Comparison Of Images Research Articles

A Comparison of Women's Image in Women's Films in Chinese and Western Cultures from a Female Perspective --Carol and Woman-Demon-Human

In the different cultural backgrounds of China and the West, the trend of feminism and related films is different. The image of women is an important part of Chinese and Western culture and a special product of the times, which is extremely important for the understanding of female subjects and social development. Based on the films Woman-Demon-Human and Carol, this paper aims to explore the survival status of women and the manifestation of feminist awakening in different times from the aspects of feminism, self-consciousness, and gender differences, to show the dilemmas and struggles faced by women in modern China and the West, as well as the impact of gender manifestation on women. Women who can break through the inherent pattern, get rid of the fate of the male gaze, and have independent subjective consciousness are particularly valuable. The American movie Carol, with Carol and Therese as the main characters, tells the story of women with different personalities who have found themselves in life and have the courage to resist the pressure of the world and the oppression of patriarchal society. Woman-Demon-Human, directed by Huang Shuqin, tells the story of Qiuyun, who is obsessed with the art of opera, plays a male role, and dedicates her life to the stage. These two films portray the image of a true woman who can be autonomous and self-controlled, and deserve to be compared and analyzed in detail in terms of feminist awakening.

Sex difference in body image, exercise motivation and social comparison among Instagram users: a cross sectional study.

In the 21 st century, impact of social media, particularly Social Networking Sites (SNSs) has been linked to a wide range of human beliefs and expectations. Growing body of research has indicated that body image concerns along with exercise motivation and social comparison are on the rise among young adults. The present study aimed to examine the sex difference in body image, exercise motivation and social comparison among people who use Instagram in the age group 20-30. A total of 212 participants (men=106, women=106) aged 20-30 years, who are users of Instagram completed Body Self Image Questionnaire Short Form as a measure of Body image, Exercise Motivation Inventory - 2 as a measure of Exercise Motivation and Instagram as a Tool for Social Comparison as a measure of Social Comparison. Results showed that a significant difference in body image exist across gender with body image issues higher among females and significant difference in exercise motivation across gender with exercise motivation higher among males. No sex differences were seen in social comparison. It was concluded that body image concerns are higher among females and the drive for exercise is higher among males who used Instagram. It was found that body image concerns were higher among people who exercised regularly as well as among those who followed fitness related pages on Instagram as compared to those who did not. These results provide an insight into the sex differences between the variables and future directions can be aimed at conducting an in-depth analysis using body image, exercise motivation and social comparison.

Comparison of Magnetic Resonance Imaging with Electrodiagnosis in the Evaluation of Clinical Suspicion of Lumbosacral Radiculopathy.

(1) Background: The diagnosis of lumbosacral radiculopathy involves anamnesis, an assessment of sensitivity and strength, diagnostic imaging-usually magnetic resonance imaging (MRI)-and electrodiagnostic testing (EDX), typically electromyography (EMG), and electroneurography (ENG). MRI evaluates the structures supporting the spinal cord, while EDX evaluates root functionality. The present study aimed to analyze the concordance of MRI and EDX findings in patients with clinically suspected radiculopathy. Additionally, we investigated the comparison between these two reference tests and various clinical variables and questionnaires. (2) Methods: We designed a prospective epidemiological study of consecutive cases with an observational, descriptive, cross-sectional, and double-blind nature following the STROBE guidelines, encompassing 142 patients with clinical suspicion of lumbosacral radiculopathy. (3) Results: Of the sample, 58.5% tested positive for radiculopathy using EDX as the reference test, while 45.8% tested positive using MRI. The comparison between MRI and EDX in the diagnosis of radiculopathy in patients with clinical suspicion was not significant; the overall agreement was 40.8%. Only the years with symptoms were comparatively significant between the positive and negative radiculopathy groups as determined by EDX. (4) Conclusion: The comparison between lumbar radiculopathy diagnoses in patients with clinically suspected pathology using MRI and EDX as diagnostic modalities did not yield statistically significant findings. MRI and EDX are complementary tests assessing different aspects in patients with suspected radiculopathy; degeneration of the structures supporting the spinal cord does not necessarily imply root dysfunction.

Clinical High-Resolution Imaging of the Inner Ear by Using Magnetic Resonance Imaging (MRI) and Cone Beam Computed Tomography (CBCT).

