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1.
Nihon Hoshasen Gijutsu Gakkai Zasshi ; 76(11): 1143-1151, 2020.
Artigo em Japonês | MEDLINE | ID: mdl-33229844

RESUMO

PURPOSE: It is well known that there is a trade-off relationship between image noise and exposure dose in X-ray computed tomography (CT) examination. Therefore, CT dose level was evaluated by using the CT image noise property. Although noise power spectrum (NPS) is a common measure for evaluating CT image noise property, it is difficult to evaluate noise performance directly on clinical CT images, because NPS requires CT image samples with uniform exposure area for the evaluation. In this study, various noise levels of CT phantom images were classified for estimating dose levels of CT images using convolutional neural network (CNN). METHOD: CT image samples of water phantom were obtained with a combination of mAs value (50, 100, 200 mAs) and X-ray tube voltage (80, 100, 120 kV). The CNN was trained and tested for classifying various noise levels of CT image samples by keeping 1) a constant kV and 2) a constant mAs. In addition, CT dose levels (CT dose index: CTDI) for all exposure conditions were estimated by using regression approach of the CNN. RESULT: Classification accuracies for various noise levels were very high (more than 99.9%). The CNN-estimated dose level of CT images was highly correlated (r=0.998) with the actual CTDI. CONCLUSION: CT image noise level classification using CNN can be useful for the estimation of CT radiation dose.


Assuntos
Redes Neurais de Computação , Tomografia Computadorizada por Raios X , Imagens de Fantasmas , Doses de Radiação , Razão Sinal-Ruído
2.
Nihon Hoshasen Gijutsu Gakkai Zasshi ; 76(10): 1009-1016, 2020.
Artigo em Japonês | MEDLINE | ID: mdl-33087646

RESUMO

PURPOSE: The purpose of this paper was to determine the optimal imaging conditions for four-dimensional cone-beam computed tomography (4D-CBCT) using an X-ray tube and a flat-panel detector mounted on a radiotherapy device. METHODS: The optimal imaging conditions were examined by changing the gantry speed (GS) parameter that affected the exposure time. Exposed dose during imaging and image quality of moving phantom were compared between examined conditions. RESULTS: The weighted computed tomography dose index (CTDIW) decreased linearly with increasing GS. However, when GS was 180°/min or faster, the image quality degraded, and errors of 1 mm or more were observed regarding the size of mock tumor in the moving phantom. The accuracy of automatic image matching was within 0.1 mm when GS of 120°/min or slower was chosen. CONCLUSION: From the results of this study, we concluded that GS of 120°/min is the optimum imaging condition. Under this imaging condition, the exposure time and CTDIW can be reduced by about 50% without compromising the accuracy of image registration, compared to the conventional GS of 70°/min. In addition, it has been clarified that there is an event that image reconstruction is not performed correctly due to the influence of phantom artifacts without depending on GS.


Assuntos
Tomografia Computadorizada de Feixe Cônico , Tomografia Computadorizada Quadridimensional , Artefatos , Processamento de Imagem Assistida por Computador , Imagens de Fantasmas
3.
Nihon Hoshasen Gijutsu Gakkai Zasshi ; 76(10): 1025-1034, 2020.
Artigo em Japonês | MEDLINE | ID: mdl-33087648

RESUMO

PURPOSE: The aim of this study was to clarify the optimal post-reconstruction filtering type in the three- dimensional ordered subset expectation maximization (3D-OSEM) method for bone single photon emission computed tomography (SPECT) from image quality and quantitative values. METHOD: We scanned a National Electrical Manufactures Association's body phantom for bone SPECT filled with radioactive solution of 99mTc whose radioactivity concentration was accurately measured. The SPECT images were created using the 3D-OSEM method. Post-reconstruction filtering was performed using a Butterworth filter (BW), a Gaussian filter (GA), and a Hanning filter (HA) with various parameters. The image quality was evaluated by the normalized mean-squared error (NMSE) value and % of contrast-to-noise ratio (QNR17). The image quality was evaluated by the error values between the measured radioactivity concentration and the true radioactivity concentration in the BG region and insert sphere. RESULTS: The minimum NMSE values were 0.034 (BW), 0.036 (GA), and 0.035 (HA), and there was no difference depending on the filter type. The values of QNR17 were 2.5 (BW), 2.6 (GA), and 2.6 (HA), and there was no difference depending on the filter type. The BG region was greatly affected by parameter changes in GA but less by those in BW and HA. The error values of the 37 mm insert sphere were 18.0% (BW), 28.2% (GA), and 26.2% (HA), and BW showed the lowest value. CONCLUSION: Our results suggest that the post-reconstruction filtering type used in the 3D-OSEM method was BW from the image quality and quantitative values.


