Ultrasound B-scan Images Research Articles

Rail Flaw B-Scan Image Analysis Using a Hierarchical Classification Model

AbstractAs railway traffic volumes and train speeds increase, rail maintenance is becoming more crucial to prevent catastrophic failures. This study aimed to develop an artificial intelligence (AI)-based solution for automatic rail flaw detection using ultrasound sensors to overcome the limitations of traditional inspection methods. Ultrasound sensors are well-suited for identifying structural abnormalities in rails. However, conventional inspection techniques like rail-walking are time-consuming and rely on human expertise, risking detection errors. To address this, a hierarchical classification model was proposed integrating ultrasound B-scan images and machine learning. It involved a two-stage approach—model A for fuzzy classification followed by Model EfficientNet-B7 was identified as the most effective architecture for both models through network comparisons. Experimental results demonstrated the model's ability to accurately detect rail flaws, achieving 88.56% accuracy. It could analyze a single ultrasound image sheet within 0.45 s. An AI-based solution using ultrasound sensors and hierarchical classification shows promise for automated, rapid, and reliable rail flaw detection to support safer railway infrastructure inspection and maintenance activities.

A Power Law Reconstruction of Ultrasound Backscatter Images

Ultrasound B-scan images are traditionally formed from the envelope of the received radiofrequency echoes, but the image texture is dominated by granular speckle patterns. Longstanding efforts at speckle reduction and deconvolution have been developed to lessen the detrimental aspects of speckle. However, we now propose an alternative approach to estimation (and image rendering) of the underlying fine grain scattering density of tissues based on power law constraints. The key steps are a whitening of the spectrum of the received signal while conforming to the original envelope shape and statistics, followed by a power law filtering in accordance with the known scattering behavior of tissues. This multiple step approach results in a high-spatial-resolution map of scattering density that is constrained by the most important properties of scattering from tissues. Examples from in vivo liver scans are shown to illustrate the change in image properties from this framework.

Ocular Disease Detection with Deep Learning (Fine-Grained Image Categorization) Applied to Ocular B-Scan Ultrasound Images.

The aim of this work is to develop a deep learning (DL) system for rapidly and accurately screening for intraocular tumor (IOT), retinal detachment (RD), vitreous hemorrhage (VH), and posterior scleral staphyloma (PSS) using ocular B-scan ultrasound images. Ultrasound images from five clinically confirmed categories, including vitreous hemorrhage, retinal detachment, intraocular tumor, posterior scleral staphyloma, and normal eyes, were used to develop and evaluate a fine-grained classification system (the Dual-Path Lesion Attention Network, DPLA-Net). Images were derived from five centers scanned by different sonographers and divided into training, validation, and test sets in a ratio of 7:1:2. Two senior ophthalmologists and four junior ophthalmologists were recruited to evaluate the system's performance. This multi-center cross-sectional study was conducted in six hospitals in China. A total of 6054 ultrasound images were collected; 4758 images were used for the training and validation of the system, and 1296 images were used as a testing set. DPLA-Net achieved a mean accuracy of 0.943 in the testing set, and the area under the curve was 0.988 for IOT, 0.997 for RD, 0.994 for PSS, 0.988 for VH, and 0.993 for normal. With the help of DPLA-Net, the accuracy of the four junior ophthalmologists improved from 0.696 (95% confidence interval [CI] 0.684-0.707) to 0.919 (95% CI 0.912-0.926, p < 0.001), and the time used for classifying each image reduced from 16.84 ± 2.34s to 10.09 ± 1.79s. The proposed DPLA-Net showed high accuracy for screening and classifying multiple ophthalmic diseases using B-scan ultrasound images across mutiple centers. Moreover, the system can promote the efficiency of classification by ophthalmologists.

Earlier detection of rop and rop sub-classification using TA-CHD-DNN and UD-TFCM from ultrasound digital B-Scan images

