A Protocol for Correction of Machine Dependency for Ultrasound Imaging (original) (raw)
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Correction Effects of Machine Dependency on the Textural Parameters of Ultrasound Images
In this paper we presented the effect of correction of machine dependency such as LookUpTable (LUT) correction , Time-Gain-Control(TGC) correction, Diffraction and Focusing correction on the textural parameters of ultrasound images. The group of texture parameters are: histogram parameters , coocurrance matrix parameters , first order gradient parameters , grey level run length matrix parameters ,texture feature Descriptors (TFD parameters),acoustical parameters. Mapping this parameters into color coded display improve the visual inspection to the sonographers. After correction an increase of some textural parameters and decrease of others improve the visual inspection from the ultrasonograohers point of view. These results can improve the segmentation quality of the ultrasound images that will facilitate the build of 3D ultrasound images and can have an accurate measurement from the images and from the 3D data.
Three-Dimensional Acoustic Tissue Model: A Computational Tissue Phantom for Image Analyses
Acoustical Imaging, 2007
A novel methodology to obtain three-dimensional (3D) acoustic tissue models (3DATMs) is introduced. 3DATMs can be used as computational tools for ultrasonic imaging algorithm development and analysis. In particular, 3D models of biological structures can provide great benefit to better understand fundamentally how ultrasonic waves interact with biological materials. As an example, such models were used to generate ultrasonic images that characterize tumor tissue microstructures. 3DATMs can be used to evaluate a variety of tissue types. Typically, excised tissue is fixed, embedded, serially sectioned, and stained. The stained sections are digitally imaged (24-bit bitmap) with light microscopy. Contrast of each stained section is equalized and an automated registration algorithm aligns consecutive sections. The normalized mutual information is used as a similarity measure, and simplex optimization is conducted to find the best alignment. Both rigid and non-rigid registrations are performed. During tissue preparation, some sections are generally lost; thus, interpolation prior to 3D reconstruction is performed. Interpolation is conducted after registration using cubic Hermite polynoms. The registered (with interpolated) sections yield a 3D histologic volume (3DHV). Acoustic properties are then assigned to each tissue constituent of the 3DHV to obtain the 3DATMs. As an example, a 3D acoustic impedance tissue model (3DZM) was obtained for a solid breast tumor (EHS mouse sarcoma) and used to estimate ultrasonic scatterer size. The 3DZM results yielded an effective scatterer size of 32.9 (±6.1) μm. Ultrasonic backscatter measurements conducted on the same tumor tissue in vivo yielded an effective scatterer size of 33 (±8) μm. This good agreement shows that 3DATMs may be a powerful modeling tool for acoustic imaging applications
PHANTOMS AND AUTOMATED SYSTEM FOR TESTING THE RESOLUTION OF ULTRASOUND SCANNERS
1997
Tissue-mimicking phantoms and an automated system have been developed for testing the resolution performance of ultrasound scanners by determining detectability of low to higher contrast spherical lesions over the entire depth of field. Axial, lateral and elevational resolutions are accounted for simuRaneously and equally. Tissue-mimicking spherical simulated lesions are either 3 or 4 mm in diameter and have one of four different intrinsic material contrasts. For each diameter and contrast, there is a set of 109 lesions in a regular array with coplanar centers extending from 0.5-15.5 cm in depth. With the scan slice superimposed on the spheres, the image is frame-grabbed for automated analysis. A diameter-dependent lesion signal-to-noise ratio is computed for each pixel position in the image, exchrdhtg a 5-mm boundary. Two universal thresholds, resulting from maximization of agreement between the automated system and human observers, give rise to a depth range, or "resolution zone", over which detection exists for each type lesion. 0 1997 World Federation for Ultrasound in Medicine & Biology.
A restoration framework for ultrasonic tissue characterization
IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, 2000
Ultrasonic tissue characterization has become an area of intensive research. This procedure generally relies on the analysis of the unprocessed echo signal. Because the ultrasound echo is degraded by the non-ideal system point spread function, a deconvolution step could be employed to provide an estimate of the tissue response that could then be exploited for a more accurate characterization. In medical ultrasound, deconvolution is commonly used to increase diagnostic reliability of ultrasound images by improving their contrast and resolution. Most successful algorithms address deconvolution in a maximum a posteriori estimation framework; this typically leads to the solution of 2 -norm or 1 -norm constrained optimization problems, depending on the choice of the prior distribution. Although these techniques are sufficient to obtain relevant image visual quality improvements, the obtained reflectivity estimates are, however, not appropriate for classification purposes. In this context, we introduce in this paper a maximum a posteriori deconvolution framework expressly derived to improve tissue characterization. The algorithm overcomes limitations associated with standard techniques by using a nonstandard prior model for the tissue response. We present an evaluation of the algorithm performance using both computer simulations and tissue-mimicking phantoms. These studies reveal increased accuracy in the characterization of media with different properties. A comparison with state-of-the-art Wiener and 1 -norm deconvolution techniques attests to the superiority of the proposed algorithm.