Assuntos
Algoritmos , Processamento de Imagem Assistida por Computador , Imagens de Fantasmas , Tomografia Computadorizada de Emissão de Fóton Único
4.
Nihon Hoshasen Gijutsu Gakkai Zasshi ; 76(10): 1035-1043, 2020.
Artigo em Japonês | MEDLINE | ID: mdl-33087649

RESUMO

This study evaluated the effects of three types of hybrid iterative reconstruction (IR) on image quality of pediatric body computed tomography images. The image quality components evaluated were noise power spectrum (NPS), task-based modulation transfer function (TTF), and system performance function (SPF). As the IR strength was increased while reducing the radiation dose, the NPS increased in a low-frequency range and the TTF decreased in low-contrast regions. In the low-contrast regions, the calculated SPF decreased over the entire frequency range. Alternatively, in the high-contrast regions, the SPF decreased in the low-frequency regions and increased in the high-frequency regions. The radiation dose reduction using the hybrid IR resulted in the deterioration of the image quality in the low-contrast regions and changes in the spatial frequency characteristics in the high-contrast regions.


Assuntos
Algoritmos , Tomografia Computadorizada por Raios X , Criança , Coleta de Dados , Humanos , Imagens de Fantasmas , Doses de Radiação
5.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 988-991, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018151

RESUMO

The acoustoelectric (AE) effect is that ultrasonic wave causes the conductivity of electrolyte to change in local position. AE imaging is an imaging method that utilizes AE effect. The decoding accuracy of AE signal is of great significance to improve the decoded signal quality and resolution of AE imaging. At present, the envelope function is adopted to decode AE signal, but the timing characteristics of the decoded signal and the source signal are not very consistent. In order to further improve the decoding accuracy, based on envelope decoding, the decoding process of AE signal is investigated. Considering with the periodic property of AE signal in time series, the upper envelope signal is further fitted by Fourier approximation. Phantom experiment validates the feasibility of AE signal decoding by Fourier approximation. And the time sequence diagram decoded with envelope is also compared. The fitted curve can represent the overall trend curve of low-frequency current signal, which has a significant correspondence with the current source signal. The main performance is of the same frequency and phase. Experiment results validate that the proposed decoding algorithm can improve the decoding accuracy of AE signal and be of potential for the clinical application of AE imaging.


Assuntos
Algoritmos , Imagens de Fantasmas
6.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 1299-1302, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018226

RESUMO

We proposed a target-based cone beam computed tomography (CBCT) imaging framework in order to optimize a free three dimensional (3D) source-detector trajectory by incorporating prior 3D image data. We aim to enable CBCT systems to provide topical information about a region of interest (ROI) using a short-scan trajectory with a reduced number of projections. The best projection views are selected by maximizing an objective function fed by the image quality by means of applying different x-ray positions on the digital phantom data. Finally, an optimized trajectory is selected which is applied to a C-arm device able to perform general source-detector positioning. An Alderson-Rando head phantom is used in order to investigate the performance of the proposed framework. Our experiments showed that the optimized trajectory could achieve a comparable image quality in the ROI with respect to the reference C-arm CBCT while using approximately one-quarter of projections. An angular range of 156° was used for the optimized trajectory.


Assuntos
Tomografia Computadorizada de Feixe Cônico Espiral , Tomografia Computadorizada de Feixe Cônico , Imageamento Tridimensional , Imagens de Fantasmas , Cintilografia
7.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 1307-1310, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018228

RESUMO

This paper presents a new 3D CT image reconstruction for limited angle C-arm cone-beam CT imaging system based on total-variation (TV) regularized in image domain and L1-penalty in projection domain. This is motivated by the facts that the CT images are sparse in TV setting and their projections are sinusoid-like forms, which are sparse in the discrete cosine transform (DCT) domain. Furthermore, the artifacts in image domain are directional due to limited angle views, so the anisotropic TV is employed. And the reweighted L1penalty in projection domain is adopted to enhance sparsity. Hence, this paper applied the anisotropic TV-norm and reweighted L1-norm sparse techniques to the limited angle Carm CT imaging system to enhance the image quality in both CT image and projection domains. Experimental results also show the efficiency of the proposed method.Clinical Relevance-This new CT reconstruction approach provides high quality images and projections for practicing clinicians.


