Zone-Shrinking Fresnel Zone Travel-Time Tomography for Sound Speed Reconstruction in Breast USCT.

Many studies have been carried out on ultrasound computed tomography (USCT) for its potential application in breast imaging. The sound speed (SS) image modality in USCT can help doctors diagnose the breast cancer, as the tumor usually has a higher sound speed than normal tissues. Travel time is commonly used to reconstruct SS image. Raypath travel-time tomography (RTT) assumes that the sound wave travels through a raypath. RTT is computationally efficient but with low contrast to noise ratio (CNR). Fresnel zone travel-time tomography (FZTT) is based on the assumption that the sound wave travels through an area called the Fresnel zone. FZTT can provide SS image with high CNR but low accuracy due to the wide Fresnel zone. Here, we propose a zone-shrinking Fresnel zone travel-time tomography (ZSFZTT), where a weighting factor is adopted to shrink the Fresnel zone during the inversion process. Numerical phantom and in vivo breast experiments were performed with ZSFZTT, FZTT, and RTT. In the numerical experiment, the reconstruction biases of size by ZSFZTT, FZTT, and RTT were 0.2%~8.3%, 2.3%~31.7%, and 1.8%~25%; the reconstruction biases of relative SS value by ZSFZTT, FZTT, and RTT were 24.7%~42%, 53%~60.8%, and 30.3%~47.8%; and the CNR by ZSFZTT, FZTT, and RTT were 67.7~96.6, 68.5~98, and 1.7~2.7. In the in vivo breast experiment, ZSFZTT provided the highest CNR of 8.6 compared to 8.1 by FZTT and 1.9 by RTT. ZSFZTT improved the reconstruction accuracy of size and the relative reconstruction accuracy of SS value compared to FZTT and RTT while maintaining a high CNR similar to that of FZTT.

The Design and Analysis of Split Row-Column Addressing Array for 2-D Transducer.

For 3-D ultrasound imaging, the row-column addressing (RCA) with 2N connections for an N × N 2-D array makes the fabrication and interconnection simpler than the fully addressing with N² connections. However, RCA degrades the image quality because of defocusing in signal channel direction in the transmit event. To solve this problem, a split row-column addressing scheme (SRCA) is proposed in this paper. Rather than connecting all the elements in the signal channel direction together, this scheme divides the elements in the signal channel direction into several disconnected blocks, thus enables focusing beam access in both signal channel and switch channel directions. Selecting an appropriate split scheme is the key for SRCA to maintaining a reasonable tradeoff between the image quality and the number of connections. Various split schemes for a 32 × 32 array are fully investigated with point spread function (PSF) analysis and imaging simulation. The result shows the split scheme with five blocks (4, 6, 12, 6, and 4 elements of each block) can provide similar image quality to fully addressing. The splitting schemes for different array sizes from 16 × 16 to 96 × 96 are also discussed.

[Research on Reconstruction of Ultrasound Diffraction Tomography Based on Compressed Sensing].

Ultrasound diffraction tomography (UDT) possesses the characteristics of high resolution, sensitive to dense tissue, and has high application value in clinics. To suppress the artifact and improve the quality of reconstructed image, classical interpolation method needs to be improved by increasing the number of projections and channels, which will increase the scanning time and the complexity of the imaging system. In this study, we tried to accurately reconstruct the object from limited projection based on compressed sensing. Firstly, we illuminated the object from random angles with limited number of projections. Then we obtained spatial frequency samples through Fourier diffraction theory. Secondly, we formulated the inverse problem of UDT by exploring the sparsity of the object. Thirdly, we solved the inverse problem by conjugate gradient method to reconstruct the object. We accurately reconstructed the object using the proposed method. Not only can the proposed method save scanning time to reduce the distortion by respiratory movement, but also can reduce cost and complexity of the system. Compared to the interpolation method, our method can reduce the reconstruction error and improve the structural similarity.

