MixTURE: L1-Norm-Based Mixed Second-Order Continuity in Strain Tensor Ultrasound Elastography.

Energy-based displacement tracking of ultrasound images can be implemented by optimizing a cost function consisting of a data term, a mechanical congruency term, and first- and second-order continuity terms. This approach recently provided a promising solution to two-dimensional axial and lateral displacement tracking in ultrasound strain elastography. However, the associated second-order regularizer only considers the unmixed second derivatives and disregards the mixed derivatives, thereby providing suboptimal noise suppression and limiting possibilities for total strain tensor imaging.

Measuring myofascial shear strain in chronic shoulder pain with ultrasound shear strain imaging: a case report.

Background: Dysfunctional gliding of deep fascia and muscle layers forms the basis of myofascial pain and dysfunction, which can cause chronic shoulder pain. Ultrasound shear strain imaging may offer a non-invasive tool to quantitatively evaluate the extent of muscular dysfunctional gliding and its correlation with pain. This case study is the first to use ultrasound shear strain imaging to report the shear strain between the pectoralis major and minor muscles in shoulders with and without chronic pain.

Enhancing Image-Guided Radiation Therapy for Pancreatic Cancer: Utilizing Aligned Peak Response Beamforming in Flexible Array Transducers.

To develop ultrasound-guided radiotherapy, we proposed an assistant structure with embedded markers along with a novel alternative method, the Aligned Peak Response (APR) method, to alter the conventional delay-and-sum (DAS) beamformer for reconstructing ultrasound images obtained from a flexible array. We simulated imaging targets in Field-II using point target phantoms with point targets at different locations. In the experimental phantom ultrasound images, image RF data were acquired with a flexible transducer with in-house assistant structures embedded with needle targets for testing the accuracy of the APR method.

Detection of COVID-19 features in lung ultrasound images using deep neural networks.

Background: Deep neural networks (DNNs) to detect COVID-19 features in lung ultrasound B-mode images have primarily relied on either in vivo or simulated images as training data. However, in vivo images suffer from limited access to required manual labeling of thousands of training image examples, and simulated images can suffer from poor generalizability to in vivo images due to domain differences. We address these limitations and identify the best training strategy.

Deep learning catheter tip locations for photoacoustic-guided cardiac interventions.

Significance: Interventional cardiac procedures often require ionizing radiation to guide cardiac catheters to the heart. To reduce the associated risks of ionizing radiation, photoacoustic imaging can potentially be combined with robotic visual servoing, with initial demonstrations requiring segmentation of catheter tips. However, typical segmentation algorithms applied to conventional image formation methods are susceptible to problematic reflection artifacts, which compromise the required detectability and localization of the catheter tip.

FLEX: FLexible Transducer With External Tracking for Ultrasound Imaging With Patient-Specific Geometry Estimation.

Flexible array transducers can adapt to patient-specific geometries during real-time ultrasound (US) image-guided therapy monitoring. This makes the system radiation-free and less user-dependency. Precise estimation of the flexible transducer's geometry is crucial for the delay-and-sum (DAS) beamforming algorithm to reconstruct B-mode US images.

Mitigating skin tone bias in linear array photoacoustic imaging with short-lag spatial coherence beamforming.

Photoacoustic (PA) imaging has the potential to deliver non-invasive diagnostic information. However, skin tone differences bias PA target visualization, as the elevated optical absorption of melanated skin decreases optical fluence within the imaging plane and increases the presence of acoustic clutter. This paper demonstrates that short-lag spatial coherence (SLSC) beamforming mitigates this bias.

Spatial Coherence Approaches to Distinguish Suspicious Mass Contents in Fundamental and Harmonic Breast Ultrasound Images.

When compared to fundamental B-mode imaging, coherence-based beamforming, and harmonic imaging are independently known to reduce acoustic clutter, distinguish solid from fluid content in indeterminate breast masses, and thereby reduce unnecessary biopsies during a breast cancer diagnosis. However, a systematic investigation of independent and combined coherence beamforming and harmonic imaging approaches is necessary for the clinical deployment of the most optimal approach. Therefore, we compare the performance of fundamental and harmonic images created with short-lag spatial coherence (SLSC), M-weighted SLSC (M-SLSC), SLSC combined with robust principal component analysis with no M-weighting (r-SLSC), and r-SLSC with M-weighting (R-SLSC), relative to traditional fundamental and harmonic B-mode images, when distinguishing solid from fluid breast masses.

