Advancing Ki67 hotspot detection in breast cancer: a comparative analysis of automated digital image analysis algorithms.

AIM: Manual detection and scoring of Ki67 hotspots is difficult and prone to variability, limiting its clinical utility. Automated hotspot detection and scoring by digital image analysis (DIA) could improve the assessment of the Ki67 hotspot proliferation index (PI). This study compared the clinical performance of Ki67 hotspot detection and scoring DIA algorithms based on virtual dual staining (VDS) and deep learning (DL) with manual Ki67 hotspot PI assessment. METHODS: Tissue sections of 135 consecutive invasive breast carcinomas were immunohistochemically stained for Ki67. Two DIA algorithms, based on VDS and DL, automatically determined the Ki67 hotspot PI. For manual assessment; two independent observers detected hotspots and calculated scores using a validated scoring protocol. RESULTS: Automated hotspot detection and assessment by VDS and DL could be performed in 73% and 100% of the cases, respectively. Automated hotspot detection by VDS and DL led to higher Ki67 hotspot PIs (mean 39.6% and 38.3%, respectively) compared to manual consensus Ki67 PIs (mean 28.8%). Comparing manual consensus Ki67 PIs with VDS Ki67 PIs revealed substantial correlation (r = 0.90), while manual consensus versus DL Ki67 PIs demonstrated high correlation (r = 0.95). CONCLUSION: Automated Ki67 hotspot detection and analysis correlated strongly with manual Ki67 assessment and provided higher PIs compared to manual assessment. The DL-based algorithm outperformed the VDS-based algorithm in clinical applicability, because it did not depend on virtual alignment of slides and correlated stronger with manual scores. Use of a DL-based algorithm may allow clearer Ki67 PI cutoff values, thereby improving the clinical usability of Ki67.

The Performance and Clinical Applicability of HER2 Digital Image Analysis in Breast Cancer: A Systematic Review.

This systematic review aims to address the research gap in the performance of computational algorithms for the digital image analysis of HER2 images in clinical settings. While numerous studies have explored various aspects of these algorithms, there is a lack of comprehensive evaluation regarding their effectiveness in real-world clinical applications. We conducted a search of the Web of Science and PubMed databases for studies published from 31 December 2013 to 30 June 2024, focusing on performance effectiveness and components such as dataset size, diversity and source, ground truth, annotation, and validation methods. The study was registered with PROSPERO (CRD42024525404). Key questions guiding this review include the following: How effective are current computational algorithms at detecting HER2 status in digital images? What are the common validation methods and dataset characteristics used in these studies? Is there standardization of algorithm evaluations of clinical applications that can improve the clinical utility and reliability of computational tools for HER2 detection in digital image analysis? We identified 6833 publications, with 25 meeting the inclusion criteria. The accuracy rate with clinical datasets varied from 84.19% to 97.9%. The highest accuracy was achieved on the publicly available Warwick dataset at 98.8% in synthesized datasets. Only 12% of studies used separate datasets for external validation; 64% of studies used a combination of accuracy, precision, recall, and F1 as a set of performance measures. Despite the high accuracy rates reported in these studies, there is a notable absence of direct evidence supporting their clinical application. To facilitate the integration of these technologies into clinical practice, there is an urgent need to address real-world challenges and overreliance on internal validation. Standardizing study designs on real clinical datasets can enhance the reliability and clinical applicability of computational algorithms in improving the detection of HER2 cancer.

Identification Tools of Microplastics from Surface Water Integrating Digital Image Processing and Statistical Techniques.

The primary objective of this study was to demonstrate the potential of digital image analysis as a tool to identify microplastic (MP) particles in surface waters and to facilitate their characterisation in terms of 2D and 3D morphology. Digital image analysis preceded by microscopic analysis was used for an exhaustive quantitative and qualitative evaluation of MPs isolated from the Vistula River. Using image processing procedures, 2D and 3D shape descriptors were determined. Principal Component Analysis was used to interpret the relationships between the parameters studied, characterising MP particle geometry, type and colour. This multivariate analysis of the data allowed three or four main factors to be extracted, explaining approximately 90% of the variation in the data characterising MP morphology. It was found that the first principal component for granules, flakes and films was largely represented by strongly correlated with 2D shape descriptors (area, perimeter, equivalent area diameter) and 3D shape descriptors (Corey Shape Factor, Compactness, Dimensionality). Considering the scraps, principal component PC1 was represented by only five of the above descriptors, and the Compactness variable had the largest contribution to principal component PC2. In addition, for granules, flakes and films, a relationship between 2D shape and the colour of their particles could be observed. For the most numerous MP group identified of multicoloured scraps, no such association was found. The results of our study can be used for further multivariate analysis regarding the presence of microplastic floating on the river surface, with a particular focus on particles of secondary origin. This is of key importance for optimising future efforts in conducting small-scale and multidimensional monitoring of and reducing plastics in the aquatic environment.

