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Amoeboid cell motility is fundamental for a multitude of biological processes such as embryogenesis, immune responses, wound healing, and cancer metastasis. It is characterized by specific cell shape changes: the extension and retraction of membrane protrusions, known as pseudopodia. A common approach to investigate the mechanisms underlying this type of cell motility is to study phenotypic differences in the locomotion of mutant cell lines. To characterize such differences, methods are required to quantify the contour dynamics of migrating cells. AmoePy is a Python-based software package that provides tools for cell segmentation, contour detection as well as analyzing and simulating contour dynamics. First, a digital representation of the cell contour as a chain of nodes is extracted from each frame of a time-lapse microscopy recording of a moving cell. Then, the dynamics of these nodes-referred to as virtual markers-are tracked as the cell contour evolves over time. From these data, various quantities can be calculated that characterize the contour dynamics, such as the displacement of the virtual markers or the local stretching rate of the marker chain. Their dynamics is typically visualized in space-time plots, the so-called kymographs, where the temporal evolution is displayed for the different locations along the cell contour. Using AmoePy, you can straightforwardly create kymograph plots and videos from stacks of experimental bright-field or fluorescent images of motile cells. A hands-on guide on how to install and use AmoePy is provided in this chapter.
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Movimento Celular , Software , Processamento de Imagem Assistida por Computador/métodos , Imagem com Lapso de Tempo/métodos , Quimografia/métodos , Dictyostelium/citologia , Dictyostelium/fisiologia , Dictyostelium/crescimento & desenvolvimento , PseudópodesRESUMO
We consider the operation of a digital linear ion trap with resonance radial ejection and mass selective instability modes. Periodic wave shape has a positive part with amplitude V+=V0 and duration 0.8T and negative part with amplitude V-=-4V0 and duration 0.2T, where T is the period. The mapping of the stability diagram, calculations of the well's depth and ion oscillations spectra are presented. The process of resonant excitation of ion oscillations by a dipole sinusoidal signal is studied, as well as ion ejection at the stability boundary. The trajectory method is used for this purpose. It is shown that the mass selectivity of dipole excitation is twice as large for rectangular wave shape compared to sinusoidal wave shape. Increasing the diameter of the round rods of the linear trap gives an increase in the resolving power. The possibility of DIT operation in mass-selective instability mode at the boundary point qb=0.39 is discussed.
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Automatic tumor segmentation via positron emission tomography (PET) and computed tomography (CT) images plays a critical role in the prevention, diagnosis, and treatment of this disease via radiation oncology. However, segmenting these tumors is challenging due to the heterogeneity of grayscale levels and fuzzy boundaries. To address these issues, in this paper, an efficient model-informed PET/CT tumor co-segmentation method that combines fuzzy C-means clustering and Bayesian classification information is proposed. To alleviate the grayscale heterogeneity of multi-modal images, in this method, a novel grayscale similar region term is designed based on the background region information of PET and the foreground region information of CT. An edge stop function is innovatively presented to enhance the localization of fuzzy edges by incorporating the fuzzy C-means clustering strategy. To improve the segmentation accuracy further, a unique data fidelity term is introduced based on PET images by combining the distribution characteristics of pixel points in PET images. Finally, experimental validation on datasets of head and neck tumor (HECKTOR) and non-small cell lung cancer (NSCLC) demonstrated impressive values for three key evaluation metrics, including DSC, RVD and HD5, achieved impressive values of 0.85, 5.32, and 0.17, respectively. These compelling results indicate that image segmentation methods based on mathematical models exhibit outstanding performance in handling grayscale heterogeneity and fuzzy boundaries in multi-modal images.
