290 resources related to Ultrasonography
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The conference program will consist of plenary lectures, symposia, workshops and invitedsessions of the latest significant findings and developments in all the major fields of biomedical engineering.Submitted full papers will be peer reviewed. Accepted high quality papers will be presented in oral and poster sessions,will appear in the Conference Proceedings and will be indexed in PubMed/MEDLINE.
The 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2020) will be held in Metro Toronto Convention Centre (MTCC), Toronto, Ontario, Canada. SMC 2020 is the flagship conference of the IEEE Systems, Man, and Cybernetics Society. It provides an international forum for researchers and practitioners to report most recent innovations and developments, summarize state-of-the-art, and exchange ideas and advances in all aspects of systems science and engineering, human machine systems, and cybernetics. Advances in these fields have increasing importance in the creation of intelligent environments involving technologies interacting with humans to provide an enriching experience and thereby improve quality of life. Papers related to the conference theme are solicited, including theories, methodologies, and emerging applications. Contributions to theory and practice, including but not limited to the following technical areas, are invited.
The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging.ISBI 2019 will be the 16th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2019 meeting will continue this tradition of fostering cross fertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.
The conference covers all aspects of the technology associated with ultrasound generation and detection and their applications.
The symposium is the premier conference for computational medicine, providing a mechanism for the exchange of ideas and technologies between academics and industrial scientists, and attracts a worldwide audience.
Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.
IEEE Computer Graphics and Applications (CG&A) bridges the theory and practice of computer graphics. From specific algorithms to full system implementations, CG&A offers a strong combination of peer-reviewed feature articles and refereed departments, including news and product announcements. Special Applications sidebars relate research stories to commercial development. Cover stories focus on creative applications of the technology by an artist or ...
Both general and technical articles on current technologies and methods used in biomedical and clinical engineering; societal implications of medical technologies; current news items; book reviews; patent descriptions; and correspondence. Special interest departments, students, law, clinical engineering, ethics, new products, society news, historical features and government.
Signal-processing aspects of image processing, imaging systems, and image scanning, display, and printing. Includes theory, algorithms, and architectures for image coding, filtering, enhancement, restoration, segmentation, and motion estimation; image formation in tomography, radar, sonar, geophysics, astronomy, microscopy, and crystallography; image scanning, digital half-toning and display, andcolor reproduction.
Telemedicine, teleradiology, telepathology, telemonitoring, telediagnostics, 3D animations in health care, health information networks, clinical information systems, virtual reality applications in medicine, broadband technologies, and global information infrastructure design for health care.
2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2007
Various statistical parameters have been tried for the computer-aided diagnosis of the liver fibrosis. The region of interest (ROI) for the liver and spleen parenchymas have been chosen, and the hepatolienal textural contrast for each ultrasound (US) image has been examined. The selectively chosen textural parameters are linearly combined with the pre-determined coefficients to give the computer-aided diagnostic parameter for ...
2012 International Conference on Biomedical Engineering and Biotechnology, 2012
Objective: To observe the feasibility of virtual organ computer-aided analysis (VOCAL) technique in estimating the fetal lung volume, and to assess the diagnostic value of ultrasound fetal lung volume in fetal pulmonary hypoplasia (PH). Methods: A total of 31 fetuses (20-32 weeks) with abnomal diagnosed with prenatal ultrasonography were enrolled in this study. The autopsy and clnical diagnosis were permitted. ...
Proceedings of 7th International Workshop on Enterprise networking and Computing in Healthcare Industry, 2005. HEALTHCOM 2005., 2005
Both breast ultrasonography (US) and scintimammography (SMM) shows limited diagnostic accuracy in the differential diagnosis of breast cancer. We investigated whether the diagnostic performance of computer-aided diagnosis (CAD) of US was improved by adding SMM results. We retrospectively reviewed 40 breast US images and corresponding SMM images from 40 patients who presented with breast masses (21 malignant and 19 benign ...
2010 4th International Conference on Bioinformatics and Biomedical Engineering, 2010
The purpose of this work was to re-examine the reasons for the appearance of power doppler artifact referred to as "twinkling" artifact, which is usually observed in hyperechoic regions and which introduces ambiguity in diagnosis. Two key parameters: physical dimensions of the analyzed object and its roughness or irregular shape were initially considered. Several tests were done on Renal and ...