Imaging of the delicate inner ear morphology has become more and more precise owing to the rapid progress in magnetic resonance imaging (MRI). However, in clinical practice, the interpretation of imaging findings is hampered by a limited knowledge of anatomical details which are frequently obscured by artifacts. Corresponding review articles are as rare in journals as they are in reference books. This shortness prompted us to perform a direct comparison of imaging with anatomical whole-mount sections as a reference. It was the intention of this paper to compare the microscopic anatomy of a human inner ear as shown on anatomical whole-mount sections with high-resolution MRI and cone beam computed tomography (CBCT). Both are available in clinical routine and depict the structures with maximum spatial resolution. It was also a goal of this work to clarify if structures that were observed on MRI in a regular manner correlate with factual inner ear anatomy or correspond with artifacts typical for imaging. A fresh human anatomical specimen was examined on a clinical 3-Tesla MRI scanner using a dedicated surface coil. The same specimen was then studied with CBCT. In each imaging modality, high-resolution 3D data sets which enabled multiplanar reformatting were created. In the second step, anatomical whole-mount sections of the specimen were cut and stained. This process enabled a direct comparison of imaging with anatomical conditions. Clinical MRI was able to depict the inner ear with remarkable anatomical precision. Strongly T2-weighted imaging protocols are exquisitely capable of showing the fluid-filled components of the inner ear. The macular organs, ampullar crests and cochlear aqueduct were clearly visible. Truncation artifacts are prone to be confused with the delicate membrane separating the endolymphatic from the perilymphatic compartment. However, it was not possible to directly depict this borderline. With the maximum resolution of magnetic resonance tomography, commonly used in everyday clinical practice, even the smallest details of the inner ear structures can be reliably displayed. However, it is important to distinguish between truncation artifacts and true anatomical structures. Therefore, this study can be useful as a reference for image analysis.

Quantification of Resection Margin following Sublobar Resection in Lung Cancer Patients through Pre- and Post-Operative CT Image Comparison: Utilizing a CT-Based 3D Reconstruction Algorithm.

Sublobar resection has emerged as a standard treatment option for early-stage peripheral non-small cell lung cancer. Achieving an adequate resection margin is crucial to prevent local tumor recurrence. However, gross measurement of the resection margin may lack accuracy due to the elasticity of lung tissue and interobserver variability. Therefore, this study aimed to develop an objective measurement method, the CT-based 3D reconstruction algorithm, to quantify the resection margin following sublobar resection in lung cancer patients through pre- and post-operative CT image comparison. An automated subvascular matching technique was first developed to ensure accuracy and reproducibility in the matching process. Following the extraction of matched feature points, another key technique involves calculating the displacement field within the image. This is particularly important for mapping discontinuous deformation fields around the surgical resection area. A transformation based on thin-plate spline is used for medical image registration. Upon completing the final step of image registration, the distance at the resection margin was measured. After developing the CT-based 3D reconstruction algorithm, we included 12 cases for resection margin distance measurement, comprising 4 right middle lobectomies, 6 segmentectomies, and 2 wedge resections. The outcomes obtained with our method revealed that the target registration error for all cases was less than 2.5 mm. Our method demonstrated the feasibility of measuring the resection margin following sublobar resection in lung cancer patients through pre- and post-operative CT image comparison. Further validation with a multicenter, large cohort, and analysis of clinical outcome correlation is necessary in future studies.

A Comparison of Chinese and Western Prostitute Images from the Perspective of Feminism

A Comparison of Chinese and Western Prostitute Images from the Perspective of Feminism

Digital Image Comparison of Cellular Yield in Bronchial Brushing: Pre- and Post-Biopsy Lavage Cytology