Strain Measurement during Quasi-Static and Cyclic Loads in AL-6XN Material Using Digital Image Correlation Technique.

A customized digital image correlation (DIC) system was implemented to monitor the strain produced in a cold-rolled AL-6XN stainless steel plate, 3.0 mm thick, subjected to quasi-static and cyclic loading tests. A comparison of the DIC strain measurements was made against those provided by conventional extensometers. Furthermore, the DIC system was used to monitor the fatigue crack initiation in low-cycle fatigue tests. The true stress-strain behavior for the AL-6XN material was properly captured by the DIC measurements. For low-cycle fatigue tests (strain control), the strain mapping generated by DIC allowed for identifying zones with higher strain than the nominal strain amplitude applied (εa) since the first stages of the fatigue life (FL). These zones become potential fatigue crack initiation sites.

Restoration of Strength in Polyamide Woven Glass Fiber Organosheets by Hot Pressing: Case Study of Impact and Compression after Impact.

Thermoplastic composite organosheets (OSs) are increasingly recognized as a viable solution for automotive and aerospace structures, offering a range of benefits including cost-effectiveness through high-rate production, lightweight design, impact resistance, formability, and recyclability. This study examines the impact response, post-impact strength evaluation, and hot-pressing repair effectiveness of woven glass fiber nylon composite OSs across varying impact energy levels. Experimental investigations involved subjecting composite specimens to impact at varying energy levels using a drop-tower test rig, followed by compression-after-impact (CAI) tests. The results underscore the exceptional damage tolerance and improved residual compressive strength of the OSs compared to traditional thermoset composites. This enhancement was primarily attributed to the matrix's ductility, which mitigated transverse crack propagation and significantly increased the amount of absorbed energy. To mitigate impact-induced damage, a localized hot-pressing repair approach was developed. This allowed to restore the post-impact strength of the OSs to pristine levels for impact energies below 40 J and by 83.6% for higher impact energies, when OS perforation was observed. The measured levels of post-repair strength demonstrate a successful restoration of OS strength over a wide range of impact energies, and despite limitations in achieving complete strength recovery above 40 J, hot-pressing repair emerges as a promising strategy for ensuring the longevity of thermoplastic composites through repairability.

Influence of prosthetic index structures and implant materials on stress distribution in implant restorations: a three-dimensional finite element analysis.

BACKGROUND: Mechanical complications affect the stability of implant restorations and are a key concern for clinicians, especially with the frequent introduction of new implant designs featuring various structures and materials. This study evaluated the effect of different prosthetic index structure types and implant materials on the stress distribution of implant restorations using both in silico and in vitro methods. METHODS: Four finite element analysis (FEA) models of implant restorations were created, incorporating two prosthetic index structures (cross-fit (CF) and torc-fit (TF)) and two implant materials (titanium and titanium-zirconium). A static load was applied to each group. An in vitro study using digital image correlation (DIC) with a research scenario identical to that of the FEA was conducted for validation. The primary strain, sensitivity index, and equivalent von Mises stress were used to evaluate the outcomes. RESULTS: Changing the implant material from titanium to titanium-zirconium did not significantly affect the stress distribution or maximum stress value of other components, except for the implant itself. In the CF group, implants with a lower elastic modulus increased the stress on the screw. The TF group showed better stress distribution on the abutment and a lower stress value on the screw. The TF group demonstrated similar sensitivity for all components. DIC analysis revealed significant differences between TF-TiZr and CF-Ti in terms of the maximum (P < 0.001) and minimum principal strains (P < 0.05) on the implants and the minimum principal strains on the investment materials in both groups (P < 0.001). CONCLUSIONS: Changes in the implant material significantly affected the maximum stress of the implant. The TF group exhibited better structural integrity and reliability.

A preliminary study of combustion flame by digital image processing and residue for fireworks flash powder.

