A deep learning approach for fast muscle water T2 mapping with subject specific fat T2 calibration from multi-spin-echo acquisitions.

This work presents a deep learning approach for rapid and accurate muscle water T2 with subject-specific fat T2 calibration using multi-spin-echo acquisitions. This method addresses the computational limitations of conventional bi-component Extended Phase Graph fitting methods (nonlinear-least-squares and dictionary-based) by leveraging fully connected neural networks for fast processing with minimal computational resources. We validated the approach through in vivo experiments using two different MRI vendors. The results showed strong agreement of our deep learning approach with reference methods, summarized by Lin's concordance correlation coefficients ranging from 0.89 to 0.97. Further, the deep learning method achieved a significant computational time improvement, processing data 116 and 33 times faster than the nonlinear least squares and dictionary methods, respectively. In conclusion, the proposed approach demonstrated significant time and resource efficiency improvements over conventional methods while maintaining similar accuracy. This methodology makes the processing of water T2 data faster and easier for the user and will facilitate the utilization of the use of a quantitative water T2 map of muscle in clinical and research studies.

Revision of the muscular system in the brachiopod Novocrania anomala using 3D reconstruction: Functional and paleontological significance.

The musculature is one of the best studied organ systems in brachiopods, being approachable not only by dissecting recent species of brachiopods, but also by exploring muscle scars in fossil material. In the present study, the muscular anatomy of Novocrania anomala is studied using 3D reconstructions based on microcomputed tomography. Muscles of N. anomala may be subdivided into two groups: those related to movements of the lophophore, and those connected to movements of shell valves. Muscles, their morphology and possible functions, such as brachial protractors, elevators, and retractors, as well as anterior adductors, are described and discussed. We also provide the discussion of craniid muscle terminology, consider the valve-opening mechanism. The investigation of muscle scars on dorsal valves supports the conclusion that the shape of muscle scars should be used for description and distinction of recent and extinct species only when visible distinctness cannot be explained by substrate differences. This study, which is aimed at improving our understanding the anatomy and functioning of muscles in craniids, will be useful not only for zoologists, but also for paleontologists.

Visible spectroscopy on lamb fat and muscle to authenticate the duration of pasture finishing.

Pasture-based livestock systems are considered environmentally-sustainable and welfare-friendly farming systems that can meet consumer demand for good-quality produce. However, trust in products labelled as 'grass-fed' depends on the ability to reliably authenticate pasture origin. The two objectives of this study were (i) to test the ability of visible spectroscopy combined with discriminant analysis on lamb perirenal fat (PF), dorsal fat (DF) and longissimus thoracis et lumborum muscle to discriminate different durations of pasture-finishing; and (ii) to determine the timing of appearance of the pasture signature and its stabilization in these tissues. Four groups of 35 lambs were used over two years, i.e. lambs fed concentrate in-stall (L0) and lambs grazing alfalfa for 21d (L21), 42d (L42) and 63d (L63) before slaughter. No one tissue satisfactorily discriminated the four treatment groups, with ≤75% of lambs correctly classified. However, visible spectroscopy discriminated L0 from L21 + L42 + L63 lambs with an accuracy of 92.8%, 92.0%, and 85.3% lambs correctly classified on PF, DF and muscle, respectively, and discriminated L0 + L21 from L42 + L63 lambs with an accuracy of 90.1%, 76.5% and 92.3% on PF, DF and muscle, respectively. The pasture fingerprint or signature on the spectrum appeared in most lambs between 0 and 21d in PF and DF and between 0 and 42d in muscle. Pasture signature gradually stabilized with increasing time on pasture but was not entirely stabilized in any tissue within the range of grazing durations explored. These promising results need to be confirmed on larger datasets with different breeds and grazing conditions.

Hyperspectral imaging of lipids in biological tissues using near-infrared and shortwave infrared transmission mode: A pilot study.