Introduction: Bronchoscopy is a useful diagnostic tool capable of performing core biopsy, forceps biopsy, bronchoalveolar lavage, and bronchial brushing. This study compares the cellularity of bronchial cytology including pre- and post-biopsy lavage by digital image analysis, aiming to increase diagnostic and tumor yield by optimizing the sequence and combination of bronchial biopsy and cytology. Methods: Alveolar macrophage, bronchial epithelium, and tumor cell cellularity from liquid-based cytology preparations of bronchial brushing and pre-biopsy and post-biopsy bronchoalveolar lavage were annotated on digitized whole-slide images and compared. Secondary analysis on the relationship of tumor cell and non-lesional cell yield was performed. Results: Overall, 118 cytology specimens from 43 patients were retrieved in total. Bronchial epithelium count was higher in pre-biopsy than post-biopsy lavage (p < 0.01) but not for alveolar macrophages nor tumor cell (p > 0.05). Tumor cell count was higher for bronchial brushing cytology samples than lavage (p = 0.018). The alveolar macrophage count was higher in post-biopsy lavage than bronchial brushing (p = 0.033); otherwise, brushing showed consistently higher bronchial epithelium and tumor cell counts. There were 33 false negative (tumor cell absent) specimens, and the combination of bronchial brushing and pre-biopsy lavage yielded the lowest false negative cases. Correlation between bronchial epithelium and alveolar macrophage counts with tumor cell count was weak (correlation coefficient = −0.168–0.203) except for post-biopsy lavage (correlation coefficient = 0.412–0.479, p < 0.05). Conclusion: Bronchial brushing yields a greater amount of tumor cell than lavage, and timing lavage before or after core biopsy does not affect tumor cell yield. Combining bronchial brushing and pre-biopsy lavage results in the lowest false negative rate.

COMPARATIVE ANALYSIS OF SPECTRAL ANOMALIES DETECTION METHODS ON IMAGES FROM ON-BOARD REMOTE SENSING SYSTEMS

The subject matter of the article is methods of detecting spectral anomalies on images from remote sensing systems. The goal is to conduct a comparative analysis of methods for detecting spectral anomalies on images from remote sensing systems. The tasks are: analysis of the main methods of detecting spectral anomalies on images from remote sensing systems; processing of images from remote sensing systems using basic methods of detecting spectral anomalies; comparative assessment of the quality of methods for detecting spectral anomalies on images from remote monitoring systems. The methods used are: methods of digital image processing, mathematical apparatus of matrix theory, methods of mathematical modeling, methods of optimization theory, analytical and empirical methods of image comparison. The following results are obtained. The main methods of detecting spectral anomalies on images from remote sensing systems were analyzed. Processing of images from remote sensing systems using the basic methods of detecting spectral anomalies was carried out. A comparative assessment of the quality of methods for detecting spectral anomalies on images from remote monitoring systems was carried out. Conclusions. The spectral difference of the considered methods is revealed by the value of information indicators - Euclidean distance, Mahalanobis distance, brightness contrast, and Kullback-Leibler information divergence. Mathematical modeling of the considered methods of detecting spectral anomalies of images with a relatively “simple” and complicated background was carried out. It was established that when searching for a spectral anomaly on an image with a complicated background, the method based on the Kullback-Leibler divergence can be more effective than the other considered methods, but is not optimal. When determining several areas of the image with high divergence indicators, they should be additionally investigated using the specified methods in order to more accurately determine the position of the spectral anomaly.

A universal pipeline to combine spatial transcriptomics, proteomics, and diagnostic H&amp;E assays on a single tissue section to study tissue microenvironment.

e14657 Background: Spatial multi-omics approaches, including spatial transcriptomics (ST) and spatial proteomics (SP), that elucidate the complex tissue microenvironment (TME) are gaining traction in cancer research studies. However, combining these approaches onto one tissue section remains challenging. ST methods visualize, locate and quantify RNA targets, evaluating the transcriptome of the TME at the subcellular level while SP methods stain and visualize protein biomarkers at the cellular level. Here we show a pipeline that combines these ST and SP methods with Hematoxylin and Eosin (H&amp;E) approach on a single tissue section to achieve single slide multi-omics data with high resolution tissue morphology images. Methods: 5µm formalin-fixed paraffin-embedded sections of human lung cancer samples were placed on a Xenium (10x Genomics, Pleasanton, CA) slides and treated to expose RNA molecules. Probe hybridization was performed with a human lung panel kit containing 289 barcoded DNA padlock probes. Downstream ligation and amplification generated copies of the barcode and thereafter, the Xenium Analyzer performed imaging and data collection. The same tissue section was then stained and imaged in COMET (Lunaphore Technologies SA, Switzerland) using sequential immunofluorescence (seqIF) method to detect 40 protein targets in situ. Serial sections of the specimens were used for direct H&amp;E and seqIF staining for comparative validation. Results: Multi-omics images generated from Xenium and COMET were overlayed, jointly analyzed and interpreted. Staining specificity of the protein targets for the post-Xenium slides remain comparable with the direct COMET-stained slide. 40-plex COMET staining intensity in post-Xenium slide was minimally weaker compared to direct COMET-stained slide. Additionally, H&amp;E staining of the post-Xenium/COMET slide and direct COMET-stained slide were comparable to the direct H&amp;E-stained section, demonstrating discernable tissue landscape features despite a fainter hematoxylin stain. Overall, tissue integrity and cell morphology were well-preserved across the different workflows performed on each section, and the protein targets remain relatively stable for labelling after in situ RNA detection process. Conclusions: We present a pipeline that combines two spatial omics approaches with the diagnostic standard H&amp;E staining on a single tissue section, allowing the same cells to be assessed for their histological, proteomic, and transcriptomic information. A visual comparison of images showed minimal compromise to cellular morphology and protein stability at the end of the pipeline compared to direct staining of serial sections. This pipeline could be potentially generalized to most of the ST and SP approaches, thus advancing multi-omics cancer research and potentially clinical diagnostics in the future.

