arXiv subjects

Roger Zemp

Publications and source records attributed to Roger Zemp.

7 recordsLinked to original sources

arXiv2026

Orthogonal Plane-Wave Transmit-Receive Isotropic-Focusing Micro-Ultrasound (OPTIMUS) with Bias-Switchable Row-Column Arrays

High quality structural volumetric imaging is a challenging goal to achieve with modern ultrasound transducers. Matrix probes have limited fields of view and element counts, whereas row-column arrays (RCAs) provide insufficient focusing. In contrast, Top-Orthogonal-to-Bottom-Electrode (TOBE) arrays, also known as bias-switchable RCAs can enable isotropic focusing on par with ideal matrix probes, with a field of view surpassing conventional RCAs. Orthogonal Plane-Wave Transmit-Receive Isotropic-Focusing Micro-Ultrasound (OPTIMUS) is a novel imaging scheme that can use TOBE arrays to achieve nearly isotropic focusing throughout an expansive volume. This approach extends upon a similar volumetric imaging scheme, Hadamard Encoded Row Column Ultrasonic Expansive Scanning (HERCULES), that is even able to image beyond the shadow of the aperture, much like typical 2D matrix probes. We simulate a grid of scatterers to evaluate how the resolution varies across the volume, and validate these simulations experimentally using a commercial calibration phantom. Experimental measurements were done with a custom fabricated TOBE array, custom biasing electronics, and a research ultrasound system. Finally we performed ex-vivo imaging to assess our ability to discern structural tissue information.

eess.IV↗

arXiv2025

An Open Source Realtime GPU Beamformer for Row-Column and Top Orthogonal to Bottom Electrode (TOBE) Arrays

Research ultrasound platforms have enabled many next-generation imaging sequences but have lacked realtime navigation capabilities for emerging 2D arrays such as row-column arrays (RCAs). We present an open-source, GPU-accelerated reconstruction and rendering software suite integrated with a programmable ultrasound platform and novel electrostrictive Top-Orthogonal-to-Bottom-Electrode (TOBE) arrays. The system supports advanced real-time modes, including cross-plane aperture-encoded synthetic-aperture imaging and aperture-encoded volumetric scanning. TOBE-enabled methods demonstrate improved image quality and expanded field of view compared with conventional RCA techniques. The software implements beamforming and rendering kernels using OpenGL compute shaders and is designed for maximum data throughput helping to minimize stalls and latency. Accompanying sample datasets and example scripts for offline reconstruction are provided to facilitate external testing.

eess.IV↗

arXiv2025

Hadamard-Based Recursive Aperture Decoded Ultrasound Imaging (READI) With Estimated Motion-Compensated Compounding (EMC2) Using Top-Orthogonal to Bottom Electrode (TOBE) Arrays

Hadamard matrix-based aperture encoding is a method for producing synthetic aperture datasets with high Signal-to-Noise Ratios. Recently, the pulse inversion capabilities of bias-sensitive Top-Orthogonal to Bottom Electrode (TOBE) arrays have driven the development of multiple Hadamard-based sequences. These sequences produce high-quality static images but are sensitive to motion. This work introduces Recursive Aperture Decoded Imaging (READI) and Estimated Motion-Compensated Compounding (EMC2), which look to reduce this sensitivity. READI is a novel decoding and beamforming technique for Hadamard aperture-encoded sequences that produces multiple low-resolution images from subsets of the full sequence. These READI images are less affected by motion and sum to form the complete high-resolution image. EMC2 describes the process of comparing these low-resolution images to estimate the underlying motion, then warping them to align before compounding. This produces a high-resolution image that is resiliant to motion. READI with EMC2 applied to the TOBE-based Fast Orthogonal Row-Column Electronic Scanning (FORCES) sequence. It is shown to fully restore images corrupted by probe motion and to recover tissue speckle and boundaries in images of a beating heart phantom. READI low-resolution images by themselves are demonstrated to be a marked improvement over a sparse Hadamard scheme with the same transmit count, and are able to recover blood speckle at a flow rate of 42 cm/s.

eess.IV↗

arXiv2025

Improving the Elevational Focusing of Fast Orthogonal Row-Column Electronic Scanning (FORCES) Ultrasound Imaging using Retrospective Transmit Beamforming (RTB)

