Machine Learning Predicts Pathologic Complete Response to Neoadjuvant Chemotherapy for ER+HER2- Breast Cancer: Integrating Tumoral and Peritumoral MRI Radiomic Features.

BACKGROUND: This study aimed to predict pathologic complete response (pCR) in neoadjuvant chemotherapy for ER+HER2- locally advanced breast cancer (LABC), a subtype with limited treatment response. METHODS: We included 265 ER+HER2- LABC patients (2010-2020) with pre-treatment MRI, neoadjuvant chemotherapy, and confirmed pathology. Using data from January 2016, we divided them into training and validation cohorts. Volumes of interest (VOI) for the tumoral and peritumoral regions were segmented on preoperative MRI from three sequences: T1-weighted early and delayed contrast-enhanced sequences and T2-weighted fat-suppressed sequence (T2FS). We constructed seven machine learning models using tumoral, peritumoral, and combined texture features within and across the sequences, and evaluated their pCR prediction performance using AUC values. RESULTS: The best single sequence model was SVM using a 1 mm tumor-to-peritumor VOI in the early contrast-enhanced phase (AUC = 0.9447). Among the combinations, the top-performing model was K-Nearest Neighbor, using 1 mm tumor-to-peritumor VOI in the early contrast-enhanced phase and 3 mm peritumoral VOI in T2FS (AUC = 0.9631). CONCLUSIONS: We suggest that a combined machine learning model that integrates tumoral and peritumoral radiomic features across different MRI sequences can provide a more accurate pretreatment pCR prediction for neoadjuvant chemotherapy in ER+HER2- LABC.

A Lightweight Deep Learning Network on a System-on-Chip for Wearable Ultrasound Bladder Volume Measurement Systems: Preliminary Study.

Bladder volume assessments are crucial for managing urinary disorders. Ultrasound imaging (US) is a preferred noninvasive, cost-effective imaging modality for bladder observation and volume measurements. However, the high operator dependency of US is a major challenge due to the difficulty in evaluating ultrasound images without professional expertise. To address this issue, image-based automatic bladder volume estimation methods have been introduced, but most conventional methods require high-complexity computing resources that are not available in point-of-care (POC) settings. Therefore, in this study, a deep learning-based bladder volume measurement system was developed for POC settings using a lightweight convolutional neural network (CNN)-based segmentation model, which was optimized on a low-resource system-on-chip (SoC) to detect and segment the bladder region in ultrasound images in real time. The proposed model achieved high accuracy and robustness and can be executed on the low-resource SoC at 7.93 frames per second, which is 13.44 times faster than the frame rate of a conventional network with negligible accuracy drawbacks (0.004 of the Dice coefficient). The feasibility of the developed lightweight deep learning network was demonstrated using tissue-mimicking phantoms.

Phase aberration correction for ultrasound imaging guided extracorporeal shock wave therapy (ESWT): Feasibility study.

Image guidance of extracorporeal shock wave therapy (ESWT) is important to enhance its efficacy while lowering pain in patients. Real-time ultrasound imaging is an appropriate modality for image guidance, but its image quality substantially reduces due to severe phase aberration from the different speed of sound between soft tissues and a gel pad, which is utilized to control a therapeutic focal point in ESWT. This paper presents a phase aberration correction method for improving image quality in the ultrasound imaging guided ESWT. To correct an error from phase aberration, a time delay based on a two-layer model with different speeds of sound is calculated for dynamic receive beamforming. For the phantom and in vivo studies, a rubber type gel pad (i.e., 1400 m/s) with a specific thickness (3 or 5-cm) was placed on the top of soft tissue and full scanline RF data were acquired. In the phantom study, with phase aberration correction, image quality was highly increased compared to image reconstructions with a fixed speed of sound (i.e., 1540 or 1400 m/s), i.e., 1.1 vs. 2.2 and 1.3 mm in -6dB lateral resolution and 0.64 vs. 0.61 and 0.56 in contrast-to-noise ratio (CNR), respectively. From an in vivo musculoskeletal (MSK) imaging, the phase aberration correction method provided a clearly improved depiction of muscle fibers in a rectus femoris region. These results indicate that the proposed method enables effective imaging guidance of ESWT by improving image quality of ultrasound imaging in real-time.

