Ultrasonic Imaging最新文献

Generalized Null Subtraction Factor: A Post-Filtering Framework for Contrast Enhancement in Ultrafast Ultrasound Imaging. 广义零减去因子：一种用于超快超声成像对比度增强的后滤波框架。

IF 2.5 4区医学

Ultrasonic Imaging Pub Date : 2026-05-06 DOI: 10.1177/01617346261445936

Xiaodong Yang, Xin Yan, Lingling Jing, Yingqi Wang, Xinwei Su

{"title":"Generalized Null Subtraction Factor: A Post-Filtering Framework for Contrast Enhancement in Ultrafast Ultrasound Imaging.","authors":"Xiaodong Yang, Xin Yan, Lingling Jing, Yingqi Wang, Xinwei Su","doi":"10.1177/01617346261445936","DOIUrl":"https://doi.org/10.1177/01617346261445936","url":null,"abstract":"Poor spatial resolution and contrast remain major challenges in ultrafast ultrasound imaging. Null subtraction imaging (NSI) improves lateral resolution but often degrades speckle quality and contrast. Its extension, dynamic DC-biased NSI (dDC-NSI), mitigates this trade-off by introducing a dynamic DC bias; however, slight speckle suppression may still occur in homogeneous regions, leading to dark-region artifacts. In this work, a generalized null subtraction factor (gNSF) is proposed as a post-processing framework. gNSF applies multiple apodizations, followed by a mirror-flipping and symmetric summation operation, and defines a weighting factor based on the energy ratio between a bias term and a zero-mean sequence. By incorporating the dynamic DC bias, coherent echoes are enhanced while incoherent noise is suppressed. Phantom experiments show that gNSF achieves a contrast performance (gCNR close to 1) comparable to GCF and dDC-NSI, and superior to DAS and NSI. In addition, gNSF improves CR and sSNR by 20% and 21% compared with dDC-NSI, indicating reduced speckle over-suppression and a better balance between contrast and speckle preservation.","PeriodicalId":49401,"journal":{"name":"Ultrasonic Imaging","volume":" ","pages":"1617346261445936"},"PeriodicalIF":2.5,"publicationDate":"2026-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147845109","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fourier Beamforming of Ultrasound Signals From Chirp Transmits Using the Chirp Scaling Algorithm. 利用啁啾缩放算法对啁啾传输的超声信号进行傅立叶波束形成。

IF 2.5 4区医学

Ultrasonic Imaging Pub Date : 2026-05-06 DOI: 10.1177/01617346261441787

Louise Zhuang, Scott Schoen, Jeremy Dahl, Marko Jakovljevic

{"title":"Fourier Beamforming of Ultrasound Signals From Chirp Transmits Using the Chirp Scaling Algorithm.","authors":"Louise Zhuang, Scott Schoen, Jeremy Dahl, Marko Jakovljevic","doi":"10.1177/01617346261441787","DOIUrl":"https://doi.org/10.1177/01617346261441787","url":null,"abstract":"Synthetic aperture transmit sequences can be used in medical ultrasound to increase image resolution without sacrificing frame rate. However, beamforming the large amount of collected data from the sequence is computationally costly for traditional delay-and-sum (DAS) beamforming, and the sequence has low SNR and limited penetration depth. These problems are especially apparent for deeper targets, when more data is collected and the low SNR results in poor visibility. Transmitting a chirp coded excitation can greatly improve the SNR and penetration depth, at the cost of some computational efficiency during beamforming, although frequency-domain beamforming can reduce the computations required for image reconstruction. This paper presents the chirp scaling algorithm (CSA), a frequency-domain beamformer originally developed for radar, that avoids the computational costs of interpolation and can account inherently for chirp excitation pulse compression for chirp transmit sequences. First, theory is presented to derive the beamforming steps for ultrasound multistatic synthetic aperture data. Then, comparative imaging with DAS and the range-Doppler algorithm (RDA, a related frequency-domain beamformer) are shown via Field II simulations and in vitro with a CIRS phantom imaged using a Verasonics Vantage 256 system. The results demonstrate similar lateral sidelobe levels (averaging) within 6 dB and resolution within 0.1 mm for the three beamformers for all sources of data. However, CSA has consistently faster median baseline runtime (at least 2.6 times faster compared to DAS), and a significant 6.5-fold runtime decrease from via precomputation, which reduces its runtime below even that of RDA. Together, our results demonstrate the feasibility for CSA to generate high-quality ultrasound images, particularly for resource-constrained devices.","PeriodicalId":49401,"journal":{"name":"Ultrasonic Imaging","volume":" ","pages":"1617346261441787"},"PeriodicalIF":2.5,"publicationDate":"2026-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147845069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Ultrasound Microvascular Imaging Using Deep Knowledge Distillation. 基于深度知识蒸馏的超声微血管成像。