Assuntos
Processamento de Imagem Assistida por Computador , Tomografia Computadorizada por Raios X , Algoritmos , Tomografia Computadorizada de Feixe Cônico , Imagens de Fantasmas
8.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 1311-1314, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018229

RESUMO

Metal Artifact Reduction (MAR) plays an important role in Computed Tomography (CT) research and application because severe artifacts degrade the image quality and diagnosis value if metal objects are present in the field of measurement. Although there are already many works for MAR, these works are for fan beam CT, not for cone beam CT, which is the trend and receiving much research attention. In this paper, we extend the Normalized Metal Artifact Reduction (NMAR) for fan beam CT to NMAR3 for cone beam CT, by replacing the linear interpolation in the NMAR with bi-linear interpolation. Experiments are carried out on 17 sets of spine phantom CT. 15 of them have reference CT as ground truth and 2 ones not. Both quantitative and qualitative results verified that NMAR3 outperforms the baseline method, i.e., bi-linear interpolation based method.


Assuntos
Algoritmos , Artefatos , Tomografia Computadorizada de Feixe Cônico , Metais , Imagens de Fantasmas
9.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 1604-1607, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018301

RESUMO

Glaucoma is the second leading cause of blindness globally. Stereophotogrammetry-based optic nerve head topographical imaging systems could potentially allow for objective glaucoma assessment in settings where technologies such as optical coherence tomography and the Heidelberg Retinal Tomograph are prohibitively expensive. In the development of such systems, eye phantoms are invaluable tools for both system calibration and performance evaluation. Eye phantoms developed for this purpose need to replicate the optical configuration of the eye, the related causes of measurement artefacts, and give the possibility to present to the imaging system the targets required for system calibration. The phantoms in the literature that show promise of meeting these requirements rely on custom lenses to be fabricated, making them very costly. Here, we propose a low-cost eye phantom comprising a vacuum formed cornea and commercially available stock bi-convex lens, that is optically similar to a gold-standard reference wide-angle schematic eye model and meets all the compliance and configurability requirements for use with stereo-photogrammetry-based ONH topographical imaging systems. Moreover, its modular design, being fabricated largely from 3D-printed components, lends itself to modification for other applications. The use of the phantom is successfully demonstrated in an ONH imager.


Assuntos
Glaucoma , Disco Óptico , Humanos , Imageamento Tridimensional , Imagens de Fantasmas , Fotogrametria
10.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 1807-1810, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018350

RESUMO

In this paper, for the first time, a triple-mode scan using electromagnetic waves, in the shape of millimeter waves, and ultrasound waves, to obtain B-mode and quasistatic elastography images of a phantom of human breast tissues is shown. A homogeneous phantom composed of nontoxic, low-cost and easy-to-handle materials (i.e. water, oil, gelatin and dishwashing liquid) was produced, with an inclusion made of water and agar. These are intended to mimic, in terms of dielectric properties, healthy adipose tissues and neoplastic tissues, respectively. A millimeter-wave imaging prototype was used to scan the phantom, by implementing a linear synthetic array of 24 antennas with a central working frequency of 30 GHz. The phantom was then scanned using an ultrasound research system and a linear-array probe at 7 MHz, acquiring both B-mode and quasi-static elastography images. The millimeter-wave system showed an excellent ability to detect the target placed at about 1.4 cm depth. Also in the ultrasound case the inclusion was correctly detected as a hypoechoic, stiff mass. This first experimental findings show that millimeter-wave, ultrasound and elasticity imaging can be used jointly to detect tumor-like targets into phantoms mimicking healthy breast tissues. Thus, they provide promising preliminary results to further study the application of this multimodal approach in all those critical cases in which such complementary imaging techniques could be exploited for an enhanced tumor detection, based on tissues dielectric, acoustic and elastic properties.