Air-Coupled Ultrasound Sealing Integrity Inspection Using Leaky Lamb Waves in a Simplified Model of a Lithium-Ion Pouch Battery: Feasibility Study.

Inspecting the sealing integrity of lead tabs is an important means of ensuring the reliability and safety of pouch-type lithium-ion (Li-ion) batteries with a thin multi-layered aluminum (Al) laminated film. This paper presents a new air-coupled ultrasonic non-destructive testing (NDT) inspection method based on leaky Lamb wave transmission; and reception for evaluating the sealing integrity between the lead tab and the Al pouch film. The proposed method uses the critical incidence angle between the air and the layer with the fastest Lamb wave velocity to maximize the signal-to-noise ratio in the through-transmission mode. To determine the critical incidence angle, phantom experiments with two test pieces (i.e., an Al tab and an Al tab sealed with an Al pouch film) are conducted. In addition, 2D scans are performed at various incidence angles for an inhouse pouch-type Li-ion battery with a 1-mm-wide foreign material inserted as a defect. At the critical incidence angle (i.e., 22°), the proposed air-coupled ultrasonic NDT method in through-transmission mode successfully identifies the shape and location of the defect through c-scan image reconstruction. These preliminary results indicate that the proposed air-coupled ultrasonic NDT method with leaky Lamb waves can be used to inspect the sealing integrity of Li-ion pouch batteries in dry test conditions.

Noninvasive Aortic Ultrafast Pulse Wave Velocity Associated With Framingham Risk Model: in vivo Feasibility Study.

BACKGROUND: Aortic pulse wave velocity (PWV) enables the direct assessment of aortic stiffness, which is an independent risk factor of cardiovascular (CV) events. The aim of this study is to evaluate the association between aortic PWV and CV risk model classified into three groups based on the Framingham risk score (FRS), i.e., low-risk (<10%), intermediate-risk (10~20%) and high-risk (>20%). METHODS: To noninvasively estimate local PWV in an abdominal aorta, a high-spatiotemporal resolution PWV measurement method (>1 kHz) based on wide field-of-view ultrafast curved array imaging (ufcPWV) is proposed. In the ufcPWV measurement, a new aortic wall motion tracking algorithm based on adaptive reference frame update is performed to compensate errors from temporally accumulated out-of-plane motion. In addition, an aortic pressure waveform is simultaneously measured by applanation tonometry, and a theoretical PWV based on the Bramwell-Hill model (bhPWV) is derived. A total of 69 subjects (aged 23-86 years) according to the CV risk model were enrolled and examined with abdominal ultrasound scan. RESULTS: The ufcPWV was significantly correlated with bhPWV (r = 0.847, p < 0.01), and it showed a statistically significant difference between low- and intermediate-risk groups (5.3 ± 1.1 vs. 8.3 ± 3.1 m/s, p < 0.01), and low- and high-risk groups (5.3 ± 1.1 vs. 10.8 ± 2.5 m/s, p < 0.01) while there is no significant difference between intermediate- and high-risk groups (8.3 ± 3.1 vs. 10.8 ± 2.5 m/s, p = 0.121). Moreover, it showed a significant difference between two evaluation groups [low- (<10%) vs. higher-risk group (≥10%)] (5.3 ± 1.1 vs. 9.4 ± 3.1 m/s, p < 0.01) when the intermediate- and high-risk groups were merged into a higher-risk group. CONCLUSION: This feasibility study based on CV risk model demonstrated that the aortic ufcPWV measurement has the potential to be a new approach to overcome the limitations of conventional systemic measurement methods in the assessment of aortic stiffness.

Feasibility study using multifocal Doppler twinkling artifacts to detect suspicious microcalcifications in ex vivo specimens of breast cancer on US.

