PhotoacousticsPub Date : 2025-01-23DOI: 10.1016/j.pacs.2025.100685
Youshen Xiao , Yuting Shen , Sheng Liao , Bowei Yao , Xiran Cai , Yuyao Zhang , Fei Gao
{"title":"Limited-view photoacoustic imaging reconstruction via high-quality self-supervised neural representation","authors":"Youshen Xiao , Yuting Shen , Sheng Liao , Bowei Yao , Xiran Cai , Yuyao Zhang , Fei Gao","doi":"10.1016/j.pacs.2025.100685","DOIUrl":"10.1016/j.pacs.2025.100685","url":null,"abstract":"<div><div>In practical applications within the human body, it is often challenging to fully encompass the target tissue or organ, necessitating the use of limited-view arrays, which can lead to the loss of crucial information. Addressing the reconstruction of photoacoustic sensor signals in limited-view detection spaces has become a focal point of current research. In this study, we introduce a self-supervised network termed HIgh-quality Self-supervised neural representation (HIS), which tackles the inverse problem of photoacoustic imaging to reconstruct high-quality photoacoustic images from sensor data acquired under limited viewpoints. We regard the desired reconstructed photoacoustic image as an implicit continuous function in 2D image space, viewing the pixels of the image as sparse discrete samples. The HIS’s objective is to learn the continuous function from limited observations by utilizing a fully connected neural network combined with Fourier feature position encoding. By simply minimizing the error between the network’s predicted sensor data and the actual sensor data, HIS is trained to represent the observed continuous model. The results indicate that the proposed HIS model offers superior image reconstruction quality compared to three commonly used methods for photoacoustic image reconstruction.</div></div>","PeriodicalId":56025,"journal":{"name":"Photoacoustics","volume":"42 ","pages":"Article 100685"},"PeriodicalIF":7.1,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143162045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
PhotoacousticsPub Date : 2025-01-21DOI: 10.1016/j.pacs.2025.100690
Chuqin Huang , Emily Zheng , Wenhan Zheng , Huijuan Zhang , Yanda Cheng , Xiaoyu Zhang , Varun Shijo , Robert W. Bing , Isabel Komornicki , Linda M. Harris , Ermelinda Bonaccio , Kazuaki Takabe , Emma Zhang , Wenyao Xu , Jun Xia
{"title":"Enhanced clinical photoacoustic vascular imaging through a skin localization network and adaptive weighting","authors":"Chuqin Huang , Emily Zheng , Wenhan Zheng , Huijuan Zhang , Yanda Cheng , Xiaoyu Zhang , Varun Shijo , Robert W. Bing , Isabel Komornicki , Linda M. Harris , Ermelinda Bonaccio , Kazuaki Takabe , Emma Zhang , Wenyao Xu , Jun Xia","doi":"10.1016/j.pacs.2025.100690","DOIUrl":"10.1016/j.pacs.2025.100690","url":null,"abstract":"<div><div>Photoacoustic tomography (PAT) is an emerging imaging modality with widespread applications in both preclinical and clinical studies. Despite its promising capabilities to provide high-resolution images, the visualization of vessels might be hampered by skin signals and attenuation in tissues. In this study, we have introduced a framework to retrieve deep vessels. It combines a deep learning network to segment skin layers and an adaptive weighting algorithm to compensate for attenuation. Evaluation of enhancement using vessel occupancy metrics and signal-to-noise ratio (SNR) demonstrates that the proposed method significantly recovers deep vessels across various body positions and skin tones. These findings indicate the method’s potential to enhance quantitative analysis in preclinical and clinical photoacoustic research.</div></div>","PeriodicalId":56025,"journal":{"name":"Photoacoustics","volume":"42 ","pages":"Article 100690"},"PeriodicalIF":7.1,"publicationDate":"2025-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143162047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
PhotoacousticsPub Date : 2025-01-20DOI: 10.1016/j.pacs.2025.100691
Zhijin Shang , Hongpeng Wu , Gang Wang , Ruyue Cui , Biao Li , Ting Gong , Guqing Guo , Xuanbing Qiu , Chuanliang Li , Lei Dong
