Physics in medicine and biology最新文献

{"title":"Hybrid modality dual-energy imaging aggregating complementary advantages of kV-CT and MV-CBCT: concept proposal and clinical validation.","authors":"Junfeng Qi, Shutong Yu, Zhengkun Dong, Jiang Liu, Juan Deng, Guojian Mei, Chuou Yin, Qiao Li, Tian Li, Shi Wang, Yibao Zhang","doi":"10.1088/1361-6560/ad84b1","DOIUrl":"https://doi.org/10.1088/1361-6560/ad84b1","url":null,"abstract":"<p><strong>Objective: </strong>Megavoltage cone-beam CT (MV-CBCT) is advantageous in metal artifact reduction during Image-Guided Radiotherapy (IGRT), although it is limited by poor soft tissue contrast. This study proposed and evaluated a novel hybrid modality dual-energy (DE) imaging method combining the complementary advantages of kV-CT and MV-CBCT.&#xD;Approach: The kV-CT and MV-CBCT images were acquired on a planning CT scanner and a Halcyon linear accelerator respectively. After rigid registration, images of basis materials were generated using the iterative decomposition method in the volumetric images. The decomposition accuracy was quantitatively evaluated on a Gammex 1472 phantom. The performance of contrast enhancement and metal artifact reduction in virtual monochromatic images were evaluated on both phantom and patient studies.&#xD;Main results: Using the proposed method, the mean percentage errors for RED and SPR were 0.90% and 0.81%, outperforming the clinical single-energy mapping method with mean errors of 1.28% and 1.07%, respectively. The contrasts of soft-tissue insets were enhanced by a factor of 2~3 at 40 keV compared to kV-CT. The standard deviation in the metal artifact area was reduced by ~67%, from 42 HU (kV-CT) to 14 HU (150 keV monochromatic). The head and neck patient test showed that the percent error of soft-tissue RED in the metal artifact area was reduced from 18.1% (HU-RED conversion) to less than 1.0% (the proposed method), which was equivalent to the maximum dosimetric difference of 28.7% based on the patient-specific plan.&#xD;Significance: Without hardware modification or extra imaging dose, the proposed hybrid modality method enabled kV-MV DE imaging, providing improved accuracy of quantitative analysis, soft-tissue contrast and metal artifact suppression for more accurate IGRT.&#xD.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142392514","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing timing performance of heterostructures with double-sided readout.","authors":"Fiammetta Pagano, Nicolaus Kratochwil, Carsten Lowis, Woon-Seng Choong, Marco Paganoni, Marco Pizzichemi, Joshua W Cates, Etiennette Auffray","doi":"10.1088/1361-6560/ad7fc8","DOIUrl":"10.1088/1361-6560/ad7fc8","url":null,"abstract":"<p><p><i>Objective.</i>Heterostructured scintillators offer a promising solution to balance the sensitivity and timing in TOF-PET detectors. These scintillators utilize alternating layers of materials with complementary properties to optimize performance. However, the layering compromises time resolution due to light transport issues. This study explores double-sided readout-enabling improved light collection and Depth-of-Interaction (DOI) information retrieval-to mitigate this effect and enhance the timing capabilities of heterostructures.<i>Approach.</i>The time resolution and DOI performances of 3 × 3 × 20 mm³BGO&EJ232 heterostructures were assessed in a single and double-sided readout (SSR and DSR, respectively) configuration using high-frequency electronics.<i>Main results.</i>Selective analysis of photopeak events yielded a DOI resolution of 6.4 ± 0.04 mm. Notably, the Coincidence Time Resolution (CTR) improved from 262 ± 8 ps (SSR) to 174 ± 6 ps (DSR) when measured in coincidence with a fast reference detector. Additionally, symmetrical configuration of two identical heterostructures in coincidence was tested, yielding in DSR a CTR of 254 ± 8 ps for all photopeak events and 107 ± 5 ps for the fastest events.<i>Significance.</i>By using high-frequency double-sided readout, we could measure DOI resolution and improve the time resolution of heterostructures of up to 40%. The DOI information resulted intrinsically captured in the average between the timestamps of the two SiPMs, without requiring any further correction.