention of blindness. In this paper, a novel and reliable method for automatic detection of microaneurysms in retinal images is proposed. In the first stage of the proposed method, several preliminary microaneurysm candidates are extracted using a gradient weighting technique and an iterative thresholding approach. In the next stage, in addition to intensity and shape descriptors, a new set of features based on local convergence index filters is extracted for each candidate. Finally, the collective set of features is fed to a hybrid sampling/boosting classifier to discriminate the MAs from non-MAs candidates. The method is evaluated on images with different resolutions and modalities (RGB and SLO) using five publicly available datasets including the Retinopathy Online Challenge's dataset. The proposed method achieves an average sensitivity score of 0.471 on the ROC dataset outperforming state-of-the-art approaches in an extensive comparison. The experimental results on the other four datasets demonstrate the effectiveness and robustness of the proposed microaneurysms detection method regardless of different image resolutions and modalities.

Natural images contain often curvilinear structures, which might be disconnected, or partly occluded. Recovering the missing connection of disconnected structures is an open issue and needs appropriate geometric reasoning. We propose to find line co-occurrence statistics from the centerlines of blood vessels in retinal images and show its remarkable similarity to a well-known probabilistic model for the connectivity pattern in the primary visual cortex. Furthermore, the probabilistic model is trained from the data via statistics and used for automated grouping of interrupted vessels in a spectral clustering based approach. Several challenging image patches are investigated around junction points, where successful results indicate the perfect match of the trained model to the profiles of blood vessels in retinal images. Also, comparisons among several statistical models obtained from different datasets reveals their high similarity i.e., they are independent of the dataset. On top of that, the best approximation of the statistical model with the symmetrized extension of the probabilistic model on the projective line bundle is found with a least square error smaller than 2%. Apparently, the direction process on the projective line bundle is a good continuation model for vessels in retinal images.

Tree-like structures such as retinal images are widely studied in computer-aided diagnosis systems for large-scale screening programs. Despite several segmentation and tracking methods proposed in the literature, there still exist several limitations specifically when two or more curvilinear structures cross or bifurcate, or in the presence of interrupted lines or highly curved blood vessels. In this paper, we propose a novel approach based on multi-orientation scores augmented with a contextual affinity matrix, which both are inspired by the geometry of the primary visual cortex (V1) and their contextual connections. The connectivity is described with a five-dimensional kernel obtained as the fundamental solution of the Fokker-Planck equation modelling the cortical connectivity in the lifted space of positions, orientations, curvatures and intensity. It is further used in a self-tuning spectral clustering step to identify the main perceptual units in the stimuli. The proposed method has been validated on several easy and challenging structures in a set of artificial images and actual retinal patches. Supported by quantitative and qualitative results, the method is capable of overcoming the limitations of current state-of-the-art techniques.

We propose a template matching method for the detection of 2D image objects that are characterized by orientation patterns. Our method is based on data representations via orientation scores, which are functions on the space of positions and orientations, and which are obtained via a wavelet-type transform. This new representation allows us to detect orientation patterns in an intuitive and direct way, namely via cross-correlations. Additionally, we propose a generalized linear regression framework for the construction of suitable templates using smoothing splines. Here, it is important to recognize a curved geometry on the position-orientation domain, which we identify with the Lie group SE(2): the roto-translation group. Templates are then optimized in a B-spline basis, and smoothness is defined with respect to the curved geometry. We achieve state-of-the-art results on three different applications: detection of the optic nerve head in the retina (99.83% success rate on 1737 images), of the fovea in the retina (99.32% success rate on 1616 images), and of the pupil in regular camera images (95.86% on 1521 images). The high performance is due to inclusion of both intensity and orientation features with effective geometric priors in the template matching. Moreover, our method is fast due to a cross-correlation based matching approach., Comment: 28 pages, 11 figures, 5 appendices. Paper accepted at ieee transaction on Pattern Analysis and Machine Inteligence (ieee tPAMI)