Automated Defect Recognition Using Spline Interpolation

Existing infrastructure systems are aged and deteriorated rapidly, state agencies started searching for more advanced way to maintain their valuable assets to the acceptable level. One of them is the application of digital image processing. This problem proposes a digital image processing method to assess a steel bridge coating surface. The image processing method was developed based on B-Spline interpolation and can be used to recognizing the existence of bridge coating rust defects. An automated defect recognition method can make a decision whether a given digitized image contains defects by image comparison. Key Words:B-Spline interpolation, Digital Image Processing, Automated defect recognition method, Image comparision

Histogram analysis comparison of readout-segmented and single-shot echo-planar imaging for differentiating luminal from non-luminal breast cancer

To compare diffusion-kurtosis imaging (DKI) and diffusion-weighted imaging (DWI) parameters of single-shot echo-planar imaging (ss-EPI) and readout-segmented echo-planar imaging (rs-EPI) in the differentiation of luminal vs. non-luminal breast cancer using histogram analysis. One hundred and sixty women with 111 luminal and 49 non-luminal breast lesions were enrolled in this study. All patients underwent ss-EPI and rs-EPI sequences on a 3.0T scanner. Histogram metrics were derived from mean kurtosis (MK), mean diffusion (MD) and the apparent diffusion coefficient (ADC) maps of two DWI sequences respectively. Student’s t test or Mann–Whitney U test was performed for differentiating luminal subtype from non-luminal subtype. The ROC curves were plotted for evaluating the diagnostic performances of significant histogram metrics in differentiating luminal from non-luminal BC. The histogram metrics MKmean, MK50th, MK75th of luminal BC were significantly higher than those of non-luminal BC for both two DWI sequences (all P<0.05). Histogram metrics from rs-EPI sequence had better diagnostic performance in differentiating luminal from non-Luminal breast cancer compared to those from ss-EPI sequence. MK75th derived from rs-EPI sequence was the most valuable single metric (AUC, 0.891; sensitivity, 78.4%; specificity, 87.8%) for differentiating luminal from non-luminal BC among all the histogram metrics. Histogram metrics of MK derived from rs-EPI yielded better diagnostic performance for distinguishing luminal from non-luminal BC than that from ss-EPI. MK75th was the most valuable metric among all the histogram metrics.

Novel systematic processing of cardiac magnetic resonance imaging identifies target regions associated with infarct-related ventricular tachycardia

