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Article in Chinese | WPRIM | ID: wpr-928892


Objective The study aims to investigate the effects of different adaptive statistical iterative reconstruction-V( ASiR-V) and convolution kernel parameters on stability of CT auto-segmentation which is based on deep learning. Method Twenty patients who have received pelvic radiotherapy were selected and different reconstruction parameters were used to establish CT images dataset. Then structures including three soft tissue organs (bladder, bowelbag, small intestine) and five bone organs (left and right femoral head, left and right femur, pelvic) were segmented automatically by deep learning neural network. Performance was evaluated by dice similarity coefficient( DSC) and Hausdorff distance, using filter back projection(FBP) as the reference. Results Auto-segmentation of deep learning is greatly affected by ASIR-V, but less affected by convolution kernel, especially in soft tissues. Conclusion The stability of auto-segmentation is affected by parameter selection of reconstruction algorithm. In practical application, it is necessary to find a balance between image quality and segmentation quality, or improve segmentation network to enhance the stability of auto-segmentation.

Algorithms , Humans , Image Processing, Computer-Assisted , Neural Networks, Computer , Radiation Dosage , Tomography, X-Ray Computed
Article in Chinese | WPRIM | ID: wpr-928873


CT image based organ segmentation is essential for radiotherapy treatment planning, and it is laborious and time consuming to outline the endangered organs and target areas before making radiation treatment plans. This study proposes a fully automated segmentation method based on fusion convolutional neural network to improve the efficiency of physicians in outlining the endangered organs and target areas. The CT images of 170 postoperative cervical cancer stage IB and IIA patients were selected for network training and automatic outlining of bladder, rectum, femoral head and CTV, and the neural network was used to localize easily distinguishable vessels around the target area to achieve more accurate outlining of CTV.

Female , Humans , Image Processing, Computer-Assisted , Neural Networks, Computer , Organs at Risk , Pelvis , Tomography, X-Ray Computed , Uterine Cervical Neoplasms/surgery
Article in Chinese | WPRIM | ID: wpr-928871


Clinical applications of cone-beam breast CT(CBBCT) are hindered by relatively higher radiation dose and longer scan time. This study proposes sparse-view CBBCT, i.e. with a small number of projections, to overcome the above bottlenecks. A deep learning method - conditional generative adversarial network constrained by image edges (ECGAN) - is proposed to suppress artifacts on sparse-view CBBCT images reconstructed by filtered backprojection (FBP). The discriminator of the ECGAN is the combination of patchGAN and LSGAN for preserving high frequency information, with a modified U-net as the generator. To further preserve subtle structures and micro calcifications which are particularly important for breast cancer screening and diagnosis, edge images of CBBCT are added to both the generator and the discriminator to guide the learning. The proposed algorithm has been evaluated on 20 clinical raw datasets of CBBCT. ECGAN substantially improves the image qualities of sparse-view CBBCT, with a performance superior to those of total variation (TV) based iterative reconstruction and FBPConvNet based post-processing. On one CBBCT case with the projection number reduced from 300 to 100, ECGAN enhances peak-signal-to-noise ratio (PSNR) and structural similarity (SSIM) on FBP reconstruction from 24.26 and 0.812 to 37.78 and 0.963, respectively. These results indicate that ECGAN successfully reduces radiation dose and scan time of CBBCT by 1/3 with only small image degradations.

Algorithms , Breast , Cone-Beam Computed Tomography , Humans , Image Processing, Computer-Assisted , Phantoms, Imaging , Tomography, X-Ray Computed
Article in Chinese | WPRIM | ID: wpr-928861


Advances in digital pathology technology have enabled pathologists and laboratory physicians to perform quick, easy, accurate and reproducible analysis of digital images of tissues and cells with the aid of electronic screens and software tools, rather than relying solely on traditional optical microscopy observations. The conventional clinical cytology testing practice is to be replaced by a digital workflow, which includes both digital imaging and image analysis. This article provides an overview of the basic principles of digital pathology techniques, the advances of development of device in cytology digital pathology, and their clinical applications in bone marrow morphology, and existing problems and prospects of digital pathology application in hematology.

