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The common non-contact, automatic body size measurement methods based on the whole livestock point cloud are complex and prone to errors. Therefore, a cattle body measuring system is proposed. The system includes a new algorithm called dynamic unbalanced octree grouping (DUOS), based on PointNet++, and an efficient method of body size measurement based on segmentation results. This system is suitable for livestock body feature sampling. The network divides the cow into seven parts, including the body and legs. Moreover, the key points of body size are located in the different parts. It combines density measurement, point cloud slicing, contour extraction, point cloud repair, etc. A total of 137 items of cattle data are collected. Compared with some of the other models, the DUOS algorithm improves the accuracy of the segmentation task and mean intersection by 0.53% and 1.21%, respectively. Moreover, compared with the manual measurement results, the relative errors of the experimental measurement results are as follows: withers height, 1.18%; hip height, 1.34%; body length, 2.52%; thoracic circumference, 2.12%; abdominal circumference, 2.26%; and cannon circumference, 2.78%. In summary, the model is proven to have a good segmentation effect on cattle bodies and is suitable for cattle body size measurement.

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Metallographic image analysis is vital in the field of metal science due to its potential to automate the sensing process for grain and particle size estimation. To ensure the good quality and reliability of metal products, analysis of the integrity of metallic components is required. In contemporary manufacturing processes, microscopic analysis is a crucial step, mainly when complex systems like gearboxes, turbines, or engines are assembled using various components from multiple suppliers. A final product's quality, durability, and lifespan are determined via the quality analysis of properties of a material with proper tolerances. A flaw in a single component can cause the breakdown of the entire finished product. To ensure the good quality of a material, micro-structural analysis is necessary, which includes the routine measurement of inclusions. The particle and grain sizes of particulate samples are the most crucial physical characteristics of metals. Their measurement is routinely conducted across various industries, and they are frequently considered essential parameters in the creation of many products. This paper discusses the role of sensors in enhancing the accuracy and efficiency of metallographic image analysis, as well as the challenges and limitations associated with this technology. The paper also highlights the potential applications of sensor-assisted metallographic image analysis in various industries, such as aerospace, automotive, and construction. The paper concludes by identifying future research directions for this emerging field, including the development of more sophisticated algorithms for grain and particle size estimation, the integration of multiple sensors for more accurate measurements, and the exploration of new sensing modalities for metallographic image analysis.

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This study focused on an innovative practical method using computer vision for particle size measurement, which serves as a key precursor for predicting the elastic modulus of polymer nanocomposites. This approach involved the morphological segmentation of the nanodispersed phase. It aimed, for the first time, to address the impractical conditions resulting from the assumption of idealized single-particle sizes in a monodispersed system during modeling. Subsequently, a micromechanical finite element framework was employed to determine the interphase thickness and modulus in ultrahigh molecular weight polyethylene/nanozeolite composites, following the quantification of nanoparticle sizes. The size measurement approach relied on morphological images extracted from scanning electron microscopy micrographs of impact-fractured surfaces. To compute the interphase thickness, experimental data was fitted to an interphase-inclusive upper-bound Hashin-Shtrikman model, with the measured average particle size per composition serving as a crucial input. Subsequently, the interphase elastic modulus was computed based on its thickness, employing a hybrid modified-Hashin-Hansen and Maxwell model. These estimated interfacial variables were then utilized as inputs for the finite element model to determine the tensile modulus. A comparison between the model results and measured data revealed a maximum discrepancy of 3.29%, indicating the effectiveness of the methodology employed in quantifying interfacial properties.

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Plastics, recognized for their convenience, disposability, and recyclability, have emerged as a significant ecological challenge, particularly with the prevalence of microplastics (MPs, 1 µm - 5 mm) and sub-micron MPs (100 - 1000 nm) in natural environments. While extensive research has focused on their occurrence and environmental impacts, quantification methods developed for MPs exhibit limitations when applied to sub-micron MPs due to their smaller size. This study addresses these limitations by introducing a novel monitoring system that integrates fluorescence labeling with a microfluidic device and particle tracking software, enabling automated quantification and size measurement of both spherical and fragmented MPs of size in the sub-micrometer range. Results showed that the developed system enabled fast quantification and size measurement of 500- and 1000-nm polystyrene (PS) sub-micron MP beads and fragmented PS and polyvinyl chloride (PVC) sub-micron MPs. Additionally, fluorescence labeling enabled the real-time discrimination of PS and PVC sub-micron MPs. Lastly, the microfluidic system allowed the monitoring of sub-micron MPs within a small quantity of water samples. This automated system has a high potential for swift and real-time monitoring of sub-micron MPs in the environment. By enhancing our ability to detect and quantify sub-micron MPs, this study contributes to a more comprehensive understanding of their presence and distribution in environmental systems.