Multifocal Doppler twinkling artifact (MDTA) imaging has shown high detection rates of microcalcifications in phantom studies. We aimed to evaluate its performance in detecting suspicious microcalcifications in comparison with mammography by using ex vivo breast cancer specimens. We prospectively included ten women with breast cancer that presented with calcifications on mammography. Both digital specimen mammography and MDTA imaging were performed for ex vivo breast cancer specimens on the day of surgery. Five breast radiologists marked cells that included suspicious microcalcifications (referred to as 'positive cell') on specimen mammographic images using a grid of 5-mm cells. Cells that were marked by at least three readers were considered as 'consensus-positive'. Matched color Doppler twinkling artifact (CDTA) signals were compared between reconstructed US-MDTA projection images and mammographic images. The median detection rate for each case was 74.7% for positive cells and 96.7% for consensus-positive cells. Of the 10 cases, 90% showed a detection rate of ≥ 80%, with 50% of cases showing a 100% detection rate for consensus-positive cells. The proposed MDTA imaging method showed high performance for detecting suspicious microcalcifications in ex vivo breast cancer specimens, and may be a feasible approach for detecting suspicious breast microcalcifications with US.

Real-Time Ultrasound Detection of Breast Microcalcifications Using Multifocus Twinkling Artifact Imaging.

Detecting microcalcifications (MCs) in real time is important in the guidance of many breast biopsies. Due to its capability in visualizing biopsy needles without radiation hazards, ultrasound imaging is preferred over X-ray mammography, but it suffers from low sensitivity in detecting MCs. Here, we present a new nonionizing method based on real-time multifocus twinkling artifact (MF-TA) imaging for reliably detecting MCs. Our approach exploits time-varying TAs arising from acoustic random scattering on MCs with rough or irregular surfaces. To obtain the increased intensity of the TAs from MCs, in MF-TA, acoustic transmit parameters, such as the transmit frequency, the number of focuses and f-number, were optimized by investigating acoustical characteristics of MCs. A real-time MF-TA imaging sequence was developed and implemented on a programmable ultrasound research system, and it was controlled with a graphical user interface during real-time scanning. From an in-house 3D phantom and ex vivo breast specimen studies, the MF-TA method showed outstanding visibility and high-sensitivity detection for MCs regardless of their distribution or the background tissue. These results demonstrated that this nonionizing, noninvasive imaging technique has the potential to be one of effective image-guidance methods for breast biopsy procedures.

Ultrafast Power Doppler Imaging Using Frame-Multiply-and-Sum-Based Nonlinear Compounding.

Ultrafast power Doppler imaging based on coherent compounding (UPDI-CC) has become a promising technique for microvascular imaging due to its high sensitivity to slow blood flows. However, since this method utilizes a limited number of plane-wave or diverging-wave transmissions for high-frame-rate imaging, it suffers from degraded image quality because of the low contrast resolution. In this article, an ultrafast power Doppler imaging method based on a nonlinear compounding framework, called frame-multiply-and-sum (UPDI-FMAS), is proposed to improve contrast resolution. In UPDI-FMAS, unlike conventional channel-domain delay-multiply-and-sum (DMAS) beamforming, the signal coherence is estimated based on autocorrelation function over plane-wave angle frames. To avoid phase distortion of blood flow signals during the autocorrelation process, clutter filtering is preferentially applied to individual beamformed plane-wave data set. Therefore, only coherent blood flow signals are emphasized, while incoherent background noise is suppressed. The performance of the UPDI-FMAS was evaluated with simulation, phantom, and in vivo studies. For the simulation and phantom studies with a constant laminar flow, the UPDI-FMAS showed improvements in the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) to those of UPDI-CC, i.e., over 10 and 7 dB for 13 plane waves, respectively, and the performances were improved as the number of plane waves increased. Moreover, the enhancement of the image quality due to the increased SNR and CNR in UPDI-FMAS was more clearly depicted with the in vivo study, in which a human kidney and a tumor-bearing mouse were evaluated. These results indicate that the FMAS compounding can improve the image quality of UPDI for microvascular imaging without loss of temporal resolution.

3D microcalcification detection using a color Doppler twinkling artifact with optimized transmit conditions: Preliminary results.