Bone Marrow , Image Processing, Computer-Assisted , Microscopy , Software , Technology
Chinese Journal of Lung Cancer ; (12): 124-129, 2022.
Article in Chinese | WPRIM | ID: wpr-928789


The incidence and mortality of lung cancer rank first among all malignant tumors in China. With the popularization of high resolution computed tomography (CT) in clinic, chest CT has become an important means of clinical screening for early lung cancer and reducing the mortality of lung cancer. Imaging findings of early lung adenocarcinoma often show partial solid nodules with ground glass components. With the development of imaging, the relationship between the imaging features of some solid nodules and their prognosis has attracted more and more attention. At the same time, with the development of 3D-reconstruction technology, clinicians can improve the accuracy of diagnosis and treatment of such nodules.This article focuses on the traditional imaging analysis of partial solid nodules and the imaging analysis based on 3D reconstruction, and systematically expounds the advantages and disadvantages of both.

Adenocarcinoma of Lung/pathology , Humans , Image Processing, Computer-Assisted , Lung Neoplasms/pathology , Solitary Pulmonary Nodule/pathology , Tomography, X-Ray Computed
Article in Chinese | WPRIM | ID: wpr-928211


As an important basis for lesion determination and diagnosis, medical image segmentation has become one of the most important and hot research fields in the biomedical field, among which medical image segmentation algorithms based on full convolutional neural network and U-Net neural network have attracted more and more attention by researchers. At present, there are few reports on the application of medical image segmentation algorithms in the diagnosis of rectal cancer, and the accuracy of the segmentation results of rectal cancer is not high. In this paper, a convolutional network model of encoding and decoding combined with image clipping and pre-processing is proposed. On the basis of U-Net, this model replaced the traditional convolution block with the residual block, which effectively avoided the problem of gradient disappearance. In addition, the image enlargement method is also used to improve the generalization ability of the model. The test results on the data set provided by the "Teddy Cup" Data Mining Challenge showed that the residual block-based improved U-Net model proposed in this paper, combined with image clipping and preprocessing, could greatly improve the segmentation accuracy of rectal cancer, and the Dice coefficient obtained reached 0.97 on the verification set.

Algorithms , Delayed Emergence from Anesthesia , Humans , Image Processing, Computer-Assisted , Rectal Neoplasms/diagnostic imaging , Tomography, X-Ray Computed
Rev. bras. med. esporte ; 27(5): 456-459, July-Sept. 2021. tab, graf
Article in English | LILACS | ID: biblio-1288616


ABSTRACT Introduction: The integrity of articular cartilage determines the functional state of the joint. In recent years, the development of MRI sequences of various articular cartilage has become the focus of many research topics. Objective: The accuracy of diagnosis of knee cartilage injury caused by motion injury was studied retrospectively by meta-three-dimensional software. Methods: Forty-six knee joints of 45 patients with sports injuries, multi-sequence MRI was performed before surgery, including conventional knee MRI (SET1WI, FSEPD/T2WI), 3D SPGR, and 3D FIESTA sequences. Results: According to the operation results, the sensitivity, specificity, positive predictive value, and negative predictive value of 3D SPGR combined with conventional MRI sequence evaluation of cartilage damage are the highest, 73%, 98%, 95%, and 90%. Conclusions: 3D SPGR combined with conventional MRI sequences can improve accurate evaluation and diagnosis of cartilage disease over a reasonable scan time. Level of evidence II; Therapeutic studies - investigation of treatment results.

RESUMO Introdução: A integridade da cartilagem articular determina o estado funcional da articulação. Nos últimos anos, o desenvolvimento de sequências de ressonância magnética de várias cartilagens articulares se tornou o foco de muitos tópicos de pesquisa. Objetivo: A precisão do diagnóstico de lesão da cartilagem do joelho causada por lesão de movimento foi estudada retrospectivamente por software meta-tridimensional. Métodos: Quarenta e seis articulações de joelho de 45 pacientes com lesões esportivas, várias sequências de ressonância magnética foram realizadas antes da cirurgia, incluindo ressonância magnética de joelho convencional (SET1WI, FSEPD / T2WI), 3D SPGR e sequências 3D FIESTA. Resultados: De acordo com os resultados da operação, a sensibilidade, especificidade, valor preditivo positivo e valor preditivo negativo de 3D SPGR combinado com avaliação de sequência de ressonância magnética convencional de danos na cartilagem são os mais altos, 73%, 98%, 95% e 90%. Conclusões: 3D SPGR combinado com sequências convencionais de ressonância magnética pode melhorar a avaliação precisa e diagnóstico de doença da cartilagem em um tempo de varredura razoável. Nível de evidência II; Estudos terapêuticos- investigação dos resultados do tratamento.