Fireworks play a vital role in festive celebrations and entertainment. These fireworks industries are administered by the Petroleum and Explosives Safety Organisation (PESO), Nagpur, Government of India. Even though PESO prescribed the standard composition for various fireworks products, concerns persist regarding the potential deviation from these standards, particularly in the pursuit of increased noise levels to attract consumers. This change in the burning and reactive properties of chemicals could potentially lead to accidents and environmental pollution. The current work investigated the combustion characteristics of two unknown market flash powder samples and a PESO standard sample. The samples were openly ignited in a controlled atmosphere, and video recordings of the resulting chemical flames were analyzed to determine fire area, flame intensity, and motion magnitude. The residues were also collected for EDAX and SEM analysis. Fire pixels from video frames are segmented to create a comprehensive database detailing flame area and motion magnitude under different circumstances. From the flame area profile, motion magnitude and SEM/EDAX analysis, it is found that PESO standard sample combustion is better than the unknown flash powder combustion.

Experimental study of rock fracture behavior under direct tension using three-dimensional digital image correlation.

Understanding the mechanical characteristics of rocks when subjected to direct tension is crucial for assessing the stability of rock formations. Within the scope of this research, a series of tests was conducted using Tage tuff to assess the deformation behavior and crack extension of rock under direct tension. The axial, lateral, and shear strain fields as well as crack propagation, localized deformation behavior, and failure mode of the rocks were analyzed using three-dimensional digital image correlation method. The results showed that the axial strain fields on the specimen surface were heterogeneous, with different locations and localization occurring in the pre-peak stage, which was similar to the evolution of shear strain, whereas the lateral strain only showed slight changes. The crack extension direction was inferred, indicating that both tensile and shear stress occurred in the tests. Furthermore, different stress-strain responses were observed for the inside and outside of the localized bands. Then, the surface patterns of specimen failure were scanned and analyzed to assess the failure mode and residual strength of the specimen under direct tensile stress. Finally, the results of direct tension, uniaxial compression, and Brazilian split tests for Tage tuff were compared, and the complete stress-strain curve of uniaxial tension (UT) was simulated using a nonlinear-variable-compliance constitutive equation. This study provides a deeper understanding into the damage behavior of rocks under direct tension.

Particle shape analysis of calcareous sand based on digital images.

Particle geometric is a key parameter that defines the eometric attributes of calcareous sand particles and is intricately related to their mechanical traits, such as compression and shear. The scanning electron microscopy and digital imaging were applied to capture the microscopic properties and geometric projections of calcareous sand. The qualitative analysis, conventional statistical methods and fractal theory were employed to describe the geometric morphology of sand particles. Additionally, we analyzed the structural and physical traits of calcareous sand based on its unique biological genesis. We developed a hypothetical structural-physical model for calcareous sand. Our findings revealed the interwoven reticulation on the surface of calcareous gravel particles, along with an uneven distribution of pores on the external surface. As the particle size increased, the global profile factor decreased and the angularity increased. The critical threshold for the variations in flatness, surface roughness, and circularity was observed at a particle size of 5 mm, with the particle size having a relatively minor effect on these characteristics for particles smaller than 5 mm. The shape of the calcareous sand particles exhibited fractal characteristics, with fractal dimension serving as a measure of surface smoothness, particle breakage, and strength. These experimental results could significantly enhance our understanding of the mechanical behavior of calcareous sand.

An improved reversible watermarking scheme using embedding optimization and quaternion moments.

Digital watermarking of images is an essential method for copyright protection and image security. This paper presents an innovative, robust watermarking system for color images based on moment and wavelet transformations, algebraic decompositions, and chaotic systems. First, we extended classical Charlier moments to quaternary Charlier moments (QCM) using quaternion algebra. This approach eliminates the need to decompose color images before applying the discrete wavelet transform (DWT), reducing the computational load. Next, we decompose the resulting DWT matrix using QR and singular value decomposition (SVD). To enhance the system's security and robustness, we introduce a modified version of Henon's 2D chaotic map. Finally, we integrate the arithmetic optimization algorithm to ensure dynamic and adaptive watermark insertion. Our experimental results demonstrate that our approach outperforms current color image watermarking methods in security, storage capacity, and resistance to various attacks, while maintaining a high level of invisibility.

Precision and accuracy of craniofacial growth and orthodontic treatment evaluation by digital image correlation: a prospective cohort study.