Label-free hyperspectral imaging (HSI) of lipids was demonstrated in the near-infrared (NIR) and shortwave infrared (SWIR) regions (950-1800 nm) using porcine tissue. HSI was performed in the transmission light-pass configuration, using a NIR-SWIR camera coupled with a liquid crystal tunable filter. The transmittance spectra of the regions of interest (ROIs), which correspond to the lipid and muscle areas in the specimen, were utilized for the spectrum unmixing. The transmittance spectra in ROIs were compared with those recorded by a spectrophotometer using samples of adipose and muscle. The lipid optical absorption bands at 1210 and 1730 nm were first used for the unmixing and mapping. Then, we performed the continuous multiband unmixing over the entire available spectral range, thereby, considering a combination of characteristic absorption bands of lipids, proteins, and water. The enhanced protocol demonstrates the ability to visualize small adipose inclusions of 1-10 µm size.

[Ultrasound in the assessment of muscle mass. The GLIM (Global Leadership Initiative on Malnutrition) criteria called into question (I)]. / Ecografía en la valoración de la masa muscular. Criterios GLIM (Global Leadership Initiative on Malnutrition) a cuestión (I).

Introduction: Ultrasound in the assessment of muscle mass. The GLIM (Global Leadership Initiative on Malnutrition) criteria called into question (I).

Introducción: Ecografía en la valoración de la masa muscular. Criterios GLIM (Global Leadership Initiative on Malnutrition) a cuestión (I).

[Ultrasound in the assessment of muscle mass. The GLIM (Global Leadership Initiative on Malnutrition) criteria called into question (II)]. / Ecografía en la valoración de la masa muscular. Criterios GLIM (Global Leadership Initiative on Malnutrition) a cuestión (II).

Introduction: Ultrasound in the assessment of muscle mass. The GLIM (Global Leadership Initiative on Malnutrition) criteria called into question (II).

Introducción: Ecografía en la valoración de la masa muscular. Criterios GLIM (Global Leadership Initiative on Malnutrition) a cuestión (II).

Predicting muscle invasion in bladder cancer based on MRI: A comparison of radiomics, and single-task and multi-task deep learning.

BACKGROUND AND OBJECTIVES: Radiomics and deep learning are two popular technologies used to develop computer-aided detection and diagnosis schemes for analysing medical images. This study aimed to compare the effectiveness of radiomics, single-task deep learning (DL) and multi-task DL methods in predicting muscle-invasive bladder cancer (MIBC) status based on T2-weighted imaging (T2WI). METHODS: A total of 121 tumours (93 for training, from Centre 1; 28 for testing, from Centre 2) were included. MIBC was confirmed with pathological examination. A radiomics model, a single-task model, and a multi-task model based on T2WI were constructed in the training cohort with five-fold cross-validation, and validation was conducted in the external test cohort. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance of each model. DeLong's test and a permutation test were used to compare the performance of the models. RESULTS: The area under the ROC curve (AUC) values of the radiomics, single-task and multi-task models in the training cohort were: 0.920, 0.933 and 0.932, respectively; and were 0.844, 0.884 and 0.932, respectively, in the test cohort. The multi-task model achieved better performance in the test cohort than did the other models. No statistically significant differences in AUC values and Kappa coefficients were observed between pairwise models, in either the training or test cohorts. According to the Grad-CAM feature visualization results, the multi-task model focused more on the diseased tissue area in some samples of the test cohort compared with the single-task model. CONCLUSIONS: The T2WI-based radiomics, single-task, and multi-task models all exhibited good diagnostic performance in preoperatively predicting MIBC, in which the multi-task model had the best diagnostic performance. Compared with the radiomics method, our multi-task DL method had the advantage of saving time and effort. Compared with the single-task DL method, our multi-task DL method had the advantage of being more lesion-focused and more reliable for clinical reference.

Assisted annotation in Deep LOGISMOS: Simultaneous multi-compartment 3D MRI segmentation of calf muscles.