IF 2.5 4区医学

Ultrasonic Imaging Pub Date : 2026-05-04 DOI: 10.1177/01617346261437268

Seonho Kim, Chunsu Park, Yubin Cho, MinWoo Kim

{"title":"Ultrasound Microvascular Imaging Using Deep Knowledge Distillation.","authors":"Seonho Kim, Chunsu Park, Yubin Cho, MinWoo Kim","doi":"10.1177/01617346261437268","DOIUrl":"https://doi.org/10.1177/01617346261437268","url":null,"abstract":"Ultrafast Doppler imaging provides critical insights into tissue perfusion but traditionally requires long acquisitions and computationally expensive filtering, such as singular value decomposition (SVD). In this work, we propose SONIC, a real-time, deep learning framework that reconstructs high-quality vascular images from limited Doppler frames using a teacher-student paradigm. The student model, designed for fast inference, is trained under the guidance of a teacher network pretrained on full-length sequences. To further enhance performance under sparse data conditions, we introduce a dual-loss strategy combining deep supervision and knowledge distillation. The deep supervision loss aids in learning clutter-suppressed intermediate features, while the knowledge distillation loss transfers high-level spatiotemporal knowledge from the teacher to the student model. Experiments on in vivo datasets demonstrate that SONIC achieves superior performance compared to SVD filtering when operating on fewer frames. Our ablation study confirms that the combination of deep supervision and knowledge distillation provides synergistic benefits, significantly improving segmentation accuracy and signal fidelity. Furthermore, SONIC achieves real-time inference speeds on GPU hardware, supporting its integration into time-constrained clinical workflows. Finally, we demonstrate the applicability of SONIC to free-hand 3D microvascular imaging by stacking high-quality 2D Doppler slices acquired during handheld scanning. This capability highlights the framework's potential for extending microvascular ultrasound imaging into portable and low-data clinical environments.","PeriodicalId":49401,"journal":{"name":"Ultrasonic Imaging","volume":" ","pages":"1617346261437268"},"PeriodicalIF":2.5,"publicationDate":"2026-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147822812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Streamlined Method for Placement of Diverging-Wave Virtual Sources for Ultrafast Ultrasound Imaging. 一种用于超快超声成像发散波虚拟源的流线型放置方法。

IF 2.5 4区医学

Ultrasonic Imaging Pub Date : 2026-05-01 Epub Date: 2025-11-21 DOI: 10.1177/01617346251382496

Kashta Dozier-Muhammad, Carl D Herickhoff

{"title":"A Streamlined Method for Placement of Diverging-Wave Virtual Sources for Ultrafast Ultrasound Imaging.","authors":"Kashta Dozier-Muhammad, Carl D Herickhoff","doi":"10.1177/01617346251382496","DOIUrl":"10.1177/01617346251382496","url":null,"abstract":"Ultrasound array probes can transmit diverging wavefronts from virtual source (VS) locations behind the array to obtain ultrafast compounded images with a broad field-of-view, but determining a practical set of diverging-wave VS locations is non-trivial, given the infinite half-plane of possibilities. In this work, we propose VS placement at a constant radial distance r from the array origin, and we compare this to a previous (and less direct) method of VS placement at a constant opening angle β relative to the ends of the array. Each method was implemented in Field II with a 64 element, 2.7 MHz phased-array geometry to simulate point-spread functions (PSFs) at regular 10 mm intervals over the field-of-view; the lateral and axial resolution, peak side-to-main lobe amplitude ratio (PSMR), and maximum amplitude of each PSF were measured. Each method was also implemented on a research scanner with a corresponding probe to acquire images of a tissue-mimicking phantom for comparison. Results from both methods in simulation and phantom experiments showed that the increase in PSF lateral resolution with range was consistent (≈38 µm/mm) and the mean axial resolution agreed within 0.01 mm; mean differences in PSMR and amplitude were <5% and <4%, respectively. Generalized contrast-to-noise ratio (gCNR) was highest for the constant-β2 method, with differences between methods within ±1%. These results indicate that, relative to the constant-β method, comparable image quality can be achieved with a streamlined constant-r method of VS placement for diverging-wave ultrafast imaging.","PeriodicalId":49401,"journal":{"name":"Ultrasonic Imaging","volume":" ","pages":"139-155"},"PeriodicalIF":2.5,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145566055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A High-Resolution and High-Contrast Beamforming Algorithm Based on Null Subtraction Imaging Applied to Synthetic Transmit Aperture. 一种应用于合成发射孔径的高分辨率、高对比度零差成像波束形成算法。