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OBJECTIVE: Target volumes for radiotherapy are usually contoured manually, which can be time-consuming and prone to inter- and intra-observer variability. Automatic contouring by convolutional neural networks (CNN) can be fast and consistent but may produce unrealistic contours or miss relevant structures. We evaluate approaches for increasing the quality and assessing the uncertainty of CNN-generated contours of head and neck cancers with PET/CT as input. Approach. Two patient cohorts with head and neck squamous cell carcinoma and baseline 18F-fluorodeoxyglucose positron emission tomography and computed tomography images (FDG-PET/CT) were collected retrospectively from two centers. The union of manual contours of the gross primary tumor and involved nodes was used to train CNN models for generating automatic contours. The impact of image preprocessing, image augmentation, transfer learning and CNN complexity, architecture, and dimension (2D or 3D) on model performance and generalizability across centers was evaluated. A Monte Carlo dropout technique was used to quantify and visualize the uncertainty of the automatic contours. Main results. CNN models provided contours with good overlap with the manually contoured ground truth (median Dice Similarity Coefficient: 0.75 - 0.77), consistent with reported inter-observer variations and previous auto-contouring studies. Image augmentation and model dimension, rather than model complexity, architecture, or advanced image preprocessing, had the largest impact on model performance and cross-center generalizability. Transfer learning on a limited number of patients from a separate center increased model generalizability without decreasing model performance on the original training cohort. High model uncertainty was associated with false positive and false negative voxels as well as low Dice coefficients. Significance. High quality automatic contours can be obtained using deep learning architectures that are not overly complex. Uncertainty estimation of the predicted contours shows potential for highlighting regions of the contour requiring manual revision or flagging segmentations requiring manual inspection and intervention. .
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Machine vision is a desirable non-contact measurement method for hot forgings, as image segmentation has been a challenging issue in performance and robustness resulting from the diversity of working conditions for hot forgings. Thus, this paper proposes an efficient and robust active contour model and corresponding image segmentation approach for forging images, by which verification experiments are conducted to prove the performance of the segmentation method by measuring geometric parameters for forging parts. Specifically, three types of continuity parameters are defined based on the geometric continuity of equivalent grayscale surfaces for forging images; hence, a new image force and external energy functional are proposed to form a new active contour model, Geometric Continuity Snakes (GC Snakes), which is more percipient to the grayscale distribution characteristics of forging images to improve the convergence for active contour robustly; additionally, a generating strategy for initial control points for GC Snakes is proposed to compose an efficient and robust image segmentation approach. The experimental results show that the proposed GC Snakes has better segmentation performance compared with existing active contour models for forging images of different temperatures and sizes, which provides better performance and efficiency in geometric parameter measurement for hot forgings. The maximum positioning and dimension errors by GC Snakes are 0.5525 mm and 0.3868 mm, respectively, compared with errors of 0.7873 mm and 0.6868 mm by the Snakes model.
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PURPOSE: We defined sagittal S-line tilt (SSLT) as the tilt of the line connecting the upper instrumented vertebra and the lower instrumented vertebra. This study aimed to: (1) examine the correlation between SSLT and proximal junctional angle (PJA) change values, and (2) determine the cut-off value of SSLT with respect to proximal junctional kyphosis (PJK) occurrence. METHODS: Eighty-six consecutive patients (81 female and 5 male; mean age: 15.8 years) with Lenke 5C AIS who underwent posterior selective spinal fusion. Pearson's correlation coefficients were used to examine the relationship between preoperative SSLT and changes in PJA from preoperative to 2 years postoperative. The impact of SSLT on PJK at 2 years after surgery was assessed using a receiver operating characteristic (ROC) curve. RESULTS: We observed a moderate positive correlation between preoperative SSLT and change in PJA (R = 0.541, P < 0.001). We identified 18 patients (21%) with PJK at 2 years postoperative. Mean preoperative SSLT in the PJK group and the non-PJK group differed significantly at 23.3 ± 4.1° and 16.1 ± 5.0°, respectively (P < 0.001). The cut-off value of preoperative SSLT for PJK at 2 years postoperative was 18° in ROC curve analysis, with a sensitivity of 94%, specificity of 68%, and area under the ROC curve of 0.868. CONCLUSION: In selective lumbar fusion for AIS Lenke type 5C curves, preoperative SSLT was significantly correlated with PJA change from preoperative to 2 years postoperative. SSLT was a predictor of PJK occurrence, with a cut-off value of 18°.
