5,631 research outputs found
Mitigation of artifacts due to isolated acoustic heterogeneities in photoacoustic computed tomography using a variable data truncation-based reconstruction method
Photoacoustic computed tomography (PACT) is an emerging computed imaging
modality that exploits optical contrast and ultrasonic detection principles to
form images of the absorbed optical energy density within tissue. If the object
possesses spatially variant acoustic properties that are unaccounted for by the
reconstruction method, the estimated image can contain distortions. While
reconstruction methods have recently been developed to compensate for this
effect, they generally require the object's acoustic properties to be known a
priori. To circumvent the need for detailed information regarding an object's
acoustic properties, we previously proposed a half-time reconstruction method
for PACT. A half-time reconstruction method estimates the PACT image from a
data set that has been temporally truncated to exclude the data components that
have been strongly aberrated. However, this method can be improved upon when
the approximate sizes and locations of isolated heterogeneous structures, such
as bones or gas pockets, are known. To address this, we investigate PACT
reconstruction methods that are based on a variable data truncation (VDT)
approach. The VDT approach represents a generalization of the half-time
approach, in which the degree of temporal truncation for each measurement is
determined by the distance between the corresponding ultrasonic transducer
location and the nearest known bone or gas void location. Computer-simulated
and experimental data are employed to demonstrate the effectiveness of the
approach in mitigating artifacts due to acoustic heterogeneities
Refraction-corrected ray-based inversion for three-dimensional ultrasound tomography of the breast
Ultrasound Tomography has seen a revival of interest in the past decade,
especially for breast imaging, due to improvements in both ultrasound and
computing hardware. In particular, three-dimensional ultrasound tomography, a
fully tomographic method in which the medium to be imaged is surrounded by
ultrasound transducers, has become feasible. In this paper, a comprehensive
derivation and study of a robust framework for large-scale bent-ray ultrasound
tomography in 3D for a hemispherical detector array is presented. Two
ray-tracing approaches are derived and compared. More significantly, the
problem of linking the rays between emitters and receivers, which is
challenging in 3D due to the high number of degrees of freedom for the
trajectory of rays, is analysed both as a minimisation and as a root-finding
problem. The ray-linking problem is parameterised for a convex detection
surface and three robust, accurate, and efficient ray-linking algorithms are
formulated and demonstrated. To stabilise these methods, novel
adaptive-smoothing approaches are proposed that control the conditioning of the
update matrices to ensure accurate linking. The nonlinear UST problem of
estimating the sound speed was recast as a series of linearised subproblems,
each solved using the above algorithms and within a steepest descent scheme.
The whole imaging algorithm was demonstrated to be robust and accurate on
realistic data simulated using a full-wave acoustic model and an anatomical
breast phantom, and incorporating the errors due to time-of-flight picking that
would be present with measured data. This method can used to provide a
low-artefact, quantitatively accurate, 3D sound speed maps. In addition to
being useful in their own right, such 3D sound speed maps can be used to
initialise full-wave inversion methods, or as an input to photoacoustic
tomography reconstructions
Calibration Using Matrix Completion with Application to Ultrasound Tomography
We study the calibration process in circular ultrasound tomography devices
where the sensor positions deviate from the circumference of a perfect circle.
This problem arises in a variety of applications in signal processing ranging
from breast imaging to sensor network localization. We introduce a novel method
of calibration/localization based on the time-of-flight (ToF) measurements
between sensors when the enclosed medium is homogeneous. In the presence of all
the pairwise ToFs, one can easily estimate the sensor positions using
multi-dimensional scaling (MDS) method. In practice however, due to the
transitional behaviour of the sensors and the beam form of the transducers, the
ToF measurements for close-by sensors are unavailable. Further, random
malfunctioning of the sensors leads to random missing ToF measurements. On top
of the missing entries, in practice an unknown time delay is also added to the
measurements. In this work, we incorporate the fact that a matrix defined from
all the ToF measurements is of rank at most four. In order to estimate the
missing ToFs, we apply a state-of-the-art low-rank matrix completion algorithm,
OPTSPACE . To find the correct positions of the sensors (our ultimate goal) we
then apply MDS. We show analytic bounds on the overall error of the whole
process in the presence of noise and hence deduce its robustness. Finally, we
confirm the functionality of our method in practice by simulations mimicking
the measurements of a circular ultrasound tomography device.Comment: submitted to IEEE Transaction on Signal Processin
Visual Quality Enhancement in Optoacoustic Tomography using Active Contour Segmentation Priors
Segmentation of biomedical images is essential for studying and
characterizing anatomical structures, detection and evaluation of pathological
tissues. Segmentation has been further shown to enhance the reconstruction
performance in many tomographic imaging modalities by accounting for
heterogeneities of the excitation field and tissue properties in the imaged
region. This is particularly relevant in optoacoustic tomography, where
discontinuities in the optical and acoustic tissue properties, if not properly
accounted for, may result in deterioration of the imaging performance.
