Ultrasonic Imaging最新文献

Large scale early scanning of fetuses via ultrasound imaging is widely used to alleviate the morbidity or mortality caused by congenital anomalies in fetal hearts and lungs. To reduce the intensive cost during manual recognition of organ regions, many automatic segmentation methods have been proposed. However, the existing methods still encounter multi-scale problem at a larger range of receptive fields of organs in images, resolution problem of segmentation mask, and interference problem of task-irrelevant features, obscuring the attainment of accurate segmentations. To achieve semantic segmentation with functions of (1) extracting multi-scale features from images, (2) compensating information of high resolution, and (3) eliminating the task-irrelevant features, we propose a multi-scale model with skip connection framework and attention mechanism integrated. The multi-scale feature extraction modules are incorporated with additive attention gate units for irrelevant feature elimination, through a U-Net framework with skip connections for information compensation. The performance of fetal heart and lung segmentation indicates the superiority of our method over the existing deep learning based approaches. Our method also shows competitive performance stability during the task of semantic segmentations, showing a promising contribution on ultrasound based prognosis of congenital anomaly in the early intervention, and alleviating the negative effects caused by congenital anomaly.

To determine the relationship between muscle echo intensity (EI) and fractal dimension (FD), and the diagnostic performance of both ultrasound parameters for the identification of frailty phenotype. A retrospective interpretation of ultrasound scans from a previous cohort (November 2014-February 2015) was performed. The sample included healthy participants <60 years old, and participants ≥60 divided into robust, pre-frail, and frail groups according to Fried frailty criteria. A region of interest of the rectus femoris from the ultrasound scan was segmented, and histogram function was applied to obtain EI. For fractal analysis, images were processed using two-dimensional box-counting techniques to calculate FD. Statistical analyses were performed with diagnostic performance tests. A total of 102 participants (mean age 63 ± 16, 57 men) were evaluated. Muscle fractal dimension correlated with EI (r = .38, p < .01) and showed different pattern in the scatter plots when participants were grouped by non-frail (control + robust) and frail (pre-frail + frail). The diagnostic accuracy for EI to categorize frailty was of 0.69 (95%CI: 0.59-0.78, p = .001), with high intra-rater (ICC: 0.98, 95%CI: 0.98-0.99); p < .001) and inter-rater (ICC: 0.89, 95%CI: 0.75-0.95; p < .001) reliability and low measurement error for both parameters (EI: -0.18, LOA95%: -10.8 to 10.5; FD: 0.00, LOA95%: -0.09 to 0.10) in arbitrary units. The ROC curve combining both parameters was not better than EI alone (p = .18). Muscle FD correlated with EI and showed different patterns according to frailty phenotype, with EI outperforming FD as a possible diagnostic tool for frailty.

Needle visualization in the ultrasound image is essential to successfully perform the ultrasound-guided core needle biopsy. Automatic needle detection can significantly reduce the procedure time, false-negative rate, and highly improve the diagnosis. In this paper, we present a CNN-based, fully automatic method for detection of core needle in 2D ultrasound images. Adaptive moment estimation optimizer is proposed as CNN architecture. Radon transform is applied to locate the needle. The network's model was trained and tested on the total of 619 2D images from 91 cases of breast cancer. The model has achieved an average weighted intersection over union (the weighted Jaccard Index) of 0.986, F1 Score of 0.768, and angle RMSE of 3.73°. The obtained results exceed the other solutions by at least 0.27 and 7° in case of F1 score and angle RMSE, respectively. Finally, the needle is detected in a single frame averagely in 21.6 ms on a modern PC.

To compare microvascular flow imaging (MVFI) to conventional Color-Doppler (CDI) and Power-Doppler (PDI) imaging in the detection of vascularity of Focal Breast Lesions (FBLs). A total of 180 solid FBLs (size: 3.5-45.2 mm) detected in 180 women (age: 21-87 years) were evaluated by means of CDI, PDI, and MVFI. Two blinded reviewers categorized lesion vascularity in absent or present, and vascularity pattern as (a) internal; (b) vessels in rim; (c) combined. The presence of a "penetrating vessel" was assessed separately. Differences in vascularization patterns (chi² test) and intra- and inter-observer agreement (Fleiss method) were calculated. ROC analysis was performed to assess performance of each technique in differentiating benign from malignant lesions. About 103/180 (57.2%) FBLs were benign and 77/180 (42.8%) were malignant. A statistically significant (p < .001) increase in blood flow detection was observed for both readers with MVFI in comparison to either CDI or PDI. Benign FBLs showed mainly absence of vascularity (p = .02 and p = .01 for each reader, respectively), rim pattern (p < .001 for both readers) or combined pattern (p = .01 and p = .04). Malignant lesions showed a statistically significant higher prevalence of internal flow pattern (p < .001 for both readers). The prevalence of penetrating vessels was significantly higher with MVFI in comparison to either CDI or PDI (p < .001 for both readers) and in the malignant FBLs (p < .001). ROC analysis showed MVFI (AUC = 0.70, 95%CI = [0.64-0.77]) more accurate than CDI (AUC = 0.67, 95%CI = [0.60-0.74]) and PDI (AUC = 0.67, 95%CI = [0.60-0.74]) though not significantly (p = .5436). Sensitivity/Specificity values for MVFI, PDI, and CDI were 76.6%/64.1%, 59.7%/73.8% and 58.4%/74.8%, respectively. Inter-reader agreement with MVFI was always very good (k-score 0.85-0.96), whereas with CDI and PDI evaluation ranged from good to very good. No differences in intra-observer agreement were noted. MVFI showed a statistically significant increase in the detection of the vascularization of FBLs in comparison to Color and Power-Doppler.