RESUMEN Introducción: La integridad del cartílago articular determina el estado funcional de la articulación. En los últimos años, el desarrollo de secuencias de resonancia magnética de varios cartílagos articulares se ha convertido en el foco de muchos temas de investigación. Objetivo: La precisión del diagnóstico de la lesión del cartílago de la rodilla causada por una lesión por movimiento se estudió retrospectivamente mediante un software meta-tridimensional. Métodos: Cuarenta y seis articulaciones de rodilla de 45 pacientes con lesiones deportivas, se realizó una resonancia magnética de secuencia múltiple antes de la cirugía, incluida la resonancia magnética de rodilla convencional (SET1WI, FSEPD/T2WI), secuencias 3D SPGR y 3D FIESTA. Resultados: De acuerdo con los resultados de la operación, la sensibilidad, la especificidad, el valor predictivo positivo y el valor predictivo negativo de 3D SPGR combinados con la evaluación de la secuencia de resonancia magnética convencional del daño del cartílago son los más altos, 73%, 98%, 95% y 90%. Conclusiones: 3D SPGR combinado con secuencias de resonancia magnética convencionales puede mejorar la evaluación y el diagnóstico precisos de la enfermedad del cartílago en un tiempo de exploración razonable. Nivel de evidencia II; Estudios terapéuticos- investigación de los resultados del tratamiento.

Humans , Male , Female , Adult , Middle Aged , Young Adult , Athletic Injuries/diagnostic imaging , Image Processing, Computer-Assisted , Trauma Severity Indices , Knee Injuries/diagnostic imaging , Predictive Value of Tests , Retrospective Studies , Sensitivity and Specificity
Rev. bras. med. esporte ; 27(4): 367-371, Aug. 2021. graf
Article in English | LILACS | ID: biblio-1288608


ABSTRACT Objective: To study the relationship between aerobic activity and cardiac autonomic nerve activity by artificial neural network algorithm and biological image fusion; because of the artificial neural network model (ANN) problems, biological image processing technology is introduced based on ANN. Methods: An Ann under biological image intelligence algorithm is proposed, a classifier suitable for electrocardiograph (ECG) screening is designed, and an ECG signal screening system is successfully established. Moreover, the data set of normal recovered ECG signals of the subjects during the experimental period is constructed, and a classifier is used to extract the characteristic data of a normal ECG signal during the experimental period. Results: The changes in resting heart rate and other physical health indicators are analyzed by combining resting physiological indicators, namely heart rate, body weight, body mass index and body fat rate. The results show that the self-designed classifier can efficiently process the ECG images, and long-term regular activities can improve the physical conditions of most people. Most subjects' body weight and body fat rate decrease with the extension of experiment time, and the resting heart rate decreases relatively. Conclusions: Certain indicators can be used to predict a person's dynamic physical health, which indicates that the experimental research of index prediction in this research has a good effect, which not only extends the application of artificial neural network but also lays a foundation for the research and implementation of ECG intelligent testing wearable devices. Level of evidence II; Therapeutic studies - investigation of treatment results.