The growth of the retinal blood vessels of the baby begins at 16 weeks and even after the birth of the baby, they don’t grow completely. For the effective analysis of Retinopathy of Prematurity (ROP), diverse methodologies are employed. Owing to the insufficient growth of tangled patterns, greater retinal layer thickness, and the presence of hyperreflective material, the majority of the traditional methodologies were unsuccessful in classifying the Choroidal Neovascularization (CNV), Diabetic Macular Edema (DME), and DRUSEN stages of ROP. Thus, for the classification of different stages of the ROP, an effective Twin Active- Cosine-Hausdorff Distance-Deep Neural Network (TA-CHD-DNN) is proposed in this paper. Chiefly, the image obtained from the retinal image dataset is pre-processed and fed into TA- CHD-DNN. After the extraction of critical features, the segmentation of the retinal layer, choroid layer, and vascular layer occurs in TA-CHD- DNN. The classifier is trained to make decisions for the classification of diverse stages of ROP centered on the extracted features. The normal or abnormal stages of CNV, DME, and DRUSEN are classified by the classifier during testing. By utilizing the Uniformly Distributed-Trapezoidal Fuzzy C Means (UD-TFCM) technique, the decision regarding the severity stage of CNV, DME, and DRUSEN is made in the abnormal stage. Thus, centered on the experimental outcomes, the proposed system performance will be analogized to the conventional techniques to confirm the proposed system’s efficiency.

Neoplastic Disorders of Visual Apparatus: Advances and Management

Purpose: Ocular neoplasms, both primary and metastatic, may present with visual disturbance or vision loss and often are asymptomatic. Clinical examination may demonstrate leukocoria, abnormal pupillary light reflex, or a mass lesion with or without retinal detachment or hemorrhage. Retinoblastoma in children and uveal melanoma and ocular metastases in adults are the most important ocular malignant neoplasms referred for imaging to aid with diagnosis and staging. Familiarity with their common imaging appearances, the common patterns of spread, and the diagnostic findings of greatest concern to the optometrist or ocular oncologist will enhance accuracy of imaging interpretation.&#x0D; Methodology: Clinical examination and imaging using B-scan ultrasound, A-scan ultrasound, fluorescein angiography, computed tomography and magnetic resonance imaging have complementary roles in ocular tumor staging and treatment assessment.&#x0D; Findings: Ocular neoplasm tumors are relatively rare but require unique diagnostic and treatment considerations given the functional importance of the eye and periocular structures and their unique metastatic behavior. In the following paper, a major malignant tumor of the ocular adnexa including the eyelid, conjunctiva and orbit will be reviewed. Frozen section control of the margins and, in selected cases, Mohs microsurgery have decreased the recurrence rate in malignant eyelid tumors. Intraoperative cryotherapy and postoperative topical mitomycin C have similarly contributed to better surgical outcomes in conjunctival malignant tumors including squamous cell carcinoma and malignant melanoma. Immunotherapy with CD20 antibodies is a developing treatment in Ocular neoplasm lymphomas.&#x0D; Unique Contribution to Theory, Practice and Policy: Optometrists by the new advances in clinical optometry training/research, and specialists in occuloplasty/ocularistry form part of the team for a multidisciplinary approach in the clinical management of neoplastic disorders of visual apparatus.

Optometry meets ophthalmology- cycloplegic refraction and examination under general anaesthesia in a paediatric high myope

Purpose: To discuss a case of shared optometric-ophthalmic (O-O) approach in objectively refracting and examining a paediatric high myope under general anaesthesia. Methods: A paediatric high myope was cyclopleged then underwent objective retinoscopy under general anaesthesia within a surgical theatre setting. Corneal diameter, interpupillary distance, immersion biometry axial lengths, intraocular pressures, keratometry readings, A-scan and B-scan ultrasound images were all subsequently obtained. Lastly, binocular indirect ophthalmoscopic examination with 360º scleral indentation was carried out. A comprehensive O-O report was dispensed with all collated parameters. Results: A refractive error of -11.00DS bilaterally was measured. Ocular health assessment showed no significant myopic abnormalities. The patient was dispensed spectacles and adapted well with improved comfort. Low dose atropine myopia control was commenced. Conclusion: O-O shared care in refracting and examining difficult and highly myopic paediatric cases under general anaesthesia is a useful and effective tool.

CUFuse: Camera and Ultrasound Data Fusion for Rail Defect Detection

This paper proposes a multi-source data fusion algorithm for rail surface defect detection in both camera-based rail inspection images and ultrasound B-scan images. First, we design a rail surface segmentation algorithm based on image bilateral filtering, Sobel edge detection, and rail surface edge detection to extract the rail surface area. Second, we build a camera and ultrasound data fusion (CUFuse) model for rail surface defect detection, including two main networks: multi-source data feature extraction and multi-scale feature fusion networks. The multi-source data feature extraction network consists of two BoTNet 50 networks as feature extraction networks to extract five stages of features in camera-based images and ultrasound B-scan images. The multi-scale feature fusion network consists of five feature fusion modules to fuse the feature information output by the multi-source data feature extraction network. Finally, we use the CUFuse model to detect the rail surface defect dataset, and output five rail surface state types, including Light, Moderate, Severe, Normal, and Joint. The results show that the accuracy of the CUFuse model is 96.97%, which can accomplish the task of rail surface defect detection on railway sites.