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142351976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring charge sharing compensation using inter-pixel coincidence counters for photon counting detectors by deep-learning from local information.","authors":"Shengzi Zhao, Le Shen, Katsuyuki Taguchi, Yuxiang Xing","doi":"10.1088/1361-6560/ad841e","DOIUrl":"https://doi.org/10.1088/1361-6560/ad841e","url":null,"abstract":"<p><strong>Objective: </strong>Photon counting detectors (PCDs) have well-acknowledged advantages in computed tomography (CT) imaging. However, charge sharing and other problems prevent PCDs from fully realizing the anticipated potential in diagnostic CT. PCDs with multi-energy inter-pixel coincidence counters (MEICC) have been proposed to provide particular information about charge sharing, thereby achieving lower Cramér-Rao Lower Bound (CRLB) than conventional PCDs when assessing its performance by estimating material thickness or virtual monochromatic attenuation integrals (VMAIs). This work explores charge sharing compensation using local spatial coincidence counter information for MEICC detectors through a deep-learning method.&#xD;Approach: By analyzing the impact of charge sharing on photon count detection, we designed our network with a focus on individual pixels. Employing MEICC data of patches centered on POIs as input, we utilized local information for effective charge sharing compensation. The output was VMAI at different energies to address real detector issues without knowledge of primary counts. To achieve data diversity, a fast and online data generation method was proposed to provide adequate training data. A new loss function was introduced to reduce bias for training with high-noise data. The proposed method was validated by Monte Carlo (MC) simulation data for MEICC detectors that were compared with conventional PCDs. &#xD;Main-Results: For conventional data as a reference, networks trained on low-noise data yielded results with a minimal bias (about 0.7%) compared with > 3% for the polynomial fitting method. The results of networks trained on high-noise data exhibited a slightly increased bias (about 1.3%) but a significantly reduced standard deviation (STD) and normalized root mean square error (NRMSE). The simulation study of the MEICC detector demonstrated superior compared to the conventional detector across all the metrics. Specifically, for both networks trained on high-noise and low-noise data, their biases were reduced to about 1% and 0.6%, respectively. Meanwhile, the results from a MEICC detector were of about 10% lower noise than a conventional detector. Moreover, an ablation study showed that the additional loss function on bias was beneficial for training on high-noise data.&#xD;Significance: We demonstrated that a network-based method could utilize local information in PCDs effectively by patch-based learning to reduce the impact of charge sharing. MEICC detectors provide very valuable local spatial information by additional coincidence counters. Compared with MEICC detectors, conventional PCDs only have limited local spatial information for charge sharing compensation, resulting in higher bias and standard deviation in VMAI estimation with the same patch strategy.&#xD.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142392511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Joint segmentation of tumors in 3D PET-CT images with a network fusing multi-view and multi-modal information.","authors":"HaoYang Zheng, Wei Zou, Nan Hu, Jiajun Wang","doi":"10.1088/1361-6560/ad7f1b","DOIUrl":"10.1088/1361-6560/ad7f1b","url":null,"abstract":"<p><p><i>Objective</i>. Joint segmentation of tumors in positron emission tomography-computed tomography (PET-CT) images is crucial for precise treatment planning. However, current segmentation methods often use addition or concatenation to fuse PET and CT images, which potentially overlooks the nuanced interplay between these modalities. Additionally, these methods often neglect multi-view information that is helpful for more accurately locating and segmenting the target structure. This study aims to address these disadvantages and develop a deep learning-based algorithm for joint segmentation of tumors in PET-CT images.<i>Approach</i>. To address these limitations, we propose the Multi-view Information Enhancement and Multi-modal Feature Fusion Network (MIEMFF-Net) for joint tumor segmentation in three-dimensional PET-CT images. Our model incorporates a dynamic multi-modal fusion strategy to effectively exploit the metabolic and anatomical information from PET and CT images and a multi-view information enhancement strategy to effectively recover the lost information during upsamping. A Multi-scale Spatial Perception Block is proposed to effectively extract information from different views and reduce redundancy interference in the multi-view feature extraction process.<i>Main results</i>. The proposed MIEMFF-Net achieved a Dice score of 83.93%, a Precision of 81.49%, a Sensitivity of 87.89% and an IOU of 69.27% on the Soft Tissue Sarcomas dataset and a Dice score of 76.83%, a Precision of 86.21%, a Sensitivity of 80.73% and an IOU of 65.15% on the AutoPET dataset.