RESUMO Objetivo: Com o objetivo de estudar a relação entre atividade aeróbia e atividade nervosa autonômica cardíaca por algoritmo de rede neural artificial e fusão biológica de imagens, tendo em vista os problemas existentes no modelo de rede neural artificial (RNA), é introduzida a tecnologia de processamento biológico de imagens com base em ANN. Métodos: um algoritmo de inteligência biológica de imagem Ann é proposto, um classificador adequado para triagem eletrocardiográfica (ECG) é projetado e um sistema de triagem de sinal de ECG é estabelecido com sucesso. Além disso, o conjunto de dados de sinais de ECG normais recuperados dos sujeitos durante o período experimental é construído e um classificador é usado para extrair os dados característicos de um sinal de ECG normal durante o período experimental. Resultados: As alterações na frequência cardíaca em repouso e outros indicadores de saúde física são analisadas pela combinação de indicadores fisiológicos de repouso, a saber, frequência cardíaca, peso corporal, índice de massa corporal e índice de gordura corporal. Os resultados mostram que o classificador autodesenhado pode processar com eficiência as imagens de ECG, e as atividades regulares de longo prazo podem melhorar as condições físicas da maioria das pessoas. O peso corporal e a taxa de gordura corporal da maioria dos indivíduos diminuem com a extensão do tempo do experimento, e a freqüência cardíaca em repouso diminui relativamente. Conclusões: Certos indicadores podem ser usados para prever a saúde física dinâmica de uma pessoa, o que indica que a pesquisa experimental de predição de índice nesta pesquisa tem um bom efeito, que não apenas estende a aplicação da rede neural artificial, mas também estabelece uma base para a pesquisa e implementação de dispositivos vestíveis de teste inteligente de ECG. Nível de evidência II; Estudos terapêuticos- investigação dos resultados do tratamento.

RESUMEN Objetivo: Para estudiar la relación entre la actividad aeróbica y la actividad del nervio autónomo cardíaco mediante el algoritmo de red neuronal artificial y la fusión de imágenes biológicas, ante los problemas existentes en el modelo de red neuronal artificial (ANN), se introduce la tecnología de procesamiento de imágenes biológicas basada en ANA. Métodos: Se propone un algoritmo de inteligencia de imagen biológica de Ann, se diseña un clasificador adecuado para el cribado electrocardiógrafo (ECG) y se establece con éxito un sistema de cribado de señales de ECG. Además, se construye el conjunto de datos de las señales de ECG recuperadas normales de los sujetos durante el período experimental, y se utiliza un clasificador para extraer los datos característicos de una señal de ECG normal durante el período experimental. Resultados: Los cambios en la frecuencia cardíaca en reposo y otros indicadores de salud física se analizan combinando indicadores fisiológicos en reposo, a saber, frecuencia cardíaca, peso corporal, índice de masa corporal y tasa de grasa corporal. Los resultados muestran que el clasificador de diseño propio puede procesar de manera eficiente las imágenes de ECG, y las actividades regulares a largo plazo pueden mejorar las condiciones físicas de la mayoría de las personas. El peso corporal y la tasa de grasa corporal de la mayoría de los sujetos disminuyen con la extensión del tiempo del experimento, y la frecuencia cardíaca en reposo disminuye relativamente. Conclusiones: Ciertos indicadores pueden usarse para predecir la salud física dinámica de una persona, lo que indica que la investigación experimental de predicción de índices en esta investigación tiene un buen efecto, lo que no solo extiende la aplicación de la red neuronal artificial sino que también sienta las bases para la investigación. e implementación de dispositivos portátiles de prueba inteligente de ECG. Nivel de evidencia II; Estudios terapéuticos- investigación de los resultados del tratamiento.

Humans , Running/physiology , Autonomic Nervous System/physiology , Image Interpretation, Computer-Assisted/methods , Neural Networks, Computer , Heart Rate/physiology , Algorithms , Image Processing, Computer-Assisted , Electrocardiography
Gac. méd. boliv ; 44(1): 92-95, jun. 2021. ilus
Article in Spanish | LILACS | ID: biblio-1286579


La hipertrofia de labios menores es la prolongación de estos más allá de los límites anatómicos de los labios mayores. La creencia de la simplicidad en la reducción de los labios menores y la falla en observar importantes aspectos de la técnica quirúrgica que llevan a la resección total del labio. En tales casos, la cirugía reconstructiva es la única forma posible de rectificar la situación. Presentamos el caso de una mujer de 36 años que acude por amputación de los labios menores secundario a cirugía de labioplastia por hipertrofia realizada por médico esteticista. Se realiza reconstrucción de labios menores en dos tiempos quirúrgicos. Los colgajos de avance en V-Y del capuchón del clítoris, con remanentes de tejido de la horquilla posterior, pueden lograr resultados satisfactorios y permitir la adaptación a la anatomía genital y los deseos estéticos únicos de cada mujer.