BACKGROUND: Automated segmentation of individual calf muscle compartments in 3D MR images is gaining importance in diagnosing muscle disease, monitoring its progression, and prediction of the disease course. Although deep convolutional neural networks have ushered in a revolution in medical image segmentation, achieving clinically acceptable results is a challenging task and the availability of sufficiently large annotated datasets still limits their applicability. PURPOSE: In this paper, we present a novel approach combing deep learning and graph optimization in the paradigm of assisted annotation for solving general segmentation problems in 3D, 4D, and generally n-D with limited annotation cost. METHODS: Deep LOGISMOS combines deep-learning-based pre-segmentation of objects of interest provided by our convolutional neural network, FilterNet+, and our 3D multi-objects LOGISMOS framework (layered optimal graph image segmentation of multiple objects and surfaces) that uses newly designed trainable machine-learned cost functions. In the paradigm of assisted annotation, multi-object JEI for efficient editing of automated Deep LOGISMOS segmentation was employed to form a new larger training set with significant decrease of manual tracing effort. RESULTS: We have evaluated our method on 350 lower leg (left/right) T1-weighted MR images from 93 subjects (47 healthy, 46 patients with muscular morbidity) by fourfold cross-validation. Compared with the fully manual annotation approach, the annotation cost with assisted annotation is reduced by 95%, from 8 h to 25 min in this study. The experimental results showed average Dice similarity coefficient (DSC) of 96.56 ± 0.26 % $96.56\pm 0.26 \%$ and average absolute surface positioning error of 0.63 pixels (0.44 mm) for the five 3D muscle compartments for each leg. These results significantly improve our previously reported method and outperform the state-of-the-art nnUNet method. CONCLUSIONS: Our proposed approach can not only dramatically reduce the expert's annotation efforts but also significantly improve the segmentation performance compared to the state-of-the-art nnUNet method. The notable performance improvements suggest the clinical-use potential of our new fully automated simultaneous segmentation of calf muscle compartments.

Panoramic ultrasound imaging does not produce muscle morphology deformation during imaging acquisition: A validity study.

PURPOSE: Despite panoramic ultrasound imaging (US) is a promising advance for the morphological and histological assessment of large musculature which cannot be entirely assessed using B-mode, there is no evidence assessing if this technology produces muscle deformation during imaging acquisition. We aimed to analyze differences in size, shape and brightness descriptors between B-mode and panoramic US images and to assess the concordance between both methods. Methods We analyzed size (cross-sectional area and perimeter), shape (circularity, aspect ratio and roundness) and brightness (mean echo-intensity) features of cervical multifidus (CM) and short rotators (SR) in 46 healthy volunteers. Images were acquired in B-mode and extended field-of-view mode. For validity analysis, mean differences between methods were calculated. For agreement analysis, intraclass correlation coefficients (ICCs), standard error of measurements (SEM), minimal detectable changes (MDC) and coefficient of variation (CV%) were calculated. RESULTS: All parameters showed no significant differences between both methods for either CM or SR (P > 0.05). Panoramic US showed excellent concordance with B-mode for assessing all CM parameters (all ICCs > 0.9), while for SR the agreement ranged from good-to-excellent (ICC from 0.861 to 0.978). CONCLUSION: Panoramic US seems to be a valid tool for assessment of muscle size, shape and brightness as no deformation in comparison with B-mode images was seen. Further research is needed to corroborate these findings comparing panoramic US imaging with Gold Standard methods.

Ultrasonographic monitoring of feline epaxial muscle height as part of an annual wellness examination to assess for the development of sarcopenia.