Congenital unilateral lower lip palsy: a case-based review.

Congenital unilateral lower lip palsy (CULLP), also referred to as congenital asymmetric crying facies (ACF), is a rare condition that causes pronounced depression of the unaffected lower lip when crying, despite symmetric appearance of the mouth and lips at rest. Unlike the acquired form of ACF, CULLP is idiopathic and often involves permanent defect. We present a case-based review of CULLP, including a thorough analysis of the relevant literature and a discussion of the exemplary case of 5-year-old patient presenting with unilateral facial asymmetry resulting from left-sided facial weakness. The patient was diagnosed with ACF at birth, and documentation from a previous neurologic consultation specifies the root cause of the asymmetry as developmental aplasia of the left depressor anguli oris muscle (DAOM). However, there is no record of electrodiagnostic testing or B-scan ultrasound imaging that would support this conclusion, and the patient's dysarthric speech may suggest lower motor neuron involvement. Botox chemodenervation of the right, unaffected side was recommended to deanimate the contralateral lower lip and achieve facial symmetry, in addition to potentially resolving some of the patient's speech difficulties. There are several approaches, both surgical and non-surgical, to the management and correction of CULLP. These include weakening the muscles of the contralateral side or increasing muscular tension on the ipsilateral side, referred to as deanimation and reanimation procedures, respectively.

Leukemic Optic Neuropathy

Background: Leukemic infiltration of the optic nerve is a neuro-oncologic emergency and also a sign of extramedullary central nervous system relapse. It presents a clinical dilemma in the early stages due to multiple differentials. Patients with leukemia receive radiation and chemotherapy are thus, susceptible to inflammatory, toxic, and infectious causes of optic neuropathy, besides infiltration with tumor cells. Clinical Description: A 15-year-old boy treated for acute lymphoblastic leukemia (ALL) and in remission for 7 months, presented with the unilateral decreased vision for 7 days. A structured evaluation was done, comprising visual acuity, color vision, field of vision, fundus, ophthalmoscopy, ultrasound b-scan, and magnetic resonance imaging of the orbit. The final diagnosis was leukemic infiltration of the optic nerve. Cerebrospinal fluid (CSF) analysis confirmed the presence of atypical lymphocytes. Management: The patient was diagnosed with extramedullary relapse of ALL. Since there are no standard guidelines, a literature review was performed, and the treating team decided to start the patient on stand-alone chemotherapy. Symptomatic resolution became apparent within 10 days. On follow-up, the optic nerve lesion resolved with residual gliosis in the surrounding retina. The CSF has become clear, and the patient is now considered to be in remission. Conclusion: It is important to use a structured clinical approach coupled with investigations to recognize the ocular involvement of ALL (especially in younger patients). There is a need for a regular routine ophthalmological examination in patients in remission for early detection of a relapse. There is a strong felt need for pediatric hemato-oncologists to plan research in this area to generate data so that recommendations for the management of extramedullary relapses are formulated.

Dosimetric assessment of antitumor treatment by enhanced bleomycin delivery via electroporation and sonoporation

Targeted and controlled techniques of intratumoral delivery of chemotherapeutic agents are under extensive development, since they diminish detrimental side-effects of conventional anticancer drugs.We investigated the effectiveness of chemotherapy using bleomycin (1 mg/ml) and Sonovue microbubbles combined with: electroporation (EP), mainly designed for subcutaneous tumor therapy, and sonoporation (SP) - for deeper localized tumors. Research was performed on hepatoma MH-22A tumors in murine models, exposed to EP or SP and combined (EP + SP) treatment.Animal survival time and the rate/ speed of tumor growth reduction were examined. Study demonstrated that both EP or SP and their combination (EP + SP) were able to induce the reduction of tumor volume from the 3rd day after treatment. The employment of EP before SP allowed to significantly reduce the values of inertial cavitation dose (ICD), necessary to induce complete tumor reduction and prolong animal survival.The analysis of ultrasound (US) side-scattered signals and B-scan imaging indicated the occurrence of inertial cavitation at our experimental conditions. Strong (R2 = 0.88; p < 0.0001) correlation of ICD with the survival time of corresponding unrecovered mice indicates the option for the dosimetric control and standardization of cavitation activities for in vivo practice.