Normalized Spatial Autocorrelation in Ultrasound B-Mode Imaging for Point-Scatterer Detection.

OBJECTIVE: Point-scatterer detection plays a key role in medical ultrasound B-mode imaging. Speckle noise and insufficient spatial resolution are important factors affecting point-scatterer detection. To address this issue, normalized spatial autocorrelation in ultrasound B-mode imaging (NSACB) is proposed. METHODS: First, the acquired data are pre-processed by adding Gaussian white noise (GWN) with a certain signal-to-Gaussian white noise ratio (SGWNR). Next, normalized spatial autocorrelation is applied to the pre-processed data, and the data are divided into several new signals with different spatial lags. Then, the new signals are performed unsigned delay multiply and sum. Finally, the NSACB beamformed data are bandpass filtered by extracting the frequency component around twice the center frequency. Simulated and in vitro experiments were designed for validation. RESULTS: Simulations revealed that the lateral resolution of NSACB measured by the -6-dB mainlobe width can reach as high as 11.11% of delay and sum (DAS), 25.01% of filtered delay multiply and sum (F-DMAS) and 50% of LAG-FDMAS-SCF. The sidelobe level of the NSACB can be reduced at most by 28 dB. Experimental results of simple and complex scatterer phantoms indicate the image resolution of the proposed NSACB can even reach up to 18.76% of DAS, 27.28% of F-DMAS and 14.29% of LAG-FDMAS-SCF. Compared with these methods, the proposed NSACB can reduce the sidelobe level at least by 18 dB. CONCLUSION: Although the proposed method causes loss of the ability to observe hypo-echoic structures, these results suggest future work to determine the ability to detect breast microcalcifications, kidney stones, biopsy needle tracking and other scenarios requiring scatterer detection.

A coupling, stabilizing, and shaping strategy for breast ultrasound computed tomography (USCT) with a ring array transducer.

Breast ultrasound computed tomography (USCT) has been gradually promoted to clinical application after years of rapid development. Compared with the traditional handheld ultrasound scanning method, the scanning plane of USCT is fixed at the coronal plane, and the scanning path is designed in advance; the acoustic window is not in direct contact with the breast, a lot of coupling medium (usually degassed water is used to fill the gaps between the probe and breast. The clinical application of breast USTC faces challenges: (1) the processes of water degassing, heating, filling, draining, and cleaning prolong the entire scan cycle and reduce patient throughput. (2) The breast is not stabilized and slight movements of the breast may cause motion artifacts in the USCT images. (3) The non-normal incidence of ultrasound into the breast causes reflected and transmitted signals received with a low signal-to-noise ratio (SNR) or even unable to be detected. This article proposes a coupling, stabilizing, and shaping strategy for the clinical application of USCT with a ring array transducer. The solid gel coupling agent (SGCA) is applied for coupling, and a set of SGCA moldings is designed to stabilize and shape the breast during scanning, the breast shape and size which vary from person to person are simplified into several models. The preparation time is reduced to less than 1 min by replacing disposable moldings. The results show that the breast after shaping is close to round in the coronal plane, and slopes of the breast skin are limited in the sagittal and transverse planes, the breast subcutaneous tissue (fat and glands) has a better contrast-to-noise ratio (CNR) and can be better distinguished in the reflection images than that of the breast without shaping. The mean value of the raw beamformed data which represents the reflection signal amplitude of breast subcutaneous tissue after shaping shows 1.5 times that of the breast without shaping, the signal-to-noise ratio (SNR) of the raw transmission signal data after breast shaping is overall higher than that of the breast without shaping. The application of SGCA moldings for breast coupling, stabilizing, and shaping also benefits establishing a standardized scanning process, the standardized diagnosis of the breast lesion, and the localization of breast lesions.

Reconstruction of reflection ultrasound computed tomography with sparse transmissions using conditional generative adversarial network.