Retracted: 3d-method For Determining the Imaging Quality of Ultrasound Probes
2015
Background: Monitoring ultrasonic probe quality remains an important problem which impacts diagnostic accuracy. Here we present a quantitative method to assess probe quality primarily based on measuring probe maximum contrast (dB) and dynamic range. Method: Contrast relevant parameters of 26 transducer models manufactured by five manufacturers were measured with a novel Random Void Phantom (RVP) approach. 3D-data were acquired and analysed to determine image quality. Results: Acoustic contrast values ranging from 15dB to 36dB were observed. Conclusion: By examining artefact producing side lobes, the novel RVP approach presented here permits a quantitative assessment of ultrasound probe quality. DOI : coming soon Corresponding Author: Dr. med. Eckhart Fröhlich, Department of Internal Medicine 1, University of Tübingen, Otfried-Müller-Straße 10, D 72076 Tübingen. Email: eckhart.froehlich@gmx.de
Correction of phasefront aberrations and pulse reverberations in medical ultrasound imaging
The Journal of the Acoustical Society of America, 2003
Suite 1210 Scatterers reflect the transmitted Sound and are individually 551 Fifth Avenue differentiated to provide Singular reference points for cor New York, NY 10176 (US) rection of Signals reflected from the Surrounding tissue. The differentiation is performed by comparison of the third or (21) Appl. No.: 09/773,335 fourth harmonic frequencies of the reflected Signals. To CORRECTION OF PHASEFRONT ABERRATIONS AND PULSE REVERBERATIONS IN MEDICAL ULTRASOUND IMAGING BACKGROUND OF THE INVENTION 0001) 1. Field of the Invention 0002 The present invention is directed to methods for estimating corrections for the image degradation produced in medical ultrasound images by phasefront aberrations and reverberations. The method hence has applications to all Situations were ultrasound imaging is used in medicine, and also other similar Situations of ultrasound imaging. 0003 2. Description of the Related Art 0004. With ultrasound imaging of objects through com plex Structures of tissue, the following effects will degrade the images 0005 i) Variations of the acoustic velocity within the complex tissue Structures produce aberrations of the acoustic wavefront, destroying the focusing of the beam mainlobe and increasing the beam Side lobes. 0006 ii) Interfaces between materials with large differences in acoustic properties can give So Strong reflections of the ultrasound pulse that multiple reflections get large amplitudes. Such multiple reflections are termed pulse reverberations, and add a tail to the propagating ultrasound pulse, which shows as noise in the ultrasound image. 0007. The reduced focusing of the beam main lobe reduces the Spatial resolution in the ultrasound imaging System. The increase in beam Side lobes and the pulse reverberations, introduce additive noise in the image, which is termed acoustic noise as it is produced by the transmitted ultrasound pulse itself. Increasing the transmitted pulse power will hence not improve the power ratio of the Signal to the noise of this type, contrary to what is found with electronic receiver noise. 0008. The materials with largest differences in acoustic properties are muscles, fat, connective tissue, cartilage, bone, air, and the ultrasound transducer itself. Mixtures of
Tissue characterization: Influence of ultrasound setting on texture features in vivo
International Conference on Medical Image Analysis and Clinical Applications, 2010
In diagnostic ultrasound, the echo graphic B-scan texture is an important area of investigation since it can be analyzed to characterize the histological state of internal tissues. An important factor requiring consideration when evaluating ultrasonic tissue texture is the ultrasound setting parameters. The aim of this study is to investigate the effect of varying the gain and the dynamic range
A new method for improvement of image quality in medical ultrasonic diagnostics
2010
The problem of dividing noise and texture elements with regard to specific features of an ultra sonic image is studied. A mathematical model is developed that describes statistical and spectral properties of various elements of the image structure. Based on the mathematical model, the procedure of noise suppres sion is realized. Clinical tests of the method proved its effectiveness.
2019
The influence of ultrasound equipment setup and region of interest (ROI) size on the grey-scale brightness values of ultrasound images was investigated using a muscle phantom. The effects of focus, gain, depth, zoom and ROI size were verified. The Echo Intensity (EI) was estimated using ImageJ software. No significant differences were found in average brightness when changes were made to focus and zoom. EI rose linearly with an increase in gain and decreased linearly with increasing depth of penetration selected on the equipment. EI decreased logarithmically with the increase in size of the ROI. We propose dividing EI values by respective gains as an option to limit the influence of gain changes on EI. Other alternatives must still be investigated regarding the influence of depth on EI. This work is intended to help researchers make decisions based on parameters that may be influenced by their EI measurements, such that valid interpretations can be made.