<i>Significance</i>. Experimental results demonstrate that MIEMFF-Net outperforms existing state-of-the-art models which implies potential applications of the proposed method in clinical practice.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142351978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Global and local feature extraction based on convolutional neural network residual learning for MR image denoising.","authors":"Meng Li, Juntong Yun, Dingxi Liu, Daixiang Jiang, Hanlin Xiong, Du Jiang, Shunbo Hu, Rong Liu, Gongfa Li","doi":"10.1088/1361-6560/ad7e78","DOIUrl":"10.1088/1361-6560/ad7e78","url":null,"abstract":"<p><p><i>Objective.</i>Given the different noise distribution information of global and local magnetic resonance (MR) images, this study aims to extend the current work on convolutional neural networks that preserve global structure and local details in MR image denoising tasks.<i>Approach.</i>This study proposed a parallel and serial network for denoising 3D MR images, called 3D-PSNet. We use the residual depthwise separable convolution block to learn the local information of the feature map, reduce the network parameters, and thus improve the training speed and parameter efficiency. In addition, we consider the feature extraction of the global image and utilize residual dilated convolution to process the feature map to expand the receptive field of the network and avoid the loss of global information. Finally, we combine both of them to form a parallel network. What's more, we integrate reinforced residual convolution blocks with dense connections to form serial network branches, which can remove redundant information and refine features to further obtain accurate noise information.<i>Main results.</i>The peak signal-to-noise ratio, structural similarity index measure, and root mean square error metrics of 3D-PSNet are as high as 47.79%, 99.81%, and 0.40%, respectively, achieving competitive denoising effect on three public datasets. The ablation experiments demonstrated the effectiveness of all the designed modules regarding all the evaluated metrics in both datasets.<i>Significance.</i>The proposed 3D-PSNet takes advantage of multi-scale receptive fields, local feature extraction and residual dense connections to more effectively restore the global structure and local fine features in MR images, and is expected to help doctors quickly and accurately diagnose patients' conditions.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142308360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Relative biological effectiveness of clinically relevant photon energies for the survival of human colorectal, cervical, and prostate cancer cell lines.","authors":"Joanna Li, Naim Chabaytah, Joud Babik, Behnaz Behmand, Hamed Bekerat, Tanner Connell, Michael Evans, Russell Ruo, Te Vuong, Shirin Abbasinejad Enger","doi":"10.1088/1361-6560/ad7d5a","DOIUrl":"10.1088/1361-6560/ad7d5a","url":null,"abstract":"<p><p><i>Objective.</i>Relative biological effectiveness (RBE) differs between radiation qualities. However, an RBE of 1.0 has been established for photons regardless of the wide range of photon energies used clinically, the lack of reproducibility in radiobiological studies, and outdated reference energies used in the experimental literature. Moreover, due to intrinsic radiosensitivity, different cancer types have different responses to radiation. This study aimed to characterize the RBE of clinically relevant high and low photon energies<i>in vitro</i>for three human cancer cell lines: HCT116 (colon), HeLa (cervix), and PC3 (prostate).<i>Approach.</i>Experiments were conducted following dosimetry protocols provided by the American Association of Physicists in Medicine. Cells were irradiated with 6 MV x-rays, an¹⁹²Ir brachytherapy source, 225 kVp and 50 kVp x-rays. Cell survival post-irradiation was assessed using the clonogenic assay. Survival fractions were fitted using the linear quadratic model, and survival curves were generated for RBE calculations.<i>Main results.</i>Cell killing was more efficient with decreasing photon energy. Using 225 kVp x-rays as the reference, the HCT116 RBE_SF0.1for 6 MV x-rays,¹⁹²Ir, and 50 kVp x-rays were 0.89 ± 0.03, 0.95 ± 0.03, and 1.24 ± 0.04; the HeLa RBE_SF0.1were 0.95 ± 0.04, 0.97 ± 0.05, and 1.09 ± 0.03, and the PC3 RBE_SF0.1were 0.84 ± 0.01, 0.84 ± 0.01, and 1.13 ± 0.02, respectively. HeLa and PC3 cells had varying radiosensitivity when irradiated with 225 and 50 kVp x-rays.<i>Significance.