Labia minora hypertrophy is the prolongation of these beyond the anatomical limits of the labia majora. The belief in simplicity in the reduction of the labia minora and the failure to observe important aspects of the surgical technique that lead to total lip resection. In such cases, reconstructive surgery is the only possible way to rectify the situation. A 36-year-old woman with medical history of labia minora amputation secondary to labiaplasty surgery for hypertrophy of the labia minora performed by a beautician. The labia minora reconstruction is performed in two surgical stages. The V-Y advancement flaps of the clitoral hood with remnants of tissue from the posterior fork can be achieved with satisfactory results and allow adaptation to the genital anatomy and unique aesthetic wishes of each woman.

Image Processing, Computer-Assisted
Journal of Biomedical Engineering ; (6): 1072-1080, 2021.
Article in Chinese | WPRIM | ID: wpr-921847


As one of the non-invasive imaging techniques, myocardial perfusion imaging provides a basis for the diagnosis of myocardial ischemia in coronary heart disease. Aiming at the bull-eye image in myocardial perfusion imaging, this paper proposed a branching structure, which included multi-layer transposed convolution up-sampling concatenate module and four-channel weighted channels attention module, and the output results of the branch structure were fused with the output results of trunk U-Net, to achieve accurate segmentation of the cardiac ischemia missing degree in myocardial perfusion bull-eye image. The experimental results show that the multi-layer transposed convolution up-sampling concatenate module realizes the fusion of different depth feature maps, and effectively reduces the interference of the severe sparse degree which is similar to the missing degree on the segmentation. Four-channel weighted attention module can further improve the ability to distinguish between the two similar degrees and the ability to learn edge details of the targets, and retain more abundant edge details features. The experimental data came from Tianjin Medical University General Hospital, Tianjin TEDA Hospital, Tianjin First Central Hospital and Third Central Hospital. The Jaccard scores in the self-built dataset was 5.00% higher than that of U-Net. The model presented in this paper is superior to other optimized models based on U-Net, and the subjective evaluation meets the accuracy requirements for clinical diagnosis.

Humans , Image Processing, Computer-Assisted , Ischemia , Myocardial Ischemia/diagnostic imaging , Neural Networks, Computer , Perfusion
Article in Chinese | WPRIM | ID: wpr-921833


In order to suppress the geometrical artifacts caused by random jitter in ray source scanning, and to achieve flexible ray source scanning trajectory and meet the requirements of task-driven scanning imaging, a method of free trajectory cone-beam computed tomography (CBCT) reconstruction is proposed in this paper. This method proposed a geometric calibration method of two-dimensional plane. Based on this method, the geometric calibration phantom and the imaging object could be simultaneously imaged. Then, the geometric parameters could be obtained by online calibration method, and then combined with the geometric parameters, the alternating direction multiplier method (ADMM) was used for image iterative reconstruction. Experimental results showed that this method obtained high quality reconstruction image with high contrast and clear feature edge. The root mean square errors (RMSE) of the simulation results were rather small, and the structural similarity (SSIM) values were all above 0.99. The experimental results showed that it had lower image information entropy (IE) and higher contrast noise ratio (CNR). This method provides some practical value for CBCT to realize trajectory freedom and obtain high quality reconstructed image.

Algorithms , Calibration , Cone-Beam Computed Tomography , Image Processing, Computer-Assisted , Phantoms, Imaging
Article in Chinese | WPRIM | ID: wpr-921819


Image registration is of great clinical importance in computer aided diagnosis and surgical planning of liver diseases. Deep learning-based registration methods endow liver computed tomography (CT) image registration with characteristics of real-time and high accuracy. However, existing methods in registering images with large displacement and deformation are faced with the challenge of the texture information variation of the registered image, resulting in subsequent erroneous image processing and clinical diagnosis. To this end, a novel unsupervised registration method based on the texture filtering is proposed in this paper to realize liver CT image registration. Firstly, the texture filtering algorithm based on L0 gradient minimization eliminates the texture information of liver surface in CT images, so that the registration process can only refer to the spatial structure information of two images for registration, thus solving the problem of texture variation. Then, we adopt the cascaded network to register images with large displacement and large deformation, and progressively align the fixed image with the moving one in the spatial structure. In addition, a new registration metric, the histogram correlation coefficient, is proposed to measure the degree of texture variation after registration. Experimental results show that our proposed method achieves high registration accuracy, effectively solves the problem of texture variation in the cascaded network, and improves the registration performance in terms of spatial structure correspondence and anti-folding capability. Therefore, our method helps to improve the performance of medical image registration, and make the registration safely and reliably applied in the computer-aided diagnosis and surgical planning of liver diseases.