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Background: The virtual scale endoscope (VSE) helps endoscopists measure colorectal polyp size more accurately compared to visual assessment (VA). However, previous studies were not adequately powered to evaluate the sizing of polyps at clinically relevant size thresholds and relative accuracy for size subgroups. Methods: We created 64 artificial polyps of varied sizes and Paris class morphology, randomly assigned 1:1 to be measured (383 total measurement datapoints with VSE and VA by 6 endoscopists blinded to true size) in a colon model. We added data from two previous trials (480 measurement datapoints). We evaluated for correct classification of polyps into size groups at 3 mm, 5 mm, 10 mm, and 20 mm size thresholds and the relative size measurement accuracy for diminutive polyps (≤5 mm), small polyps (5-9 mm), large polyps at 10-19 mm, and polyps (≥20). Results: VSE had significantly less size group misclassifications at the 5 mm, and 10 mm thresholds (28 percent vs. 45 percent, P = 0.0159 and 26 percent vs. 44 percent, P = 0.0135, respectively). For the 3 mm and 20 mm thresholds, VSE had lower misclassifications; however, this was not statistically significant (36 percent vs. 46 percent, P = 0.3853 and 38 percent vs. 41 percent, P = 0.2705, respectively). The relative size measurement accuracy was significantly higher for VSE compared to VA for all size subgroups (diminutive (P < 0.01), small polyps (P < 0.01), 10-19 mm (P < 0.01), and ≥20 mm (P < 0.01)). Conclusion: VSE outperforms VA in categorizing polyps into size groups at the clinically relevant size thresholds of 5 mm and 10 mm. Using VSE resulted in significantly higher relative measurement accuracy for all size subgroups.

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Single-particle inductively coupled plasma mass spectrometry (spICP-MS) has been used for particle size measurement of diverse types of individual nanoparticles and micrometer-sized carbon-based particles such as microplastics. However, its applicability to the measurement of micrometer-sized non-carbon-based particles such as silica (SiO2) particles is unclear. In this study, the applicability of spICP-MS to particle size measurement of non-porous/mesoporous SiO2 microspheres with a nominal diameter of 5.0 µm or smaller was investigated. Particle sizes of these microspheres were measured using both spICP-MS based on a conventional calibration approach using an ion standard solution and scanning electron microscopy as a reference technique, and the results were compared. The particle size distributions obtained using both techniques were in agreement within analytical uncertainty. The applicability of this technique to the detection of metal-containing protein-binding mesoporous SiO2 microspheres was also investigated. Bound iron (Fe)-containing proteins (i.e., lactoferrin and transferrin) of mesoporous SiO2 microspheres were detected using Fe as a presence marker for the proteins. Thus, spICP-MS is applicable to the particle size measurement of large-sized and non-porous/mesoporous SiO2 microspheres. It has considerable potential for element-based detection and qualification of bound proteins of mesoporous SiO2 microspheres in a variety of applications.