IF 2.5 4区医学

Ultrasonic Imaging Pub Date : 2026-05-01 Epub Date: 2025-12-02 DOI: 10.1177/01617346251384583

Roya Paridar, Babak Mohammadzadeh Asl

{"title":"A High-Resolution and High-Contrast Beamforming Algorithm Based on Null Subtraction Imaging Applied to Synthetic Transmit Aperture.","authors":"Roya Paridar, Babak Mohammadzadeh Asl","doi":"10.1177/01617346251384583","DOIUrl":"10.1177/01617346251384583","url":null,"abstract":"In medical ultrasound imaging, achieving high-quality reconstructed images while avoiding a huge computational burden is an important challenge. The Null subtraction imaging (NSI) algorithm results in a high-resolution reconstructed image. However, this method is not successful in recovering the background speckle information. In this paper, a novel algorithm, known as NSI-based generalized coherence factor (GCF)-along with delay-and-sum (DAS), which is abbreviated as NSG-DAS, is developed to overcome this limitation. In the proposed method, by using a hybrid technique, the desired resolution and effective noise suppression of the NSI algorithm, as well as the background speckle information of the conventional DAS beamformer are recovered simultaneously. More precisely, by using the GCF method, a new weighing factor is introduced that enhances the coherent regions of the image and suppresses the off-axis signals. Evaluations prove the favorable performance of the suggested technique; in particular, by using the proposed NSG-DAS method, a resolution comparable to the NSI algorithm is achieved for the geabr0 dataset, which is improved by about 42% compared to DAS. Also, the contrast evaluation parameter of the suggested technique is comparable to the DAS algorithm and is improved by about 63% compared to the NSI method. This indicates the ability of the suggested technique to improve either resolution or contrast simultaneously.","PeriodicalId":49401,"journal":{"name":"Ultrasonic Imaging","volume":" ","pages":"156-170"},"PeriodicalIF":2.5,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145656235","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Novel Clinical Hybrid Deep Framework for Denoising and Anatomical Segmentation in Challenging Ultrasound Conditions. 在具有挑战性的超声条件下用于去噪和解剖分割的新型临床混合深度框架。

IF 2.5 4区医学

Ultrasonic Imaging Pub Date : 2026-05-01 Epub Date: 2025-11-21 DOI: 10.1177/01617346251384596

Taher Slimi, Anouar Ben Khalifa

{"title":"Novel Clinical Hybrid Deep Framework for Denoising and Anatomical Segmentation in Challenging Ultrasound Conditions.","authors":"Taher Slimi, Anouar Ben Khalifa","doi":"10.1177/01617346251384596","DOIUrl":"10.1177/01617346251384596","url":null,"abstract":"Speckle noise in ultrasound imaging remains a major obstacle to accurate clinical interpretation and reliable anatomical segmentation. Existing enhancement methods often compromise anatomical details while reducing noise, particularly under challenging imaging conditions. To address this, we introduce an innovative hybrid framework combining the Smart Adaptive Framework for Image Enhancement (SAFIE), a denoising engine based on adaptive fractional convolutions and gradient-based refinement, with a segmentation strategy integrating superpixel-based hypergraph modeling and neural ordinary differential equations. This framework enables effective noise suppression and precise segmentation of anatomical structures by capturing both spatial coherence and temporal feature dynamics. The enhanced images reveal improved visibility of anatomical structures and boundaries. Qualitative evaluation by four experienced radiologists confirmed this improvement, with strong inter-observer agreement measured by Fleiss' kappa, highlighting the robustness and clinical relevance of the approach. Quantitative results corroborate these observations, demonstrating performance substantially superior to several state-of-the-art methods. Ablation studies further indicate that each component contributes significantly to overall improvement. These findings suggest that the proposed framework enhances segmentation reliability and provides robust support for diagnostic interpretation in ultrasound imaging.","PeriodicalId":49401,"journal":{"name":"Ultrasonic Imaging","volume":" ","pages":"171-200"},"PeriodicalIF":2.5,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145566053","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

DAUS-Net: Toward Ultrasound Scanner-Agnostic Domain Generalized Robust and Accurate Segmentation. DAUS-Net：面向超声扫描仪不可知域的广义鲁棒准确分割。

IF 2.5 4区医学

Ultrasonic Imaging Pub Date : 2026-05-01 Epub Date: 2025-12-25 DOI: 10.1177/01617346251388454