Ultrasound computed tomography (UCT) has attracted increasing attention due to its potential for early breast cancer diagnosis and screening. Synthetic aperture imaging is a widely used means for reflection UCT image reconstruction, due to its ability to produce isotropic and high-resolution anatomical images. However, obtaining fully sampled UCT data from all directions over multiple transmissions is a time-consuming scanning process. Even though sparse transmission strategy could mitigate the data acquisition complication, image quality reconstructed by traditional Delay and Sum (DAS) methods may degrade substantially. This study presents a deep learning framework based on a conditional generative adversarial network, UCT-GAN, to efficiently reconstruct reflection UCT image from sparse transmission data. The evaluation experiments using breast imaging data in vivo show that the proposed UCT-GAN is able to generate high-quality reflection UCT images when using 8 transmissions only, which are comparable to that reconstructed from the data acquired by 512 transmissions. Quantitative assessment in terms of peak signal-to-noise ratio (PSNR), normalized mean square error (NMSE), and structural similarity index measurement (SSIM) show that the proposed UCT-GAN is able to efficiently reconstruct high-quality reflection UCT images from sparsely available transmission data, outperforming several other methods, such as RED-GAN, DnCNN-GAN, BM3D. In the experiment of 8-transmission sparse data, the PSNR is 29.52 dB, and the SSIM is 0.7619. The proposed method has the potential of being integrated into the UCT imaging system for clinical usage.

Full waveform inversion using frequency shift envelope-based global correlation norm for ultrasound computed tomography.

Many studies have been carried out on ultrasound computed tomography (USCT) for its ability to offer quantitative measurements of tissue sound speed. Full waveform inversion (FWI) is a technique for reconstructing high-resolution sound speed images by iteratively minimizing the difference between the observed ultrasound data and the synthetic data based on the waveform equation. However, FWI suffers from cycle-skipping, which usually causes FWI convergence at a local minimum. Cycle-skipping occurs when the phase difference between the observed data and the synthetic data exceeds half a cycle. The simplest way to avoid cycle-skipping is to use low-frequency information for reconstruction. Nevertheless, in imaging systems, the response bandwidth of the probe is limited, and reliable low-frequency information often exceeds the response band. Therefore, it is a challenge to perform FWI imaging and avoid cycle-skipping problems without low-frequency information. In this paper, we propose a frequency shift envelope-based global correlation norm (FSEGCN), where an artificial source wavelet with a lower frequency is adopted to calculate synthetic data. FSEGCN compared with FWI, envelope inversion (EI), global correlation norm (GCN), envelope-based global correlation norm (EGCN) through concentric circle phantom without low-frequency information. The experimental results demonstrated the capability of the proposed method to recover the sound speed close to the exact model in the absence of low-frequency information, whereas FWI, EI, GCN, and EGCN cannot. Experiments on phantoms of the human head and calf show that artificial source wavelets can reduce image artifacts and enhance reconstruction robustness, when original low-frequency information is absent.

Effect of spatial-domain pulse width on the resolution of scattering images in ultrasound computed tomography.

Full-aperture tomography (FAT) is the major image reconstruction method for a circular ring array (CRA)-based ultrasound computed tomography (USCT) system. The FAT technique requires transferring the reconstruction process from the temporal domain to the spatial domain, during which the imaging resolution of the USCT is degraded by the spatial-domain pulse width (SDPW) of backprojection areas. To tackle this challenge, this study investigates the characteristics of the SDPW and how it degrades the image resolution. We show that the SDPW depends on the frequency of the ultrasound and the position of the transmitting elements, receiving elements and the imaging point. To quantify the deterioration of image resolution associated with the position of the transmitting and receiving elements, a SDPW broadening factor (SDPWBF) is introduced. The results of numerical simulation show a smaller SDPWBFprovides a better reflection image resolution, and the distribution of SDPWBFshows that a shorter distance between the receiving element and the transmitting element yields a smaller SDPWBF. The SDPWBFis therefore able to be an indicator of selecting the signals acquired from the transmitting and receiving elements to perform optimal image resolution. Single-scatterer phantom andinvivoexperiments demonstrate how the SDPWBFaffects the USCT image spatial resolution and signal-to-noise ratio (SNR), and the results agree well with the theoretical predictions.