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OBJECTIVES: Ultrasound (US) imaging has been observed to underestimate tumor size in clinical practice. This study aims to compare the size measurements of breast cancer and benign tumors using two-dimensional ultrasound (2DUS) and contrast-enhanced ultrasound (CEUS). METHODS: The study included 42 clinically confirmed breast cancer and 47 benign breast tumors. Two experienced physicians independently measured the maximal longitudinal and transverse diameters of the masses in 2DUS and CEUS. All analyses were performed in R (4.2.2) and GraphPad Prism 6. RESULTS: The maximal longitudinal and transverse diameters of breast cancer measured by CEUS were 26.61 ± 0.21% and 26.24 ± 0.19% larger compared with 2DUS, and benign breast tumors had an 11.74 ± 0.21% and 11.06 ± 0.14% increase in size compared with 2DUS. The area under the curve (AUC) of the receiver operating characteristic curve (ROC) for the difference between 2DUS and CEUS was 0.870 for longitudinal diameters (95% CI: 0.795-0.945, sensitivity 0.842, specificity 0.783, threshold value 0.215), and 0.863 for transverse diameters (95% CI: 0.785-0.942, sensitivity 0.667, specificity 0.936, threshold value 0.203). CONCLUSIONS: The size measurements of both breast cancer and benign tumors were larger in CEUS compared with 2DUS, with CEUS measurements of breast cancer being more pronounced than those of benign breast tumors. These findings suggest that CEUS may provide a more precise assessment of tumor size, which is crucial for determining optimal treatment strategies and improving patient outcomes in breast cancer management.

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BACKGROUND: While multiple cyst features are evaluated for stratifying pancreatic intraductal papillary mucinous neoplasms (IPMN), cyst size is an important factor that can influence treatment strategies. When magnetic resonance imaging (MRI) is used to evaluate IPMNs, no universally accepted sequence provides optimal size measurements. T2-weighted coronal/axial have been suggested as primary measurement sequences; however, it remains unknown how well these and maximum all-sequence diameter measurements correlate with pathology size. This study aims to compare agreement and bias between IPMN long-axis measurements on seven commonly obtained MRI sequences with pathologic size measurements. METHODS: This retrospective cohort included surgically resected IPMN cases with preoperative MRI exams. Long-axis diameter tumor measurements and the presence of worrisome features and/orhigh-risk stigmata were noted on all seven MRI sequences. MRI size and pathology agreement and MRI inter-observer agreement involved concordance correlation coefficient (CCC) and intraclass correlation coefficient (ICC), respectively. The presence of worrisome features and high-risk stigmata were compared to the tumor grade using kappa analysis. The Bland-Altman analysis assessed the systematic bias between MRI-size and pathology. RESULTS: In 52 patients (age 68 ± 13 years, 22 males), MRI sequences produced mean long-axis tumor measurements from 2.45-2.65 cm. The maximum MRI lesion size had a strong agreement with pathology (CCC = 0.82 (95% CI: 0.71-0.89)). The maximum IPMN size was typically observed on the axial T1 arterial post-contrast and MRCP coronal series and overestimated size versus pathology with bias +0.34 cm. The radiologist interobserver agreement reached ICCs 0.74 to 0.91 on the MRI sequences. CONCLUSION: The maximum MRI IPMN size strongly correlated with but tended to overestimate the length compared to the pathology, potentially related to formalin tissue shrinkage during tissue processing.

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Particle size and particle size distribution (PSD) are important properties of polymer latexes because they strongly affect the film formation and the rheological properties of the latexes. Thus, monitoring the particle size is of paramount importance during the production of waterborne polymeric dispersions, for which online/inline measurements of the particle size are required. Herein, turbidity spectroscopy (TUS) is used to measure the particle size of nanoparticles in dispersed media. Calibration curves based on a modified wavelength exponent method are introduced and assessed to monitor the evolution of a broad range of particle sizes in seeded semibatch emulsion polymerizations of methyl methacrylate, butyl acrylate, methacrylic acid (MMA/BA/MAA 51/47/2) terpolymers. It is shown that the wavelength exponent based calibration curves can be successfully used to retrieve the particle size during the polymerization process.

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Vertical beam size measurements were carried out at Beijing Electron-Positron Collider II (BEPCII) using a phase grating and an absorption grating based on the Talbot effect. The transverse coherence of synchrotron radiation is closely related to beam size. Due to the partial coherence of the synchrotron radiation source, the coherence length can be calculated by measuring the visibility decay of interferograms recorded at different distances behind the gratings. A vertical beam size of 68.19 ± 2 µm was obtained based on the relationship between the coherence length and beam size at the 3W1 beamline of BEPCII. A comparison of the vertical emittance derived from the grating Talbot method and the synchrotron radiation visible light interferometer method was presented. The vertical emittances from the two methods are 1.41 nm rad and 1.40 nm rad, respectively. The 0.1% difference indicates that the grating Talbot method for beam size measurement is reliable. This technique has great potential for small beam size measurement of fourth-generation synchrotron radiation light sources, considering its small diffraction limitation and simple experimental setups.