</i>This difference supports the notion that RBE may not be 1.0 for all photons through experimental investigations that employed precise dosimetry. It highlights that different cancer types may not have identical responses to the same irradiation quality. Additionally, the RBE of clinically relevant photons was updated to the reference energy of 225 kVp x-rays.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142293206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Macrophage uptake rate of Sonazoid in breast lymphosonography is highly conserved in healthy controls.","authors":"Kenneth M Tichauer, Priscilla Machado, Ji-Bin Liu, A S Chalmika Sarathchandra, Maria Stanczak, Walter K Kraft, Flemming Forsberg","doi":"10.1088/1361-6560/ad7f1c","DOIUrl":"10.1088/1361-6560/ad7f1c","url":null,"abstract":"<p><p>Subcutaneous microbubble administration in connection with contrast enhanced ultrasound (CEUS) imaging is showing promise as a noninvasive and sensitive way to detect tumor draining sentinel lymph nodes (SLNs) in patients with breast cancer. Moreover, there is potential to harness the results from these approaches to directly estimate cancer burden, since some microbubble formulas, such as the Sonazoid used in this study, are rapidly phagocytosed by macrophages, and the macrophage concentration in a lymph node is inversely related to the cancer burden. This work presents a mathematical model that can approximate a rate constant governing macrophage uptake of Sonazoid,<i>k_i</i>, given dynamic CEUS Sonazoid imaging data. Twelve healthy women were injected with 1.0 ml of Sonazoid in an upper-outer quadrant of one of their breasts and SLNs were imaged in each patient immediately after injection, and then at 0.25, 0.5, 1, 2, 4, 6, and 24 h after injection. The mathematical model developed was fit to the dynamic CEUS data from each subject resulting in a mean ± sd of 0.006 ± 0.005 h^-1and 0.4 ± 0.1 h^-1for relative lymphatic flow (<i>EF_l</i>) and<i>k_i</i>, respectively. Furthermore, the roughly 25% sd of the<i>k_i</i>measurement was similar to the sd that would be expected from realistic noise simulations for a stable 0.4 h^-1value of<i>k_i</i>, suggesting that macrophage concentration is highly consistent among cancer-free SLNs. These results, along with the significantly smaller variance in<i>k_i</i>measurement observed compared to relative lymphatic flow suggest that<i>k_i</i>may be a more precise and promising approach of estimating macrophage abundance, and inversely cancer burden. Future studies comparing tumor-free to tumor-bearing nodes are planned to verify this hypothesis.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142351979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Towards a fully automatic workflow for investigating the dynamics of lung cancer cachexia during radiotherapy using cone beam computed tomography.","authors":"Lars H B A Daenen, Wouter R P H van de Worp, Behzad Rezaeifar, Joël de Bruijn, Peiyu Qiu, Justine M Webster, Stéphanie Peeters, Dirk De Ruysscher, Ramon C J Langen, Cecile J A Wolfs, Frank Verhaegen","doi":"10.1088/1361-6560/ad7d5b","DOIUrl":"10.1088/1361-6560/ad7d5b","url":null,"abstract":"<p><p><i>Objective.</i>Cachexia is a devastating condition, characterized by involuntary loss of muscle mass with or without loss of adipose tissue mass. It affects more than half of patients with lung cancer, diminishing treatment effects and increasing mortality. Cone-beam computed tomography (CBCT) images, routinely acquired during radiotherapy treatment, might contain valuable anatomical information for monitoring body composition changes associated with cachexia. For this purpose, we propose an automatic artificial intelligence (AI)-based workflow, consisting of CBCT to CT conversion, followed by segmentation of pectoralis muscles.<i>Approach.</i>Data from 140 stage III non-small cell lung cancer patients was used. Two deep learning models, cycle-consistent generative adversarial network (CycleGAN) and contrastive unpaired translation (CUT), were used for unpaired training of CBCT to CT conversion, to generate synthetic CT (sCT) images. The no-new U-Net (nnU-Net) model was used for automatic pectoralis muscle segmentation. To evaluate tissue segmentation performance in the absence of ground truth labels, an uncertainty metric (UM) based on Monte Carlo dropout was developed and validated.<i>Main results.</i>Both CycleGAN and CUT restored the Hounsfield unit fidelity of the CBCT images compared to the planning CT (pCT) images and visually reduced streaking artefacts. The nnU-Net model achieved a Dice similarity coefficient (DSC) of 0.93, 0.94, 0.92 for the CT, sCT and CBCT images, respectively, on an independent test set. The UM showed a high correlation with DSC with a correlation coefficient of -0.84 for the pCT dataset and -0.89 for the sCT dataset.<i>Significance.