Time-of-flight completion in ultrasound computed tomography based on the singular value threshold algorithm.

Ultrasound computed tomography (USCT) has been developed for breast tumor screening. The sound-speed modal of USCT can provide quantitative sound-speed values to help tumor diagnosis. Time-of-flight (TOF) is the critical input in sound-speed reconstruction. However, we found that the missing data problem in the detected TOF causes artifacts on the reconstructed sound-speed images, which may affect the tumor identification. In this study, to address the missing TOF data problem, we first adopted the singular value threshold (SVT) algorithm to complete the TOF matrix. The threshold value in SVT is difficult to determine, so we proposed a selection strategy, that is, to enumerate the threshold values as the multiples of the maximum singular value of the incomplete matrix and then evaluate the image quality to select the proper threshold value. In the numerical breast phantom experiment, the artifacts are eliminated, and the accuracy is higher than the accuracy of the compared methods. In the in vivo experiment, we reconstructed the sound-speed image of the breast of a volunteer with invasive breast cancer, and the SVT algorithm improved the image sharpness. The completion of DTOF based on SVT gives better accuracy than the compared methods, but too large a threshold value decreases the accuracy. In the future, the selection method of the threshold value needs further research, and more USCT cases should be included in the experiments.

Combination of variational mode decomposition and coherent factor for ultrasound computer tomography.

BACKGROUND: Ultrasound computed tomography (USCT) is a promising technique for improving the detection of breast cancer. Image quality of USCT has a major impact on the breast cancer diagnosis. OBJECTIVE: This paper investigates the combination of variational mode decomposition (VMD) and coherent factor method for USCT image quality enhancement. METHODS: The signals can be decomposed into multiple intrinsic mode functions (IMFs) sifting through the frequency by VMD method. Refactoring the remaining IMFs, spatio-temporally smoothed coherence factor (STSCF) beamforming method is applied to reconstructed data for USCT. RESULTS: The validation of combination the VMD and STSCF is described through the breast phantom experiment and in vivo experiments. The evaluation indicators such as contrast ratio (CR), contrast to noise ratio (CNR) and signal to noise ratio (SNR) have been better improved in the experimental results. For the breast phantom, the proposed method gives a higher resolution and the better contrast properties for the hyperechoic cyst. The borders of cysts and tumors in the breast phantom can be distinguished clearly. For volunteer breast experiments, artifacts are removed more efficiently while the clutters are suppressed simultaneously. CONCLUSION: The combination of VMD and STSCF can further reduce the noise and suppress the side lobes.

Design and Implementation of a Modular and Scalable Research Platform for Ultrasound Computed Tomography.

Increasing attention has been attracted to the research of ultrasound computed tomography (USCT). This article reports the design considerations and implementation details of a novel USCT research system named UltraLucid, which aims to provide a user-friendly platform for researchers to develop new algorithms and conduct clinical trials. The modular design strategy is adopted to make the system highly scalable. A prototype has been assembled in our laboratory, which is equipped with a 2048-element ring transducer, 1024 transmit (TX) channels, 1024 receive (RX) channels, two servers, and a control unit. The prototype can acquire raw data from 1024 channels simultaneously using a modular data acquisition and a transfer system, consisting of 16 excitation and data acquisition (EDAQ) boards. Each EDAQ board has 64 independent TX and RX channels and 4-Gb Ethernet interfaces for raw data transmission. The raw data can be transferred to two servers at a theoretical rate of 64 Gb/s. Both servers are equipped with a 10.9-TB solid-state drive (SSD) array that can store raw data for offline processing. Alternatively, after processing by onboard field-programmable gate arrays (FPGAs), the raw data can be processed online using multicore central processing units (CPUs) and graphics processing units (GPUs) in each server. Through control software running on the host computer, the researchers can configure parameters for transmission, reception, and data acquisition. Novel TX-RX scheme and coded imaging can be implemented. The modular hardware structure and the software-based processing strategy make the system highly scalable and flexible. The system performance is evaluated with phantoms and in vivo experiments.