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Grasping information about street trees can assist urban environmental managers in quantifying and evaluating their costs and ecological benefits. Street view imagery has the potential for urban street tree surveys. However, few studies have been conducted on the inventory of street tree species, size structures and diversity based on street view imagery at the urban scale. In this study, we tried to conduct a survey of street trees in urban areas of Hangzhou using street view images. First, we constructed a size reference items system and determined that using it for street view measurements of street trees was comparable to field measurements results (R2 = 0.913-0.987). On this basis, we investigated the distribution characteristics and differences of street trees in Hangzhou using Baidu Street View and found that Cinnamomum camphora was the dominant tree species in Hangzhou (46.58 %), and the high proportion made urban street trees susceptible to ecological hazards. In addition, surveys conducted separately in various urban districts revealed that the diversity of street trees in new urban areas was smaller and less uniform. Additionally, as the gradient got further away from the city center, the street trees are smaller, the diversity first increased and then decreased, and the evenness gradually decreased. This study analyzes the use of Street View to investigate the distribution of species, size structure, and diversity of urban street trees. The use of street view imagery will simplify the collection of data on urban street trees and provide urban environmental managers with a foundation for strategy development.

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This paper presents a case study on the first in-line application of AI-based image analysis for real-time pharmaceutical particle size measurement in a continuous milling process. An AI-based imaging system, which utilises a rigid endoscope, was tested for the real-time particle size measurement of solid NaCl powder used as a model API in the range of 200-1000 µm. After creating a dataset containing annotated images of NaCl particles, it was used to train an AI model for detecting particles and measuring their size. The developed system could analyse overlapping particles without dispersing air, thus broadening its applicability. The performance of the system was evaluated by measuring pre-sifted NaCl samples with the imaging tool, after which it was installed into a continuous mill for in-line particle size measurement of a milling process. By analysing ∼100 particles/s, the system was able to accurately measure the particle size of sifted NaCl samples and detect particle size reduction when applied in the milling process. The Dv50 values and PSDs measured real-time with the AI-based system correlated well with the reference laser diffraction measurements (<6% mean absolute difference over the measured samples). The AI-based imaging system shows great potential for in-line particle size analysis, which, in line with the latest pharmaceutical QC trends, can provide valuable information for process development and control.

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BACKGROUND: There is consensus that postoperative adjuvant therapy is not recommended in patients with stage 1a non-small cell lung cancer (NSCLC). Meanwhile, it is still controversial whether postoperative adjuvant chemotherapy is recommended for NSCLC patients with T2aN0M0 (stage 1b). In some patients with stage 1b NSCLC without pleural invasion, tumor diameter was measured between 3 and 4 cm by preoperative imaging and less than 3 cm by postoperative pathology specimens. TNM staging in such patients is both radiologic stage 1b and pathologic stage 1a. Thoracic surgeons are often confused about whether such patients with NSCLC will require subsequent treatment and how the survival prognosis for this group of patients will be. METHODS: All data of radiographic TNM stage 1b patients who underwent radical R0 resection at the department of thoracic surgery, the First Affiliated Hospital of Soochow University between January 2013 and July 2017 were retrieved, and 208 patients were finally included in the study. Clinical data, including imaging data, pathology data, were obtained by reviewing the patients' electronic medical records. Disease-free survival (DFS) and overall survival (OS) were obtained by telephone interview. Statistical analysis was performed using SPSS (SPSS 26.0 for windows, SPSS). RESULTS: A total of 208 patients were included in this study, 61 patients with T-stage migration (observation group) and 147 patients without T-stage migration (control group). There were significant statistical differences between the two groups in terms of preoperative FEV1/FVC and tumor diameter (specimens, CT and 3-dimensional measurements). Logistic regression results showed that lower FEV1/FVC and smaller CT measurements would make the patient's T stage more likely to migrate. Bland-Altman plots showed that tumor length measured by imaging was significantly higher than that measured by pathological specimens. Taking DFS as the outcome, the survival curve of the observation group was significantly better than that of the control group. Similarly, there was a significant difference in OS between the two groups. CONCLUSIONS: For NSCLC patients whose preoperative imaging evaluation was stage 1b (tumor diameter more than 3 cm, no main bronchus, pleura, no atelectasis), the presence of lung tissue with smaller tumor diameter and/or higher air content may indicate that the postoperative pathological staging may be changed to stage 1a (tumor diameter less than 3 cm). These patients had better survival prognosis than those who did not undergo TNM stage change and were diagnosed with stage 1b non-small cell lung cancer before and after surgery.