Retinal images provide early signs of diabetic retinopathy, glaucoma, and hypertension. These signs can be investigated based on microaneurysms or smaller vessels. The diagnostic biomarkers are the change of vessel widths and angles especially at junctions, which are investigated using the vessel segmentation or tracking. Vessel paths may also be interrupted; crossings and bifurcations may be disconnected. This paper addresses a novel contextual method based on the geometry of the primary visual cortex (V1) to study these difficulties. We have analyzed the specific problems at junctions with a connectivity kernel obtained as the fundamental solution of the Fokker-Planck equation, which is usually used to represent the geometrical structure of multi-orientation cortical connectivity. Using the spectral clustering on a large local affinity matrix constructed by both the connectivity kernel and the feature of intensity, the vessels are identified successfully in a hierarchical topology each representing an individual perceptual unit., Comment: submitted to and accepted by JMIV

Left-invariant PDE-evolutions on the roto-translation group $SE(2)$ (and their resolvent equations) have been widely studied in the fields of cortical modeling and image analysis. They include hypo-elliptic diffusion (for contour enhancement) proposed by Citti & Sarti, and Petitot, and they include the direction process (for contour completion) proposed by Mumford. This paper presents a thorough study and comparison of the many numerical approaches, which, remarkably, is missing in the literature. Existing numerical approaches can be classified into 3 categories: Finite difference methods, Fourier based methods (equivalent to $SE(2)$-Fourier methods), and stochastic methods (Monte Carlo simulations). There are also 3 types of exact solutions to the PDE-evolutions that were derived explicitly (in the spatial Fourier domain) in previous works by Duits and van Almsick in 2005. Here we provide an overview of these 3 types of exact solutions and explain how they relate to each of the 3 numerical approaches. We compute relative errors of all numerical approaches to the exact solutions, and the Fourier based methods show us the best performance with smallest relative errors. We also provide an improvement of Mathematica algorithms for evaluating Mathieu-functions, crucial in implementations of the exact solutions. Furthermore, we include an asymptotical analysis of the singularities within the kernels and we propose a probabilistic extension of underlying stochastic processes that overcomes the singular behavior in the origin of time-integrated kernels. Finally, we show retinal imaging applications of combining left-invariant PDE-evolutions with invertible orientation scores., Comment: A final and corrected version of the manuscript is Published in Numerical Mathematics: Theory, Methods and Applications (NM-TMA), vol. (9), p.1-50, 2016

This paper presents a method for retinal vasculature extraction based on biologically inspired multi-orientation analysis. We apply multi-orientation analysis via so-called invertible orientation scores, modeling the cortical columns in the visual system of higher mammals. This allows us to generically deal with many hitherto complex problems inherent to vessel tracking, such as crossings, bifurcations, parallel vessels, vessels of varying widths and vessels with high curvature. Our approach applies tracking in invertible orientation scores via a novel geometrical principle for curve optimization in the Euclidean motion group SE(2). The method runs fully automatically and provides a detailed model of the retinal vasculature, which is crucial as a sound basis for further quantitative analysis of the retina, especially in screening applications., Comment: Accepted at JMIV. The final publication will become available at springerlink.com

Textures often show multiscale properties and hence multiscale techniques are considered useful for texture analysis. Scale-space theory as a biologically motivated approach may be used to construct multiscale textures. In this paper various ways are studied to combine features on different scales for texture classification of small image patches. We use the N-jet of derivatives up to the second order at different scales to generate distinct pattern representations (DPR) of feature subsets. Each feature subset in the DPR is given to a base classifier (BC) of a two-stage combined classifier. The decisions made by these BCs are combined in two stages over scales and derivatives. Various combining systems and their significances and differences are discussed. The learning curves are used to evaluate the performances. We found for small sample sizes combining classifiers performs significantly better than combining feature spaces (CFS). It is also shown that combining classifiers performs better than the support vector machine on CFS in multiscale texture classification., Comment: 28 pages

