1,720,981 research outputs found
Ultrasound Image Beamforming Optimization Using a Generative Adversarial Network
Full text linkRecently, research has been focusing on the development of artificial intelligence ultrasound beamforming methods to improve the contrast and resolution of B-mode images. In this work, we propose an innovative beamforming domain transfer method using a generative adversarial network (GAN). The GAN takes as input a plane-wave (PW) delay and sum (DAS) image and generates an image as if it had been acquired using the focused modality and reconstructed with the filtered Delay Multiply and Sum (F-DMAS) beamforming technique. A Verasonics Vantage 256 system (L11-5v linear array) was used to acquire 560 (480 and 80 for train and test set, respectively) in-vivo musculoskeletal US images. Images were acquired on five muscles (gastrocnemius lateralis, gastrocnemius medialis, vastus lateralis, vastus medialis, and biceps) on both sides of 14 healthy volunteers (50% female). RF data were acquired both in plane-wave (PW) and focused mode and beamformed using the UltraSound ToolBox (USTB). The DAS beamforming method was employed for PW data, whereas the focused data were reconstructed using F-DMAS. Various dynamic ranges (dR) were employed to create the final 8-bit PW DAS images (dR = 55, 65, 75, 85 dB) while an automatic dR was employed to optimize focused F-DMAS images. A Pix2Pix GAN architecture was designed to formulate the task of beamforming as the translation from one domain (PW DAS image) to another (focused F-DMAS image). Our GAN employed a UNet as the generator and a 3-layer fully convolutional PatchGAN as the discriminator. The proposed GAN architecture shows promising results, generating a GAN image comparable to the F-DMAS image, i.e., in terms of SSIM (0.5183 +/- 0.0437 and 0.5152 +/- 0.0519 for GAN images vs DAS images and F-DMAS images vs DAS images). Overall, our GAN enhances image quality and simulates focused F-DMAS beamforming starting from a PW DAS image without needing to access the raw RF data, which is typically unavailable with clinical ultrasound devices
Dynamic Range-Invariant GAN Reconstruction via Optimized Target Training in Medical Ultrasound Imaging
Full text linkUltrasound imaging is sensitive to operatordependent
parameters such as dynamic range (DR), when
considering 8-bit reconstructed images, which can compromise
both clinical interpretation and the reliability of artificial
intelligence (AI)-based reconstruction pipelines. This work
validates an automatic dynamic range optimization (autoDR)
method as a standardized training reference for Generative
Adversarial Network (GAN) models. By evaluating GAN
robustness to DR variability, we demonstrate that autoDR
enables consistent, high-quality reconstructions across diverse
acquisition settings, outperforming classical enhancement
techniques. These findings highlight autoDR as a practical
solution for reducing operator dependence, improving
reproducibility, and a robust reference standard for GAN-based
ultrasound image reconstruction when there is no access to raw
radiofrequency data
Automatic Dynamic Range Estimation for Ultrasound Image Visualization and Processing
Full text linkNumerous beamforming methods exist for ultrasound B-mode imaging, but it is known that adaptive/non-linear beamformers may alter the image dynamic range. To obtain an 8-bit image for further processing, it is necessary to determine a specific dynamic range, which may vary between beamforming methods in order to obtain a visually similar image. The aim here is to present an automated method to estimate the optimal dynamic range. We tested two phantom images and one in vivo image using six different beamforming techniques. The cumulative sums of the image histograms are compared with a standard dynamic range (i.e., 60 dB) and the contrast ratio and contrast-to-noise ratio are computed. We show that the automatically determined dynamic range is able to standardize the image among various beamforming techniques, which is essential when further image processing methods are employed
Robustness Analysis of Texture Features with Different Beamforming Techniques
Full text linkTexture features are often used on ultrasound images in various applications to give forth important clinical information. Recently, many beamforming techniques have been developed to provide better resolution and contrast in the final image. It is currently unknown, however, how these different techniques may also alter pixel intensity spatial distribution, known as texture. We provide here a robustness analysis of first and second order texture features using six beamforming techniques, on both phantom and in vivo musculoskeletal images. We show that second order texture features are more robust compared to first order features, especially when considering in vivo musculoskeletal images
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Non-invasive analysis of actinic keratosis before and after topical treatment using a cold stimulation and near-infrared spectroscopy
No full textBackground and objectives: The possible evolution of actinic keratoses (AKs) into invasive squamous cell carcinomas (SCC) makes their treatment and monitoring essential. AKs are typically monitored before and after treatment only through a visual analysis, lacking a quantitative measure to determine treatment effectiveness. Near-infrared spectroscopy (NIRS) is a non-invasive measure of the relative change of oxy-hemoglobin and deoxy-hemoglobin (O2Hb and HHb) in tissues. The aim of our study is to determine if a time and frequency analysis of the NIRS signals acquired from the skin lesion before and after a topical treatment can highlight quantitative differences between the AK skin lesion area. Materials and Methods: The NIRS signals were acquired from the skin lesions of twenty-two patients, with the same acquisition protocol: baseline signals, application of an ice pack near the lesion, removal of ice pack and acquisition of vascular recovery. We calculated 18 features from the NIRS signals, and we applied multivariate analysis of variance (MANOVA) to compare differences between the NIRS signals acquired before and after the therapy. Results: The MANOVA showed that the features computed on the NIRS signals before and after treatment could be considered as two statistically separate groups, after the ice pack removal. Conclusions: Overall, the NIRS technique with the cold stimulation may be useful to support non-invasive and quantitative lesion analysis and regression after a treatment. The results provide a baseline from which to further study skin lesions and the effects of various treatments
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Detecting anatomical characteristics of single motor units by combining high density electromyography and ultrafast ultrasound: a simulation study
Full text linkMuscle force production is the result of a sequence of electromechanical events that translate the neural drive issued to the motor units (MUs) into tensile forces on the tendon. Current technology allows this phenomenon to be investigated non-invasively. Single MU excitation and its mechanical response can be studied through high-density surface electromyography (HDsEMG) and ultrafast ultrasound (US) imaging respectively. In this study, we propose a method to integrate these two techniques to identify anatomical characteristics of single MUs. Specifically, we tested two algorithms, combining the tissue velocity sequence (TVS, obtained from ultrafast US images), and the MU firings (extracted from HDsEMG decomposition). The first is the Spike Triggered Averaging (STA) of the TVS based on the occurrences of individual MU firings, while the second relies on the correlation between the MU firing patterns and the TVS spatio-temporal independent components (STICA). A simulation model of the muscle contraction was adapted to test the algorithms at different degrees of neural excitation (number of active MUs) and MU synchronization. The performances of the two algorithms were quantified through the comparison between the simulated and the estimated characteristics of MU territories (size, location). Results show that both approaches are negatively affected by the number of active MU and synchronization levels. However, STICA provides a more robust MU territory estimation, outperforming STA in all the tested conditions. Our results suggest that spatio-temporal independent component decomposition of TVS is a suitable approach for anatomical and mechanical characterization of single MUs using a combined HDsEMG and ultrafast US approach
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