Respiratory motion correction in free-breathing ultrasound image sequence for quantification of hepatic perfusion.

PURPOSE: Evaluation of regional hepatic perfusion by contrast-enhanced ultrasound (CEUS) is helpful to the differential diagnosis of focal liver lesions (FLLs). Because most patients cannot hold their breath for the duration of the entire hepatic perfusion scan, ultrasonographists tend to employ free-breathing acquisition method. A new strategy using a combination of template matching and frame selection is proposed to correct the respiratory motion and improve the accuracy of the quantification evaluation of the perfusion. METHODS: Considering that most commercial ultrasound machines can provide a dual display mode for simultaneously visualizing contrast and tissue images, the registration of the contrast images was achieved by the registration of the corresponding tissue images. After the template was located, the rough search space was estimated using a priori knowledge of the tumor location in the free-breathing image sequence. Then, a simple double-selection method was proposed to select the similar images from a large number of successive matched images via global and local threshold settings. In this method, alpha and m were the offset of the global threshold and the time interval for setting local sampling range, respectively. These two parameters were also investigated. The strategy was tested on ten liver CEUS acquisitions with a handle probe by using sum of absolute differences (SAD) metric. The visual evaluation for 2D image sequences and the extracted time-intensity curves from the regions of interest were performed. Simpler curve descriptors of the motion-uncorrected and motion-corrected image sequences were calculated on a pixel-by-pixel basis and evaluated as parametric perfusion maps. The quality of these parametric images was compared, in terms of both the accuracy and spatial resolution. For the corrected and uncorrected sequences, their mean deviation values (mDVs) and mean quality-of-fits (mQOFs) were measured. RESULTS: When alpha and m were both set to 0.5, 9.20 +/- 3.22% of the total number of frames were selected. After the motion correction, the mDVs of all the image sequences decreased from 21.69 +/- 2.80 to 13.78 +/- 2.68. The mQOFs of all the corrected sequences increased by an average of 15.32 +/- 5.13%. The quality of curve fitting and the corresponding parametric imaging computed on motion-corrected sequences were improved. On the average, the motion correction of a sequence containing about 100 frames was performed in approximately 3 min using MATLAB, whereas a completely manual approach requires approximately 10 min. CONCLUSIONS: The image-based strategy independent of the tumor size can quickly correct respiratory motion in CEUS image sequences. Simple manual operation is only needed, such as the selection of the template image and search space. It is user-friendly and suitable for most clinical cases affected by adverse factors of sampling. Due to the merit of the saving time, this strategy can be widely applied to clinical practice, and the diagnostic efficiency of FLLs will be improved. Moreover, the correction strategy is a key preprocessing step toward local quantification of hepatic perfusion studies.

Ultrasound Planar Array Imaging Metric Analysis.

Planar array design makes the tradeoff between the 3-D ultrasound image quality and the system complexity based on the imaging metrics. The -6 dB mainlobe width (MW), mainlobe-to-sidelobe energy ratio (MSR), peak sidelobe level (PSL), and average sidelobe level (ASL) are the common imaging metrics for linear array design. MW is used for lateral resolution evaluation, while MSR, PSL, and ASL are adopted for contrast resolution evaluation. However, simulation results show that these metrics cannot fully evaluate the planar array performance. This article proposes several new imaging metrics for planar array: averaged mainlobe acoustic energy level and mainlobe energy density curve are the lateral resolution metrics, while mainlobe-to-sidelobe energy density ratio is the contrast resolution metric. The new metrics take into account the influence of the mainlobe area on the planar array performance evaluation. PSF analysis and simulated images show that the proposed metrics can evaluate planar array performance more accurately than the existing metrics. Moreover, uniform planar arrays with different scales and random sparse arrays are tested to show how to use the proposed metrics in planar array design.