Assuntos
Neoplasias da Mama , Técnicas de Imagem por Elasticidade , Neoplasias da Mama/diagnóstico por imagem , Elasticidade , Humanos , Imagens de Fantasmas , Ultrassonografia
11.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 2007-2010, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018397

RESUMO

In this paper, we propose a novel framework for time delay estimation in ultrasound elastography. In the presence of high acquisition noise, the state-of-the-art motion tracking techniques suffer from inaccurate estimation of displacement field. To resolve this issue, instead of one, we collect several ultrasound Radio-Frequency (RF) frames from both pre- and post-deformed scan planes to better investigate the data statistics. We formulate a non-linear cost function incorporating all observation frames from both levels of deformations. Beside data similarity, we impose axial and lateral continuity to exploit the prior information of spatial coherence. Most importantly, we consider the continuity among the displacement estimates obtained from different observation RF frames. This novel continuity constraint mainly contributes to the robustness of the proposed technique to high noise power. We efficiently optimize the aforementioned cost function to derive a sparse system of linear equations where we solve for millions of variables to estimate the displacement of all samples of all of the incorporated RF frames simultaneously. We call the proposed algorithm GLobal Ultrasound Elastography using multiple observations (mGLUE). Our primary validation of mGLUE against soft and hard inclusion simulation phantoms proves that mGLUE is capable of obtaining high quality strain map while dealing with noisy ultrasound data. In case of the soft inclusion phantom, Signal-to-Noise Ratio (SNR) and Contrast-to-Noise Ratio (CNR) have improved by 75.37% and 57.08%, respectively. In addition, SNR and CNR improvements of 32.19% and 38.57% have been observed for the hard inclusion case.


Assuntos
Técnicas de Imagem por Elasticidade , Algoritmos , Imagens de Fantasmas , Razão Sinal-Ruído , Ultrassonografia
12.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 2023-2026, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018401

RESUMO

Microwave ablation has become a common treatment method for liver cancers. Unfortunately, microwave ablation success is correlated with clinician's ability for proper electrode placement and assess ablative margins, requiring accurate imaging of liver tumors and ablated zones. Conventionally, ultrasound and computed tomography are utilized for this purpose, yet both have their respective drawbacks. As an alternate approach, electrode displacement elastography offers promise but is still plagued by decorrelation artifacts reducing lesion depiction and visualization. A recent filtering method, namely dictionary representation, has improved contrast-to-noise ratios without reducing delineation contrast. As a supplement to this recent work, this paper evaluates adaptations on this initial dictionary-learning algorithm and applies them to an EDE phantom and 15 in-vivo patient datasets. Two new adaptations of dictionary representations were evaluated, namely a combined dictionary and magnitude-based dictionary representation. When comparing numerical results, the combined dictionary representation algorithm outperforms the previous developed dictionary representation in signal-to-noise (1.54 dB) and contrast-to-noise (0.67 dB) ratios, while a magnitude dictionary representation produces higher noise levels, but improves visualized strain tensor resolution.


Assuntos
Técnicas de Imagem por Elasticidade , Neoplasias Hepáticas , Eletrodos , Humanos , Neoplasias Hepáticas/diagnóstico por imagem , Imagens de Fantasmas
13.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 2027-2030, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018402

RESUMO

Ultrasound elastography is used to estimate the mechanical properties of the tissue by monitoring its response to an internal or external force. Different levels of deformation are obtained from different tissue types depending on their mechanical properties, where stiffer tissues deform less. Given two radio frequency (RF) frames collected before and after some deformation, we estimate displacement and strain images by comparing the RF frames. The quality of the strain image is dependent on the type of motion that occurs during deformation. In-plane axial motion results in high-quality strain images, whereas out-of-plane motion results in low-quality strain images. In this paper, we introduce a new method using a convolutional neural network (CNN) to determine the suitability of a pair of RF frames for elastography in only 5.4 ms. Our method could also be used to automatically choose the best pair of RF frames, yielding a high-quality strain image. The CNN was trained on 3,818 pairs of RF frames, while testing was done on 986 new unseen pairs, achieving an accuracy of more than 91%. The RF frames were collected from both phantom and in vivo data.


