Arterial Distension Monitoring Scheme Using FPGA-Based Inference Machine in Ultrasound Scanner Circuit System.

This paper presents an arterial distension monitoring scheme using a field-programmable gate array (FPGA)-based inference machine in an ultrasound scanner circuit system. An arterial distension monitoring requires a precise positioning of an ultrasound probe on an artery as a prerequisite. The proposed arterial distension monitoring scheme is based on a finite state machine that incorporates sequential support vector machines (SVMs) to assist in both coarse and fine adjustments of probe position. The SVMs sequentially perform recognitions of ultrasonic A-mode echo pattern for a human carotid artery. By employing sequential SVMs in combination with convolution and average pooling, the number of features for the inference machine is significantly reduced, resulting in less utilization of hardware resources in FPGA. The proposed arterial distension monitoring scheme was implemented in an FPGA (Artix7) with a resource utilization percentage less than 9.3%. To demonstrate the proposed scheme, we implemented a customized ultrasound scanner consisting of a single-element transducer, an FPGA, and analog interface circuits with discrete chips. In measurements, we set virtual coordinates on a human neck for 9 human subjects. The achieved accuracy of probe positioning inference is 88%, and the Pearson coefficient (r) of arterial distension estimation is 0.838.

Switchable preamplifier for dual modal photoacoustic and ultrasound imaging.

Photoacoustic (PA) imaging is a high-fidelity biomedical imaging technique based on the principle of molecular-specific optical absorption of biological tissue constitute. Because PA imaging shares the same basic principle as that of ultrasound (US) imaging, the use of PA/US dual-modal imaging can be achieved using a single system. However, because PA imaging is limited to a shallower depth than US imaging due to the optical extinction in biological tissue, the PA signal yields a lower signal-to-noise ratio (SNR) than US images. To selectively amplify the PA signal, we propose a switchable preamplifier for acoustic-resolution PA microscopy implemented on an application-specific integrated circuit. Using the preamplifier, we measured the increments in the SNR with both carbon lead and wire phantoms. Furthermore, in vivo whole-body PA/US imaging of a mouse with a preamplifier showed enhancement of SNR in deep tissues, unveiling deeply located organs and vascular networks. By selectively amplifying the PA signal range to a level similar to that of the US signal without contrast agent administration, our switchable amplifier strengthens the mutual complement between PA/US imaging. PA/US imaging is impending toward clinical translation, and we anticipate that this study will help mitigate the imbalance of image depth between the two imaging modalities.

Human glioblastoma arises from subventricular zone cells with low-level driver mutations.

Glioblastoma (GBM) is a devastating and incurable brain tumour, with a median overall survival of fifteen months1,2. Identifying the cell of origin that harbours mutations that drive GBM could provide a fundamental basis for understanding disease progression and developing new treatments. Given that the accumulation of somatic mutations has been implicated in gliomagenesis, studies have suggested that neural stem cells (NSCs), with their self-renewal and proliferative capacities, in the subventricular zone (SVZ) of the adult human brain may be the cells from which GBM originates3-5. However, there is a lack of direct genetic evidence from human patients with GBM4,6-10. Here we describe direct molecular genetic evidence from patient brain tissue and genome-edited mouse models that show astrocyte-like NSCs in the SVZ to be the cell of origin that contains the driver mutations of human GBM. First, we performed deep sequencing of triple-matched tissues, consisting of (i) normal SVZ tissue away from the tumour mass, (ii) tumour tissue, and (iii) normal cortical tissue (or blood), from 28 patients with isocitrate dehydrogenase (IDH) wild-type GBM or other types of brain tumour. We found that normal SVZ tissue away from the tumour in 56.3% of patients with wild-type IDH GBM contained low-level GBM driver mutations (down to approximately 1% of the mutational burden) that were observed at high levels in their matching tumours. Moreover, by single-cell sequencing and laser microdissection analysis of patient brain tissue and genome editing of a mouse model, we found that astrocyte-like NSCs that carry driver mutations migrate from the SVZ and lead to the development of high-grade malignant gliomas in distant brain regions. Together, our results show that NSCs in human SVZ tissue are the cells of origin that contain the driver mutations of GBM.

A Single-Chip 64-Channel Ultrasound RX-Beamformer Including Analog Front-End and an LUT for Non-Uniform ADC-Sample-Clock Generation.

