Detection of carotid intima and media thicknesses based on ultrasound B-mode images clustered with Gaussian mixture model / 生物医学工程学杂志

In clinic, intima and media thickness are the main indicators for evaluating the development of atherosclerosis. At present, these indicators are measured by professional doctors manually marking the boundaries of the inner and media on B-mode images, which is complicated, time-consuming and affected by many artificial factors. A grayscale threshold method based on Gaussian Mixture Model (GMM) clustering is therefore proposed to detect the intima and media thickness in carotid arteries from B-mode images in this paper. Firstly, the B-mode images are clustered based on the GMM, and the boundary between the intima and media of the vessel wall is then detected by the gray threshold method, and finally the thickness of the two is measured. Compared with the measurement technique using the gray threshold method directly, the clustering of B-mode images of carotid artery solves the problem of gray boundary blurring of inner and middle membrane, thereby improving the stability and detection accuracy of the gray threshold method. In the clinical trials of 120 healthy carotid arteries, means of 4 manual measurements obtained by two experts are used as reference values. Experimental results show that the normalized root mean square errors (NRMSEs) of the estimated intima and media thickness after GMM clustering were 0.104 7 ± 0.076 2 and 0.097 4 ± 0.068 3, respectively. Compared with the results of the direct gray threshold estimation, means of NRMSEs are reduced by 19.6% and 22.4%, respectively, which indicates that the proposed method has higher measurement accuracy. The standard deviations are reduced by 17.0% and 21.7%, respectively, which indicates that the proposed method has better stability. In summary, this method is helpful for early diagnosis and monitoring of vascular diseases, such as atherosclerosis.

Realistic deformable 3D numeric phantom for transcutaneous ultrasound

Abstract Introduction Numerical phantoms are important tools to design, calibrate and evaluate several methods in various image-processing applications, such as echocardiography and mammography. We present a framework for creating ultrasound numerical deformable phantoms based on Finite Element Method (FEM), Linear Isomorphism and Field II. The proposed method considers that the scatterers map is a property of the tissue; therefore, the scatterers should move according to the tissue strain. Methods First, a volume representing the target tissue is loaded. Second, parameter values, such as Young’s Modulus, scatterers density, attenuation and scattering amplitudes are inserted for each different regions of the phantom. Then, other parameters related to the ultrasound equipment, such as ultrasound frequency and number of transducer elements, are also defined in order to perform the ultrasound acquisition using Field II. Third, the size and position of the transducer and the pressures that are applied against the tissue are defined. Subsequently, FEM is executed and deformation is computed. Next, 3D linear isomorphism is performed to displace the scatterers according to the deformation. Finally, Field II is carried out to generate the non-deformed and deformed ultrasound data. Results The framework is evaluated by comparing strain values obtained the numerical simulation and from the physical phantom from CIRS. The mean difference between both phantoms is lesser than 10%. Conclusion The acoustic and deformation outcomes are similar to those obtained using a physical phantom. This framework led to a tool, which is available online and free of charges for educational and research purposes.

Radius measurement and depth correction of veins in upper extremity venous ultrasound image / 军事医学

Objective To calculate and measure the depth and radius of the target vessel in the upper limb venous ultrasound image in order to contribute to automatic venipuncture.Methods Two methods of measuring the radius of veins in an ultrasonic vein cross section image were adopted.One method was to segment the vein based on the threshold selected after evaluation, and then scan the upper and lower edges of the vein to obtain the radius.The other method was based on Otsu method,which was to divide the vein and then morphologically process the binary image.The radius was calculated in a manner similar to the first method.After the radius was obtained, the depth of the vein was corrected in conjunction with the radius.Results The above two methods were tested on 500 upper limb venous ultrasound images.The accuracy rate of the first method was 93.0%, and that of the second method was 99.4%.Conclusion The method based on Otsu and morphological processing is more effective for radius measurement of veins in upper limb venous ultrasound image.

Breast tumor classification in ultrasound images using support vector machines and neural networks

Abstract Introduction The use of tools for computer-aided diagnosis (CAD) has been proposed for detection and classification of breast cancer. Concerning breast cancer image diagnosing with ultrasound, some results found in literature show that morphological features perform better than texture features for lesions differentiation, and indicate that a reduced set of features performs better than a larger one. Methods This study evaluated the performance of support vector machines (SVM) with different kernels combinations, and neural networks with different stop criteria, for classifying breast cancer nodules. Twenty-two morphological features from the contour of 100 BUS images were used as input for classifiers and then a scalar feature selection technique with correlation was used to reduce the features dataset. Results The best results obtained for accuracy and area under ROC curve were 96.98% and 0.980, respectively, both with neural networks using the whole set of features. Conclusion The performance obtained with neural networks with the selected stop criterion was better than the ones obtained with SVM. Whilst using neural networks the results were better with all 22 features, SVM classifiers performed better with a reduced set of 6 features.

Endocarditis de Libman-Sacks / Libman-Sacks endocarditis

La endocarditis de Libman-Sacks es una manifestación cardiaca bien reconocida del lupus eritematoso sistémico en la que se observan vegetaciones valvulares estériles, con predominio en el lado izquierdo del corazón, especialmente en la válvula mitral. La mayoría de los pacientes son asintomáticos; sin embargo, en la presentación clínica la forma aguda puede imitar a la de una endocarditis infecciosa (endocarditis pseudoinfecciosa) y complicar tanto el diagnóstico diferencial como el tratamiento. Se reporta el caso de un paciente de género masculino, de 63 años, quien manifestó signos y síntomas compatibles con endocarditis infecciosa, y cuyos diferentes estudios demostraron una endocarditis de Libman-Sacks que respondió de forma favorable al tratamiento inmunosupresor.

The Libman-Sacks endocarditis is a well-recognized systemic lupus erythematosus manifestation in which cardiac valvular sterile vegetations are observed predominantly in the left side of the heart, especially in the mitral valve. Most patients are asymptomatic; however, the acute clinical presentation may mimic an infectious endocarditis (pseudo-infectious endocarditis) and complicate both the differential diagnosis and treatment. The case of a 63 year-old male patient, who presented signs and symptoms consistent with infectious endocarditis and whose several studies demonstrated Libman-Sacks endocarditis and who responded favorably to immunosuppressive therapy, is reported.

Diagnóstico muy precoz de siameses: caso clínico y revisión de la literatura / Early diagnosis of conjoined twins: clinical case and literature review

We report a clinical case in which an early ultrasound diagnosis of retained abortion of thoracoomphalopagus siamese twins is performed by embryonic biometry at 9.5 weeks of gestation. 2D and 3D images clearly illustrate the condition and the accuracy of prompt diagnosis of a disease with such a low prevalence among the world population.

Se reporta caso clínico en el cual se realiza el diagnóstico ecográfico precoz de aborto retenido de siameses tóraco onfalópagos de 9 1/2 semanas por biometría embrionaria. Destacables son las imágenes 2D y 3D que ilustran claramente la condición y la precocidad del diagnóstico de una patología tanpoco prevalente en la población mundial.

From ultrasound images to block based region motion estimation

By applying a hexagon-diamond search (HDS) method to an ultrasound image, the path of an object is able to be monitored by extracting images into macro-blocks, thereby achieving image redundancy is reduced from one frame to another, and also ascertaining the motion vector within the parameters searched. The HDS algorithm uses six search points to form the six sides of the hexagon pattern, a centre point, and a further four search points to create diamond pattern within the hexagon that clarifies the focus of the subject area.