Abstract Introduction In the clinic, complete characterization of reentrant ventricular tachycardia (VT) circuits using classical electrophysiological criteria and state-of-the-art high density mapping during VT is complex, and often cannot be completed because of hemodynamic instability. This common limitation has motivated the implementation of mapping strategies during sinus rhythm or ventricular pacing aiming to identify scar regions associated with VT isthmuses or potential arrhythmogenicity. Complementary imaging-based strategies including advanced analyses of scar tissue characteristics have been also proposed for procedure planning and identification of potential arrhythmogenic regions. However, the most recent expert consensus report on catheter ablation of ventricular arrhythmia highlights the lack of agreement on the preferable signal intensity (SI) cut-off values for assessment of tissue heterogeneity and scar areas on late gadolinium enhancement cardiac magnetic resonance (LGE-CMR) images. The latter makes LGE-CMR imaging processing highly operator-dependent and potentially sensitive to selection bias. Purpose We aimed at developing and validating a systematic processing approach on LGE-CMR images to identify potential VT corridors that may include protected isthmuses associated with VT maintenance. Methods Translational study including 18 pigs with established myocardial infarction and inducible VT undergoing in vivo characterization of the anatomical and functional myocardial substrate associated with VT maintenance. Clinical validation was conducted in a multicenter series of 33 patients with ischemic cardiomyopathy undergoing VT ablation. Three-dimensional CMR-LGE images were processed using systematic scanning of 15 signal intensity cut-off ranges to obtain surface visualization of all potential VT corridors. Analysis and comparisons of imaging and electrophysiological data were performed in individuals with full electrophysiological characterization of the isthmus sites of at least one VT morphology. Results In both the experimental pig model and patients undergoing VT ablation, all the electrophysiologically-defined isthmus sites (n=11 and n=19, respectively) showed overlapping regions with CMR-based potential VT corridors. Such imaging-based VT corridors were less specific than electrophysiologically-guided ablation lesions at functionally relevant isthmus sites (Figure). However, in patients, decreasing from 15 to 7 the number of signal intensity cut-off ranges for systematic imaging processing significantly reduced the area of imaging-based potential VT corridors, without diminishing the capability to detect functionally relevant VT isthmus sites. Conclusions Systematic processing of 3D LGE-CMR images provides unbiased identification of imaging based potential VT corridors that contain functionally relevant protected isthmus sites.

Differentiating Low-Grade from High-Grade Intracranial Ependymomas: Comparison of Dynamic Contrast-Enhanced MRI and Diffusion-Weighted Imaging.

The aim of this study was to determine the diagnostic value of fractional plasma volume derived from dynamic contrast-enhanced perfusion MR imaging versus ADC, obtained from DWI in differentiating between grade 2 (low-grade) and grade 3 (high-grade) intracranial ependymomas. A hospital database was created for the period from January 2013 through June 2022, including patients with histologically-proved ependymoma diagnosis with available dynamic contrast-enhanced MR imaging. Both dynamic contrast-enhanced perfusion and DWI were performed on each patient using 1.5T and 3T scanners. Fractional plasma volume maps and ADC maps were calculated. ROIs were defined by a senior neuroradiologist manually by including the enhancing tumor on every section and conforming a VOI to obtain the maximum value of fractional plasma volume (Vpmax) and the minimum value of ADC (ADCmin). A Mann-Whitney U test at a significance level of corrected P = .01 was used to evaluate the differences. Additionally, receiver operating characteristic curve analysis was applied to assess the sensitivity and specificity of Vpmax and ADCmin values. A total of 20 patients with ependymomas (10 grade 2 tumors and 10 grade 3 tumors) were included. Vpmax values for grade 3 ependymomas were significantly higher (P < .002) than those for grade 2. ADCmin values were overall lower in high-grade lesions. However, no statistically significant differences were found (P = .12114). As a dynamic contrast-enhanced perfusion MR imaging metric, fractional plasma volume can be used as an indicator to differentiate grade 2 and grade 3 ependymomas. Dynamic contrast-enhanced perfusion MR imaging plays an important role with high diagnostic value in differentiating low- and high-grade ependymoma.

FruitPhenoBox – a device for rapid and automated fruit phenotyping of small sample sizes

BackgroundFruit appearance of apple (Malus domestica Borkh.) is accession-specific and one of the main criteria for consumer choice. Consequently, fruit appearance is an important selection criterion in the breeding of new cultivars. It is also used for the description of older varieties or landraces. In commercial apple production, sorting devices are used to classify large numbers of fruit from a few cultivars. In contrast, the description of fruit from germplasm collections or breeding programs is based on only a few fruit from many accessions and is mostly performed visually by pomology experts. Such visual ratings are laborious, often difficult to compare and remain subjective.ResultsHere we report on a morphometric device, the FruitPhenoBox, for automated fruit weighing and appearance description using computer-based analysis of five images per fruit. Recording of approximately 100 fruit from each of 15 apple cultivars using the FruitPhenoBox was rapid, with an average handling and recording time of less than eleven seconds per fruit. Comparison of fruit images from the 15 apple cultivars identified significant differences in shape index, fruit width, height and weight. Fruit shape was characteristic for each cultivar, while fruit color showed larger variation within sample sets. Assessing a subset of 20 randomly selected fruit per cultivar, fruit height, width and weight were described with a relative margin of error of 2.6%, 2.2%, and 6.2%, respectively, calculated from the mean value of all available fruit.ConclusionsThe FruitPhenoBox allows for the rapid and consistent description of fruit appearance from individual apple accessions. By relating the relative margin of error for fruit width, height and weight description with different sample sizes, it was possible to determine an appropriate fruit sample size to efficiently and accurately describe the recorded traits. Therefore, the FruitPhenoBox is a useful tool for breeding and the description of apple germplasm collections.