Extrapolating microdomain Ca(2+) dynamics using BK channels as a Ca(2+) sensor.

Ca(2+) ions play crucial roles in mediating physiological and pathophysiological processes, yet Ca(2+) dynamics local to the Ca(2+) source, either from influx via calcium permeable ion channels on plasmic membrane or release from internal Ca(2+) stores, is difficult to delineate. Large-conductance calcium-activated K(+) (BK-type) channels, abundantly distribute in excitable cells and often localize to the proximity of voltage-gated Ca(2+) channels (VGCCs), spatially enabling the coupling of the intracellular Ca(2+) signal to the channel gating to regulate membrane excitability and spike firing patterns. Here we utilized the sensitivity and dynamic range of BK to explore non-uniform Ca(2+) local transients in the microdomain of VGCCs. Accordingly, we applied flash photolysis of caged Ca(2+) to activate BK channels and determine their intrinsic sensitivity to Ca(2+). We found that uncaging Ca(2+) activated biphasic BK currents with fast and slow components (time constants being τf ≈ 0.2 ms and τs ≈ 10 ms), which can be accounted for by biphasic Ca(2+) transients following light photolysis. We estimated the Ca(2+)-binding rate constant kb (≈1.8 × 10(8) M(-1) s(-1)) for mSlo1 and further developed a model in which BK channels act as a calcium sensor capable of quantitatively predicting local microdomain Ca(2+) transients in the vicinity of VGCCs during action potentials.

Preliminary work of real-time ultrasound imaging system for 2-D array transducer.

Ultrasound (US) has emerged as a non-invasive imaging modality that can provide anatomical structure information in real time. To enable the experimental analysis of new 2-D array ultrasound beamforming methods, a pre-beamformed parallel raw data acquisition system was developed for 3-D data capture of 2D array transducer. The transducer interconnection adopted the row-column addressing (RCA) scheme, where the columns and rows were active in sequential for transmit and receive events, respectively. The DAQ system captured the raw data in parallel and the digitized data were fed through the field programmable gate array (FPGA) to implement the pre-beamforming. Finally, 3-D images were reconstructed through the devised platform in real-time.

Diagnosis of thyroid nodules using virtual touch tissue quantification value and anteroposterior/transverse diameter ratio.

This paper proposes an effective approach to differential diagnosis of thyroid nodules using a hierarchical classification model based on the Virtual Touch tissue quantification (VTQ) value and anteroposterior/transverse diameter (A/T) ratio. One hundred twenty nodules (92 benign, 28 malignant) were analyzed using this approach by combining the quantitative elastic characteristic with the conventional sonographic feature. First, nodules were classified as benign (VTQ values <2.27 m/s), malignant (VTQ values >2.73 m/s) and indeterminate (2.27 m/s ≤ VTQ values ≤2.73 m/s) using two cutoff points selected on the basis of receiver operating characteristic analysis. Second, the indeterminate nodules were separated into malignant and benign nodules using an A/T ratio ≥1. The advantage of this approach was that it could alleviate the limitation of an overlap in VTQ values between benign and malignant nodules. According to the pathologic results, the accuracy of this approach was 95%. The proposed approach may potentially improve diagnostic accuracy.

Sparse-view ultrasound diffraction tomography using compressed sensing with nonuniform FFT.

Accurate reconstruction of the object from sparse-view sampling data is an appealing issue for ultrasound diffraction tomography (UDT). In this paper, we present a reconstruction method based on compressed sensing framework for sparse-view UDT. Due to the piecewise uniform characteristics of anatomy structures, the total variation is introduced into the cost function to find a more faithful sparse representation of the object. The inverse problem of UDT is iteratively resolved by conjugate gradient with nonuniform fast Fourier transform. Simulation results show the effectiveness of the proposed method that the main characteristics of the object can be properly presented with only 16 views. Compared to interpolation and multiband method, the proposed method can provide higher resolution and lower artifacts with the same view number. The robustness to noise and the computation complexity are also discussed.