Ultrasound water-marking for simultaneous B-scan imaging and bio-telemetry

Ultrasound imaging technology has undergone a revolution during the last decade due to the availability of transducers that can operate over a large range of frequencies, and also due to the availability of high-speed, high-resolution analog-to-digital converters and signal processors. The large data acquisition and computational bandwidth afforded on these portable and bench-top ultrasound imaging systems could potentially be leveraged for designing energy-efficient bio-telemetry links that can be used for communicating with devices implanted in vivo. In this paper, we discuss an ultrasound water-marking approach that can be used for simultaneous imaging and bio-telemetry. The trade-off involves supporting a reasonable data-rate bio-telemetry link and at the same time minimizing artifacts due to bio-telemetry data in the B-scan images. Specifically, we exploit a variance-based signal representation where the image background noise is modulated to encode the data to be transmitted or sensed. Using a B-scan ultrasound imaging system and a phantom setup we show that the approach can support biotelemetry links at sub-nanowatt transmission power and at depths greater than 10 cm.

The MOLES system to guide the management of melanocytic choroidal tumours: can optometrists apply it?

ABSTRACTClinical relevanceAlthough melanocytic choroidal tumours of the choroid are a common eye pathology, no standardised protocol exists for their management in the community.BackgroundChoroidal naevi are found in approximately 6% of the adult White population, whereas choroidal melanomas are rare, with an annual incidence of 5–10/million/year. Multimodal imaging has advanced the understanding of malignancy imaging biomarkers, but distinguishing between a small melanoma and naevus remains difficult and an algorithm for their management by community practitioners has not been uniformly adopted. One of the authors (BD) devised the MOLES scoring system, which indicates malignancy likelihood according to mushroom shape, orange pigment, large size, enlargement, and subretinal fluid. When applied by ocular oncologists, the system accurately distinguishes choroidal naevi from melanomas. The aim of this study was to evaluate whether community optometrists can appropriately manage patients with melanocytic choroidal tumours using this system.MethodsClinical images of 25 melanocytic choroidal tumours were presented in an online survey, including colour fundus photographs, fundus autofluorescence, optical coherence tomography, and B-scan ultrasound images. Using the MOLES system, 39 optometrists diagnosed tumours as naevus or probable melanoma and decided between community monitoring and ophthalmologist referral. Responses were compared to MOLES grading of the same clinical images by ocular oncologists.ResultsUsing MOLES, optometrists correctly identified 389/406 probable melanomas (95.8% sensitivity) and 331/516 choroidal naevi (64.1% specificity); correctly referred 773/778 tumours to an ophthalmologist (99.4% sensitivity); and correctly managed 80/144 lesions (55.6% specificity) in the community.ConclusionOptometrists safely applied the MOLES scoring system in this survey. Further measures are indicated to reduce choroidal naevi over-referral and evaluate MOLES system usage in clinical optometric practice, where some imaging modalities may not be readily available.

Острая задняя отслойка стекловидного тела

The detachment of the posterior hyaloid membrane (posterior vitreous detachment /PVD/) means the separation of the posterior vitreous cortex from the internal limiting membrane of the retina and the optic disc. Traditionally, PVD is considered as a physiological process associated with the involutional changes of the vitreous body. In most cases, the early stages of acute PVD are asymptomatic. Patients do not seek for medical care until an acute condition occurs along with the development of typical symptoms. It happens when the posterior hyaloid membrane completely separates from the retina and the optic disc, or when complications of this process develop, such as hemorrhages in the vitreous and retina, retinal breaks/tears and detachment, and macular lesions. Taking into consideration the spontaneous PVD onset and the risk of various complications, it is necessary to conduct a thorough research of the etiology and pathogenesis of this process, identify potential predisposing and triggering factors, and to define tactics of patient management, timely detection and treatment of complications. It is important to assess the informational value of special instrumental methods of patient examination, such as B-scan ultrasound imaging and optical coherence tomography. These methods open new perspectives for verifying the diagnostic accuracy, revealing complications, visualizing residual vitreoretinal adhesions, and offering tactics for further patient management. Keywords: acute posterior vitreous detachment, posterior hyaloid membrane, peripheral retinal breaks/tears, rhegmatogenous retinal detachment, vitreomacular traction syndrome, B-scan ultrasonography, optical coherence tomography. For citation: Volodin P.L., Belyanina S.I. Аcute posterior vitreous detachment. Russian Journal of Clinical Ophthalmology. 2022;22(4):247– 253 (in Russ.). DOI: 10.32364/2311-7729-2022-22-4-247-253.