OBJECTIVES: The aim of this study was to determine if epaxial muscle height (EMH) could be reliably incorporated into annual routine wellness screenings, and also determine its relationship to age, body condition score (BCS), subjective muscle assessment (SMA), breed and sex in mature cats. METHODS: EMH was determined independently by three observers from ultrasonographic examinations - collected by an additional trained individual - of cats enrolled at the Feline Healthy Ageing Clinic, University of Liverpool, UK. Age, body weight, BCS and SMA data were also collected. RESULTS: A total of 92 cats were included, 35 of which had repeat ultrasonographic examinations 12 months apart. Enrolled cats were a median age of 8 years and 9 months at the time of the first measurement. Variation in the quality of ultrasonographic images collected did not affect muscle depth measurements (P = 0.974). Further, there was good intra- and inter-observer repeatability for all observations (intraclass correlation range 0.97-0.99). There was a moderate positive association between EMH and body weight (r = 0.49, P <0.001) but no association with age (r = -0.05, P = 0.680). There were also positive associations in EMH among cats with different BCSs (P = 0.001) and SMAs (thoracic spine, P = 0.021; lumbar spine, P = 0.014), but breed (P = 0.429) and sex (P = 0.187) had no effect. Finally, there was no change in EMH measurements in the paired samples (P = 0.145) or correlation between percentage weight and EMH change over 12 months. CONCLUSIONS AND RELEVANCE: The accuracy of EMH measurement using ultrasonographic imaging is good, irrespective of observer experience and provided that the ultrasonographer has some training. This suggests that ultrasonographic measurement of EMH could have a major practical impact as a non-invasive determination of muscle mass in pet cat populations. Further research is required to assess longitudinal changes in muscle mass over time in senior pet cats.

Comparison between biparametric and multiparametric MRI in predicting muscle invasion by bladder cancer based on the VI-RADS.

This study aimed to compare the diagnostic validity of biparametric magnetic resonance imaging (bpMRI) with that of multiparametric MRI (mpMRI) based on the Vesicle Imaging-Reporting and Data System (VI-RADS) in predicting muscle invasion by bladder cancer (BCa). We retrospectively examined 357 patients with an initial diagnosis of BCa who underwent preoperative MRI; 257 and 100 patients underwent mpMRI and bpMRI, respectively. Two urogenital radiologists evaluated all bpMRI and mpMRI scans using VI-RADS, and the diagnostic validity of VI-RADS for predicting muscle invasion by BCa was analyzed based on histopathology of the first and/or second transurethral resection of bladder tumors and radical cystectomy. Receiver operating characteristic (ROC) curves were plotted with the calculation of area under the curves (AUCs), and the level of significance was P < 0.05. Both groups showed optimal performance with a VI-RADS score ≥ 3. BpMRI showed comparable diagnostic performance to mpMRI (reader 1: AUC, 0.903 [0.827-0.954] vs. 0.935 [0.884-0.968], p = 0.510; and reader 2: AUC, 0.901 [0.814-0.945] vs. 0.915 [0.874-0.946]; p = 0.655). The inter-reader agreement between both readers was excellent (Cohen's kappa value = 0.942 and 0.905 for bpMRI and mpMRI, respectively). This comparative study suggests that bpMRI has comparable diagnostic performance to mpMRI and may be an alternative option to predict muscle invasion by BCa.

The ant abdomen: The skeletomuscular and soft tissue anatomy of Amblyopone australis workers (Hymenoptera: Formicidae).

Recent studies of insect anatomy evince a trend towards a comprehensive and integrative investigation of individual traits and their evolutionary relationships. The abdomen of ants, however, remains critically understudied. To address this shortcoming, we describe the abdominal anatomy of Amblyopone australis Erichson, using a multimodal approach combining manual dissection, histology, and microcomputed tomography. We focus on skeletomusculature, but additionally describe the metapleural and metasomal exocrine glands, and the morphology of the circulatory, digestive, reproductive, and nervous systems. We describe the muscles of the dorsal vessel and the ducts of the venom and Dufour's gland, and characterize the visceral anal musculature. Through comparison with other major ant lineages, apoid wasps, and other hymenopteran outgroups, we provide a first approximation of the complete abdominal skeletomuscular groundplan in Formicidae, with a nomenclatural schema generally applicable to the hexapod abdomen. All skeletal muscles were identifiable with their homologs, while we observe potential apomorphies in the pregenital skeleton and the sting musculature. Specifically, we propose the eighth coxocoxal muscle as an ant synapomorphy; we consider possible transformation series contributing to the distribution of states of the sternal apodemes in ants, Hymenoptera, and Hexapoda; and we address the possibly synapomorphic loss of the seventh sternal-eighth gonapophyseal muscles in the vespiform Aculeata. We homologize the ovipositor muscles across Hymenoptera, and summarize demonstrated and hypothetical muscle functions across the abdomen. We also give a new interpretation of the proximal processes of gonapophyses VIII and the ventromedial processes of gonocoxites IX, and make nomenclatural suggestions in the context of evolutionary anatomy and ontology. Finally, we discuss the utility of techniques applied and emphasize the value of primary anatomical research.