2009 Second International Conference on Emerging Trends in Engineering & Technology, 2009
This research aims at developing an optimal neural network based DSS, which is aimed at precise and reliable diagnosis of chronic active hepatitis (CAH) and cirrhosis (CRH). The principal component analysis neural network is designed scrupulously for classification of these diseases. The neural network is trained by eight quantified texture features, which were extracted from five different region of interests ...
Various statistical parameters have been tried for the computer-aided diagnosis of the liver fibrosis. The region of interest (ROI) for the liver and spleen parenchymas have been chosen, and the hepatolienal textural contrast for each ultrasound (US) image has been examined. The selectively chosen textural parameters are linearly combined with the pre-determined coefficients to give the computer-aided diagnostic parameter for the liver fibrosis, whose final stage is named as cirrhosis. From the comparison with the clinical diagnosis it is suggested that the proposed calculation scheme using the textural parameters show the quite promising classification performance for the computer-aided diagnosis of the liver cirrhosis.
Objective: To observe the feasibility of virtual organ computer-aided analysis (VOCAL) technique in estimating the fetal lung volume, and to assess the diagnostic value of ultrasound fetal lung volume in fetal pulmonary hypoplasia (PH). Methods: A total of 31 fetuses (20-32 weeks) with abnomal diagnosed with prenatal ultrasonography were enrolled in this study. The autopsy and clnical diagnosis were permitted. The fetal lung volume was estimated with four- dimensional ultrasonography using VOCAL technique, the value of fetal lung volume in the diagnosis of fetal PH was evaluated. Results: The sensitivity value of fetal lung volume in diagnosing fetal PH was 81.1% and the accuracy ratio was 76.92%. Conclusion: The fetal lung volume can be estimated precisely with four-dimensional ultrasonography using VOCAL technique. Fetal lung volume may be useful in the prenatal diagnosis of fetal PH.
Both breast ultrasonography (US) and scintimammography (SMM) shows limited diagnostic accuracy in the differential diagnosis of breast cancer. We investigated whether the diagnostic performance of computer-aided diagnosis (CAD) of US was improved by adding SMM results. We retrospectively reviewed 40 breast US images and corresponding SMM images from 40 patients who presented with breast masses (21 malignant and 19 benign tumors). The morphologic features of the breast lesions on US were extracted and quantitated using the automated CAD software program (So no Eye, CAD Impact, Inc., Seoul, Korea), which calculated the probability of malignancy based on the stored database. The quantitative data of SMM were obtained as the uptake ratio of lesion to contralateral normal breast on SMM SPECT. The diagnostic accuracy of CAD of US and SMM was determined using ROC curve analysis, respectively. The best discriminating function combining the CAD results of US and SMM uptake value was created using linear discriminant analysis and the diagnostic performance was compared to that using only one diagnostic modality. Both US and SMM showed a relatively good diagnostic accuracy (area under curve=0.831 and 0.846, respectively). Combining CAD results of US and SMM resulted in improved diagnostic accuracy (area under curve =0.860), but it was not statistically significant. The diagnostic performance of CAD of breast US in the differential diagnosis of the breast mass was not significantly improved by adding SMM. However, SMM SPECT may be complementary to CAD of US in differential diagnosis of breast cancer.
The purpose of this work was to re-examine the reasons for the appearance of power doppler artifact referred to as "twinkling" artifact, which is usually observed in hyperechoic regions and which introduces ambiguity in diagnosis. Two key parameters: physical dimensions of the analyzed object and its roughness or irregular shape were initially considered. Several tests were done on Renal and artificially generated stones in order to visualize twinkling artifact and to obtain meaningful results. It is shown that "Radiation force" which is generated by a change in the energy density of an incident acoustic field, causes an oscillation with a frequency equal to the PRF of the sonography device and therefore movement in the object being imaged which will cause the twinkling artifact. This artifact is modeled in the MATLAB programming language. The radiation force factor causing the vibration is applied to a stone which is assumed to be made of some random scatterers. The velocity of the scatterers movement which is causing the appearance of the twinkling artifact is calculated. Later the effects of different vibration parameters on the production of the twinkling artifact are shown. It is shown that the increase in vibration amplitude and frequency, both cause a velocity increase of the object being imaged. The size of the object being imaged has an indirect influence on the production of this artifact, while the roughness of the object intensifies the artifact.
