There is a need for noninvasive methods to detect liver steatosis, which can be a factor of liver fibrosis progression. This work aims to evaluate a novel ultrasonic controlled attenuation parameter (CAP) devised to target, specifically, liver steatosis using a sophisticated process based on vibration control transient elastography (VCTE™). CAP was first validated as an estimate of ultrasonic attenuation at 3.5 MHz using Field II simulations and tissue-mimicking phantoms. Performance of the CAP was then appraised on 115 patients, taking the histological grade of steatosis as reference. CAP was significantly correlated to steatosis (Spearman ρ = 0.81, p < 10(-16)). Area under receiver operative characteristic (ROC) curve (AUC) was equal to 0.91 and 0.95 for the detection of more than 10% and 33% of steatosis, respectively. Furthermore, results show that CAP can efficiently separate several steatosis grades. These promising results suggest that CAP is a noninvasive, immediate, objective and efficient method to detect and quantify steatosis.

Controlled Attenuation Parameter (CAP): A Novel VCTE™ Guided Ultrasonic Attenuation Measurement for the Evaluation of Hepatic Steatosis: Preliminary Study and Validation in a Cohort of Patients with Chronic Liver Disease from Various Causes

The paper describes a new method for determining the velocity vector of a remotely sensed object using either sound or electromagnetic radiation. The movement of the object is determined from a field with spatial oscillations in both the axial direction of the transducer and in one or two directions transverse to the axial direction. By using a number of pulse emissions, the inter-pulse movement can be estimated and the velocity found from the estimated movement and the time between pulses. The method is based on the principle of using transverse spatial modulation for making the received signal influenced by transverse motion. Such a transverse modulation can be generated by using apodization on individual transducer array elements together with a special focusing scheme. A method for making such a field is presented along with a suitable two-dimensional velocity estimator. An implementation usable in medical ultrasound is described, and simulated results are presented. Simulation results for a flow of 1 m/s in a tube rotated in the image plane at specific angles (0, 15, 35, 55, 75, and 90 degrees) are made and characterized by the estimated mean value, estimated angle, and the standard deviation in the lateral and longitudinal direction. The average performance of the estimates for all angles is: mean velocity 0.99 m/s, longitudinal S.D. 0.015 m/s, and lateral S.D. 0.196 m/s. For flow parallel to the transducer the results are: mean velocity 0.95 m/s, angle 0.10, longitudinal S.D. 0.020 m/s, and lateral S.D. 0.172 m/s.

A new method for estimation of velocity vectors

This paper, the first from a series of three papers on the application of coded excitation signals in medical ultrasound, discusses the basic principles and ultrasound-related problems of pulse compression. The concepts of signal modulation and matched filtering are given, and a simple model of attenuation relates the matched filter response with the ambiguity function, known from radar. Based on this analysis and the properties of the ambiguity function, the selection of coded waveforms suitable for ultrasound imaging is discussed. It is shown that linear frequency modulation (FM) signals have the best and most robust features for ultrasound imaging. Other coded signals such as nonlinear FM and binary complementary Golay codes also have been considered and characterized in terms of signal-to-noise ratio (SNR) and sensitivity to frequency shifts. Using the simulation program Field II, it is found that in the case of linear FM signals, a SNR improvement of 12 to 18 dB can be expected for large imaging depths in attenuating media, without any depth-dependent filter compensation. In contrast, nonlinear FM modulation and binary codes are shown to give a SNR improvement of only 4 to 9 dB when processed with a matched filter. Other issues, such as depth-dependent matched filtering and use of filters other than the matched filter (inverse and Wiener filters) also are addressed.

Use of modulated excitation signals in medical ultrasound. Part I: basic concepts and expected benefits

The semantic image segmentation task consists of classifying each pixel of an image into an instance, where each instance corresponds to a class. This task is a part of the concept of scene understanding or better explaining the global context of an image. In the medical image analysis domain, image segmentation can be used for image-guided interventions, radiotherapy, or improved radiological diagnostics. In this review, we categorize the leading deep learning-based medical and non-medical image segmentation solutions into six main groups of deep architectural, data synthesis-based, loss function-based, sequenced models, weakly supervised, and multi-task methods and provide a comprehensive review of the contributions in each of these groups. Further, for each group, we analyze each variant of these groups and discuss the limitations of the current approaches and present potential future research directions for semantic image segmentation.

Deep semantic segmentation of natural and medical images: a review

Most of ultrasound medical imaging systems currently on the market implement standard Delay and Sum (DAS) beamforming to form B-mode images. However, image resolution and contrast achievable with DAS are limited by the aperture size and by the operating frequency. For this reason, different beamformers have been presented in the literature that are mainly based on adaptive algorithms, which allow achieving higher performance at the cost of an increased computational complexity. In this paper, we propose the use of an alternative nonlinear beamforming algorithm for medical ultrasound imaging, which is called Delay Multiply and Sum (DMAS) and that was originally conceived for a RADAR microwave system for breast cancer detection. We modify the DMAS beamformer and test its performance on both simulated and experimentally collected linear-scan data, by comparing the Point Spread Functions, beampatterns, synthetic phantom and in vivo carotid artery images obtained with standard DAS and with the proposed algorithm. Results show that the DMAS beamformer outperforms DAS in both simulated and experimental trials and that the main improvement brought about by this new method is a significantly higher contrast resolution (i.e., narrower main lobe and lower side lobes), which turns out into an increased dynamic range and better quality of B-mode images.

The Delay Multiply and Sum Beamforming Algorithm in Ultrasound B-Mode Medical Imaging

A method for simulation of pulsed pressure fields from arbitrarily shaped, apodized and excited ultrasound transducers is suggested. It relies on the Tupholme-Stepanishen method for calculating pulsed pressure fields, and can also handle the continuous wave and pulse-echo case. The field is calculated by dividing the surface into small rectangles and then Summing their response. A fast calculation is obtained by using the far-field approximation. Examples of the accuracy of the approach and actual calculation times are given. >

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N.B. Svendsen

Papers

Calculation of pressure fields from arbitrarily shaped, apodized, and excited ultrasound transducers