Introduction: A precise and accurate method for structural superimposition is essential for analyzing dentofacial growth and orthodontic or surgical treatment in longitudinal studies. The errors associated with different superimposition methods have not yet been assessed in high-quality studies. Objectives: This study aimed to assess the precision and accuracy of digital image correlation (DIC) for structural superimposition. Methods: Two cephalometric images from 30 consecutive patients were superimposed using three DIC methods, each measured twice by two examiners. Areas including the contours of the sella, the whole cranial base (CB), and Walker's point and lamina cribrosa (WPLC) were compared using a random coefficient model. Inter-rater and intra-rater errors were assessed for each method. Results: WPLC provided the best precision for image rotation and cephalometric landmarks. Systematic bias was observed between the WPLC and CB methods for image rotation and most landmarks. The intra-rater error in image rotation during DIC was strongly correlated with the intra-rater error in the landmarks of the anterior nasal spine, articulare, and pogonion. Conclusion: Structural superimposition using DIC with WPLC is a precise method for analyzing dentofacial growth and orthodontic or surgical treatment. Moreover, the best method is the measurement of longitudinal dental and craniofacial changes on structurally superimposed cephalometric radiographs with WPLC and a reference grid including the true vertical and horizontal lines from Walker's point.

Digital quantification of PRAME for distinguishing melanoma from nevi compared to manual assessment.

AIMS: In this proof-of-concept study, we propose a new method for automated digital quantification of PRAME (PReferentially expressed Antigen of MElanoma) as a diagnostic aid to distinguish between benign and malignant melanocytic lesions. The proposed method utilizes immunohistochemical virtual double nuclear staining for PRAME and SOX10 to precisely identify the melanocytic cells of interest, which is combined with digital image analyse to quantify a PRAME-index. METHODS: Our study included 10 compound nevi, 3 halo nevi, and 10 melanomas. Tissue slides were stained with PRAME, scanned, the cover glass removed, stained with SOX10, scanned again, and finally analysed digitally. The digitally quantified PRAME-index was compared with a manual qualitative assessment by a dermatopathologist using the standard PRAME-scoring system. RESULTS: The digitally quantified PRAME-index showed a sensitivity of 70 % and a specificity of 100 % for separating melanomas from benign lesions. The manual qualitative PRAME-score showed a sensitivity of 60 % and a specificity of 100 %. Comparing the two methods using ROC-analyses, our digital quantitative method (AUC: 0.931, 95 % CI: 0.834;1.00, SD: 0.050) remains on par with the manual qualitative method (AUC: 0.877, 95 % CI: 0.725;1.00, SD: 0.078). CONCLUSION: We found our novel digital quantitative method was at least as precise at classifying lesions as benign or malignant as the current manual qualitative assessment. Our method has the advantages of being operator-independent, objective, and replicable. Furthermore, our method can easily be implemented in an already digitalized pathology department. Given the small cohort size, more studies are to be done to validate our findings.

Strength and Electrostatic Discharge Resistance Analysis of Additively Manufactured Polyethylene Terephthalate Glycol (PET-G) Parts for Potential Electronic Application.

Optoelectronic components are crucial across various industries. They benefit greatly from advancements in 3D printing techniques that enable the fabrication of intricate parts. Among these techniques, Material Extrusion (MEX) stands out for its simplicity and cost-effectiveness. Integrating 3D printing into production processes offers the potential to create components with enhanced electrostatic discharge (ESD) resistance, a critical factor for ensuring the reliability and safety of optoelectronic devices. Polyethylene terephthalate glycol-modified (PET-G) is an amorphous copolymer renowned for its high transparency, excellent mechanical properties, and chemical resistance, which make it particularly suitable for 3D printing applications. This study focuses on analyzing the mechanical, structural, and electrostatic properties of pure PET-G as well as PET-G doped with additives to evaluate the effects of doping on its final properties. The findings highlight that pure PET-G exhibits superior mechanical strength compared to doped variants. Conversely, doped PET-G demonstrates enhanced resistance to electrostatic discharge, which is advantageous for applications requiring ESD mitigation. This research underscores the importance of material selection and optimization in 3D printing processes to achieve desired mechanical and electrical properties in optoelectronic components. By leveraging 3D printing technologies like MEX and exploring material modifications, industries can further innovate and enhance the production of optoelectronic devices, fostering their widespread adoption in specialized fields.

Effects of Mix Components on Fracture Properties of Seawater Volcanic Scoria Aggregate Concrete.