Algorithms , Humans , Image Processing, Computer-Assisted , Liver Diseases , Tomography, X-Ray Computed
Article in Chinese | WPRIM | ID: wpr-879263


With the wide application of deep learning technology in disease diagnosis, especially the outstanding performance of convolutional neural network (CNN) in computer vision and image processing, more and more studies have proposed to use this algorithm to achieve the classification of Alzheimer's disease (AD), mild cognitive impairment (MCI) and normal cognition (CN). This article systematically reviews the application progress of several classic convolutional neural network models in brain image analysis and diagnosis at different stages of Alzheimer's disease, and discusses the existing problems and gives the possible development directions in order to provide some references.

Alzheimer Disease/diagnostic imaging , Cognitive Dysfunction/diagnosis , Humans , Image Processing, Computer-Assisted , Magnetic Resonance Imaging , Neural Networks, Computer
Article in Chinese | WPRIM | ID: wpr-879252


The three-dimensional (3D) liver and tumor segmentation of liver computed tomography (CT) has very important clinical value for assisting doctors in diagnosis and prognosis. This paper proposes a tumor 3D conditional generation confrontation segmentation network (T3scGAN) based on conditional generation confrontation network (cGAN), and at the same time, a coarse-to-fine 3D automatic segmentation framework is used to accurately segment liver and tumor area. This paper uses 130 cases in the 2017 Liver and Tumor Segmentation Challenge (LiTS) public data set to train, verify and test the T3scGAN model. Finally, the average Dice coefficients of the validation set and test set segmented in the 3D liver regions were 0.963 and 0.961, respectively, while the average Dice coefficients of the validation set and test set segmented in the 3D tumor regions were 0.819 and 0.796, respectively. Experimental results show that the proposed T3scGAN model can effectively segment the 3D liver and its tumor regions, so it can better assist doctors in the accurate diagnosis and treatment of liver cancer.

Humans , Image Processing, Computer-Assisted , Liver Neoplasms/diagnostic imaging , Tomography, X-Ray Computed
Article in Chinese | WPRIM | ID: wpr-880459


Aiming at the problem of timeliness of CBCT reconstruction, a CBCT fast short scan reconstruction method is proposed. At the same time, the image reconstruction process in which a new attenuation compensation algorithm is applied to improve image quality. When performing FDK three-dimensional reconstruction of a single-frame acquisition image, the Parker-weighted image is calculated in real time, and a new attenuation compensation algorithm is applied in the back projection process to complete the short scan Parker-weighted reconstruction. This method simulates the CBCT synchronous acquisition and reconstruction process by establishing collection and reconstruction threads. Under the premise of satisfying the reconstruction quality, the reconstruction can be completed within 1 to 2 seconds after the patient collection is completed, which achieves the purpose of real-time.

Algorithms , Cone-Beam Computed Tomography , Humans , Image Processing, Computer-Assisted , Spiral Cone-Beam Computed Tomography
São José dos Campos; s.n; 2021. 44 p. ilus, graf, tab.
Thesis in Portuguese | LILACS, BBO | ID: biblio-1362245


Analise de textura (AT) é um método de processamento de imagens utilizado para potencializar a capacidade de diagnóstico. Desta forma este estudo teve por objetivo caracterizar os parâmetros de AT da medular do côndilo e músculo pterigóideo lateral (ventre superior) em imagens de Ressonância Magnética (RM) com o intuito de identificar possíveis alterações de indivíduos que apresentam disfunção temporomandibular (DTM), em comparação aos resultados obtidos com um grupo controle. Foram selecionados 40 exames de RM das articulações temporomandibulares de arquivo, sendo 20 exames de pacientes sem alteração na articulação temporomandibular (ATM) (grupo controle) e 20 exames de indivíduos diagnosticados com disfunção tempormandibular (grupo DTM). Todos os exames de RM foram adquiridos com o mesmo protocolo, utilizando uma bobina de superfícies bilateral de 8,0 cm de diâmetro, com imagens parassagitais látero-mediais, ponderadas em T2 e Densidade Protônica (DP), em boca fechada e máxima abertura bucal. Para a AT utilizou-se o software MaZda 4.20 (Institute of Electronics, Technical Universityof Lodz, Polônia), determinou-se a região de interesse (ROIs), sendo a mesma para todas as imagens e então foram calculados os parâmetros de textura, por meio da matriz de co-ocorrência (MCO). Os resultados foram tabulados e submetidos ao teste de Mann-Whitney. Pode-se verificar o parâmetro de Correlação (C) e o Momento da Diferença Inversa (MDI), apresentou diferença estatisticamente significante, entre os grupos analisados C x DTM verificados nas imagens ponderadas em DP, para a região da medular condilar e músculo pterigoideo lateral, respectivamente. Para as imagens analisadas em T2 nos grupos estudados, não apresentaram parâmetros que fossem estatisticamente significantes. Concluiu-se que a analise de textura é um método que potencialmente pode fornecer informações para melhorar o diagnóstico e precisão na classificação da DTM.