Flexible array transducer for photoacoustic-guided interventions: phantom and demonstrations.

Photoacoustic imaging has demonstrated recent promise for surgical guidance, enabling visualization of tool tips during surgical and non-surgical interventions. To receive photoacoustic signals, most conventional transducers are rigid, while a flexible array is able to deform and provide complete contact on surfaces with different geometries. In this work, we present photoacoustic images acquired with a flexible array transducer in multiple concave shapes in phantom and bovine liver experiments targeted toward interventional photoacoustic applications.

Optical absorption spectra and corresponding photoacoustic visualization of exposed peripheral nerves.

Significance: Multispectral photoacoustic imaging has the potential to identify lipid-rich, myelinated nerve tissue in an interventional or surgical setting (e.g., to guide intraoperative decisions when exposing a nerve during reconstructive surgery by limiting operations to nerves needing repair, with no impact to healthy or regenerating nerves).

Ultrasound Imaging with Flexible Array Transducer for Pancreatic Cancer Radiation Therapy.

Pancreatic cancer with less than 10% 3-year survival rate is one of deadliest cancer types and greatly benefits from enhanced radiotherapy. Organ motion monitoring helps spare the normal tissue from high radiation and, in turn, enables the dose escalation to the target that has been shown to improve the effectiveness of RT by doubling and tripling post-RT survival rate. The flexible array transducer is a novel and promising solution to address the limitation of conventional US probes.

Photoacoustic Imaging and Characterization of Bone in Medicine: Overview, Applications, and Outlook.

Photoacoustic techniques have shown promise in identifying molecular changes in bone tissue and visualizing tissue microstructure. This capability represents significant advantages over gold standards (i.e.

Roadmap on Deep Learning for Microscopy.

Through digital imaging, microscopy has evolved from primarily being a means for visual observation of life at the micro- and nano-scale, to a quantitative tool with ever-increasing resolution and throughput. Artificial intelligence, deep neural networks, and machine learning are all niche terms describing computational methods that have gained a pivotal role in microscopy-based research over the past decade. This Roadmap is written collectively by prominent researchers and encompasses selected aspects of how machine learning is applied to microscopy image data, with the aim of gaining scientific knowledge by improved image quality, automated detection, segmentation, classification and tracking of objects, and efficient merging of information from multiple imaging modalities.

A Review of Deep Learning Applications in Lung Ultrasound Imaging of COVID-19 Patients.

The massive and continuous spread of COVID-19 has motivated researchers around the world to intensely explore, understand, and develop new techniques for diagnosis and treatment. Although lung ultrasound imaging is a less established approach when compared to other medical imaging modalities such as X-ray and CT, multiple studies have demonstrated its promise to diagnose COVID-19 patients. At the same time, many deep learning models have been built to improve the diagnostic efficiency of medical imaging.

Coherence Metrics for Reader-Independent Differentiation of Cystic From Solid Breast Masses in Ultrasound Images.

Traditional breast ultrasound imaging is a low-cost, real-time and portable method to assist with breast cancer screening and diagnosis, with particular benefits for patients with dense breast tissue. We previously demonstrated that incorporating coherence-based beamforming additionally improves the distinction of fluid-filled from solid breast masses, based on qualitative image interpretation by board-certified radiologists. However, variable sensitivity (range: 0.

A phantom-based analysis for tracking intra-fraction pancreatic tumor motion by ultrasound imaging during radiation therapy.

Purpose: In this study, we aim to further evaluate the accuracy of ultrasound tracking for intra-fraction pancreatic tumor motion during radiotherapy by a phantom-based study.

Methods: Twelve patients with pancreatic cancer who were treated with stereotactic body radiation therapy were enrolled in this study. The displacement points of the respiratory cycle were acquired from 4DCT and transferred to a motion platform to mimic realistic breathing movements in our phantom study.

Theoretical Framework to Predict Generalized Contrast-to-Noise Ratios of Photoacoustic Images With Applications to Computer Vision.