Assuntos
Técnicas de Imagem por Elasticidade , Algoritmos , Movimento (Física) , Redes Neurais de Computação , Imagens de Fantasmas
14.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 2035-2038, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018404

RESUMO

In ultrasound imaging, there is a trade-off between imaging depth and axial resolution because of physical limitations. Increasing the center frequency of the transmitted ultrasound wave improves the axial resolution of resulting image. However, High Frequency (HF) ultrasound has a shallower depth of penetration. Herein, we propose a novel method based on Generative Adversarial Network (GAN) for achieving a high axial resolution without a reduction in imaging depth. Results on simulated phantoms show that a mapping function between Low Frequency (LF) and HF ultrasound images can be constructed.


Assuntos
Imagens de Fantasmas , Ultrassonografia
15.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 2051-2054, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018408

RESUMO

Cancer is known to induce significant structural changes to tissue. In most cancers, including breast cancer, such changes yield tissue stiffening. As such, imaging tissue stiffness can be used effectively for cancer diagnosis. One such imaging technique, ultrasound elastography, has emerged with the aim of providing a low-cost imaging modality for effective breast cancer diagnosis. In quasi-static breast ultrasound elastography, the breast is stimulated by ultrasound probe, leading to tissue deformation. The tissue displacement data can be estimated using a pair of acquired ultrasound radiofrequency (RF) data pertaining to pre- and post-deformation states. The data can then be used within a mathematical framework to construct an image of the tissue stiffness distribution. Ultrasound RF data is known to include significant noise which lead to corruption of estimated displacement fields, especially the lateral displacements. In this study, we propose a tissue mechanics-based method aiming at improving the quality of estimated displacement data. We applied the method to RF data acquired from a tissue-mimicking phantom. The results indicated that the method is effective in improving the quality of the displacement data.


Assuntos
Técnicas de Imagem por Elasticidade , Algoritmos , Feminino , Humanos , Imagens de Fantasmas , Reprodutibilidade dos Testes , Ultrassonografia Mamária
16.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 2055-2058, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018409

RESUMO

Many types of cancers are associated with changes in tissue mechanical properties. This has led to the development of elastography as a clinically viable method where tissue mechanical properties are mapped and visualized for cancer detection and staging. In quasi-static ultrasound elastography, a mechanical stimulation is applied to the tissue using ultrasound probe. Using ultrasound radiofrequency (RF) data acquired before and after the stimulation, the tissue displacement field can be estimated. Elasticity image reconstruction algorithms use this displacement data to generate images of the tissue elasticity properties. The accuracy of the generated elasticity images depends highly on the accuracy of the tissue displacement estimation. Tissue incompressibility can be used as a constraint to improve the estimation of axial and, more importantly, the lateral displacements in 2D ultrasound elastography. Especially in clinical applications, this requires accurate estimation of the out-of-plane strain. Here, we propose a method for providing an accurate estimate of the out-of-plane strain which is incorporated in the incompressibility equation to improve the axial and lateral displacements estimation before elastography image reconstruction. The method was validated using in silico and tissue mimicking phantom studies, leading to significant improvement in the estimated displacement.


Assuntos
Técnicas de Imagem por Elasticidade , Algoritmos , Processamento de Imagem Assistida por Computador , Imagens de Fantasmas , Ultrassonografia
17.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 2067-2070, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018412

RESUMO

Ultrasound data often suffers from an excessive amount of noise especially from deep tissue or in synthetic aperture imaging where the acoustic wave is weak. Such noisy data renders Time Delay Estimation (TDE) inaccurate in the context of ultrasound elastography. Herein, a novel two-step elastography technique is presented to ensure accurate TDE while dealing with noisy ultrasound data. In the first step, instead of one, we acquire several Radio-Frequency (RF) frames from both pre- and post-deformed positions of the tissue. We stack the frames collected from pre- and post-deformed planes in separate data matrices. Since each set is collected from the same level of tissue compression, we assume that the Casorati data matrices exhibit underlying low-rank structures, which are sought by taking the low-rank and sparse decomposition framework into account. This Robust Principal Component Analysis (RPCA) approach removes the random noise from the datasets as sparse error components. In the second step, we select one frame from each denoised ensemble and employ GLobal Ultrasound Elastography (GLUE) to perform the strain elastography. We call the proposed technique RPCA-GLUE. Our preliminary validation of RPCA-GLUE against simulation phantoms containing hard and soft inclusions proves its robustness to large noise. Substantial improvement in Signal-to-Noise Ratio (SNR) and Contrast-to-Noise Ratio (CNR) has also been observed. Simulation results show that in the presence of large noise, the proposed method substantially improves CNR from 5.0 to 22.6 in a soft inclusion and from 2.2 to 21.7 in a hard inclusion phantom.