PCB Image Defects Detection by Artificial Neural Networks and Resistance Analysis

The approach contains the sequence of algorithms and formulas for image processing. They are single-layer neural networks, thinning, clustering, mathematical image comparison, and measurements of the trace length and width. All these procedures solve the task of selection and separation of the main objects in the printed circuit board: contacts, traces, and defects. The calculated features connect the conductance resistance of traces with the characteristics of defects. Imposing a tolerance on the distributed or concentrated changes of resistance it is possible to mark the defective and suspicious printed circuit boards.

Comparison of Doppler Imaging and Microvascular Imaging in Cervical Lymph Node Blood Flow Analysis.

Cervical lymph node metastasis is an important determinant of cancer stage and the selection of an appropriate treatment plan for patients with head and neck cancer. Therefore, metastatic cervical lymph nodes should be effectively differentiated from lymphoma, tuberculous lymphadenitis, and other benign lymphadenopathies. The aim of this work is to describe the performance of Doppler ultrasound and superb microvascular imaging (SMI) in evaluating blood flow information of cervical lymph nodes. In addition, the features of flow imaging in metastatic lymph nodes, lymphoma, and tuberculous lymphadenitis were described. Compared with Doppler ultrasound, SMI, the latest blood flow imaging technology, could detect more blood flow signals because the sensitivity, specificity, and accuracy of SMI in the diagnosis of cervical lymph node disease were higher. This article summarizes the value of Doppler ultrasound and SMI in evaluating cervical lymph node diseases and focuses on the diagnostic performance of SMI.

Near-infrared Spectrum Characteristics of Micro-Nano Material Based Diffraction Optical Devices

Diffractive optics devices are optical devices in which the amplitude or phase of the incident light is spatially modulated periodically by a micro-nanomaterial based structure. The study of diffractive optics devices in the field of micro and nano can change the spectroscopic behavior of micro and nano diffractive optics devices by varying the microstructure of the structure and the optical wave properties, which can effectively and reasonably modulate the optical wave signal. To study the effect of different parameter structures on the performance of micro-nano diffraction optical devices, in this paper, two three-dimensional array structures of diffractive optical devices are proposed, which are a vertex-intersecting regular tetrahedron structure and a base-intersecting regular frustum structure. Using the Finite-Difference Time-Domain method, the spectroscopic images of the diffractive optics of the constructed micro-nano diffractive devices are studied in the near-infrared band by varying the height of the constructed structures, the type of structures, the wavelength of the incident light waves, and the polarization direction of the light waves in different 3D height coordinates. The effects of different parameter changes on the performance of the micro-nano diffractive optics devices were analyzed by image comparison. The results show that the best diffraction effect is achieved at a structure height of 0.9 μm for both models with different structure types. The study of both structures at this structure height reveals that the location of diffraction occurrence and the intensity of diffraction can be tuned by varying the structure and the relevant parameters such as the polarization of the light wave. This paper has some theoretical applications for the study of high-performance diffractive optics.

Multi-Bottleneck progressive propulsion network for medical image semantic segmentation with integrated macro-micro dual-stage feature enhancement and refinement