A 64-channel RX digital beamformer was implemented in a single chip for 3-D ultrasound medical imaging using 2-D phased-array transducers. The RX beamformer chip includes 64 analog front-end branches including 64 non-uniform sampling ADCs, a FIFO/Adder, and an on-chip look-up table (LUT). The LUT stores the information on the rising edge timing of the non-uniform ADC sampling clocks. To include the LUT inside the beamformer chip, the LUT size was reduced by around 240 times by approximating an ADC-sample-time profile w.r.t. focal points (FP) along a scanline (SL) for a channel into a piece-wise linear form. The maximum error between the approximated and accurate sample times of ADC is eight times the sample time resolution (Ts) that is 1/32 of the ultrasound signal period in this work. The non-uniform sampling reduces the FIFO size required for digital beamforming by around 20 times. By applying a 9-dot image from Field-II program and 2-D ultrasound phantom images to the fabricated RX beamformer chip, the original images were successfully reconstructed from the measured output. The chip in a 0.13-um CMOS occupies 30.25 [Formula: see text] and consumes 605 mW.

MRI artifact correction using sparse + low-rank decomposition of annihilating filter-based hankel matrix.

PURPOSE: Magnetic resonance imaging (MRI) artifacts are originated from various sources including instability of an magnetic resonance (MR) system, patient motion, inhomogeneities of gradient fields, and so on. Such MRI artifacts are usually considered as irreversible, so additional artifact-free scan or navigator scan is necessary. To overcome these limitations, this article proposes a novel compressed sensing-based approach for removal of various MRI artifacts. THEORY: Recently, the annihilating filter based low-rank Hankel matrix approach was proposed. The annihilating filter based low-rank Hankel matrix exploits the duality between the low-rankness of weighted Hankel structured matrix and the sparsity of signal in a transform domain. Because MR artifacts usually appeared as sparse k-space components, the low-rank Hankel matrix from underlying artifact-free k-space data can be exploited to decompose the sparse outliers. METHODS: The sparse + low-rank decomposition framework using Hankel matrix was proposed for removal of MRI artifacts. Alternating direction method of multipliers algorithm was employed for the minimization of associated cost function with the initialized matrices from a factorization-based matrix completion. RESULTS: Experimental results demonstrated that the proposed algorithm can correct MR artifacts including herringbone (crisscross), motion, and zipper artifacts without image distortion. CONCLUSION: The proposed method may be a robust correction solution for various MRI artifacts that can be represented as sparse outliers. Magn Reson Med 78:327-340, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

A single-chip 32-channel analog beamformer with 4-ns delay resolution and 768-ns maximum delay range for ultrasound medical imaging with a linear array transducer.

A single-chip 32-channel analog beamformer is proposed. It achieves a delay resolution of 4 ns and a maximum delay range of 768 ns. It has a focal-point based architecture, which consists of 7 sub-analog beamformers (sub-ABF). Each sub-ABF performs a RX focusing operation for a single focal point. Seven sub-ABFs perform a time-interleaving operation to achieve the maximum delay range of 768 ns. Phase interpolators are used in sub-ABFs to generate sampling clocks with the delay resolution of 4 ns from a low frequency system clock of 5 MHz. Each sub-ABF samples 32 echo signals at different times into sampling capacitors, which work as analog memory cells. The sampled 32 echo signals of each sub-ABF are originated from one target focal point at one instance. They are summed at one instance in a sub-ABF to perform the RX focusing for the target focal point. The proposed ABF chip has been fabricated in a 0.13- µ m CMOS process with an active area of 16 mm (2). The total power consumption is 287 mW. In measurement, the digital echo signals from a commercial ultrasound medical imaging machine were applied to the fabricated chip through commercial DAC chips. Due to the speed limitation of the DAC chips, the delay resolution was relaxed to 10 ns for the real-time measurement. A linear array transducer with no steering operation is used in this work.

An analog-digital hybrid RX beamformer chip with non-uniform sampling for ultrasound medical imaging with 2D CMUT array.

To reduce the memory area, a two-stage RX beamformer (BF) chip with 64 channels is proposed for the ultrasound medical imaging with a 2D CMUT array. The chip retrieved successfully two B-mode phantom images with a steering angle from -45 (°) to +45 (°), the maximum delay range of 8 µs, and the delay resolution of 6.25 ns. An analog-digital hybrid BF (HBF) is chosen for the proposed chip to utilize the easy beamforming operation in the digital domain and also to reduce chip area by minimizing the number of ADCs. The chip consists of eight analog beamformers (ABF) for the 1st-stage and a digital beamformer (DBF) for the 2nd-stage. The two-stage architecture reduces the memory area of both ABF and DBF by around four times. The DBF circuit is divided into three steps to further reduce the digital FIFO memory area by around twice. Coupled with the non-uniform sampling scheme, the proposed two-stage HBF chip reduces the total memory area by around 40 times compared to the uniform-sampling single-stage BF chip. The chip fabricated in a 0.13- µm CMOS process occupies the area of 19.4 mm(2), and dissipates 1.14 W with the analog supply of 3.3 V and the digital supply of 1.2 V.