Comparison of cross-sectional area and fat infiltration of suboccipital muscles between normal dogs and dogs with atlantoaxial instability.

BACKGROUND: Atlantoaxial instability (AAI) is primarily a congenital neurological disorder affecting young toy-breed dogs. So far, most studies have focused on bones and ligaments related to AAI, and there are no studies on the suboccipital muscles (SOMs) that occupy a large area from the occipital bone to C2 in dogs. This study evaluated the cross-sectional area (CSA) and fat infiltration of the SOMs using magnetic resonance imaging (MRI), specifically, T1-weighted images, in normal dogs (≤ 5 kg) and AAI dogs. The relationship between the severity of the neurological symptoms of AAI (group A and group B) and the values from MRI was also assessed. RESULTS: AAI dogs had significantly smaller CSA (P = 0.029) and greater fat infiltration (P = 0.044) of the SOMs compared to normal dogs. AAI dogs with mild neurological symptoms for a long period (group A) had greater fat infiltration than AAI dogs with severe neurological symptoms (group B) (P = 0.035). CONCLUSIONS: The muscle changes are most likely due to spinal cord compression resulting from instability; however, the possibility that chronic changes of the muscle may play an additional role in maintaining stability in this region cannot be excluded. This study provides fundamental quantitative information of the SOMs in normal and AAI dogs.

CT-based radiomics to predict muscle invasion in bladder cancer.

OBJECTIVES: This study investigated the feasibility of a computed tomography (CT)-based radiomics prediction model to evaluate muscle invasive status in bladder cancer. METHODS: Patients who underwent CT urography at two medical centers from October 2014 to May 2020 and had bladder urothelial carcinoma confirmed by postoperative histopathology were retrospectively enrolled. In total, 441 cases were collected and randomized into a training cohort (n = 293), an internal testing cohort (n = 73), and an external testing cohort (n = 75). The images were first filtered, and then, 1218 features were extracted. The best features related to muscle invasiveness of bladder cancer were identified by ANOVA. A prediction model was built by using the logistic regression method. Statistical analysis was performed by plotting the receiver operating characteristic curve. Indicators of the diagnostic performance of the prediction model, including sensitivity, specificity, accuracy, and area under curve (AUC), were evaluated. RESULTS: In the training, internal testing, and external testing cohorts, the prediction model diagnosed muscle-invasive bladder cancer with AUCs of 0.885 (95% confidence interval [95% CI] 0.841-0.929), 0.820 (95% CI 0.698-0.941), and 0.784 (95% CI 0.674-0.893), respectively. In the internal testing cohort, the sensitivity, specificity, and accuracy of the model were 0.667 (95% CI 0.387-0.870), 0.845 (95% CI 0.721-0.922), and 0.782 (95% CI 0.729-0.827), respectively. In the external testing cohort, the sensitivity, specificity, and accuracy of the model were 0.742 (95% CI 0.551-0.873), 0.750 (95% CI 0.594-0.863), and 0.782 (95% CI 0.729-0.827), respectively. CONCLUSIONS: CT-based radiomics prediction model can evaluate muscle invasiveness of bladder cancer before surgery with a good diagnostic performance. KEY POINTS: • CT-based radiomics model can evaluate muscle invasive status in bladder cancer. • The radiomics model shows good diagnostic performance to differentiate muscle-invasive bladder cancer from non-muscle-invasive bladder cancer. • This preoperative CT-based prediction method might complement MR evaluation of bladder cancer and supplement biopsy.