Phase grouping-based needle segmentation in 3-D trans-rectal ultrasound-guided prostate trans-perineal therapy.

A robust and efficient needle segmentation method used to localize and track the needle in 3-D trans-rectal ultrasound (TRUS)-guided prostate therapy is proposed. The algorithmic procedure begins by cropping the 3-D US image containing a needle; then all voxels in the cropped 3-D image are grouped into different line support regions (LSRs) based on the outer product of the adjacent voxels' gradient vector. Two different needle axis extraction methods in the candidate LSR are presented: least-squares fitting and 3-D randomized Hough transform. Subsequent local optimization refines the position of the needle axis. Finally, the needle endpoint is localized by finding an intensity drop along the needle axis. The proposed methods were validated with 3-D TRUS tissue-mimicking agar phantom images, chicken breast phantom images and patient images obtained during prostate cryotherapy. The results of the in vivo test indicate that our method can localize the needle accurately and robustly with a needle endpoint localization accuracy <1.43 mm and detection accuracy >84%, which are favorable for 3-D TRUS-guided prostate trans-perineal therapy.

Spatio-temporally smoothed coherence factor for ultrasound imaging.

Coherence-factor-like beamforming methods, such as the coherence factor (CF), the phase coherence factor (PCF), or the sign coherence factor (SCF), have been applied to suppress side and/or grating lobes and clutter in ultrasound imaging. These adaptive weighting factors can be implemented effectively with low computational complexity to improve image contrast properties. However, because of low SNR, the resulting images may suffer from deficiencies, including reduced overall image brightness, increased speckle variance, black-region artifacts surrounding hyperechoic objects, and underestimated magnitudes of point targets. To overcome these artifacts, a new spatio-temporal smoothing procedure is introduced to the CF method. It results in a smoothed coherence factor which measures the signal coherence among the beamsums of the divided subarrays over the duration of a transmit pulse. In addition, the procedure is extended to the SCF using the sign bits of the received signals. Simulated and real experimental data sets demonstrate that the proposed methods can improve the robustness of the CF and SCF with reduced speckle variance and significant removal of black-region artifacts, while preserving the ability to suppress clutter. Consequently, image contrast can be enhanced, especially for anechoic cysts.

Variability in the morphologic assessment of human sperm: use of the strict criteria recommended by the World Health Organization in 2010.

OBJECTIVE: To determine the variability in the recognition of normal sperm and various sperm defects using the strict criteria recommended by the World Health Organization (5th edition, 2010). DESIGN: Sperm morphologic assessment by three experienced evaluators. SETTING: Image processing laboratory and reproduction research institute. PATIENT(S): Semen donors from a sperm bank. INTERVENTION(S): The morphology of 5,296 sperm was evaluated using statistical analyses of variability. MAIN OUTCOME MEASURE(S): The proportion and coefficients of variation (CVs) of normal sperm, defects of specific parts, and the categories of defects were measured. The degree of agreement between any two of the three evaluators was calculated. The multiple anomalies index, teratozoospermia index, sperm deformity index, and the CVs were also measured. RESULT(S): The CVs of normal sperm, multiple anomalies index, teratozoospermia index, and sperm deformity index were 4.80%, 4.14%, 5.75%, and 6.81%, respectively. A broader range (4.80%-132.97%) of CVs was observed for the recognition of various defects. The coefficients of the degree of agreement concerning specific morphologic parts of sperm varied (0.387-0.607), with lower relative values for the head and mid-piece than for the tail and cytoplasm. CONCLUSION(S): The sperm head is more difficult to evaluate than the other parts using the criteria recommended by the World Health Organization in 2010. The degree of agreement concerning specific parts and various defects varied in broad ranges. A stricter definition for each defect is needed.