</i>This paper shows a proof-of-concept for automatic AI-based monitoring of the pectoralis muscle area of lung cancer patients during radiotherapy treatment based on CBCT images, which provides an unprecedented time resolution of muscle mass loss during cachexia progression. Ultimately, the proposed workflow could provide valuable information for early intervention of cachexia, ideally resulting in improved cancer treatment outcome.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142293249","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A dynamic approach for MR T2-weighted pelvic imaging.","authors":"Jing Cheng, Qingneng Li, Naijia Liu, Jun Yang, Yu Fu, Zhuoxu Cui, Zhenkui Wang, Guobin Li, Huimao Zhang, Dong Liang","doi":"10.1088/1361-6560/ad8335","DOIUrl":"https://doi.org/10.1088/1361-6560/ad8335","url":null,"abstract":"<p><strong>Objective: </strong>T2-weighted 2D fast spin echo sequence serves as the standard sequence in&#xD;clinical pelvic MR imaging protocols. However, motion artifacts and blurring caused&#xD;by peristalsis present significant challenges. Patient preparation such as administering&#xD;antiperistaltic agents is often required before examination to reduce artifacts, which&#xD;discomfort the patients. This work introduce a novel dynamic approach for T2&#xD;weighted pelvic imaging to address peristalsis-induced motion issue without any patient&#xD;preparation.&#xD;Approach: A rapid dynamic data acquisition strategy with complementary sampling&#xD;trajectory is designed to enable highly undersampled motion-resistant data sampling,&#xD;and an unrolling method based on deep equilibrium model is leveraged to reconstruct&#xD;images from the dynamic sampled k-space data. Moreover, the fix-point convergence of&#xD;the equilibrium model ensures the stability of the reconstruction. The high acceleration&#xD;factor in each temporal phase, which is much higher than that in traditional static&#xD;imaging, has the potential to effectively freeze pelvic motion, thereby transforming&#xD;the imaging problem from conventional motion prevention or removal to motion&#xD;reconstruction.&#xD;Main results: Experiments on both retrospective and prospective data have&#xD;demonstrated the superior performance of the proposed dynamic approach in reducing&#xD;motion artifacts and accurately depicting structural details compared to standard static&#xD;imaging.&#xD;Significance: The proposed dynamic approach effectively captures motion states&#xD;through dynamic data acquisition and deep learning-based reconstruction, addressing&#xD;motion-related challenges in pelvic imaging.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142372587","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving microvascular sensitivity of color doppler using phase mask based flow recycling algorithm.","authors":"Hao Yu, Jiabin Zhang, Jingyi Yin, Jinyu Yang, Daichao Chen, Yu Xia, Jue Zhang","doi":"10.1088/1361-6560/ad8292","DOIUrl":"https://doi.org/10.1088/1361-6560/ad8292","url":null,"abstract":"<p><strong>Objective: </strong>&#xD;Blood flow sensitivity is a crucial metric for appraising the effectiveness of color Doppler flow imaging (CDFI). Color Doppler velocity maps based on classic autocorrelation techniques are widely used in clinical practice. However, these techniques often produce twinkling artifacts in noisy regions due to the inherent randomness of noise phases. To mitigate artifacts and improve image quality, Power Mask (PoM) technology becomes imperative. Nevertheless, PoM technology unintentionally filters out small flow signals that have similar power and frequency characteristics to noise signals, thereby reducing the imaging system's sensitivity to flow. &#xD;Approach:&#xD;To address this issue, a novel Flow Recycling Algorithm (FRA) based on phase anomaly is introduced in this study. This algorithm, excavating small flow signals from noise, aims to enhance the small flow signals with low-velocity by the phase characteristics of the color Doppler flow information. &#xD;Main results: &#xD;Experiments in multi-organ imaging have shown that the FRA-CDFI approach is more effective in suppressing twinkling artifacts in noisy regions, preserving intricate small flow signals, and markedly improving small blood flow sensitivity. This novel approach provides adequate technical support for clinical ultrasound imaging of organs with dense small blood vessels, such as the brain, kidneys, liver, and more. &#xD;Significance: &#xD;As a novel post-processing method, FRA-CDFI holds significant potential for future deployment in clinical high-frame-rate ultrasound imaging devices.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142366167","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}