Investigations into Fourier beamforming for medical ultrasound imaging have largely been limited to plane-wave and single-element transmissions. The main aim of this work is to generalize Fourier beamforming to enable synthetic aperture imaging with arbitrary transmit sequences. When applied to focused transmit beams, the proposed approach yields a full-waveform-based alternative to virtual-source synthetic aperture, which has implications for both coherence imaging and sound speed estimation. When compared to virtual-source synthetic aperture and retrospective encoding for conventional ultrasound sequences (REFoCUS), the proposed imaging technique shows an 8.6 and 3.8 dB improvement in contrast over virtual source synthetic aperture and REFoCUS, respectively, and a 55% improvement in point target resolution over virtual source synthetic aperture. The proposed image reconstruction technique also demonstrates general imaging improvements in vivo, while avoiding limitations seen in prior techniques.

The ultrasound phantoms used to educate medical students should not only closely mimic the ultrasound characteristics of human soft tissues but also be inexpensive and easy to manufacture. I have been studying handmade ultrasound phantoms and proposed an ultrasound phantom comprising calcium alginate hydrogel that met these requirements but caused a speckle pattern similar to that observed in ultrasound images of liver. In this study, I show that adding ethanol to the precursors used to fabricate the phantom reduces the speckle pattern. The ultrasound propagation velocity and attenuation coefficient of the phantom were 1561 ± 8 m/s and 0.54 ± 0.18 dB/cm/MHz, respectively (mean ± standard deviation), which are within the ranges of those in human soft tissues (1530-1600 m/s and 0.3-1.0 dB/cm/MHz, respectively). This phantom is easy to fabricate without special equipment, is inexpensive, and is suitable for elementary training on ultrasound diagnosis, operation of ultrasound-guided needles, and blind catheter insertion.

Uterine disorders are often presented with overlapping symptoms. The microvasculature holds specific information important for diagnosing uterine disorders. Conventional sonography is an established diagnostic technique in gynecology, but is limited by its inability to image the microvasculature. Contrast-enhanced ultrasound (CEUS), is capable of imaging the microvasculature by means of intravascular contrast agents; that is, gas-filled microbubbles. We provide a literature overview on the use of CEUS in diagnosing myometrial and endometrial disorders, that is, fibroids, adenomyosis, leiomyosarcomas and endometrial carcinomas, as well as for monitoring and enhancing the effectiveness of minimally invasive therapies. A systematic literature search with quality assessment was performed until December 2020. In total 34 studies were included, published between 2007 and 2020.The results entail a description of contrast-enhancement patterns obtained from healthy tissue and from malignant and benign tissue; providing a first base for potential diagnostic differentiation in gynecology. In addition it is also possible to determine the degree of myometrial invasion in case of endometrial carcinoma using CEUS. The effectiveness of minimally invasive therapies for uterine disorders can safely and accurately be assessed with CEUS. In conclusion, the abovementioned applications of CEUS are promising and it is worth further exploring its full potential for gynecology by designing innovative and methodologically high-quality clinical studies.

Portable ultrasound has been extensively used for diagnostic applications in health monitoring, emergency rooms, and ambulances. However, these handheld ultrasound systems may suffer from heat and battery issues attributed to the large power consumption of the transmitter. Additionally, the largest portion of the direct current (DC) power consumption can be attributed to the amplifier in the digital-to-analog converter (DAC) of the transmitter and to the analog-to-digital converter (ADC) of the receiver. Therefore, the number of transmit/receive channels in a portable ultrasound instrument is one of the crucial design factors regarding heat and battery related issues. To address these problems, we propose an acoustic-field beamforming (AFB) technique for low-power portable ultrasound systems with a single receive and five transmit channels. Finally, the simulation, experimental, and in vivo results verified the feasibility of this approach.