Texture analysis (TA) is an image processing method used to enhance the diagnostic capacity. Thus, this study aimed to characterize the TA parameters of the medullary cortex of the condyle and lateral pterygoid muscle (upper belly) in Magnetic Resonance Images(MRI) in order to identify possible changes in the temporomandibular joints (TMJ) of individuals who have temporomandibular disorder (TMD), compared to the results obtained with a control group. Forty MRI exams of the TMJ files were selected, 20 of which were patients with no TMJ alteration (control group) and 20 exams of individuals diagnosed with tempormandibular dysfunction (TMD group). All MRI exams were acquired using the same protocol, using a bilateral coil of 8.0 cm in diameter, with lateral-medial parasagital images, weighted in T2 and Protonic Density (PD), in closed mouth and maximum mouth opening. For TA, the MaZda 4.20 software (Institute of Electronics, Technical Universityof Lodz, Poland) was used, the region of interest (ROI) was determined, being the same for all images and then the texture parameters were calculated, by through the co-occurrence matrix (COM). The results were tabulated and submitted to the Mann-Whitney test. The Correlation parameter (C) and the Inverse Moment of Difference (IMD) showed a statistically significant difference between the analyzed groups C x TMD, verified in the DP-weighted images, for the condylar medullary region and lateral pterygoid muscle, respectively. For the images analyzed in T2 in the studied groups, they did not present parameters that were statistically significant. It was concluded that texture analysis is a method that can potentially provide prognostic information to improve diagnostic accuracy in TMD classification.

Humans , Image Processing, Computer-Assisted , Magnetic Resonance Imaging , Temporomandibular Joint Dysfunction Syndrome , Statistics, Nonparametric
ABCD arq. bras. cir. dig ; 34(2): e1608, 2021. graf
Article in English, Portuguese | LILACS | ID: biblio-1345008


ABSTRACT Background: Heart dysfunction and liver disease often coexist because of systemic disorders. Any cause of right ventricular failure may precipitate hepatic congestion and fibrosis. Digital image technologies have been introduced to pathology diagnosis, allowing an objective quantitative assessment. The quantification of fibrous tissue in liver biopsy sections is extremely important in the classification, diagnosis and grading of chronic liver disease. Aim: To create a semi-automatic computerized protocol to quantify any amount of centrilobular fibrosis and sinusoidal dilatation in liver Masson's Trichrome-stained specimen. Method: Once fibrosis had been established, liver samples were collected, histologically processed, stained with Masson's trichrome, and whole-slide images were captured with an appropriated digital pathology slide scanner. After, a random selection of the regions of interest (ROI's) was conducted. The data were subjected to software-assisted image analysis (ImageJ®). Results: The analysis of 250 ROI's allowed to empirically obtain the best application settings to identify the centrilobular fibrosis (CF) and sinusoidal lumen (SL). After the establishment of the colour threshold application settings, an in-house Macro was recorded to set the measurements (fraction area and total area) and calculate the CF and SL ratios by an automatic batch processing. Conclusion: Was possible to create a more detailed method that identifies and quantifies the area occupied by fibrous tissue and sinusoidal lumen in Masson's trichrome-stained livers specimens.

