Stensgaardhunt1308

A total number of 3104 data are obtained from simulation and experiments, with 2480 simulated signals for training the CNN model and the remaining 620 simulated data together with 4 experimental signals for verifying the performance of the proposed algorithm. This approach achieves the prediction accuracy of 98.5% on validation set, particularly with the prediction accuracy of 100% for the 4 experimental data. This work proves the feasibility and reliability of the proposed method for quantifying the width of subsurface defects and can be further expanded as an universal approach to various other defects detection, such as defect locations and shapes.The lack of time resolution restricts the quantitative detection of shallow subsurface defects with ultrasonic time-of-flight diffraction (TOFD) technique due to the superposition between lateral wave and diffracted waves from upper and lower tips. In this paper, frequency domain sparsity-decomposability inversion (FDSDI) method was proposed to enhance the time resolution in TOFD based on the sparsity and decomposability of ultrasonic reflection sequence. An optimization problem was formulated in frequency domain by combining l1 and l2 norm constraints. The simulation was performed with a carbon steel model containing a series of shallow subsurface cracks at the depths of 2.0 mm, 2.5 mm, 3.0 mm, 3.5 mm, and 4.0 mm. The relative measurement errors of defect depths and heights were no more than 6.57%, and the depth of dead zone was reduced by 70%. Subsequently, the feasibility of FDSDI method was experimentally verified on a carbon steel specimen with an artificial defect. The defect depth and height were calculated with relative errors within 6.0%. Finally, the detection capacity of FDSDI method was discussed, and the effects of frequency bandwidth, regularization parameter, and noise on inversion results were analyzed by experiments. It is concluded that the FDSDI method decouples the multiple overlapped signals and significantly improves the time resolution to quantify the small defects in dead zone.This paper investigates the dependence of transmitting sensitivity on the top electrode design of piezoelectric micromachined ultrasonic transducers (PMUTs). Two typical top electrodes, namely inner electrode (IE) and outer electrode (OE), are designed and fabricated. The measured transmitting velocities of the fabricated PMUTs at resonance under a drive voltage of 5 Vp-p (peak-to-peak) are 15.36 mm/s for the IE design and 20.67 mm/s for the OE design with a circular diaphragm, and 16.62 mm/s for the IE design and 22.18 mm/s for the OE design with a hexagonal diaphragm, respectively. The OE design demonstrates a transmitting velocity improvement of 34.57% for the circular diaphragm and 33.45% for the hexagonal diaphragm. The improvement is due to the fact that the OE design shows higher quality factor (Q) than the IE counterpart. Moreover, the resonant frequency of the OE design is higher compared to the IE design, which results in a larger acoustic pressure output and hence higher transmitting sensitivity. This work highlights an effective and simple approach for PMUTs to achieve high transmitting sensitivity, which is an important parameter in the applications that require large sound pressures, such as fingerprint imaging, gesture recognition and ranging.Three-dimensional (3D) freehand ultrasound (US) imaging has been applied to the investigation of spine deformity. However, it is a challenge for the current 3D imaging reconstruction algorithms to achieve a balance between image quality and computation time. The objectives of this paper are to implement a new fast reconstruction algorithm which can fulfill the request of immediate demonstration and processing for high-quality 3D spine imaging, and to evaluate the reliability and accuracy of scoliotic curvature measurement when using the algorithm. The Fast Dot-Projection (FDP) algorithm was applied for Voxel-based Nearest Neighbor (VNN), Multiple Plane Interpolation (MPI) and Pixel Nearest Neighbor (PNN) protocols to reduce the reconstruction time. The 3D image volume was reconstructed from the data sets acquired from scoliotic subjects. The computational cost, image characteristics and statistical analyses of curve measurements were compared and evaluated among different reconstruction protocols. The results illustrated that the 3D spine images using the FDP-MPI4 algorithm showed higher brightness (20%), contrast (14%) and SNR (26%) than FDP-VNN. The measurement performed by trainee rater exhibited significant improvement on measurement reliability and accuracy using FDP-MPI4 in comparison with FDP-VNN (p less then 0.01), and the ICC of inter-rater measurement increased from 0.88 to 0.96. The FDP-PNN method could acquire and reconstruct spine images simultaneously and present the results in 1-2 minutes, which showed the potential to provide the approximate real-time visualization for the fast screening.Virtual clinical trials (VCTs) of medical imaging require realistic models of human anatomy. For VCTs in breast imaging, a multi-scale Perlin noise method is proposed to simulate anatomical structures of breast tissue in the context of an ongoing breast phantom development effort. Four Perlin noise distributions were used to replace voxels representing the tissue compartments and Cooper's ligaments in the breast phantoms. Digital mammography and tomosynthesis projections were simulated using a clinical DBT system configuration. Pilaralisib nmr Power-spectrum analyses and higher-order statistics properties using Laplacian fractional entropy (LFE) of the parenchymal texture are presented. These objective measures were calculated in phantom and patient images using a sample of 140 clinical mammograms and 500 phantom images. Power-law exponents were calculated using the slope of the curve fitted in the low frequency [0.1, 1.0] mm-1 region of the power spectrum. The results show that the images simulated with our prior and proposed Perlin method have similar power-law spectra when compared with clinical mammograms. The power-law exponents calculated are -3.10, -3.55, and -3.46, for the log-power spectra of patient, prior phantom and proposed phantom images, respectively. The results also indicate an improved agreement between the mean LFE estimates of Perlin-noise based phantoms and patients than our prior phantoms and patients. Thus, the proposed method improved the simulation of anatomic noise substantially compared to our prior method, showing close agreement with breast parenchyma measures.