Development of Convolutional Neural Network to Segment Ultrasound Images of Histotripsy Ablation.

OBJECTIVE: Histotripsy is a focused ultrasound therapy that ablates tissue via the action of bubble clouds. It is under investigation to treat a number of ailments, including renal tumors. Ultrasound imaging is used to monitor histotripsy, though there remains a lack of definitive imaging metrics to confirm successful treatment outcomes. In this study, a convolutional neural network (CNN) was developed to segment ablation on ultrasound images. METHODS: A transfer learning approach was used to replace classification layers of the residual network ResNet-18. Inputs to the classification layers were based on ultrasound images of ablated red blood cell phantoms. Digital photographs served as the ground truth. The efficacy of the CNN was compared to subtraction imaging, and manual segmentation of images by two board-certified radiologists. RESULTS: The CNN had a similar performance to manual segmentation, though was improved relative to segmentation with subtraction imaging. Predictions of the network improved over the course of treatment, with the Dice similarity coefficient less than 20% for fewer than 500 applied pulses, but 85% for more than 750 applied pulses. The network was also applied to ultrasound images of ex vivo kidney exposed to histotripsy, which indicated a morphological shift in the treatment profile relative to the phantoms. These findings were consistent with histology that confirmed ablation of the targeted tissue. CONCLUSION: Overall, the CNN showed promise as a rapid means to assess outcomes of histotripsy and automate treatment. SIGNIFICANCE: Data collected in this study indicate integration of CNN image segmentation to gauge outcomes for histotripsy ablation holds promise for automating treatment procedures.

All-Quantum-Dot Infrared Light-Emitting Diodes.

Colloidal quantum dots (CQDs) are promising candidates for infrared electroluminescent devices. To date, CQD-based light-emitting diodes (LEDs) have employed a CQD emission layer sandwiched between carrier transport layers built using organic materials and inorganic oxides. Herein, we report the infrared LEDs that use quantum-tuned materials for each of the hole-transporting, the electron-transporting, and the light-emitting layers. We successfully tailor the bandgap and band position of each CQD-based component to produce electroluminescent devices that exhibit emission that we tune from 1220 to 1622 nm. Devices emitting at 1350 nm achieve peak external quantum efficiency up to 1.6% with a low turn-on voltage of 1.2 V, surpassing previously reported all-inorganic CQD LEDs.

Adjoint sensitivity analysis of plasmonic structures using the FDTD method.

We present an adjoint variable method for estimating the sensitivities of arbitrary responses with respect to the parameters of dispersive discontinuities in nanoplasmonic devices. Our theory is formulated in terms of the electric field components at the vicinity of perturbed discontinuities. The adjoint sensitivities are computed using at most one extra finite-difference time-domain (FDTD) simulation regardless of the number of parameters. Our approach is illustrated through the sensitivity analysis of an add-drop coupler consisting of a square ring resonator between two parallel waveguides. The computed adjoint sensitivities of the scattering parameters are compared with those obtained using the accurate but computationally expensive central finite difference approach.

Time domain adjoint sensitivity analysis of electromagnetic problems with nonlinear media.

In this paper, we propose a theory for wideband adjoint sensitivity analysis of problems with nonlinear media. We show that the sensitivities of the desired response with respect to all shape and material parameters are obtained through one extra adjoint simulation. Unlike linear problems, the system matrices of this adjoint simulation are time varying. Their values are determined during the original simulation. The proposed theory exploits the time-domain transmission line modeling (TLM) and provides an efficient AVM approach for sensitivity analysis of general time domain objective functions. The theory has been illustrated through a number of examples.

Realizing vertical light coupling and splitting in nano-plasmonic multilevel circuits.

We present a novel technique for vertical coupling of light guided by nanoscale plasmonic slot waveguides (PSWs). A triangularly-shaped plasmonic slot waveguide rotator is exploited to attain such coupling with a good efficiency over a wide bandwidth. Using this approach, light propagating in a horizontal direction is efficiently coupled to propagate in the vertical direction and vice versa. We also propose a power divider configuration to evenly split a vertically coupled light wave to two horizontal channels. A detailed parametric study of the triangular rotator is demonstrated with multiple configurations analyzed. This structure is suitable for efficient coupling in multilevel nano circuit environment.

Polarization-controlled excitation of multilevel plasmonic nano-circuits using single silicon nanowire.

We propose a surface plasmon polarization-controlled beam splitter based on plasmonic slot waveguides (PSWs). It couples light of different polarizations from a silicon nanowire into multilevel plasmonic networks. Two orthogonal PSWs are utilized as the guiding waveguides for each polarization. The proposed structure overcomes inherent polarization limitation in plasmonic structures by providing multilevel optical signal processing. This ability of controlling polarization can be exploited to achieve 3-D multilevel plasmonic circuits and polarization controlled chip to chip channel. Our device is of a compact size and a wide band operation. The device utilizes both quasi-TE and quasi-TM polarizations to allow for increased optical processing capability. The crosstalk is minimal between the two polarizations propagating in two different levels. We achieve good transmission efficiency at a wavelength of 1.55 µm for different polarizations. We analyze and simulate the structure using the FDTD method. The proposed device can be utilized in integrated chips for optical signal processing and optical computations.

Modeling and design of nano-plasmonic structures using transmission line modeling.

For the first time, we demonstrate the application of the time domain transmission line method (TLM) to accurate modeling of surface plasmon polariton (SPP) structures. The constructed TLM node allows for modeling of dispersive materials through simple time-difference equations. Using such node, an ultra-wide band excitation can be applied to obtain the response over the band of interest. Bérenger's perfectly matched layer (PML) boundary condition can readily be implemented using the same node. We illustrate our TLM approach through the modeling of different challenging structures including SPPs filters and focusing structures.