Sangheon Lee, Dongkyu Jung, Nizar Guezzi, Sangwoo Nam, Jaesok Yu

{"title":"DAUS-Net: Toward Ultrasound Scanner-Agnostic Domain Generalized Robust and Accurate Segmentation.","authors":"Sangheon Lee, Dongkyu Jung, Nizar Guezzi, Sangwoo Nam, Jaesok Yu","doi":"10.1177/01617346251388454","DOIUrl":"10.1177/01617346251388454","url":null,"abstract":"In medical imaging, segmentation is a critical task for analysis and diagnosis. Deep learning-based segmentation has been actively studied and has shown remarkable performance. Building high-accuracy segmentation models requires a large amount of high-quality labeled data, but the cost of collecting such data is extremely high in medical imaging. In ultrasound imaging, the differences in image features depending on the equipment are significantly greater compared to other medical imaging modalities. Consequently, models need to be trained for each specific device, which entails substantial costs and time, leading to various practical challenges. To address these challenges, we propose a robust and accurate segmentation network that can operate independently of the ultrasound equipment. We integrated the Deep Frequency Filtering (DFF) module into a U-Net-based model. The proposed model retains the U-Net's encoder-decoder structure but applies frequency filtering within the latent space of each encoder layer, enabling adaptive selection of frequency components for breast tumor detection. Moreover, batch normalization was replaced with instance normalization to remove stylish features. We evaluated the model using three public datasets acquired from different scanners, achieving superior performance on unseen testing datasets compared to existing models. Notably, when tested on the unseen BUS-BRA dataset, DAUS-Net achieved a Dice score of 0.76, compared to 0.61 by the conventional U-Net. This improvement is attributed to the synergy between the DFF module and instance normalization. Our results demonstrate that the proposed model consistently detects and segments breast tumors, highlighting its potential for generalized clinical segmentation task. The source code for implementing DAUS-Net is publicly available at https://github.com/shlee8638/DAUS-Net.","PeriodicalId":49401,"journal":{"name":"Ultrasonic Imaging","volume":" ","pages":"201-214"},"PeriodicalIF":2.5,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145835168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimizing Diagnosis of Non-Microcalcified BI-RADS 4 Breast Lesions Using Multimodal Ultrasound Logistic Regression. 多模态超声Logistic回归对非微钙化BI-RADS 4型乳腺病变的优化诊断

IF 2.5 4区医学

Ultrasonic Imaging Pub Date : 2026-04-07 DOI: 10.1177/01617346261434982

Yuqing He, Shuai Guo, Zizheng Wu, Qingzhuang Gao, Hui Li, Shanbing Gao

{"title":"Optimizing Diagnosis of Non-Microcalcified BI-RADS 4 Breast Lesions Using Multimodal Ultrasound Logistic Regression.","authors":"Yuqing He, Shuai Guo, Zizheng Wu, Qingzhuang Gao, Hui Li, Shanbing Gao","doi":"10.1177/01617346261434982","DOIUrl":"https://doi.org/10.1177/01617346261434982","url":null,"abstract":"To develop a logistic prediction model based on multimodal ultrasound to enhance the diagnostic performance for non-microcalcified BI-RADS 4 breast lesions. We retrospectively analyzed ultrasound data from 334 patients with BI-RADS 4 breast lesions, incorporating 10 multimodal features. Model 1 was constructed using the entire cohort, while Model 2 focused on a subset of 225 non-microcalcified cases, with features selected via Lasso regularization and performance evaluated through 10-fold cross-validation. Model 1 identified lesion size >2 cm (OR = 1.65, p = .041), microcalcification (OR = 3.62, p < .001), and Emax (OR = 1.02, p = .001) as independent predictors, with an AUC of 0.85 (95%CI: 0.78-0.91). Model 2 selected lesion size, Adler grade, and Emax as significant features, achieving an AUC of 0.88 (95%CI: 0.81-0.92), with a 10-fold cross-validated accuracy of 0.81, Kappa of .57, and Hosmer-Lemeshow test (χ2 = 5.23, p = .850) for calibration. The multimodal ultrasound-based logistic model significantly improves the diagnosis of non-microcalcified BI-RADS 4 breast lesions (AUC = 0.88), with lesion size, Adler grade, and Emax as key predictors, offering a cost-effective tool to reduce unnecessary biopsies in clinical practice.","PeriodicalId":49401,"journal":{"name":"Ultrasonic Imaging","volume":" ","pages":"1617346261434982"},"PeriodicalIF":2.5,"publicationDate":"2026-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147628822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimization of Ultrasound Phase-Encoded Multiplane Wave Tissue Harmonic Imaging. 超声相位编码多平面波组织谐波成像的优化。