The successful integration of computer vision, robotic actuation, and photoacoustic imaging to find and follow targets of interest during surgical and interventional procedures requires accurate photoacoustic target detectability. This detectability has traditionally been assessed with image quality metrics, such as contrast, contrast-to-noise ratio, and signal-to-noise ratio (SNR). However, predicting target tracking performance expectations when using these traditional metrics is difficult due to unbounded values and sensitivity to image manipulation techniques like thresholding.

Erratum: Empirical assessment of laser safety for photoacoustic-guided liver surgeries: erratum.

[This corrects the article on p. 1205 in vol. 12, PMID: 33796347.

The Feasibility of Haar Feature-Based Endoscopic Ultrasound Probe Tracking for Implanting Hydrogel Spacer in Radiation Therapy for Pancreatic Cancer.

Purpose: We proposed a Haar feature-based method for tracking endoscopic ultrasound (EUS) probe in diagnostic computed tomography (CT) and Magnetic Resonance Imaging (MRI) scans for guiding hydrogel injection without external tracking hardware. This study aimed to assess the feasibility of implementing our method with phantom and patient images.

Materials And Methods: Our methods included the pre-simulation section and Haar features extraction steps.

Translational Photoacoustic Imaging for Disease Diagnosis, Monitoring, and Surgical Guidance: introduction to the feature issue.

This feature issue of covered all aspects of translational photoacoustic research. Application areas include screening and diagnosis of diseases, imaging of disease progression and therapeutic response, and image-guided treatment, such as surgery, drug delivery, and photothermal/photodynamic therapy. The feature issue also covers relevant developments in photoacoustic instrumentation, contrast agents, image processing and reconstruction algorithms.

Spatial Coherence Beamforming With Multi-Line Transmission to Enhance the Contrast of Coherent Structures in Ultrasound Images Degraded by Acoustic Clutter.

This work demonstrates that the combination of multi-line transmission (MLT) and short-lag spatial coherence (SLSC) imaging improves the contrast of highly coherent structures within soft tissues when compared to both traditional SLSC imaging and conventional delay and sum (DAS) beamforming. Experimental tests with small (i.e.

Comparison of compressional and elastic wave simulations for patient-specific planning prior to transcranial photoacoustic-guided neurosurgery.

Significance: Simulations have the potential to be a powerful tool when planning the placement of photoacoustic imaging system components for surgical guidance. While elastic simulations (which include both compressional and shear waves) are expected to more accurately represent the physical transcranial acoustic wave propagation process, these simulations are more time-consuming and memory-intensive than the compressional-wave-only simulations that our group previously used to identify optimal acoustic windows for transcranial photoacoustic imaging.

Aim: We present qualitative and quantitative comparisons of compressional and elastic wave simulations to determine which option is more suitable for preoperative surgical planning.

Deep Learning for Ultrasound Image Formation: CUBDL Evaluation Framework and Open Datasets.

Deep learning for ultrasound image formation is rapidly garnering research support and attention, quickly rising as the latest frontier in ultrasound image formation, with much promise to balance both image quality and display speed. Despite this promise, one challenge with identifying optimal solutions is the absence of unified evaluation methods and datasets that are not specific to a single research group. This article introduces the largest known international database of ultrasound channel data and describes the associated evaluation methods that were initially developed for the challenge on ultrasound beamforming with deep learning (CUBDL), which was offered as a component of the 2020 IEEE International Ultrasonics Symposium.

Deep Learning for Ultrasound Beamforming in Flexible Array Transducer.

Ultrasound imaging has been developed for image-guided radiotherapy for tumor tracking, and the flexible array transducer is a promising tool for this task. It can reduce the user dependence and anatomical changes caused by the traditional ultrasound transducer. However, due to its flexible geometry, the conventional delay-and-sum (DAS) beamformer may apply incorrect time delay to the radio-frequency (RF) data and produce B-mode images with considerable defocusing and distortion.

Photoacoustic-Guided Laparoscopic and Open Hysterectomy Procedures Demonstrated With Human Cadavers.

Hysterectomy (i.e., surgical removal of the uterus) requires severing the main blood supply to the uterus (i.