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Background: Artificial intelligence-assisted colonoscopy (AIAC) has been proposed and validated in recent years, but the effectiveness of clinic application remains unclear since it was only validated in some clinical trials rather than normal conditions. In addition, previous clinical trials were mostly concerned with colorectal polyp identification, while fewer studies are focusing on adenoma identification and polyps size measurement. In this study, we validated the effectiveness of AIAC in the clinical environment and further investigated its capacity for adenoma identification and polyps size measurement. Methods: The information of 174 continued patients who went for coloscopy in Chongqing Rongchang District People's hospital with detected colon polyps was retrospectively collected, and their coloscopy images were divided into three validation datasets, polyps dataset, polyps/adenomas dataset (all containing narrow band image, NBI images), and polyp size measurement dataset (images with biopsy forceps and polyps) to assess the competence of the artificial intelligence system, and compare its diagnostic ability with endoscopists with different experiences. Results: A total of 174 patients were included, and the sensitivity of the colorectal polyp recognition model was 99.40%, the accuracy of the colorectal adenoma diagnostic model was 93.06%, which was higher than that of endoscopists, and the mean absolute error of the polyp size measurement model was 0.62 mm and the mean relative error was 10.89%, which was lower than that of endoscopists. Conclusion: Artificial intelligence-assisted model demonstrated higher competence compared with endoscopists and stable diagnosis ability in clinical use.

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Flow cytometry is a widespread and powerful technique whose resolution is determined by its capacity to accurately distinguish fluorescently positive populations from negative ones. However, most informative results are discarded while performing the measurements of conventional flow cytometry, e.g., the cell size, shape, morphology, and distribution or location of labeled exosomes within the unpurified biological samples. Herein, we propose a novel approach using an anti-diffraction light sheet with anisotroic feature to excite fluorescent tags. Constituted by an anti-diffraction Bessel-Gaussian beam array, the light sheet is 12 µm wide, 12 µm high, and has a thickness of ~0.8 µm. The intensity profile of the excited fluorescent signal can, therefore, reflect the size and allow samples in the range from O (100 nm) to 10 µm (e.g., blood cells) to be transported via hydrodynamic focusing in a microfluidic chip. The sampling rate is 500 kHz, which provides a capability of high throughput without sacrificing the spatial resolution. Consequently, the proposed anti-diffraction light sheet flow cytometry (ADLSFC) can obtain more informative results than the conventional methodologies, and is able to provide multiple characteristics (e.g., the size and distribution of fluorescent signal) helping to distinguish the target samples from the complex backgrounds.

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To overcome the disadvantages of small and random samples in static detection, this paper presents a study on dynamic measurements of solid particles in jet fuel using large samples. In this paper, the Mie scattering theory and Lambert-Beer law are used to analyze the scattering characteristics of copper particles in jet fuel. We have presented a prototype for multi-angle scattered and transmitted light intensity measurements of particle swarms in jet fuel which is used to test the scattering characteristics of the jet fuel mixture with 0.5-10 µm particle sizes and 0-1 mg/L concentrations of copper particles. The vortex flow rate was converted to an equivalent pipe flow rate using the equivalent flow method. Tests were conducted at equivalent flow rates of 187, 250 and 310 L/min. Through numerical calculations and experiments, it has been discovered that the intensity of the scattering signal decreases as the scattering angle increases. Meanwhile, both the scattered light intensity and transmitted light intensity would vary with the particle size and mass concentration. Finally, the relationship equation between light intensity and particle parameters has also been summarized in the prototype based on the experimental results, which proves its detection capability.