Hole-filling based on content loss indexed 3D partial convolution network for freehand ultrasound reconstruction

Background and objectiveDuring the 3D reconstruction of ultrasound volume from 2D B-scan ultrasound images, holes are usually found in the reconstructed 3D volumes due to the fast scans. This condition will affect the positioning and judgment of the doctor to the lesion. Hence, in this study, we propose to fill the holes by using a novel content loss indexed 3D partial convolution network for 3D freehand ultrasound volume reconstruction. The network can synthesize novel ultrasound volume structures and reconstruct ultrasound volume with missing regions with variable sizes and at arbitrary locations. MethodsFirst, the 3D partial convolution is introduced into the convolutional layer, which is masked and renormalized to be conditioned on only valid voxels. Then, the mask in the next layer is automatically updated as a part of the forward pass. To better preserve texture and structure details of the reconstruction results, we couple the adversarial loss of the least squares generative adversarial network (LSGAN) with the innovative content loss, which consists of the context loss, the feature-matching loss and the total variation loss. Thereafter, we introduce a novel spectral-normalized LSGAN by adding spectral normalization (SN) to the generator and discriminator of the LSGAN. The proposed method is simple in formulation, and is stable in training. ResultsExperiments on public and in-vivo ultrasound datasets and comparisons with popular algorithms demonstrate that the proposed approach can generate high-quality hole-filling results with preserved perceptual image details. ConclusionsConsidering the high quality of the hole-filling results, the proposed method can effectively fill the missing regions in the reconstructed 3D ultrasound volume from 2D ultrasound image sequences.

Deep Learning for the Detection and Recognition of Rail Defects in Ultrasound B-Scan Images

Rail defect detection is crucial to rail operations safety. Addressing the problem of high false alarm rates and missed detection rates in rail defect detection, this paper proposes a deep learning method using B-scan image recognition of rail defects with an improved YOLO (you only look once) V3 algorithm. Specifically, the developed model can automatically position a box in B-scan images and recognize EFBWs (electric flash butt welds), normal bolt holes, BHBs (bolt hole breaks), and SSCs (shells, spalling, or corrugation). First, the network structure of the YOLO V3 model is modified to enlarge the receptive field of the model, thus improving the detection accuracy of the model for small-scale objects. Second, B-scan image data are analyzed and standardized. Third, the initial training parameters of the improved YOLO V3 model are adjusted. Finally, the experiments are performed on 453 B-scan images as the test data set. Results show that the B-scan image recognition model based on the improved YOLO V3 algorithm reached high performance in its precision. Additionally, the detection accuracy and efficiency are improved compared with the original model and the final mean average precision can reach 87.41%.

Swept Source Optical Coherence Tomography Compared to Ultrasound and Biomicroscopy for Diagnosis of Posterior Vitreous Detachment.

BackgroundBiomicroscopy, B-scan ultrasound imaging, and SD-OCT are all modalities used to characterize a posterior vitreous detachment (PVD). Our objective is to assess the precision of the diagnosis of PVD by SS-OCT.MethodsThis prospective observational study examines ninety-five eyes of forty-nine patients with biomicroscopy, B-scan ultrasound, and SS-OCT for the presence or absence of a complete PVD. All SS-OCT images were reviewed by two retina specialists (RWSC, ZM). All three diagnostic methods were evaluated for agreement by Cohen’s kappa statistic.ResultsThe inter-rater reliability between retina specialists reading the SS-OCT images was 97.9% (κ = 0.957). Agreement on PVD status between SS-OCT and biomicroscopy was 85.3% (κ = 0.711). Agreement between SS-OCT and B-scan ultrasound was 83.2% (κ = 0.667). Agreement between B-scan ultrasound and biomicroscopy was 87.4% (κ = 0.743).ConclusionFor the diagnosis of complete PVD, SS-OCT allows for high accuracy and agreement between graders.

Sub-Nanowatt Ultrasonic Bio-Telemetry Using B-Scan Imaging.