PURPOSE: Mammography is the only method that has been proven to detect breast microcalcifications (MCs), but the sensitivity of mammography varies according to breast density. This paper proposes an ultrasound (US) color Doppler twinkling artifact (CDTA) method with optimized transmit conditions to identify breast MCs without ionizing radiation. METHODS: The transmit conditions for US color Doppler imaging (CDI) were optimized to enhance the sensitivity of the twinkling artifact (TA) that arises from random scattering on rough surfaces of breast MCs. To validate the proposed breast MC detection method, a chicken breast phantom with MC particles (groups of particles <400  µ m and <240  µ m ) was fabricated and scanned by a digital mammography system and an US research platform by an L11-5v linear array probe with a three-dimensional (3D) motion tracking system. RESULTS: From the phantom experiment, the proposed 3D CDTA imaging method with optimized transmit conditions (i.e., a center frequency of 5.0 MHz, an f-number of 1.3, and a peak negative pressure of 1.83 MPa) successfully detected all 16 MC particles, comparable to detection with mammography. For a human breast surgical specimen in the ex vivo study, all 10 MC clusters, marked by a radiologist on the mammogram, were identified with the proposed 3D CDTA imaging method. CONCLUSIONS: In the phantom and ex vivo breast specimen studies, the proposed 3D CDTA imaging method successfully detected MCs, and the spatial localization was highly correlated with the mammogram results. These results indicate that the proposed 3D CDTA imaging method has great potential for the detection of MCs without ionizing radiation.

Wide Field-of-View Ultrafast Curved Array Imaging Using Diverging Waves.

Ultrafast ultrasound imaging provides great opportunities for very high frame rate applications, such as shear wave elastography and microvascular imaging. However, ultrafast imaging with curved array transducers remains challenging in terms of element directivity and a limited field-of-view (FOV) for a fully synthetic area. In this paper, a wide FOV ultrafast curved array imaging method based on diverging wave transmissions is presented for high frame rate abdominal ultrasound applications. For this method, a theoretical model for a diverging wave solution based on a virtual point source originating from a circular line is proposed, and the FOV and element directivity are analyzed by this model. Furthermore, an integrated model for plane wave and diverging wave imaging along the location of the virtual point source is derived. The proposed method was evaluated with simulation, phantom, and in vivo studies. In the simulation and phantom studies, the image quality (i.e., spatial resolution, cystic resolution, and contrast-to-noise ratio), and effective FOV were assessed. For the in vivo study, a preliminary result from abdominal microvascular imaging, where diverging wave excitation was utilized to depict the vasculature, was also presented. In the renal cortex microvessels, the diverging wave imaging yielded a higher signal-to-clutter ratio value than the plane wave imaging, i.e., 6.35 vs. 4.26 dB, due to the wider synthetic field. These studies demonstrated that the proposed ultrafast curved array imaging technique based on diverging wave excitation allowed for an extended FOV with high spatiotemporal resolution.

High PRF ultrafast sliding compound doppler imaging: fully qualitative and quantitative analysis of blood flow.

Ultrafast compound Doppler imaging based on plane-wave excitation (UCDI) can be used to evaluate cardiovascular diseases using high frame rates. In particular, it provides a fully quantifiable flow analysis over a large region of interest with high spatio-temporal resolution. However, the pulse-repetition frequency (PRF) in the UCDI method is limited for high-velocity flow imaging since it has a tradeoff between the number of plane-wave angles (N) and acquisition time. In this paper, we present high PRF ultrafast sliding compound Doppler imaging method (HUSDI) to improve quantitative flow analysis. With the HUSDI method, full scanline images (i.e. each tilted plane wave data) in a Doppler frame buffer are consecutively summed using a sliding window to create high-quality ensemble data so that there is no reduction in frame rate and flow sensitivity. In addition, by updating a new compounding set with a certain time difference (i.e. sliding window step size or L), the HUSDI method allows various Doppler PRFs with the same acquisition data to enable a fully qualitative, retrospective flow assessment. To evaluate the performance of the proposed HUSDI method, simulation, in vitro and in vivo studies were conducted under diverse flow circumstances. In the simulation and in vitro studies, the HUSDI method showed improved hemodynamic representations without reducing either temporal resolution or sensitivity compared to the UCDI method. For the quantitative analysis, the root mean squared velocity error (RMSVE) was measured using 9 angles (-12° to 12°) with L of 1-9, and the results were found to be comparable to those of the UCDI method (L = N = 9), i.e. ⩽0.24 cm s-1, for all L values. For the in vivo study, the flow data acquired from a full cardiac cycle of the femoral vessels of a healthy volunteer were analyzed using a PW spectrogram, and arterial and venous flows were successfully assessed with high Doppler PRF (e.g. 5 kHz at L = 4). These results indicate that the proposed HUSDI method can improve flow visualization and quantification with a higher frame rate, PRF and flow sensitivity in cardiovascular imaging.