The fracture mechanism and macro-properties of SVSAC were studied using a novel test system combined with numerical simulations, which included three-point bending beam tests, the digital image correlation (DIC) technique, scanning electron microscopy (SEM), and ABAQUS analyses. In total, 9 groups and 36 specimens were fabricated by considering two critical parameters: initial notch-to-depth ratios (a0/h) and concrete mix components (seawater and volcanic scoria coarse aggregate (VSCA)). Changes in fracture parameters, such as the load-crack mouth opening displacement curve (P-CMOD), load-crack tip opening displacement curve (P-CTOD), and fracture energy (Gf), were obtained. The typical double-K fracture parameters (i.e., initial fracture toughness (KICini) and unstable fracture toughness (KICun)) and tension-softening (σ-CTOD) curve were analyzed. The test results showed that the initial cracking load (Pini), Gf, and characteristic length (Lch) of the SVSAC increased with decreasing a0/h. Compared with the ordinary concrete (OC) specimen, the P-CMOD and P-CTOD curves of the specimen changed after using seawater and VSCA. The evolution of the crack propagation length was obtained through the DIC technique, indicating cracks appeared earlier and the fracture properties of specimen decreased after using VSCA. Generally, the KICun and KICini of SVSAC were 36.17% and 8.55% lower than those of the OC specimen, respectively, whereas the effects of a0/h were negligible. The reductions in Pini, Gf, and Lch of the specimen using VSCA were 10.94%, 32.66%, and 60.39%, respectively; however, seawater efficiently decreased the negative effect of VSCA on the fracture before the cracking width approached 0.1 mm. Furthermore, the effects of specimen characteristics on the fracture mechanism were also studied through numerical simulations, indicating the size of the beam changed the fracture toughness. Finally, theoretical models of the double-K fracture toughness and the σ-CTOD relations were proposed, which could prompt their application in marine structures.

Testing Protocol Development for the Fracture Toughness of Parts Built with Big Area Additive Manufacturing.

The mechanical testing of additively manufactured parts has largely relied on the existing standards developed for traditional manufacturing. While this approach leverages the investment made in current standards development, it inaccurately assumes that the mechanical response of additive manufacturing (AM) parts is identical to that of parts manufactured through traditional processes. When considering thermoplastic, material extrusion AM, the differences in response can be attributed to an AM part's inherent inhomogeneity caused by porosity, interlayer zones, and surface texture. Additionally, the interlayer bonding of parts printed with large-scale AM is difficult to adequately assess, as much testing is performed such that stress is distributed across many layer interfaces; therefore, the lack of AM-specific standards to assess interlayer bonding is a significant research gap. To quantify interlayer bonding via fracture toughness, double cantilever beam (DCB) testing has been used for some AM materials, and DCB has been generally used for a variety of materials including metal, wood, and laminates. Mode I DCB testing was performed on thermoplastic matrix composites printed with Big Area Additive Manufacturing (BAAM). Of particular interest was the notch shape and deflection speed during testing. The results examine the differences when using two notch types and three deflection speeds. The testing method introduced by the following paper differentiates itself from the ones described in the standards used by modernizing the methodology. This was conducted with the introduction of Digital Image Correlation (DIC) to gather displacement and load data simultaneously without human intervention.

Method for computer tomography voxel-based finite element analysis and validation with digital image correlation system.

Understanding the mechanical behavior of heterogeneous materials is becoming increasingly crucial across various fields, including aerospace engineering, composite materials development, geology, and biomechanics. While substantial literature exists on this topic, conventional methods often rely on commercial software packages. This study presents a framework for computed tomography (CT) scan-based finite element (FE) analysis of such materials using open-source software in most of the workflow. Our work focuses on three key aspects:1.Mesh generation that incorporates spatially varying mechanical properties and well-defined boundary conditions.2.Validation of the FE results through comparison with digital image correlation (DIC) system measurements.3.Open-source software utilization throughout the entire process, making it more accessible and cost-effective.This work aims to demonstrate the effectiveness of this framework for analyzing heterogeneous materials in various fields, offering a more accessible and affordable approach.

Early Bolt Loosening Detection Method Based on Digital Image Correlation.