Case Report: Disseminated Cysticercosis due to Intentional Ingestion of Parasitic Worm Eggs for Weight Loss.

A 20-year-old female resident of Beijing intended to consume the eggs of the parasitic worm, Taenia saginata, for weight loss; however, she apparently inadvertently ingested Taenia solium (pork tapeworm) eggs, which resulted in disseminated cysticercosis. Cysticerci developed in the brain, tongue, muscles, liver, peritoneum, and subcutaneous tissues. She was administered oral albendazole and praziquantel. After four 10-day courses of treatment, most of the cysts disappeared and she recovered. After 3 years, the patient remains in good health.

A novel parameter derived from post-processing procedure of dual energy CT for identification of gout.

ROI analysis is frequently used for obtaining acid content on rapid-kV-switching dual energy CT (DECT), providing inadequate accuracy. A new parameter derived from post-processing procedure, maximum lower limit with stain visible (MLLSV), was used by us to diagnose gout. 30 gout patients and 20 healthy volunteers were analyzed by using MLLSV. MLLSV was defined as the maximum lower limit of display window allowing only one stained site visible. Radiologists were asked to continuously increase the lower limit of display window of uric acid to decrease number of stained sites until the last stained site disappeared. MLLSV obtained by this way was compared between gout patients and volunteers. Receiver operating characteristic (ROC) curve was used to determine the performance. MLLSV of gout patients was significantly higher than that of volunteers (1373.3 ± 23.0 mg/cm3 vs. 1315.4 ± 20.7 mg/cm3, p = 0.000). The area under ROC curve of MLLSV was 0.993 in identifying gout. When using the optimal cutoff of 1342 mg/cm3, the sensitivity and specificity of MLLSV in identification of gout were 96.7% and 95% respectively. MLLSV derived from post-processing procedure of DECT is useful in discriminating gout patients from healthy people.

Assessment of flow within developing chicken vasculature and biofabricated vascularized tissues using multimodal imaging techniques.

Fluid flow shear stresses are strong regulators for directing the organization of vascular networks. Knowledge of structural and flow dynamics information within complex vasculature is essential for tuning the vascular organization within engineered tissues, by manipulating flows. However, reported investigations of vascular organization and their associated flow dynamics within complex vasculature over time are limited, due to limitations in the available physiological pre-clinical models, and the optical inaccessibility and aseptic nature of these models. Here, we developed laser speckle contrast imaging (LSCI) and side-stream dark field microscopy (SDF) systems to map the vascular organization, spatio-temporal blood flow fluctuations as well as erythrocytes movements within individual blood vessels of developing chick embryo, cultured within an artificial eggshell system. By combining imaging data and computational simulations, we estimated fluid flow shear stresses within multiscale vasculature of varying complexity. Furthermore, we demonstrated the LSCI compatibility with bioengineered perfusable muscle tissue constructs, fabricated via molding techniques. The presented application of LSCI and SDF on perfusable tissues enables us to study the flow perfusion effects in a non-invasive fashion. The gained knowledge can help to use fluid perfusion in order to tune and control multiscale vascular organization within engineered tissues.

Analysis of ultrasound image biological image algorithm in the restoration of muscle group movement function / Análise do algoritmo de imagem biológica por ultrassom na restauração da função de movimento do grupo muscular / Análisis del algoritmo de imágenes biológicas de imágenes de ultrasonido en la restauración de la función de movimiento del grupo muscular

