Count-Free Single-Photon 3D Imaging with Race Logic.

Single-photon cameras (SPCs) have emerged as a promising new technology for high-resolution 3D imaging. A single-photon 3D camera determines the round-trip time of a laser pulse by precisely capturing the arrival of individual photons at each camera pixel. Constructing photon-timestamp histograms is a fundamental operation for a single-photon 3D camera. However, in-pixel histogram processing is computationally expensive and requires large amount of memory per pixel. Digitizing and transferring photon timestamps to an off-sensor histogramming module is bandwidth and power hungry. Can we estimate distances without explicitly storing photon counts? Yes-here we present an online approach for distance estimation suitable for resource-constrained settings with limited bandwidth, memory and compute. The two key ingredients of our approach are (a) processing photon streams using race logic, which maintains photon data in the time-delay domain, and (b) constructing count-free equi-depth histograms as opposed to conventional equi-width histograms. Equi-depth histograms are a more succinct representation for "peaky" distributions, such as those obtained by an SPC pixel from a laser pulse reflected by a surface. Our approach uses a binner element that converges on the median (or, more generally, to another k-quantile) of a distribution. We cascade multiple binners to form an equi-depth histogrammer that produces multi-bin histograms. Our evaluation shows that this method can provide at least an order of magnitude reduction in bandwidth and power consumption while maintaining similar distance reconstruction accuracy as conventional histogram-based processing methods.

CASPI: collaborative photon processing for active single-photon imaging.

Image sensors capable of capturing individual photons have made tremendous progress in recent years. However, this technology faces a major limitation. Because they capture scene information at the individual photon level, the raw data is sparse and noisy. Here we propose CASPI: Collaborative Photon Processing for Active Single-Photon Imaging, a technology-agnostic, application-agnostic, and training-free photon processing pipeline for emerging high-resolution single-photon cameras. By collaboratively exploiting both local and non-local correlations in the spatio-temporal photon data cubes, CASPI estimates scene properties reliably even under very challenging lighting conditions. We demonstrate the versatility of CASPI with two applications: LiDAR imaging over a wide range of photon flux levels, from a sub-photon to high ambient regimes, and live-cell autofluorescence FLIM in low photon count regimes. We envision CASPI as a basic building block of general-purpose photon processing units that will be implemented on-chip in future single-photon cameras.

Split thickness skin graft in active psoriasis in patient with clear cell variant squamous cell carcinoma.

The case report discusses split thickness skin grafting in a patient with active psoriasis. This also reports a case of a rare variant of squamous cell carcinoma.

A kernel smoothing algorithm for ablation visualization in ultrasound elastography.

Three-dimensional visualization of tumor ablation procedures have significant clinical value because the ability to accurately visualize ablated volumes can help clinicians gauge the extent of ablated tissue necrosis and plan future treatment steps. Better control over ablation volume can prevent recurrence of tumors treated using ablative procedures. This paper presents a kernel based smoothing algorithm called MatérnSmooth to reconstruct shear wave velocity maps from data acquired through ultrasound electrode vibration elastography. Shear wave velocity estimates are acquired on several intersecting imaging planes that share a common axis of intersection collinear with the ablation needle. An objective method of choosing smoothing parameters from underlying data is outlined through simulations. Experimental validation was performed on data acquired from a tissue mimicking phantom. Volume estimates were found to be within 20% of the true value.

Efficient 3-D Reconstruction in Ultrasound Elastography via a Sparse Iteration Based on Markov Random Fields.

Percutaneous needle-based liver ablation procedures are becoming increasingly common for the treatment of small isolated tumors in hepatocellular carcinoma patients who are not candidates for surgery. Rapid 3-D visualization of liver ablations has potential clinical value, because it can enable interventional radiologists to plan and execute needle-based ablation procedures with real time feedback. Ensuring the right volume of tissue is ablated is desirable to avoid recurrence of tumors from residual untreated cancerous cells. Shear wave velocity (SWV) measurements can be used as a surrogate for tissue stiffness to distinguish stiffer ablated regions from softer untreated tissue. This paper extends the previously reported sheaf reconstruction method to generate complete 3-D visualizations of SWVs without resorting to an approximate intermediate step of reconstructing transverse C planes. The noisy data are modeled using a Markov random field, and a computationally tractable reconstruction algorithm that can handle grids with millions of points is developed. Results from simulated ellipsoidal inclusion data show that this algorithm outperforms standard nearest neighbor interpolation by an order of magnitude in mean squared reconstruction error. Results from the phantom experiments show that it also provides a higher contrast-to-noise ratio by almost 2 dB and better signal-to-noise ratio in the stiff inclusion by over 2 dB compared with nearest neighbor interpolation and has lower computational complexity than linear and spline interpolation.

Post-Procedure Evaluation of Microwave Ablations of Hepatocellular Carcinomas Using Electrode Displacement Elastography.