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The accuracy of artificial intelligence (AI) generated contours for intact-breast and post-mastectomy radiotherapy plans was evaluated. Geometric and dosimetric comparisons were performed between auto-contours (ACs) and manual-contours (MCs) produced by physicians for target structures. Breast and regional nodal structures were manually delineated on 66 breast cancer patients. ACs were retrospectively generated. The characteristics of the breast/post-mastectomy chestwall (CW) and regional nodal structures (axillary [AxN], supraclavicular [SC], internal mammary [IM]) were geometrically evaluated by Dice similarity coefficient (DSC), mean surface distance, and Hausdorff Distance. The structures were also evaluated dosimetrically by superimposing the MC clinically delivered plans onto the ACs to assess the impact of utilizing ACs with target dose (Vx%) evaluation. Positive geometric correlations between volume and DSC for intact-breast, AxN, and CW were observed. Little or anti correlations between volume and DSC for IM and SC were shown. For intact-breast plans, insignificant dosimetric differences between ACs and MCs were observed for AxNV95% (p = 0.17) and SCV95% (p = 0.16), while IMNV90% ACs and MCs were significantly different. The average V95% for intact-breast MCs (98.4%) and ACs (97.1%) were comparable but statistically different (p = 0.02). For post-mastectomy plans, AxNV95% (p = 0.35) and SCV95% (p = 0.08) were consistent between ACs and MCs, while IMNV90% was significantly different. Additionally, 94.1% of AC-breasts met ΔV95% variation <5% when DSC > 0.7. However, only 62.5% AC-CWs achieved the same metrics, despite AC-CWV95% (p = 0.43) being statistically insignificant. The AC intact-breast structure was dosimetrically similar to MCs. The AC AxN and SC may require manual adjustments. Careful review should be performed for AC post-mastectomy CW and IMN before treatment planning. The findings of this study may guide the clinical decision-making process for the utilization of AI-driven ACs for intact-breast and post-mastectomy plans. Before clinical implementation of this auto-segmentation software, an in-depth assessment of agreement with each local facilities MCs is needed.
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The fundamental function of an optimal cervical pillow is to provide sufficient support to maintain normal spinal alignment and minimize biological stress on the contact surface throughout sleep. The recent advancements in cervical pillows have mainly focused on the subjective and objective evaluations of support comfort, as well as the relationship between pillow height and cervical vertebrae posture. However, only a few studies have addressed shape design guidelines and mechanical performances of the pillows themselves. In this study, a two-sectional contour cervical pillow comprising an arc and a Bezier curve is designed to support the head and neck. The design of the arc-shaped neck section incorporates the Cobb's angle and Borden value from healthy individuals to reflect the consistency of normal cervical anatomical features. The Bezier curve-based head section takes the head length and neck depth into account as significant individual differences. Static analysis and lattice optimization are performed in ANSYS Workbench to develop a variable-density cellular structure, aimed at improving air permeability and reducing the risk of pressure ulcers associated with the cervical pillow. The rapid prototyping technique fused deposition modeling (FDM) and thermoplastic material polylactic acid (PLA) are employed for fabricating different cellular structures. The results demonstrate that the neck section experiences less stress and greater deformation in comparison to the head section, indicating good comfort and support provided by the designed cervical pillow. Additionally, the compressive, bending, and cushion properties of the 3D-printed cervical pillow with variable-density cellular structure are experimentally validated, further confirming its effectiveness.
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OBJECTIVE: Lip rejuvenation has several aims, including enhancing lip volume, adjusting the upper and lower lip's length, diminishing fine lines, contouring and redefining the cupid bow and vermilion border, and eversion of the vermilion. Within the scope of this research, we aimed to compare popular injection techniques to augment the size of the lips. MATERIALS AND METHODS: This randomized retrospective study included 216 female patients aged 19 to 39, who desired a lip filler treatment from 2017 to 2023. Pre- and post-procedure results were elaborated with top-to-the-bottom technique in Group 1, bottom-to-the-top technique in Group 2, and lateral-to-medial techniques in Groups 3 and 4.Once the patients were sufficiently anesthetized, the hyaluronic acid at a concentration of 20 mg/mL with 0.3% (3 mg/mL) lidocaine, was used in all groups. Patients were followed up for three weeks. Patient satisfaction scores were evaluated on a scale from 0 to 5 using a survey on the last follow-up day. RESULTS: A statistically significant difference was found between the groups regarding satisfaction scores (p<0.05). The patient satisfaction scores after injection were 4.78/5 in Group 1, 3.70/5 in Group 2, 4.15/5 in Group 3, and 3.85/5 in Group 4. Kruskal-Wallis variance analysis for more than two groups revealed statistically significant differences between Group 1 and Group 2 (p<0.001), Group 1 and Group 3 (p<0.001), Group 1 and Group 4 (p<0.001), and Group 2 and Group 3 (p=0.009) (Mann Whitney U-Test with Bonferroni adjusted). No major complication was observed in any of the patients. CONCLUSION: In this study, patient satisfaction was found to be highest in the group with needle orientation top to bottom, taking into account migration to the upper lip. These findings showed that the direction of the needle during injection also determines the direction of distribution of the filler on the lip and may be an important factor in patient satisfaction.