Resumo Racional: Tecnologias de imagem digital têm sido introduzidas ao diagnóstico patológico, permitindo avaliações quantitativas objetivas. A quantificação de tecido fibroso em biópsias de fígado é extremamente importante para a classificação, diagnóstico e graduação de doenças crônicas hepáticas. Objetivo: Criar um protocolo computadorizado semi-automático para quantificação de fibrose centrolobular e dilatação sinusoidal em amostras de fígado coradas por Tricrômico de Masson. Método: Uma vez instaurada a fibrose, amostras de fígado foram coletadas, processadas histologicamente, coradas por Tricrômico de Masson e WSI (Whole Slide Images) foram capturadas por scanner digital patológico apropriado. Uma seleção aleatória das regiões de interesse (ROI) foi realizada. Os dados foram submetidos a uma análise de imagem assistida por software (ImageJ®). Resultados: A análise de 250 ROIs permitiu obter-se empiricamente as melhores configurações capazes de identificar fibrose centrolobular (FC) e lúmen sinusoidal (LS). Após o estabelecimento das configurações de padrão de cor, uma Macro de autoria própria foi gravada para definir as medidas (área da fração e área total) e calcular as razões de FC e LS por processamento em grupo/lote (batch mode). Conclusão: Foi possível criar um método detalhado capaz de identificar e quantificar a área ocupada por tecido fibroso e lúmen sinusoidal em espécimes de fígado coradas por Tricrômico de Masson.

Humans , Image Processing, Computer-Assisted , Software , Fibrosis , Dilatation , Liver/pathology , Liver/diagnostic imaging , Liver Cirrhosis
Rev. cuba. invest. bioméd ; 40(supl.1): e1614, 2021. tab, graf
Article in Spanish | LILACS, CUMED | ID: biblio-1289470


Uno de los desafíos que los programadores tienen que enfrentar es la alta dimensión de grupos de datos. El proceso de reconocimiento de patrones en imagen y la minería de datos para los volúmenes grandes de información son ejemplos de ellos, optimizar la cantidad de veces que se recorre el conjunto de datos, disminuye el tiempo de procesamiento. Éste documento tiene el objetivo de caracterizar el algoritmo de tres pasos (S3), paralelo a K-medias, como una alternativa para afrontar la alta dimensión del conjunto de datos, en la clasificación no supervisada de imagen. Para el análisis de la concurrencia, se escoge, flujo de datos y el esquema instrucción única con datos múltiples. El resultado obtenido confirma que la concurrencia en ambos es posible, S3 no depende de la selección inicial de los representantes y puede ser el proceso de escogimiento de los primeros vectores centrales en K-medias. S3 es una alternativa a ser tenida en cuenta en la clasificación no supervisada de imágenes médicas y procesos de minería de datos(AU)

One of the challenges to be faced by programmers is the large dimensions of data groups. The process of pattern recognition in images and data mining for great volumes of information is an example. Optimizing the number of times that the set of data is run saves processing time. The purpose of the study was to characterize the three-step (S3) algorithm, parallel to k-means, as an alternative to cope with the large dimension of the data set in unsupervised image classification. Concurrence analysis is based on data flow and the single instruction multiple data scheme. The result obtained confirms that concurrence of both is possible. S3 does not depend on initial selection of representatives, and may be the process for selection of the first central vectors in k-means. S3 is an alternative to be considered in the unsupervised classification of medical images and data mining(AU)

Humans , Algorithms , Image Processing, Computer-Assisted/methods , Records
Int. j. morphol ; 38(5): 1296-1301, oct. 2020. tab, graf
Article in Spanish | LILACS | ID: biblio-1134439


RESUMEN: La Microscopía Virtual es una herramienta tecnológica que permite la visualización de imágenes digitales microscópicas de gran resolución a través de un computador imitando la funcionalidad de un microscopio óptico tradicional. El presente trabajo presenta nuestra experiencia en el uso de esta modalidad de trabajo, útil hoy en día, en medio de la pandemia por Covid-19.

SUMMARY: Virtual Microscopy is a technological tool that allows the visualization of high resolution microscopic digital images through a computer, imitating the functionality of a traditional light microscope. The present work presents our experience in the use of this working modality, useful today, in the midst of the Covid-19 pandemic.

Humans , Animals , Image Processing, Computer-Assisted/methods , Embryonic and Fetal Development , Microscopy/methods , Virtual Reality , Microscopy/trends