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The goal of this study was to evaluate ultrasound contrast microbubbles (MB) stability during a typical cystometrogram (CMG) for bladder pressure measurement application using the subharmonic-aided pressure estimation technique. A detailed study of MB stability was required given two unique characteristics of this application: first, bulk infusion of MBs into the bladder through the CMG infusion system, and second, duration of a typical CMG which may last up to 30 min. To do so, a series of size measurement and contrast-enhanced ultrasound imaging studies under different conditions were performed and the effects of variables that we hypothesized have an effect on MB stability, namely, i) IV bag air headspace, ii) MB dilution factor, and iii) CMG infusion system were investigated. The results verified that air volume in intravenous (IV) bag headspace was not enough to have a significant effect on MB stability during a CMG. We also showed that higher MB dosage results in a more stable condition. Finally, the results indicated that the CMG infusion system adversely affects MB stability. In summary, to ensure MB stability during the entire duration of a CMG, lower filling rates (limited by estimated bladder capacity in clinical applications) and/or higher MB dosage (limited by FDA regulations and shadowing artifact) and/or the consideration of alternative catheter design may be needed.

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Bacterial amyloids decorate the cell surface of many bacteria by forming functional amyloid fibers. These amyloids have structural and biochemical similarities with many disease-related amyloids in eukaryotes. Amyloid aggregation starts at the individual monomer level, and the end product is the amyloid fibril. The process of amyloid aggregation involves a continuous increase of the aggregate size, and therefore size is a critical parameter to measure in aggregation experiments. Also, our understanding of the aggregation process, and our ability to design interventions, can benefit from a measurement of the conformational dynamics of proteins undergoing aggregation. Fluorescence correlation spectroscopy (FCS) is perhaps the most sensitive and rapid technique available currently for this purpose. It can measure the average size and the size distribution of molecules and aggregates down to sub-nm length scales and can also measure fast nanosecond time-scale conformational dynamics, all in an equilibrium solution. FCS achieves this by measuring the fluorescence intensity fluctuations of freely diffusing protein molecules in an optically defined microscopic probe volume in a solution. Here, we present a set of instructions for effectively measuring the size and dynamics of amyloid aggregates with FCS.

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In this work, we investigated a platform for real-time emulsion droplet detection and size measurement in optofluidic platforms. An 8.2 µm core diameter input optical fiber and a multi-mode Gradient Refractive Index (GRIN) output fiber were integrated into an acrylic microfluidic channel platform consisting of three layers. Water-in-oil emulsions were investigated, since relevant applications have emerged in the recent past for these types of emulsions, such as drug encapsulation as well as droplet-based Polymerase Chain Reaction (PCR) amplification of DNA, among others. The main contribution of this work is in understanding the main physical phenomena (i.e., total internal reflection, refraction, and interference) behind the complex transmittance pattern obtained for these droplets. For this purpose, a frequency domain electromagnetic wave propagation modelling of the structure using the Finite Element Method (FEM) was used along with experimental measurements.

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The scaffold pore size influences many critical physical aspects of tissue engineering, including tissue infiltration, biodegradation rate, and mechanical properties. Manual measurements of pore sizes from scanning electron micrographs using ImageJ/FIJI are commonly used to characterize scaffolds, but these methods are both time-consuming and subject to user bias. Current semi-automated analysis tools are limited by a lack of accessibility or limited sample size in their verification process. The work here describes the development of a new MATLAB algorithm, PoreScript, to address these limitations. The algorithm was verified using three common scaffold fabrication methods (e.g., salt leaching, gas foaming, emulsion templating) with varying pore sizes and shapes to demonstrate the versatility of this new tool. Our results demonstrate that the pore size characterization using PoreScript is comparable to manual pore size measurements. The PoreScript algorithm was further evaluated to determine the effect of user-input and image parameters (relative image magnification, pixel intensity threshold, and pore structure). Overall, this work validates the accuracy of the PoreScript algorithm across several fabrication methods and provides user-guidance for semi-automated image analysis and increased throughput of scaffold characterization.