Bolt loosening can significantly impact the accuracy, stability, and safety of equipment. The detection of bolt loosening in a timely manner is crucial for ensuring the safety, reliability, performance, and service life of equipment, structures, and systems. Various methods exist for detecting bolt loosening, such as strain gauges and ultrasonic waves. However, these technologies have some limitations that impede their widespread application. In this paper, for the high-pressure pipe manifolds that may experience leakage accidents due to the loosening of bolts, an early bolt loosening detection method based on digital image correlation is proposed. Initially, a model is established through tensile tests to relate the average strain on the side of the bolt head to the axial force. Subsequently, an industrial camera captures images of bolts with random speckles under operational conditions. Using digital image correlation technology, the average strain in a specific region on the side of the bolt head is calculated. By integrating the average strain into the established relationship model between the average strain and axial force, the axial force of the bolt under operational conditions can be predicted, enabling the early assessment of bolt loosening. The findings show that the average strain on the side of the bolt head increases proportionally with the axial force, indicating a strong linear relationship. This method enables accurate prediction of the bolt's axial force, offering a new approach for identifying the early loosening of bolts in high-pressure manifolds and monitoring structural health.

Experimental Protocols to Test Aortic Soft Tissues: A Systematic Review.

Experimental protocols are fundamental for quantifying the mechanical behaviour of soft tissue. These data are crucial for advancing the understanding of soft tissue mechanics, developing and calibrating constitutive models, and informing the development of more accurate and predictive computational simulations and artificial intelligence tools. This paper offers a comprehensive review of experimental tests conducted on soft aortic tissues, employing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology, based on the Scopus, Web of Science, IEEE, Google Scholar and PubMed databases. This study includes a detailed overview of the test method protocols, providing insights into practical methodologies, specimen preparation and full-field measurements. The review also briefly discusses the post-processing methods applied to extract material parameters from experimental data. In particular, the results are analysed and discussed providing representative domains of stress-strain curves for both uniaxial and biaxial tests on human aortic tissue.

Poisson function and volume ratio of soft anisotropic materials under large deformations.

Accurate transverse deformation measurements are required for the estimation of the Poisson function and volume ratio. In this study, pure silicone and soft composite specimens were subjected to uniaxial tension, and the digital image correlation method was used to measure longitudinal and in- and out-of-plane transverse stretches. To minimize the effects of measurement errors on parameter estimation, the measured transverse stretches were defined in terms of the longitudinal stretch using a new formulation based on Poisson's ratios and two stretch-dependent parameters. From this formulation, Poisson functions and volume ratio for soft materials under large deformations were obtained. The results showed that pure silicone can be considered isotropic and nearly incompressible under large deformations, as expected. In contrast, Poisson's ratio of silicone reinforced with extensible fabric can exceed classical bounds, including negative value (auxetic behavior). The incompressibility assumption can be employed for describing the stress-stretch curve of pure silicone, while volume ratios are required for soft composites. Data of human skin, aortic wall, and annulus fibrosus from the literature were selected and analyzed. Except for the aortic wall, which can be considered nearly incompressible, the studied soft tissues must be regarded as compressible. All tissues presented anisotropic behavior.

Optimizing anterior urethral stricture assessment: leveraging AI-assisted three-dimensional sonourethrography in clinical practice.

PURPOSE: This investigation sought to validate the clinical precision and practical applicability of AI-enhanced three-dimensional sonographic imaging for the identification of anterior urethral stricture. METHODS: The study enrolled 63 male patients with diagnosed anterior urethral strictures alongside 10 healthy volunteers to serve as controls. The imaging protocol utilized a high-frequency 3D ultrasound system combined with a linear stepper motor, which enabled precise and rapid image acquisition. For image analysis, an advanced AI-based segmentation process using a modified U-net algorithm was implemented to perform real-time, high-resolution segmentation and three-dimensional reconstruction of the urethra. A comparative analysis was performed against the surgically measured stricture lengths. Spearman's correlation analysis was executed to assess the findings. RESULTS: The AI model completed the entire processing sequence, encompassing recognition, segmentation, and reconstruction, within approximately 5 min. The mean intraoperative length of urethral stricture was determined to be 14.4 ± 8.4 mm. Notably, the mean lengths of the urethral strictures reconstructed by manual and AI models were 13.1 ± 7.5 mm and 13.4 ± 7.2 mm, respectively. Interestingly, no statistically significant disparity in urethral stricture length between manually reconstructed and AI-reconstructed images was observed. Spearman's correlation analysis underscored a more robust association of AI-reconstructed images with intraoperative urethral stricture length than manually reconstructed 3D images (0.870 vs. 0.820). Furthermore, AI-reconstructed images provided detailed views of the corpus spongiosum fibrosis from multiple perspectives. CONCLUSIONS: The research heralds the inception of an innovative, efficient AI-driven sonographic approach for three-dimensional visualization of urethral strictures, substantiating its viability and superiority in clinical application.