A New Dynamic Complex Baseband Pulse Compression Method for Chirp-Coded Excitation in Medical Ultrasound Imaging.

Chirp-coded excitation can increase the signal-to-noise ratio (SNR) without degrading the axial resolution. Effective pulse compression (PC) is important to maintain the axial resolution and can be achieved with radio frequency (RF) and complex baseband (CBB) data (i.e., and , respectively). can further reduce the computational complexity compared to ; however, suffers from a degraded SNR due to tissue attenuation. In this paper, we propose a new dynamic CBB PC method ( that can improve the SNR while compensating for tissue attenuation. The compression filter coefficients in the method are generated by dynamically changing the demodulation frequencies along with the depth. For PC, the obtained coefficients are independently applied to the in-phase and quadrature components of the CBB data. To evaluate the performance of the proposed method, simulation, phantom, and in vivo studies were conducted, and all three studies showed improved SNR, i.e., maximally 3.87, 7.41, and 5.75 dB, respectively. In addition, the measured peak range sidelobe level of the proposed method yielded lower values than the and , and it also derived a suitable target location, i.e., a <0.07-mm target location error, while maintaining the axial resolution. In an in vivo abdominal experiment, the method depicted brighter and clearer features in the hyperechoic region because highly correlated signals were produced by compensating for tissue attenuation. These results demonstrated that the proposed method can improve the SNR of chirp-coded excitation while preserving the axial resolution and the target location and reducing the computational complexity.

A System-on-Chip Solution for Point-of-Care Ultrasound Imaging Systems: Architecture and ASIC Implementation.

In this paper, we present a novel system-on-chip (SOC) solution for a portable ultrasound imaging system (PUS) for point-of-care applications. The PUS-SOC includes all of the signal processing modules (i.e., the transmit and dynamic receive beamformer modules, mid- and back-end processors, and color Doppler processors) as well as an efficient architecture for hardware-based imaging methods (e.g., dynamic delay calculation, multi-beamforming, and coded excitation and compression). The PUS-SOC was fabricated using a UMC 130-nm NAND process and has 16.8 GFLOPS of computing power with a total equivalent gate count of 12.1 million, which is comparable to a Pentium-4 CPU. The size and power consumption of the PUS-SOC are 27×27 mm(2) and 1.2 W, respectively. Based on the PUS-SOC, a prototype hand-held US imaging system was implemented. Phantom experiments demonstrated that the PUS-SOC can provide appropriate image quality for point-of-care applications with a compact PDA size ( 200×120×45 mm(3)) and 3 hours of battery life.

A New Feature-Enhanced Speckle Reduction Method Based on Multiscale Analysis for Ultrasound B-Mode Imaging.

GOAL: Effective speckle reduction in ultrasound B-mode imaging is important for enhancing the image quality and improving the accuracy in image analysis and interpretation. In this paper, a new feature-enhanced speckle reduction (FESR) method based on multiscale analysis and feature enhancement filtering is proposed for ultrasound B-mode imaging. In FESR, clinical features (e.g., boundaries and borders of lesions) are selectively emphasized by edge, coherence, and contrast enhancement filtering from fine to coarse scales while simultaneously suppressing speckle development via robust diffusion filtering. In the simulation study, the proposed FESR method showed statistically significant improvements in edge preservation, mean structure similarity, speckle signal-to-noise ratio, and contrast-to-noise ratio (CNR) compared with other speckle reduction methods, e.g., oriented speckle reducing anisotropic diffusion (OSRAD), nonlinear multiscale wavelet diffusion (NMWD), the Laplacian pyramid-based nonlinear diffusion and shock filter (LPNDSF), and the Bayesian nonlocal means filter (OBNLM). Similarly, the FESR method outperformed the OSRAD, NMWD, LPNDSF, and OBNLM methods in terms of CNR, i.e., 10.70 ± 0.06 versus 9.00 ± 0.06, 9.78 ± 0.06, 8.67 ± 0.04, and 9.22 ± 0.06 in the phantom study, respectively. Reconstructed B-mode images that were developed using the five speckle reduction methods were reviewed by three radiologists for evaluation based on each radiologist's diagnostic preferences. All three radiologists showed a significant preference for the abdominal liver images obtained using the FESR methods in terms of conspicuity, margin sharpness, artificiality, and contrast, p<0.0001. For the kidney and thyroid images, the FESR method showed similar improvement over other methods. However, the FESR method did not show statistically significant improvement compared with the OBNLM method in margin sharpness for the kidney and thyroid images. These results demonstrate that the proposed FESR method can improve the image quality of ultrasound B-mode imaging by enhancing the visualization of lesion features while effectively suppressing speckle noise.