Efficient segmentation of optoacoustic images is often hampered by the
relatively low intrinsic contrast of large anatomical structures, which is
further impaired by the limited angular coverage of some commonly employed
tomographic imaging configurations. Herein, we analyze the performance of
active contour models for boundary segmentation in cross-sectional optoacoustic
tomography. The segmented mask is employed to construct a two compartment model
for the acoustic and optical parameters of the imaged tissues, which is
subsequently used to improve accuracy of the image reconstruction routines. The
performance of the suggested segmentation and modeling approach are showcased
in tissue-mimicking phantoms and small animal imaging experiments.Comment: Accepted for publication in IEEE Transactions on Medical Imagin
Online monitoring instantaneous 2D temperature distributions in a furnace using acoustic tomography based on frequency division multiplexing
The online and accurate capture of dynamic changes in furnace temperature distribution is crucial for production efficiency improvement and international environmental policy compliance in power plants. To achieve this, a measurement system with a reliable online reconstruction capability and high temporal resolution is necessary. This paper presents a novel technique that can improve the temporal resolution of the currently existing acoustic tomography (AT) system using frequency division multiplexing (FDM). This method allows for concurrent transmissions of acoustic signals in several different frequency bands instead of a sequential manner, which leads to more efficient channel utilization and allows all acoustic signals to be acquired at the same time, so that a better temporal uniformity of multipath acoustic signals can be realized. Theoretical analysis and experiments have been conducted to verify the effectiveness of this technique. The results prove that the proposed method can significantly improve the temporal resolution of the AT system while maintaining the accuracy and robustness of the reconstruction
Development, Optimization and Clinical Evaluation Of Algorithms For Ultrasound Data Analysis Used In Selected Medical Applications.
The assessment of soft and hard tissues is critical when selecting appropriate protocols for restorative and regenerative therapy in the field of dental surgery. The chosen treatment methodology will have significant ramifications on healing time, success rate and overall long-time oral health. Currently used diagnostic methods are limited to visual and invasive assessments; they are often user-dependent, inaccurate and result in misinterpretation. As such, the clinical need has been identified for objective tissue characterization, and the proposed novel ultrasound-based approach was designed to address the identified need. The device prototype consists of a miniaturized probe with a specifically designed ultrasonic transducer, electronics responsible for signal generation and acquisition, as well as an optimized signal processing algorithm required for data analysis. An algorithm where signals are being processed and features extracted in real-time has been implemented and studied. An in-depth algorithm performance study has been presented on synthetic signals. Further, in-vitro laboratory experiments were performed using the developed device with the algorithm implemented in software on animal-based samples. Results validated the capabilities of the new system to reproduce gingival assessment rapidly and effectively. The developed device has met clinical usability requirements for effectiveness and performance
A triple-modality ultrasound computed tomography based on full-waveform data for industrial processes
Ultrasound computed tomography (USCT) is gaining interests in many application areas in industrial processes. The recent scientific research focuses on the possible uses of USCT for varied fields of industry such as flow monitoring in pipes, non-destructive inspection, and monitoring of stirred tanks chemical processes. Until now, most transmission tomography (UTT) and reflection tomography (URT) have been demonstrated individually for these applications. A full waveform USCT contain large amount of information on process under evaluation. The developed approach in this paper is focusing on demonstration of a triple modality USCT. First, an optimised transmission image is formed by fusion of time-of-flight (TOF) and acoustic attenuation (AA) images. Secondly, a reflection image is being optimised by using the information from the transmission image. This triple modality method enables integration of a shape-based approach obtained by URT mode with the quantitative image-based approach UTT mode. A delicate combination of the different information provided by various features of the full-wave signal offers optimal and increased spatial resolution and provides complementary information. Verification tests have been implemented using experimental phantoms of different combinations, sizes, and shapes, to investigate the qualitative imaging features. Moreover, experiments with different concentrations solutions further validate the quantitative traits to benefit from both reflection and transmission modes. This work displays the potential of the full-waveform USCT for industrial applications.</p
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