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Sorghum production in semi-arid areas of Zimbabwe is constrained by low and erratic rainfall, low fertility and soil moisture stress. Sorghum grain yields ranges from 0.2 to 0.4 t ha-1 in sandy-to-sandy loam soils respectively. The objective of the study was to assess cattle manure and rainwater harvesting techniques in improving sorghum grain yield in a semi-arid region of Zimbabwe. The experiment used a randomised complete block design with rainwater harvesting technique as a main treatment factor at three levels. Sub-plot factor was cattle manure at five levels (0, 2.5, 5, 10 and 15 t ha-1) and two sorghum varieties (Macia and SV1) as sub-sub plot factor. Sorghum grain yields were improved significantly (p < 0.05) for both varieties using tied contours. Increasing application rates of cattle manure, showed significant increase (p < 0.05) in sorghum grain yield over the control (0 t ha-1). Tied contour had higher grain yield (1.15 t ha-1) with the use of Macia variety. Stover yield was highly influenced by rainwater harvesting method of tied contour (p < 0.05) compared with infiltration pit and standard contour. Increase in application levels of cattle manure show significant (p < 0.05) increase in stover yields. Tied contour had the highest (3.11 kg ha-1 mm-1) rainwater use efficiency which show significant differences (p < 0.05) from infiltration pits and standard contour. Interaction of tied contour and different rates of cattle manure showed significant increments in rainwater use efficiency with increases in manure application rates. Tied contours, 15 t ha-1 cattle manure and Macia variety are potential strategy to achieve climate smart agriculture and improve food security in semi-arid areas. Sorghum production in marginalised areas can be productive with adoption of tested techniques.
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The Woven EndoBridge (WEB) and other intrasaccular flow disruptors show promise in treating intracranial aneurysms. We performed a bibliometric analysis to provide novel insights into the trends and trajectory of these devices. We systematically assessed bibliometric data such as citations, journals, study designs, open access status, and multi-institutional involvement for the top-cited articles on WEB and other disruptors. The top 100 cited studies on the WEB had citations from 7 to 144 (mean ± standard deviation 35.6 ± 29.5), while only 33 studies were published for other intrasaccular flow disruptors (4.24 ± 8.45). Of the other devices, the Contour has the most publications (n = 21). Retrospective reviews were the most common study design for both WEB and other intrasaccular devices. France published the most studies in the top 100 WEB papers (n = 35), while Germany led for other flow disruptors (n = 10). In all studies analyzed, no senior authors from Africa are present. The top 100 WEB publications had a higher mean citation count (35.6 vs. 4.24, P<0.001), higher mean citations per year (5.24 vs. 1.03, P<0.01), and a higher proportion of multi-institutional collaborations (44.0% vs. 12.1%, P<0.01) than other intrasaccular flow disruptors. In conclusion, countries with the most publications on WEB are not necessarily the ones leading the way with newer intrasaccular devices, while study designs remain similar. There is a limited contribution to the literature outside of Europe and North America. Our findings identify notable collaborators and trends, providing a snapshot of the field and a roadmap for future research.
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PURPOSE: To analyze the upper eyelid contour after Müller's muscle conjunctiva resection (MMCR) performed by four different surgeons. METHODS: Comparative cross-sectional analysis of the pre- and postoperative contours of a control group and four groups of upper lids (n = 88) of 65 patients who underwent MMCR at four international centers. The procedure employed was essentially the same as described by Putterman but performed with different instruments to entrap the posterior lamella. Multiple medial and lateral margin lid distances were measured on Bézier lines expressing the pre- and postoperative lid contours. RESULTS: Preoperatively, two groups had significant lateral and medial ptosis. After MMCR, the lateral segment of the lid's contour was corrected in all groups. In the two groups with more pronounced ptosis, the nasal lid contour was undercorrected. CONCLUSIONS: In MMCR, regardless of the instrument used to entrap the posterior lamella, the amount of medial tissue resection is essential to avoid postoperative nasal undercorrection. LEVEL OF EVIDENCE III: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .
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Objective.Online adaptive radiation therapy requires fast and automated contouring of daily scans for treatment plan re-optimization. However, automated contouring is imperfect and introduces contour uncertainties. This work aims at developing and comparing robust optimization strategies accounting for such uncertainties.Approach.A deep-learning method was used to predict the uncertainty of deformable image registration, and to generate a finite set of daily contour samples. Ten optimization strategies were compared: two baseline methods, five methods that convert contour samples into voxel-wise probabilities, and three methods accounting explicitly for contour samples as scenarios in robust optimization. Target coverage and organ-at-risk (OAR) sparing were evaluated robustly for simplified proton therapy plans for five head-and-neck cancer patients.Results.We found that explicitly including target contour uncertainty in robust optimization provides robust target coverage with better OAR sparing than the baseline methods, without increasing the optimization time. Although OAR doses first increased when increasing target robustness, this effect could be prevented by additionally including robustness to OAR contour uncertainty. Compared to the probability-based methods, the scenario-based methods spared the OARs more, but increased integral dose and required more computation time.Significance.This work proposed efficient and beneficial strategies to mitigate contour uncertainty in treatment plan optimization. This facilitates the adoption of automatic contouring in online adaptive radiation therapy and, more generally, enables mitigation also of other sources of contour uncertainty in treatment planning.
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Neoplasias de Cabeça e Pescoço , Órgãos em Risco , Planejamento da Radioterapia Assistida por Computador , Incerteza , Planejamento da Radioterapia Assistida por Computador/métodos , Humanos , Neoplasias de Cabeça e Pescoço/radioterapia , Órgãos em Risco/efeitos da radiação , Terapia com Prótons/métodos , Dosagem Radioterapêutica , Aprendizado Profundo , Processamento de Imagem Assistida por Computador/métodosRESUMO
Objective: To evaluate the accuracy of non-calibrated multi-beat analysis continuous cardiac output (CCOMBA), against calibrated pulse-contour analysis continuous cardiac output (CCOPCA) during a passive leg raise (PLR) and/or a fluid challenge (FC). Design: Observational, single-centre, prospective study. Setting: Tertiary academic medical intensive care unit, Lyon, France. Participants: Adult patients receiving norepinephrine, monitored by CCOPCA, and in which a PLR and/or a FC was indicated. Main outcome measures: CCOMBA and CCOPCA were recorded prior to and during the PLR/FC to evaluate bias and evaluate changes in CCOMBA and CCOPCA (∆%CCOMBA and ∆%CCOPCA). Fluid responsiveness was identified by an increase >15% in calibrated cardiac output after FC, to identify the optimal ∆%CCOMBA threshold during PLR to predict fluid responsiveness. Results: 29 patients (median age 68 [IQR: 57-74]) performed 28 PLR and 16 FC. The bias between methods increased with higher CCOPCA values, with a percentage error of 64% (95%confidence interval: 52%-77%). ∆%CCOMBA adequately tracked changes in ∆%CCOPCA with an angular bias of 2 ± 29°. ∆%CCOMBA during PLR had an AUROC of 0.92 (P < 0.05), with an optimal threshold >14% to predict fluid responsiveness (sensitivity: 0.99, specificity: 0.87). Conclusions: CCOMBA showed a non-constant bias and a percentage error >30% against calibrated CCOPCA, but an adequate ability to track changes in CCOPCA and to predict fluid responsiveness.