ABSTRACT Objective: By studying the recognition effect of ultrasonic biological image data analysis on muscle group motion function, the evaluation value and significance of ultrasonic biomedical image combination algorithm on muscle group motion function are discussed. Methods: A Gabor filtering algorithm is proposed to smooth the original image. The MVEF algorithm is used to enhance the ultrasonic image and binary further the image again. Using the principle of the Hove transform, the thickness of the muscle is automatically estimated. Results: The square of correlation coefficients of the manual measurement method, Gabor filtering algorithm and MVEF algorithm are 91.3%, 91.3% and 87.8%, respectively. The difference between the manual measurement and the estimation based on the Gabor filtering algorithm is 1.45 ± 0.48mm. The difference between the results of manual measurement and the MVEF algorithm is 1.38 ± 0.56mm. The computation time of the MVEF algorithm and Gabor algorithm are 5 seconds and 0.3 seconds, respectively. Conclusions: The algorithm proposed in this study can effectively measure the muscle thickness, fast, convenient and accurate, and can reflect the contractility of skeletal muscle well, which is of great value for the recognition and evaluation of muscle group movement function. Level of evidence II; Therapeutic studies - investigation of treatment results.

RESUMO Objetivo: Ao estudar o efeito de reconhecimento da análise de dados de imagem biológica ultrassônica na função de movimento do grupo muscular, o valor de avaliação e a importância do algoritmo de combinação de imagem biomédica ultrassônica na função de movimento do grupo muscular são discutidos. Métodos: Um algoritmo de filtragem Gabor é proposto para suavizar a imagem original. O algoritmo MVEF é usado para aprimorar ainda mais a imagem ultrassônica e binar a imagem novamente. Usando o princípio da transformada de H ove, a espessura do músculo é automaticamente estimada. Resultados: O quadrado dos coeficientes de correlação do método de medição manual, algoritmo de filtragem Gabor e algoritmo MVEF são 91,3%, 91,3% e 87,8%, respectivamente. A diferença entre a medição manual e a estimativa baseada no algoritmo de filtragem Gabor é 1,45 ± 0,48 mm. A diferença entre os resultados da medição manual e o algoritmo MVEF é de 1,38 ± 0,56 mm. O tempo de cálculo do algoritmo MVEF e do algoritmo Gabor é de 5 segundos e 0,3 segundos, respectivamente. Conclusões: O algoritmo proposto neste estudo pode medir efetivamente a espessura muscular, de forma rápida, conveniente e precisa, e pode refletir bem a contratilidade do músculo esquelético, o que é de grande valor para o reconhecimento e avaliação da função de movimento do grupo muscular. Nível de evidência II; Estudos terapêuticos- investigação dos resultados do tratamento.

RESUMEN Objetivo: Al estudiar el efecto de reconocimiento del análisis de datos de imágenes biológicas ultrasónicas sobre la función del movimiento del grupo muscular, se discuten el valor de evaluación y la importancia del algoritmo de combinación de imágenes biomédicas ultrasónicas sobre la función del movimiento del grupo muscular. Métodos: Se propone un algoritmo de filtrado de Gabor para suavizar la imagen original. El algoritmo MVEF se utiliza para mejorar aún más la imagen ultrasónica y volver a binar la imagen. Utilizando el principio de la transformada de H ove, el grosor del músculo se estima automáticamente. Resultados: El cuadrado de los coeficientes de correlación del método de medición manual, el algoritmo de filtrado de Gabor y el algoritmo MVEF son 91,3%, 91,3% y 87,8%, respectivamente. La diferencia entre la medición manual y la estimación basada en el algoritmo de filtrado de Gabor es de 1,45 ± 0,48 mm. La diferencia entre los resultados de la medición manual y el algoritmo MVEF es 1,38 ± 0,56 mm. El tiempo de cálculo del algoritmo MVEF y el algoritmo de Gabor son 5 segundos y 0,3 segundos respectivamente. Conclusiones: El algoritmo propuesto en este estudio puede medir eficazmente el grosor muscular, de forma rápida, conveniente y precisa, y puede reflejar bien la contractilidad del músculo esquelético, lo cual es de gran valor para el reconocimiento y evaluación de la función del movimiento de grupos musculares. Nivel de evidencia II; Estudios terapéuticos- investigación de los resultados del tratamiento.