Microwave ablation has been used clinically as an alternative to surgical resection. However, lack of real-time imaging to assess treated regions may compromise treatment outcomes. We previously introduced electrode displacement elastography (EDE) for strain imaging and verified its feasibility in vivo on porcine animal models. In this study, we evaluated EDE on 44 patients diagnosed with hepatocellular carcinoma, treated using microwave ablation. The ablated region was identified on EDE images for 40 of the 44 patients. Ablation areas averaged 13.38 ± 4.99 cm2 on EDE, compared with 7.61 ± 3.21 cm2 on B-mode imaging. Contrast and contrast-to-noise ratios obtained with EDE were 232% and 98%, respectively, significantly higher than values measured on B-mode images (p < 0.001). This study indicates that EDE is feasible in patients and provides improved visualization of the ablation zone compared with B-mode ultrasound.

Comparison of three dimensional strain volume reconstructions using SOUPR and wobbler based acquisitions: A phantom study.

PURPOSE: Ultrasound strain imaging is a relatively low cost and portable modality for monitoring percutaneous thermal ablation of liver neoplasms. However, a 3D strain volume reconstruction from existing 2D strain images is necessary to fully delineate the thermal dose distribution. Tissue mimicking (TM) phantom experiments were performed to validate a novel volume reconstruction algorithm referred to as sheaf of ultrasound planes reconstruction (SOUPR), based on a series of 2D rotational imaging planes. METHODS: Reconstruction using SOUPR was formulated as an optimization problem with constraints on data consistency with 2D strain images and data smoothness of the volume data. Reconstructed ablation inclusion dimensions, volume, and elastographic signal to noise ratio (SNRe) and contrast to noise ratio (CNRe) were compared with conventional 3D ultrasound strain imaging based on interpolating a series of quasiparallel 2D strain images with a wobbler transducer. RESULTS: Volume estimates of the phantom inclusion were in a similar range for both acquisition approaches. SNRe and CNRe obtained with SOUPR were significantly higher on the order of 250% and 166%, respectively. The mean error of the inclusion dimension reconstructed with a wobbler transducer was on the order of 10.4%, 3.5%, and 19.0% along the X, Y, and Z axes, respectively, while the error with SOUPR was on the order of 2.6%, 2.8%, and 9.6%. A qualitative comparison of SOUPR and wobbler reconstruction was also performed using a thermally ablated region created in ex vivo bovine liver tissue. CONCLUSIONS: The authors have demonstrated using experimental evaluations with a TM phantom that the reconstruction results obtained with SOUPR were superior when compared with a conventional wobbler transducer in terms of inclusion shape preservation and detectability.

Ultrasonic tracking of shear waves using a particle filter.

PURPOSE: This paper discusses an application of particle filtering for estimating shear wave velocity in tissue using ultrasound elastography data. Shear wave velocity estimates are of significant clinical value as they help differentiate stiffer areas from softer areas which is an indicator of potential pathology. METHODS: Radio-frequency ultrasound echo signals are used for tracking axial displacements and obtaining the time-to-peak displacement at different lateral locations. These time-to-peak data are usually very noisy and cannot be used directly for computing velocity. In this paper, the denoising problem is tackled using a hidden Markov model with the hidden states being the unknown (noiseless) time-to-peak values. A particle filter is then used for smoothing out the time-to-peak curve to obtain a fit that is optimal in a minimum mean squared error sense. RESULTS: Simulation results from synthetic data and finite element modeling suggest that the particle filter provides lower mean squared reconstruction error with smaller variance as compared to standard filtering methods, while preserving sharp boundary detail. Results from phantom experiments show that the shear wave velocity estimates in the stiff regions of the phantoms were within 20% of those obtained from a commercial ultrasound scanner and agree with estimates obtained using a standard method using least-squares fit. Estimates of area obtained from the particle filtered shear wave velocity maps were within 10% of those obtained from B-mode ultrasound images. CONCLUSIONS: The particle filtering approach can be used for producing visually appealing SWV reconstructions by effectively delineating various areas of the phantom with good image quality properties comparable to existing techniques.

Slope Estimation in Noisy Piecewise Linear Functions.

This paper discusses the development of a slope estimation algorithm called MAPSlope for piecewise linear data that is corrupted by Gaussian noise. The number and locations of slope change points (also known as breakpoints) are assumed to be unknown a priori though it is assumed that the possible range of slope values lies within known bounds. A stochastic hidden Markov model that is general enough to encompass real world sources of piecewise linear data is used to model the transitions between slope values and the problem of slope estimation is addressed using a Bayesian maximum a posteriori approach. The set of possible slope values is discretized, enabling the design of a dynamic programming algorithm for posterior density maximization. Numerical simulations are used to justify choice of a reasonable number of quantization levels and also to analyze mean squared error performance of the proposed algorithm. An alternating maximization algorithm is proposed for estimation of unknown model parameters and a convergence result for the method is provided. Finally, results using data from political science, finance and medical imaging applications are presented to demonstrate the practical utility of this procedure.

C-plane Reconstructions from Sheaf Acquisition for Ultrasound Electrode Vibration Elastography.