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OBJECTIVE: The aim of this study was to further guide the diagnosis and treatment programs for clinical facial contouring with injectable fillers by studying the facial contour parameters and proportion preferences consistent with Asian aesthetics. METHODS: A total of 89 subjects (42 males and 47 females aged 20-60 years) who met the inclusion criteria were enrolled in this study. The subjects were grouped by age, sex, and external contour attractiveness score, and the external contour aesthetic parameters and proportions of the subjects in different groups were measured and analysed. RESULTS: The upper facial breadth and lower facial breadth decreased with age, with significant differences between the 50-60-year age group and other age groups (P < 0.01). The nasomental angle showed a decreasing trend with age, with significant differences between the 40-49-year age group and the 20-29-year and 30-39-year age groups (P < 0.05). Males and females were significantly different in calva height, total head height, lower facial height, and calva height to total head height ratio (P < 0.05). With increasing age, the external contour attractiveness scores of males and females both showed decreasing trends, with significant differences between the 50-60-year age group and other age groups (P < 0.05). CONCLUSION: The calva height and the cranioauricular angle have a significant impact on external contour attractiveness. In general, temporal depression, cheek sagging, lateral cheek depression, and an ill-defined mandibular border will occur due to ageing, collagen loss, ligament laxity and sagging, and soft tissue atrophy and sagging, reducing the attractiveness of the external contour. LEVEL OF EVIDENCE IV: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .
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Purpose: Image registration is a crucial component of the adaptive radiotherapy workflow. This study investigates the accuracy of the deformable image registration (DIR) and contour propagation features of SmartAdapt, an application in the Eclipse treatment planning system (TPS) version 16.1. Materials and Methods: The registration accuracy was validated using the Task Group No. 132 (TG-132) virtual phantom, which features contour evaluation and landmark analysis based on the quantitative criteria recommended in the American Association of Physicists in Medicine TG-132 report. The target registration error, Dice similarity coefficient (DSC), and center of mass displacement were used as quantitative validation metrics. The performance of the contour propagation feature was evaluated using clinical datasets (head and neck, pelvis, and chest) and an additional four-dimensional computed tomography (CT) dataset from TG-132. The primary planning and the second CT images were appropriately registered and deformed. The DSC was used to find the volume overlapping between the deformed contours and the radiation oncologist (RO)-drawn contour. The clinical value of the DIR-generated structure was reviewed and scored by an experienced RO to make a qualitative assessment. Results: The registration accuracy fell within the specified tolerances. SmartAdapt exhibited a reasonably propagated contour for the chest and head-and-neck regions, with DSC values of 0.80 for organs at risk. Misregistration is frequently observed in the pelvic region, which is specified as a low-contrast region. However, 78% of structures required no modification or minor modification, demonstrating good agreement between contour comparison and the qualitative analysis. Conclusions: SmartAdapt has adequate efficiency for image registration and contour propagation for adaptive purposes in various anatomical sites. However, there should be concern about its performance in regions with low contrast and small volumes.
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BACKGROUND: Masseter muscle hypertrophy is characterized by a symmetrical or asymmetrical increase in muscle volume. Although it can be asymptomatic, it may be associated with bruxism. Therefore, patients may seek intervention for esthetic and/or functional concerns. This study aimed to establish patient characteristics, purpose of undergoing botulinum toxin injection into the masseter muscles, efficacy, and side effects of the procedure at a dermatology clinic. METHODS: A retrospective chart review was carried out over a period of one year from January 2022 to January 2023 for the patients who underwent botulinum toxin injection into the masseter muscles. The general characteristics of patients, the purpose of botulinum toxin treatment, relief levels regarding bruxism according to the Visual Analog Scale (VAS), side effects, and complications were recorded. RESULTS: The study group comprised 74 female and 6 male patients with a mean age of 31.20 ± 6.71 years. Eighteen (22.5%) patients were treated only for narrowing the lower face contour, 28 (35%) patients were treated only for the relief of bruxism, and 34 (42.5%) patients were treated for both indications. Fifteen (18.8%) patients experienced 16 treatment-related side effects, including two (2.5%) with smile asymmetry and two (2.5%) with paradoxical bulging. CONCLUSIONS: Botulinum toxin injection into the masseter muscles with the intention of lower face contouring and/or relieving bruxism offers a minimally invasive, safe, and effective treatment option. Although it has a favorable safety profile, the risks of significant side effects or complications remain.