Goal: The objective of this paper is to investigate if the use of a B-scan ultrasound imaging system can reduce the energy requirements, and hence the power-dissipation requirements to support wireless bio-telemetry at an implantable device. Methods: B-scan imaging data were acquired using a commercial 256-element linear ultrasound transducer array which was driven by a commercial echoscope. As a transmission medium, we used a water-bath and the operation of the implantable device was emulated using a commercial-off-the-shelf micro-controller board. The telemetry parameters (e.g. transmission rate and transmission power) were wirelessly controlled using a two-way radio-frequency transceiver. B-scan imaging data were post-processed using a maximum-threshold decoder and the quality of the ultrasonic telemetry link was quantified in terms of its bit-error-rate (BER). Results: Measured results show that a reliable B-scan communication link with an implantable device can be achieved at transmission power levels of 100 pW and for implantation depths greater than 10 cm. Conclusions: In this paper we demonstrated that a combination of B-scan imaging and a simple decoding algorithm can significantly reduce the energy-budget requirements for reliable ultrasonic telemetry.

Automatic Recognition and Positioning of Wheel Defects in Ultrasonic B-Scan Image Using Artificial Neural Network and Image Processing

Abstract Wheels are one of the most important testing components in rail transport that play a significant role in the safety of train, and thence, research on wheel defect detection is of great significance. In this article, a method using image processing techniques and artificial neural network techniques is proposed for the purpose of recognizing defects in ultrasound B-scan image. A noise reduction and filtering algorithm and a feature extraction algorithm are proposed to simplify identification steps and improve the accuracy of the later recognition. Then, two back propagation neural networks with two hidden layers are built respectively for two classification steps. One is to identify noise, while the other is to identify the echo of real defects. Finally, a 93 % recognition rate is achieved by using the algorithm proposed in this article. The result shows that appropriate feature extraction algorithms and artificial neural network techniques are efficient and reliable in defects recognition of ultrasound B-scan images.

Real-time H-scan ultrasound imaging using a Verasonics research scanner

H-scan ultrasound (US) is a new imaging technique that relies on matching a model that describes US image formation to the mathematics of a class of Gaussian-weighted Hermite polynomials (GH). In short, H-scan US (where the ‘H’ denotes Hermite or hue) is a tissue classification technique that images the relative size of acoustic scatterers. Herein, we detail development of a real-time H-scan US imaging technology that was implemented on a programmable US research scanner (Vantage 256, Verasonics Inc, Kirkland, WA). This custom US imaging system has a dual display for real-time visualization of both the H-scan and B-scan US images. This MATLAB-based (Mathworks Inc, Natick, MA) system includes a graphical user interface (GUI) for controlling the entire US scan sequence including the raw radio frequency (RF) data acquisition parameters, image processing, variable control of a parallel set of convolution filters used to derive the H-scan US signal, and data (cine loop) save. The system-level structure used for software-based image reconstruction and display is detailed. Imaging studies were conducted using a series of homogeneous and heterogeneous tissue-mimicking phantom materials embedded with monodisperse spherical US scatterers of size 15–40 µm in diameter. Relative to H-scan US image measurements from a phantom with 15 µm-sized scatterers, data from phantoms with the 30 and 40 µm-sized scatterers exhibited mean intensity increases of 5.2% and 11.6%, respectively. Overall, real-time H-scan US imaging is a promising approach for visualizing the relative size and distribution of acoustic scattering objects.

Improvement of B-scan spatial resolution by pulse-echo ultrasound transit time spectroscopy

The ability of pulse-echo ultrasound transit time spectroscopy (PE-UTTS) to improve the axial and lateral spatial resolution of an ultrasound B-scan image was investigated in this study. An acrylic step-wedge sample was used, consisting of 6 axial steps of both 0.2 and 0.1 mm height, at lateral separations ranging from 0.75 mm to 24 mm. The sample was immersed in water and conventional B-scan images obtained using an industrial Olympus Omniscan system with 2.25, 5 and 10 MHz transducers along with a clinical GE Voluson scanner with a 12 MHz transducer. PE-UTTS B-scan images were also created utilising the Omniscan RF data.From a qualitative perspective, the PE-UTTS B-scan images, at all three frequencies, demonstrated significantly greater axial and lateral spatial resolution than the corresponding conventional B-scan images. Quantitative analysis was performed by comparing the actual depth and length of the acrylic step surfaces with those measured from the conventional and PE-UTTS B-scan images. Of particular note, the depth accuracy for PE-UTTS at 10 MHz was greater than the conventional clinical B-scan at 12 MHz, being 99.90–99.94% compared to 95.95–97.77%. Lateral accuracy was also higher for PE-UTTS at 10 MHz, ranging from 86.67% to 96.67%, compared to 40.00% to 84.58% for the conventional scanner at a frequency of 12 MHz. This scientific study suggests that PE-UTTS has potential to improve clinical ultrasound B-scan image fidelity.