Does adding diffuse optical tomography to sonography improve differentiation between benign and malignant breast lesions? Observer performance study.

OBJECTIVES: The purpose of this study was to investigate the added value of diffuse optical tomographic categories combined with conventional sonography for differentiating between benign and malignant breast lesions. METHODS: In this retrospective database review, we included 145 breast lesions (116 benign and 29 malignant) from 145 women (mean age, 46 years; range, 16-86 years). Five radiologists independently reviewed sonograms with and without a diffuse optical tomographic category. Each lesion was scored on a scale of 0% to 100% for suspicion of malignancy and rated according to the American College of Radiology Breast Imaging Reporting and Data System classification. Diagnostic performance was analyzed by comparing area under receiver operating characteristic curve values. Reader agreement was assessed by intraclass correlation coefficients. RESULTS: In the multireader multicase receiver operating characteristic analysis, adding a diffuse optical tomographic category to sonography improved the diagnostic accuracy of sonography (mean areas under the curve, 0.923 for sonography alone and 0.969 for sonography with diffuse optical tomography; P = .039). The interobserver correlation was also improved (0.798 for sonography alone and 0.904 for sonography with diffuse optical tomography). The specificity increased for 4 reviewers from a mean of 19.5% to 45.8% (P < .001 for reviewers 1-4; P = .238 for reviewer 5) with no significant change in the sensitivity. When the diffuse optical tomographic category was applied strictly, the specificity increased for all reviewers from a mean of 19.5% to 68.3% (P < .001 for all reviewers) with no significant change in the sensitivity. CONCLUSIONS: The addition of diffuse optical tomographic categories to sonography may improve diagnostic performance and markedly decrease false-positive biopsy recommendations.

A prototype hand-held tri-modal instrument for in vivo ultrasound, photoacoustic, and fluorescence imaging.

Multi-modality imaging is beneficial for both preclinical and clinical applications as it enables complementary information from each modality to be obtained in a single procedure. In this paper, we report the design, fabrication, and testing of a novel tri-modal in vivo imaging system to exploit molecular/functional information from fluorescence (FL) and photoacoustic (PA) imaging as well as anatomical information from ultrasound (US) imaging. The same ultrasound transducer was used for both US and PA imaging, bringing the pulsed laser light into a compact probe by fiberoptic bundles. The FL subsystem is independent of the acoustic components but the front end that delivers and collects the light is physically integrated into the same probe. The tri-modal imaging system was implemented to provide each modality image in real time as well as co-registration of the images. The performance of the system was evaluated through phantom and in vivo animal experiments. The results demonstrate that combining the modalities does not significantly compromise the performance of each of the separate US, PA, and FL imaging techniques, while enabling multi-modality registration. The potential applications of this novel approach to multi-modality imaging range from preclinical research to clinical diagnosis, especially in detection/localization and surgical guidance of accessible solid tumors.

Automatic dynamic range adjustment for ultrasound B-mode imaging.

In medical ultrasound imaging, dynamic range (DR) is defined as the difference between the maximum and minimum values of the displayed signal to display and it is one of the most essential parameters that determine its image quality. Typically, DR is given with a fixed value and adjusted manually by operators, which leads to low clinical productivity and high user dependency. Furthermore, in 3D ultrasound imaging, DR values are unable to be adjusted during 3D data acquisition. A histogram matching method, which equalizes the histogram of an input image based on that from a reference image, can be applied to determine the DR value. However, it could be lead to an over contrasted image. In this paper, a new Automatic Dynamic Range Adjustment (ADRA) method is presented that adaptively adjusts the DR value by manipulating input images similar to a reference image. The proposed ADRA method uses the distance ratio between the log average and each extreme value of a reference image. To evaluate the performance of the ADRA method, the similarity between the reference and input images was measured by computing a correlation coefficient (CC). In in vivo experiments, the CC values were increased by applying the ADRA method from 0.6872 to 0.9870 and from 0.9274 to 0.9939 for kidney and liver data, respectively, compared to the fixed DR case. In addition, the proposed ADRA method showed to outperform the histogram matching method with in vivo liver and kidney data. When using 3D abdominal data with 70 frames, while the CC value from the ADRA method is slightly increased (i.e., 0.6%), the proposed method showed improved image quality in the c-plane compared to its fixed counterpart, which suffered from a shadow artifact. These results indicate that the proposed method can enhance image quality in 2D and 3D ultrasound B-mode imaging by improving the similarity between the reference and input images while eliminating unnecessary manual interaction by the user.