Assuntos
Técnicas de Imagem por Elasticidade , Algoritmos , Imagens de Fantasmas , Ondas de Rádio , Razão Sinal-Ruído
18.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 2071-2074, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018413

RESUMO

Ultrasound elastography is a non-invasive technique for detecting pathological alterations in tissue. It is known that pathological alteration of tissue often has a direct impact on its elastic modulus, which can be revealed using elastography. For estimating elastic modulus, we need to estimate both axial and lateral displacement accurately. Current state of the art elastography techniques provide a substantially less accurate lateral displacement field as compared to the axial displacement field. One of the most important factors in poor lateral estimation is a low sampling frequency in the lateral direction. In this paper, we use synthetic aperture beamforming to benefit from its capability of high sampling frequency in the lateral direction. We compare highly sampled data and focused line per line beam formed data by feeding them to our recently published elastography method, OVERWIND [1]. According to simulation and phantom experiments, not only the lateral displacement estimation is substantially improved, but also the axial displacement estimation is improved.


Assuntos
Técnicas de Imagem por Elasticidade , Módulo de Elasticidade , Imagens de Fantasmas
19.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 2075-2078, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018414

RESUMO

Convolutional Neural Networks (CNN) have been extensively used for many computer vision applications including optical flow estimation. Although CNNs have been very successful in optical flow problem, they have been rarely used for displacement estimation in Ultrasound Elastography (USE) due to vast differences between ultrasound data and computer vision images. In USE, a main goal is to obtain the strain image which is the derivative of the axial displacement in axial direction; therefore, a very accurate displacement estimation is required. Radio Frequency (RF) data is needed to obtain accurate displacement estimation. RF data contains high frequency contents which cannot be downsampled without significant loss of information, in contrast to computer vision images. We propose a novel technique to utilize LiteFlowNet for USE. For the first time, we incorporate analytic signal to improve the quality of the displacement estimation. We show that this network with the designed inputs is more suitable for USE compared to more complex networks such as FlowNet2. The network is adopted to our application and it is compared with FlowNet2 and a state-of-the-art elastography method (GLUE). The results show that this network performs well and comparable to GLUE. Furthermore, not only this network is faster and has lower memory footprint compared to FlowNet2, but also it obtains higher quality strain images which makes it suitable for portable and real-time elastography devices.


Assuntos
Técnicas de Imagem por Elasticidade , Algoritmos , Redes Neurais de Computação , Imagens de Fantasmas , Ultrassonografia
20.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 2079-2083, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018415

RESUMO

The placenta is a vital organ for growth and development of the fetus. Shear Wave Absolute Vibro-Elastography (SWAVE) is a new elastography technique proposed to detect placenta disorders. Elastography involves applying a force on the tissue and measuring the resulting tissue deformation. All types of compression cause the tissue to expand in three directions given the biological tissues are nearly incompressible. Hence, 3D displacement estimation should lead to the most accurate elasticity reconstruction compared to the traditional 1D methods. Previous studies estimated 3D displacements over ultrasound volumes mostly for quasi-static compression to generate strain images. However, accurate displacement tracking of dynamic motion continues to be a challenge. In this work, a novel volumetric regularized algorithm, 3D GLobal Ultrasound Elastography (GLUE3D), is presented to estimate the 3D displacement over a volume of ultrasound data, following by a 3D Young's modulus reconstruction. The proposed method outperforms the previous 2D method over a volume and is compared with a 3D technique using phantom data for which the elasticity are provided by the values from magnetic resonance elastography on the same phantom and also the manufacturer reference numbers. We then present Young's modulus reconstruction results obtained from clinical data of placenta which shows more uniform elasticity maps compared to the traditional 1D displacement measurements over a volume of ultrasound data. Furthermore, the dependency of the elasticity values to the frequency is investigated in this study.


Assuntos
Técnicas de Imagem por Elasticidade , Módulo de Elasticidade , Elasticidade , Feminino , Humanos , Imagens de Fantasmas , Placenta/diagnóstico por imagem , Gravidez
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