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Aiming at the problems of the poor robustness and universality of traditional contour matching algorithms in engineering applications, a method for improving the surface defect detection of industrial products based on contour matching algorithms is detailed in this paper. Based on the image pyramid optimization method, a three-level matching method is designed, which can quickly obtain the candidate pose of the target contour at the top of the image pyramid, combining the integral graph and the integration graph acceleration strategy based on weak classification. It can quickly obtain the rough positioning and rough angle of the target contour, which greatly improves the performance of the algorithm. In addition, to solve the problem that a large number of duplicate candidate points will be generated when the target candidate points are expanded, a method to obtain the optimal candidate points in the neighborhood of the target candidate points is designed, which can guarantee the matching accuracy and greatly reduce the calculation amount. In order to verify the effectiveness of the algorithm, functional test experiments were designed for template building function and contour matching function, including uniform illumination condition, nonlinear condition and contour matching detection under different conditions. The results show that: (1) Under uniform illumination conditions, the detection accuracy can be maintained at about 93%. (2) Under nonlinear illumination conditions, the detection accuracy can be maintained at about 91.84%. (3) When there is an external interference source, there will be a false detection or no detection, and the overall defect detection rate remains above 94%. It is verified that the proposed method can meet the application requirements of common defect detection, and has good robustness and meets the expected functional requirements of the algorithm, providing a strong technical guarantee and data support for the design of embedded image sensors in the later stage.
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In most silent speech research, continuously observing tongue movements is crucial, thus requiring the use of ultrasound to extract tongue contours. Precisely and in real-time extracting ultrasonic tongue contours presents a major challenge. To tackle this challenge, the novel end-to-end lightweight network DAFT-Net is introduced for ultrasonic tongue contour extraction. Integrating the Convolutional Block Attention Module (CBAM) and Attention Gate (AG) module with entropy-based optimization strategies, DAFT-Net establishes a comprehensive attention mechanism with dual functionality. This innovative approach enhances feature representation by replacing traditional skip connection architecture, thus leveraging entropy and information-theoretic measures to ensure efficient and precise feature selection. Additionally, the U-Net's encoder and decoder layers have been streamlined to reduce computational demands. This process is further supported by information theory, thus guiding the reduction without compromising the network's ability to capture and utilize critical information. Ablation studies confirm the efficacy of the integrated attention module and its components. The comparative analysis of the NS, TGU, and TIMIT datasets shows that DAFT-Net efficiently extracts relevant features, and it significantly reduces extraction time. These findings demonstrate the practical advantages of applying entropy and information theory principles. This approach improves the performance of medical image segmentation networks, thus paving the way for real-world applications.
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Purpose: This study aimed to propose a fully automatic eyelid measurement system and compare the contours of both the upper and lower eyelids of normal individuals according to age and gender. Design: Prospective study. Participants: Five hundred and forty healthy Chinese aged 0 to 79 years in a tertiary hospital were included. Methods: Facial images in the primary gazing position were used to train and test the proposed automatic system for eye recognition and eye segmentation. According to the 10-millimeter diameter circular marker, measurements were transformed from pixel sizes into factual distances. Main Outcome Measures: Midpupil lid distances (MPLDs) every 15° of all participants were automatically measured in both genders (30 males and 30 females in each age group) by the proposed deep learning (DL)-based system. Intraclass correlation coefficients (ICCs) were performed to assess the agreement between the automatic and manual margin reflex distances (MRDs). The eyelid contour, eyelid asymmetry, and palpebral fissure obliquity were analyzed using MPLD, temporal-versus-nasal MPLD ratio, and the angle between the inner and outer canthi, respectively. Results: The measurement of MRDs by the automatic system excellently agreed with that of the expert, with ICCs ranging from 0.863 to 0.886. As the age of the participants increased, the values of MPLDs reached a peak in those in their 20s or 30s and then gradually decreased at all angles. The temporal sector showed greater changes in MPLDs than the nasal sector, and the changes were more significant in females than in males. The maximum value of palpebral fissure obliquity appeared before 10 years in both genders and remained relatively stable after the 20s (P > 0.05). Conclusions: The proposed DL-based eyelid analysis system allowed automatic, accurate, and comprehensive measurement of the eyelid contour. The refinement of eyelid shape quantification could be beneficial for future objective assessment preocular and postocular plastic surgery. Financial Disclosures: The authors have no proprietary or commercial interest in any materials discussed in this article.