This research aims at developing an optimal neural network based DSS, which is aimed at precise and reliable diagnosis of chronic active hepatitis (CAH) and cirrhosis (CRH). The principal component analysis neural network is designed scrupulously for classification of these diseases. The neural network is trained by eight quantified texture features, which were extracted from five different region of interests (ROIs) uniformly distributed in each B-mode ultrasonic image of normal liver (NL), chronic active hepatitis (CAH) and cirrhosis (CRH). The proposed PCA NN classifier is the most efficient learning machine that is able to classify all three cases of diffused liver with average classification accuracy of 95.23%; 6 cases of cirrhosis out of 7 (6/7), all 7 cases of chronic active hepatitis (7/7) and all 15 cases of normal liver (15/15).
Assessing and optimizing diagnostic performance of medical imaging technology is important and challenging. We have extended an information theoretic approach based on the ideal observer for the discrimination of breast lesions in sonography to discover system configurations optimized for specific lesions features. The focus in this work is to examine the effects of various beamforming strategies on the discrimination of lesion boundary features.
NC100100 (SONAZOID/sup TM/) is a new contrast agent for ultrasonography consisting of surfactant stabilised perfluorocarbon microbubbles in aqueous suspension. By use of custom developed in vitro sonometry techniques, we have studied relations between the acoustic properties of NC100100 and the microbubble size distribution. By comparing measurements to theoretical predictions of the attenuation spectrum, the authors found that NC100100 microbubbles with a diameter of 3.5 /spl mu/m may be described by a bulk modulus and volume viscosity of 0.6 MPa and 0.015 Pa s, respectively. Using these values in theoretical expressions the authors found that the extinction and scattering cross sections per microbubble volume varies strongly with size, showing distinct maxima with respect to microbubble diameter. Sizes for optimal backscatter per volume were found to 2.9 and 5.3 /spl mu/m, for 5.0 and 2.0 MHz, respectively. Utilising multivariate partial least square regression methods, the predictions from the theoretical model were verified by empirical observations. The results were used to motivate the choice of the microbubble volume concentration as assay and dosage parameter for NC100100. The relevance of this choice was demonstrated by in vitro analysis of more than 50 batches of NC100100, resulting in relatively precise linear correlations between microbubble volume and the acoustic attenuation, fundamental and second harmonic backscatter. In comparison the correlations between these acoustic properties and the microbubble number concentration of the same batches was not significant. These findings were confirmed in vivo in a second harmonic study of myocardial perfusion in dog hearts.
In this work, blood flow data which were taken from middle cerebral artery(MCA) was recorded using Doppler Ultrasonography from 30 healthy individuals at 37-40 weeks gestation age who came to Fırat University Faculty of Medicine Hospital Gynecology and Obstetrics Department. Fetal blood flow data were taken seperately for each condition that female and maternal individuals were singing the lullaby during 2 minutes and non-stimulating. Recorded Doppler signals were processed with fast Fourier transform(FFT) and discrete wavelet transform(DWT) methods to understand whether fetus has sensitivity to maternal voice or not. Furthermore, achievements of FFT and DWT methods researched by comparing their results. Power spectral density(PSD)-frequency changes observed in both method. As a consequence of this work, fetus gave noticeably reactions to maternal voice in 3000-4000 and 8000-10000 frequency bands. This sensitivity to maternal voice can prove that fetus has a learning process with experience in uterus.
A computer support system works in our sonography laboratory providing essential services like the data-base for medical findings combined with the image data-base. The system is based on the digitization of the video-signal output of the sonograph. We have studied the possibility of easing various picture processing methods to further support the diagnosis-making process. We report here on our experience with three particular methods. So far the most successful method we have developed was the quasi-tomographical processing of images. We take up to 16 scans of the same section plane from different positions of the ultrasonic probe. The final image is obtained as a suitable average of the matched images. The method proved to be very helpful in the diagnostic process and is used on an everyday basis. On a somewhat more academic level we are studying the use of simple neural net classifiers to evaluate textural content in the images. The nets are trained on sets of texture patterns and then used to classify the testing samples. We present here two particular examples: classifying malignant tissue in testes and segmentation (sinus vs parenchyma) in kidney. Our experience with these methods is still limited. However, our conjecture is that the texture information can be used as a supportive tool in clinical praxis.
Ultrasonic images are generally affected by multiplicative shot noise. This paper analyzes and models the coefficients of 2D multiresolution wavelet decomposition of logarithmically transformed images using the alpha stable distribution. We propose a new function that performs the nonlinear operation on the data of classifying the coefficients, thus obtaining a new noise- removal method based on multiresolution wavelet decomposition and the alpha stable model.
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