IF 2.5 4区医学

Ultrasonic Imaging Pub Date : 2026-03-30 DOI: 10.1177/01617346261436047

Che-Chou Shen, Ching-Che Chiu, You-Lin Chu

{"title":"Optimization of Ultrasound Phase-Encoded Multiplane Wave Tissue Harmonic Imaging.","authors":"Che-Chou Shen, Ching-Che Chiu, You-Lin Chu","doi":"10.1177/01617346261436047","DOIUrl":"https://doi.org/10.1177/01617346261436047","url":null,"abstract":"Tissue harmonic imaging has superior spatial and contrast resolution compared to conventional linear imaging but suffers from low signal-to-noise ratio (SNR). While phase-encoded excitation can be used to improve the harmonic SNR, distortion of the harmonic signal may compromise the accuracy of bipolar code sequence, leading to axial artifacts in tissue harmonic imaging after decoding. In this study, phase-encoded tissue harmonic imaging with multiplane wave (MW) transmission is compared among coding matrices (i.e., Hadamard, S-sequence and orthogonal Golay) as well as different design of bit waveform. Both simulations and experiments are conducted to validate our analysis on the coding schemes and bit waveforms. Results demonstrate that Hadamard and Golay are affected by phase distortion of harmonic waveform due to their bipolar nature. However, Hadamard can avoid these axial artifacts by sacrificing the first plane wave (PW) angle in the angular compounding. In contrast, the unipolar S-sequence is not affected by phase distortion but suffers from the reduced SNR gain compared to Hadamard. Regarding the bit waveform, the rectangular waveform provides the higher SNR but induces severe spectral distortion of the transmit phase due to its discontinuities in the envelope. This distortion becomes prominent when combined with Golay, leading to severe axial artifacts and a noticeable reduction in image contrast. It is concluded that the Hadamard with rectangular waveform and selective compounding is the optimal configuration for phase-encoded MW tissue harmonic imaging due to its higher SNR than the S-sequence and higher image quality than the orthogonal Golay.","PeriodicalId":49401,"journal":{"name":"Ultrasonic Imaging","volume":" ","pages":"1617346261436047"},"PeriodicalIF":2.5,"publicationDate":"2026-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147582119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Region-Adaptive Null Subtraction Imaging Using Generalized Coherence Factor for Coherent Plane Wave Compounding. 基于广义相干因子的相干平面波合成区域自适应零差成像。

IF 2.5 4区医学

Ultrasonic Imaging Pub Date : 2026-03-03 DOI: 10.1177/01617346261421141

Yijun Xu, Yaoting Yue, Hao Wang, Wenting Gu, Boyi Li, Lingxiao Liu, Xin Liu

{"title":"Region-Adaptive Null Subtraction Imaging Using Generalized Coherence Factor for Coherent Plane Wave Compounding.","authors":"Yijun Xu, Yaoting Yue, Hao Wang, Wenting Gu, Boyi Li, Lingxiao Liu, Xin Liu","doi":"10.1177/01617346261421141","DOIUrl":"https://doi.org/10.1177/01617346261421141","url":null,"abstract":"Coherent plane wave compounding (CPWC) is a widely used technique for ultrafast ultrasound imaging. However, the unfocused beams limit its image quality. The null subtraction imaging (NSI) has been proposed to improve its image quality. However, the image's contrast, resolution, and speckle quality depend on the variable DC offset parameter. Since NSI employs a fixed offset in a single image, a trade-off arises among these three aspects. To address this issue, a region-adaptive NSI (raNSI) is proposed in this work. In raNSI, a modified generalized coherence factor (GCF) is used to identify different regions within an image. raNSI then applies different offset to points in the identified different regions. The neighborhood statistics-based cleaning (NSBC) algorithm is applied to eliminate unexpected outliers in the selected offsets. The effectiveness of raNSI is demonstrated through simulated, experimental and in vivo datasets. The phantom experimental results show that comparing with NSI with an offset of 1, the contrast ratio (CR), speckle signal-to-noise ratio (sSNR) and contrast-to-noise ratio (gCNR) of the proposed raNSI are improved by 57.94 dB, 0.19 and 0.0327, respectively, while passing the Kolmogorov-Smirnov test-confirming that its speckle pattern remains intact. Furthermore, the lateral resolution is enhanced by 6.9%. It indicates that raNSI can achieve high resolution and high contrast while preserving the speckle pattern well. In addition, raNSI has shown the potential to reduce the number of required plane waves by a factor of five.","PeriodicalId":49401,"journal":{"name":"Ultrasonic Imaging","volume":" ","pages":"1617346261421141"},"PeriodicalIF":2.5,"publicationDate":"2026-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147349464","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0