Vein visualization using a smart phone with multispectral Wiener estimation for point-of-care applications.

Effective vein visualization is clinically important for various point-of-care applications, such as needle insertion. It can be achieved by utilizing ultrasound imaging or by applying infrared laser excitation and monitoring its absorption. However, while these approaches can be used for vein visualization, they are not suitable for point-of-care applications because of their cost, time, and accessibility. In this paper, a new vein visualization method based on multispectral Wiener estimation is proposed and its real-time implementation on a smart phone is presented. In the proposed method, a conventional RGB camera on a commercial smart phone (i.e., Galaxy Note 2, Samsung Electronics Inc., Suwon, Korea) is used to acquire reflectance information from veins. Wiener estimation is then applied to extract the multispectral information from the veins. To evaluate the performance of the proposed method, an experiment was conducted using a color calibration chart (ColorChecker Classic, X-rite, Grand Rapids, MI, USA) and an average root-mean-square error of 12.0% was obtained. In addition, an in vivo subcutaneous vein imaging experiment was performed to explore the clinical performance of the smart phone-based Wiener estimation. From the in vivo experiment, the veins at various sites were successfully localized using the reconstructed multispectral images and these results were confirmed by ultrasound B-mode and color Doppler images. These results indicate that the presented multispectral Wiener estimation method can be used for visualizing veins using a commercial smart phone for point-of-care applications (e.g., vein puncture guidance).

Pixel based focusing for photoacoustic and ultrasound dual-modality imaging.

It is desired that the same imaging functional modules such as beamformation, envelope detection, and digital scan conversion (DSC) are employed for the efficient development of a cross-sectional photoacoustic (PA) and ultrasound (US) dual-modality imaging system. The beamformation can be implemented using either delay-and-sum beamforming (DAS-BF) or adaptive beamforming methods, each with their own advantages and disadvantages for the dual-modality imaging. However, the DSC is always problematic because it causes blurring the fine details of an image, e.g., edges. This paper demonstrates that the pixel based focusing method is suitable for the dual-modality imaging; beamformation is directly conducted on each display pixel and thus DSC is not necessary. As a result, the artifacts by DSC are no longer a problem, so that the proposed method is capable of providing the maximum spatial resolution achievable by DAS-BF. The performance of the proposed method was evaluated through simulation and ex vivo experiments with a microcalcification-contained breast specimen, and the results were compared with those from DAS-BF and adaptive beamforming methods with DSC. The comparison demonstrated that the proposed method effectively overcomes the disadvantages of each beamforming method.

An efficient pulse compression method of chirp-coded excitation in medical ultrasound imaging.

Coded excitation can improve the SNR in medical ultrasound imaging. In coded excitation, pulse compression is applied to compress the elongated coded signals into a short pulse, which typically requires high computational complexity, i.e., a compression filter with a few hundred coefficients. In this paper, we propose an efficient pulse compression method of chirp-coded excitation, in which the pulse compression is conducted with complex baseband data after downsampling, to lower the computational complexity. In the proposed method, although compression is conducted with the complex data, the L-fold downsampling is applied for reducing both data rates and the number of compression filter coefficients; thus, total computational complexity is reduced to the order of 1/L(2). The proposed method was evaluated with simulation and phantom experiments. From the simulation and experiment results, the proposed pulse compression method produced similar axial resolution compared with the conventional pulse compression method with negligible errors, i.e., ≫36 dB in signal-to-error ratio (SER). These results indicate that the proposed method can maintain the performance of pulse compression of chirp-coded excitation while substantially reducing computational complexity.