Recent developments in Row Column Arrays (RCAs) have presented promising options for volumetric imaging without the need for the excessive channel counts of fully wired 2D-arrays. Bias programmable RCAs, also known as Top Orthogonal to Bottom Electrode (TOBE) Arrays, show further promise in that imaging schemes, such as Fast Orthogonal Row-Column Electronic Scanning (FORCES) allow for full transmit and receive focusing everywhere in the image plane. However, due to its fixed elevational focus and large transmit aperture, FORCES experiences poor elevational focusing away from the focal point. In this study we present a modification to the FORCES imaging scheme by applying Retrospective Transmit Beamforming (RTB) in the elevational direction to allow for elevational transmit focusing everywhere in the imaging plane. We evaluate FORCES and uFORCES methods, with and without RTB applied, when imaging both a cyst and wire phantom. With experiment we show improved elevational focusing capabilities away from the focal point when RTB is applied to both FORCES and uFORCES. At the focal point, performance with RTB remains comparable or improved relative to standard FORCES. This is quantified by the measurement of Full Width Half Max when imaging the wire phantom, and by the generalized Contrast to Noise Ratio when imaging the tubular cyst phantom. We also demonstrate the volumetric imaging capabilities of FORCES RTB with the wire phantom.

eess.SP↗

arXiv2025

Hadamard Encoded Row Column Ultrasonic Expansive Scanning (HERCULES) with Bias-Switchable Row-Column Arrays

Top-Orthogonal-to-Bottom-Electrode (TOBE) arrays, also known as bias-switchable row-column arrays (RCAs), allow for imaging techniques otherwise impossible for non-bias-switachable RCAs. Hadamard Encoded Row Column Ultrasonic Expansive Scanning (HERCULES) is a novel imaging technique that allows for expansive 3D scanning by transmitting plane or cylindrical wavefronts and receiving using Hadamard-Encoded-Read-Out (HERO) to perform beamforming on what is effectively a full 2D synthetic receive aperture. This allows imaging beyond the shadow of the aperture of the RCA array, potentially allows for whole organ imaging and 3D visualization of tissue morphology. It additionally enables view large volumes through limited windows. In this work we demonstrated with simulation that we are able to image at comparable resolution to existing RCA imaging methods at tens to hundreds of volumes per second. We validated these simulations by demonstrating an experimental implementation of HERCULES using a custom fabricated TOBE array, custom biasing electronics, and a research ultrasound system. Furthermore, we assess our imaging capabilities by imaging a commercial phantom, and comparing our results to those taken with traditional RCA imaging methods. Finally, we verified our ability to image real tissue by imaging a xenograft mouse model.

eess.IV↗

arXiv2025

Bias-Switchable Row-Column Array Imaging using Fast Orthogonal Row-Column Electronic Scanning (FORCES) Compared with Conventional Row-Column Array Imaging

Row-Column Arrays (RCAs) offer an attractive alternative to fully wired 2D-arrays for 3D-ultrasound, due to their greatly simplified wiring. However, conventional RCAs face challenges related to their long elements. These include an inability to image beyond the shadow of the aperture and an inability to focus in both transmit and receive for desired scan planes. To address these limitations, we recently developed bias-switchable RCAs, also known as Top Orthogonal to Bottom Electrode (TOBE) arrays. These arrays provide novel opportunities to read out from every element of the array and achieve high-quality images. While TOBE arrays and their associated imaging schemes have shown promise, they have not yet been directly compared experimentally to conventional RCA imaging techniques. This study aims to provide such a comparison, demonstrating superior B-scan and volumetric images from two electrostrictive relaxor TOBE arrays, using a method called Fast Orthogonal Row-Column Electronic scanning (FORCES), compared to conventional RCA imaging schemes, including Tilted Plane Wave (TPW) compounding and Virtual Line Source (VLS) imaging. The study quantifies resolution and Generalized Contrast to Noise Ratio (gCNR) in phantoms, and also demonstrates volumetric acquisitions in phantom and animal models.

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arXiv2023

MyriadAL: Active Few Shot Learning for Histopathology

Active Learning (AL) and Few Shot Learning (FSL) are two label-efficient methods which have achieved excellent results recently. However, most prior arts in both learning paradigms fail to explore the wealth of the vast unlabelled data. In this study, we address this issue in the scenario where the annotation budget is very limited, yet a large amount of unlabelled data for the target task is available. We frame this work in the context of histopathology where labelling is prohibitively expensive. To this end, we introduce an active few shot learning framework, Myriad Active Learning (MAL), including a contrastive-learning encoder, pseudo-label generation, and novel query sample selection in the loop. Specifically, we propose to massage unlabelled data in a self-supervised manner, where the obtained data representations and clustering knowledge form the basis to activate the AL loop. With feedback from the oracle in each AL cycle, the pseudo-labels of the unlabelled data are refined by optimizing a shallow task-specific net on top of the encoder. These updated pseudo-labels serve to inform and improve the active learning query selection process. Furthermore, we introduce a novel recipe to combine existing uncertainty measures and utilize the entire uncertainty list to reduce sample redundancy in AL. Extensive experiments on two public histopathology datasets show that MAL has superior test accuracy, macro F1-score, and label efficiency compared to prior works, and can achieve a comparable test accuracy to a fully supervised algorithm while labelling only 5% of the dataset.

cs.CV↗