This paper presents a novel algorithm for reconstructing and visualizing ablated volumes using radiofrequency ultrasound echo data acquired with the electrode vibration elastography approach. The ablation needle is vibrated using an actuator to generate shear wave pulses that are tracked in the ultrasound image plane at different locations away from the needle. This data is used for reconstructing shear wave velocity maps for each imaging plane. A C-plane reconstruction algorithm is proposed which estimates shear wave velocity values on a collection of transverse planes that are perpendicular to the imaging planes. The algorithm utilizes shear wave velocity maps from different imaging planes that share a common axis of intersection. These C-planes can be used to generate a 3D visualization of the ablated region. Experimental validation of this approach was carried out using data from a tissue mimicking phantom. The shear wave velocity estimates were within 20% of those obtained from a clinical scanner, and a contrast of over 4 dB was obtained between the stiff and soft regions of the phantom.

Three-dimensional sheaf of ultrasound planes reconstruction (SOUPR) of ablated volumes.

This paper presents an algorithm for 3-D reconstruction of tumor ablations using ultrasound shear wave imaging with electrode vibration elastography. Radio-frequency ultrasound data frames are acquired over imaging planes that form a subset of a sheaf of planes sharing a common axis of intersection. Shear wave velocity is estimated separately on each imaging plane using a piecewise linear function fitting technique with a fast optimization routine. An interpolation algorithm then computes velocity maps on a fine grid over a set of C-planes that are perpendicular to the axis of the sheaf. A full 3-D rendering of the ablation can then be created from this stack of C-planes; hence the name "Sheaf Of Ultrasound Planes Reconstruction" or SOUPR. The algorithm is evaluated through numerical simulations and also using data acquired from a tissue mimicking phantom. Reconstruction quality is gauged using contrast and contrast-to-noise ratio measurements and changes in quality from using increasing number of planes in the sheaf are quantified. The highest contrast of 5 dB is seen between the stiffest and softest regions of the phantom. Under certain idealizing assumptions on the true shape of the ablation, good reconstruction quality while maintaining fast processing rate can be obtained with as few as six imaging planes suggesting that the method is suited for parsimonious data acquisitions with very few sparsely chosen imaging planes.

Three dimensional shear wave elastographic reconstruction of ablations.

This paper presents an algorithm for three dimensional (3D) reconstruction of tumor ablations using ultrasound electrode vibration elastography. Shear wave velocity, which is used as a surrogate for tissue stiffness, is estimated by perturbing the ablation needle and tracking frame-to-frame displacements using radiofrequency ultrasound echo data. This process is repeated over many imaging planes that share a common axis of intersection collinear with needle. A 3D volume is reconstructed by solving an optimization problem which smoothly approximates shear wave velocities on a stack of transverse planes. The mean shear wave velocity estimates obtained in the phantom experiments are within 20% of those measured using a commercial shear wave imaging system.

Stochastic piecewise linear function fitting with application to ultrasound shear wave imaging.

Piecewise linear function fitting is ubiquitous in many signal processing applications. Inspired by an application to shear wave velocity imaging in ultrasound elastography, this paper presents a discrete state-space Markov model for noisy piecewise linear data and also proposes a tractable algorithm for maximum a posteriori estimation of the slope of each segment in the piecewise linear function. The number and locations of breaks is handled indirectly by the stochastics of the Markov model. In the ultrasound shear wave imaging application, these slope values have concrete physical interpretation as being the reciprocal of the shear wave velocities in the imaged medium. Data acquired on an ellipsoidal inclusion phantom shows that this algorithm can provide good contrast of around 6 dB and contrast to noise ratio of 25 dB between the stiff inclusion and surrounding soft background. The phantom validation study also shows that this algorithm can be used to preserve sharp boundary details, which would otherwise be blurred out if a sliding window least squares filter is applied.

A COMPARISON OF MODEL BASED AND DIRECT OPTIMIZATION BASED FILTERING ALGORITHMS FOR SHEARWAVE VELOCITY RECONSTRUCTION FOR ELECTRODE VIBRATION ELASTOGRAPHY.

Tissue stiffness estimation plays an important role in cancer detection and treatment. The presence of stiffer regions in healthy tissue can be used as an indicator for the possibility of pathological changes. Electrode vibration elastography involves tracking of a mechanical shear wave in tissue using radio-frequency ultrasound echoes. Based on appropriate assumptions on tissue elasticity, this approach provides a direct way of measuring tissue stiffness from shear wave velocity, and enabling visualization in the form of tissue stiffness maps. In this study, two algorithms for shear wave velocity reconstruction in an electrode vibration setup are presented. The first method models the wave arrival time data using a hidden Markov model whose hidden states are local wave velocities that are estimated using a particle filter implementation. This is compared to a direct optimization-based function fitting approach that uses sequential quadratic programming to estimate the unknown velocities and locations of interfaces. The mean shear wave velocities obtained using the two algorithms are within 10%of each other. Moreover, the Young's modulus estimates obtained from an incompressibility assumption are within 15 kPa of those obtained from the true stiffness data obtained from mechanical testing. Based on visual inspection of the two filtering algorithms, the particle filtering method produces smoother velocity maps.