Semantic segmentation can assist doctors to locate key lesion areas intelligently, rapidly and with high precision in medical imaging, which is of great clinical significance for the diagnosis and rehabilitation of patients in various medical fields such as oncology and neurology. Existing segmentation networks face accuracy bottlenecks because enriched information at the decoding end can’t disperse over multiple layers of semantic depth. This is compounded by challenges like complex anatomical structures and varying imaging modalities. In this study, we propose a Multi-Bottleneck Progressive Semantic Segmentation Network (MBP-SSNet), which is essentially a new Baseline based on our proposal: Multi-Bottleneck based Progressive Propulsion Feature Guidance Network (MB-PPFG Net). Its Multi-Bottleneck solves the problem of coding and decoding multiplexed transmission of enriched information, and the propulsive transmission alleviates the problem of insufficient semantic fusion. In addition, under the macro–micro processing idea, MacroFocus Pre-Bottleneck Feature Enhancer (MPBFE) is proposed at the codec intersection in order to better enhance the image contextual semantic dependency association; while MicroDetail Post- Decoding Feature Refiner (MPDFR) is proposed at the tail of the network for fine-grained polishing. In the experiment, the MBP-SSNet was compared with 17 other models across 7 datasets, including diverse medical imaging scenarios, involving metric exploration, image comparison, process validation, and statistical analysis. Concurrently, 22 types of ablation analyses were conducted on it, along with detailed discussions on two critical issues. The experimental results demonstrate that MBP-SSNet achieves an average performance improvement of 0.6809 % in medical image segmentation compared to the optimal benchmark model. The official web address of MBP-SSNet is at: https://github.com/YF-W/MBP-SSNet.

A two‐dimensional, reach‐scale implementation of space‐time image velocimetry (STIV) and comparison to particle image velocimetry (PIV)

AbstractImage‐based algorithms have become a powerful tool for estimating flow velocities in rivers. In this study, we generalize the space‐time image velocimetry (STIV) framework for reach‐scale application rather than along a cross section. The new algorithm provides information on both the magnitude and orientation of velocity vectors, and we refer to the algorithm as two‐dimensional STIV, or 2D‐STIV. The workflow involves setting up a grid, using centreline tangent vectors as initial estimates of flow direction, and then extracting space‐time images (STIs) along search lines radiating from each grid node. The autocorrelation function is used to infer the inclination of streak lines present in STIs, which represents the advection of water surface features. Information on flow direction is obtained by evaluating various candidate search lines and identifying that which yields the highest velocity. This search can be performed exhaustively or via optimization. We applied the new 2D‐STIV algorithm to three test cases, one simulated data set and two natural channels, and compared image‐derived velocities to modelled or measured values. We also applied two established particle image velocimetry (PIV) algorithms to the same data sets. 2D‐STIV performed as well as the two PIV algorithms for simulated images. For a natural river with distinct water surface features, 2D‐STIV was effective for much of the channel but also led to a more patchy, irregular velocity field than the two PIV algorithms. For a site lacking obvious surface features, exhaustive 2D‐STIV led to velocity estimates uncorrelated with field data while the optimization‐based version produced erratic flow directions. 2D‐STIV also required greater image sequence durations, higher frame rates, and generally longer computational run times. Overall, ensemble PIV was the most reliable algorithm.

Objective Comparison of White Light and Narrow-Band Imaging for Detecting Scars, Sulci and Nodules.

Narrow-band imaging (NBI) can improve detection of lesions in the aerodigestive tract. However, its role in benign lesions of the larynx is unclear. This study aims to determine whether NBI improves the detection of scars, sulci, and nodules compared to panchromatic lighting using objective image analysis. In total, 120 vocal folds (VFs) were analyzed with and without NBI (21 normal, 15 scars, 16 sulci, and 45 nodules). Each VF image had anterior, middle, and posterior thirds analyzed for brightness using an area morphometry software (Optimas 5.1a). The middle-third with the lesion was analyzed against surrounding VF segments for average and standard deviation (SD) in absolute grayscale. The use of panchromatic light resulted in greater illumination and grayscale values than NBI. All lesions tended to be in the mid-membranous fold. Under panchromatic light, change in brightness when comparing anterior versus middle (A-M) was +6.1% for normal, versus 6.5%, 8.1%, and 7.1% for sulci, nodules, and scars, respectively. Under NBI, they were 9.0% (normal), 12.3% (sulci), 13.7% (nodules), and 13.1% (scars). A greater SD of luminescence was observed at pathology sites (p < 0.05) when using NBI. The change in absolute grayscale at all lesion sites was greater when using NBI than when using panchromatic light (p < 0.05). NBI significantly enhanced the area of pathology in patients with nodules, sulci, and scars. Greater SD values in grayscale at pathologic sites were observed compared at normal sites. Thus, NBI may improve the detection of phonotraumatic lesions compared to panchromatic light. N/A Laryngoscope, 134:4066-4070, 2024.