We describe a device to conveniently measure the positions of the phase boundaries in a dilution refrigerator. We show how a simple modification of a standard capacitive level gauge (segmentation of one of the electrodes) permits a direct calibration of the capacitance versus phase boundary position. We compare this direct calibration with the indirect procedure that must be adopted for a conventional capacitive level gauge. The device facilitates the correct adjustment of the 3He/4He fraction in the dilution refrigerator., Comment: 3 pages

Single crystals of Zn_(1-x)Mn_xIn_2Se_4 were grown by the chemical vapour phase transport technique (CVT). The Mn concentration was varied from x=1 to x=0.01. Through X-rays powder diffraction patterns and Laue diagrams of single crystals we studied the transformation from the hexagonal structure of MnIn_2Se_4 to the tetragonal structure of ZnIn_2Se_4., Comment: 8 pages, 3 figures. Final form as published in J. Phys. Cond. Matter

We have performed spectroscopy measurements on two coupled flux qubits. The qubits are coupled inductively, which results in a $\sigma_1^z\sigma_2^z$ interaction. By applying microwave radiation, we observe resonances due to transitions from the ground state to the first two excited states. From the position of these resonances as a function of the magnetic field applied we observe the coupling of the qubits. The coupling strength agrees well with calculations of the mutual inductance.

The magnetization of Pb_{1-x}Eu_{x}Te samples with x = 1.9, 2.6 and 6.0% was measured at 20 mK in fields up to 50 kOe, and at 0.6 K in fields up to 180 kOe. The 20 mK data show the magnetization steps (MSTs) arising from pairs and from triplets. The pair MSTs are used to obtain the dominant Eu-Eu antiferromagnetic exchange constant, J/k_{B} = -0.264 \pm 0.018 K. The exchange constant for triplets is the same. Comparison of the magnetization curves with theoretical simulations indicates that the Eu ions are not randomly distributed over all the cation sites. The deviation from a random distribution is much smaller if J is assumed to be the nearest-neighbor exchange constant J_{1} rather than the next-nearest-neighbor exchange constant J_{2}. On this basis, J is tentatively identified as J_{1}. To obtain agreement with the data, it must be assumed that the Eu ions tend to bunch together. Comparision with microprobe data indicates that the length scale for these concentration variations is smaller than a few micrometer. The theoretical simulations in the present work improve on those performed earlier by including clusters larger than three spins., Comment: 9 pages, 6 figs, Revtex, accepted for publication in Phys. Rev. B

Cancer treatment by extracorporeal high intensity focused ultrasound (HIFU) is constrained by the time needed to ablate relevant tumour volumes clinically. Controlled cavitation might be used to optimise HIFU treatments, but such control requires a greater understanding of its role in lesion formation, and the provision of appropriate techniques to monitor cavitation in tissue. During HIFU exposure various forms of cavitation can occur: acoustic cavitation (both non-inertial and inertial), and bubble formation due to two thermally-driven effects (the vaporisation of liquid into vapour, and the exsolution of formerly dissolved permanent gas out of the liquid and into gas spaces). Different forms of cavitation gives rise to characteristic signals that can be monitored during HIFU. Furthermore, the character of the signal can change depending on the stage of the cavitation in question (nucleation, established cavitation, population effects etc.). Prior to undertaking experiments using tissue, studies were performed by exposing degassed water. The aim of these experiments was to test a detection system in a minimally attenuating medium known to cavitate, in order to provide data for comparison with ex-vivo tissue results. This report is written in support of the journal paper "A Study of Bubble Activity Generated in Ex-Vivo Tissue by High Intensity Focused Ultrasound (HIFU)" by the same authors (McLaughlan et al. 2010). It outlines supporting material for the discussion and conclusions contained in that paper, a study involving monitoring clinically relevant HIFU exposures in degassed water and ex-vivo bovine liver. Monitoring is accomplished using a suite of cavitation detection techniques (exploiting passive and active acoustics, audible and ultrasonic emissions and electrical drive power fluctuations). The aim of the paper is to allow informed progress towards a monitoring system specifically tailored for use during clinical HIFU treatments. [ABSTRACT FROM AUTHOR]