{"title":"Robust and compact light-induced thermoelastic sensor for atmospheric methane detection based on a vacuum-sealed subminiature tuning fork","authors":"Zhijin Shang , Hongpeng Wu , Gang Wang , Ruyue Cui , Biao Li , Ting Gong , Guqing Guo , Xuanbing Qiu , Chuanliang Li , Lei Dong","doi":"10.1016/j.pacs.2025.100691","DOIUrl":"10.1016/j.pacs.2025.100691","url":null,"abstract":"<div><div>A compact light-induced thermoelastic spectroscopy (LITES) instrument incorporating a subminiature quartz tuning fork (QTF) was developed for atmospheric methane (CH<sub>4</sub>) sensing. The QTF features prong dimensions of 1700 µm in length and 120 µm in width, which enable substantial thermoelastic expansion at the microscale, significantly enhancing the piezoelectric signal. The subminiature QTF was vacuum sealed to achieve a high quality factor of 20,511 and a temperature coefficient of frequency of − 0.91 ppm/℃, ensuring a high detection sensitivity and robustness for the LITES sensor. Under identical vacuum conditions, the subminiature QTF demonstrated a twofold signal enhancement compared to the standard QTF, resulting in a minimum detection limit (MDL) of 47 ppb with a 300-ms averaging time. Continuous measurements of atmospheric CH<sub>4</sub> levels over five days were conducted to evaluate the accuracy and robustness of the developed sensor for long-duration monitoring applications.</div></div>","PeriodicalId":56025,"journal":{"name":"Photoacoustics","volume":"42 ","pages":"Article 100691"},"PeriodicalIF":7.1,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143162044","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
PhotoacousticsPub Date : 2025-01-15DOI: 10.1016/j.pacs.2025.100688
Mu Liang , Mingqi Jiao , Mingyang Feng , Pengbo Chen , Yang Gao , Yingying Qiao , Lei Li , Chongxin Shan
{"title":"Multi-gas photoacoustic sensor using multi-mode demodulation","authors":"Mu Liang , Mingqi Jiao , Mingyang Feng , Pengbo Chen , Yang Gao , Yingying Qiao , Lei Li , Chongxin Shan","doi":"10.1016/j.pacs.2025.100688","DOIUrl":"10.1016/j.pacs.2025.100688","url":null,"abstract":"<div><div>Modulation technology is the necessary means for generating periodic acoustic waves in photoacoustic gas detection, primarily including intensity modulation and wavelength modulation. In multi-gas detection, when multiple lasers employ the same modulation technique, current technologies include time-division multiplexing (TDM) for measurements at different times and frequency-division multiplexing (FDM) for simultaneous measurements; when multiple lasers employ different modulation techniques, the only available technology is TDM with measurements conducted at different times, and whether simultaneous measurement can be achieved has not yet been verified. We propose, for the first time, a multi-gas photoacoustic sensor using multi-mode demodulation. This sensor employs multi-mode frequency division multiplexing (MMFDM) technology to separate and demodulate the multi-mode photoacoustic signal, thereby enabling the simultaneous measurement of multiple gases under different modulation techniques. To demonstrate the feasibility of this method, we used SO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> and HF, the SF<span><math><msub><mrow></mrow><mrow><mn>6</mn></mrow></msub></math></span> decomposition products in gas-insulated switchgear (GIS), as target gases and simultaneously detected their mixture using different modulation modes. Experimental results show that when the frequency difference is 10 Hz, multi-mode photoacoustic signal can be successfully separated, with the minimum detection limits for SO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> and HF reaching 117.9 ppb and 65.5 ppb, respectively. This study is the first to validate the separability of multi-mode photoacoustic signal and achieve multi-gas simultaneous measurement under multi-mode modulation, thereby eliminating the limitations of modulation mode in simultaneous photoacoustic multi-gas detection.</div></div>","PeriodicalId":56025,"journal":{"name":"Photoacoustics","volume":"42 ","pages":"Article 100688"},"PeriodicalIF":7.1,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11787612/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143082268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
PhotoacousticsPub Date : 2025-01-13DOI: 10.1016/j.pacs.2025.100689
Luigi Melchiorre , Francesco Anelli , Giansergio Menduni , Andrea Annunziato , Laurine Bodin , Solenn Cozic , Giovanni Magno , Angelo Sampaolo , Francesco Prudenzano , Vincenzo Spagnolo
{"title":"Dual-gas quartz-enhanced photoacoustic spectroscopy sensor exploiting two fiber-combined interband cascade lasers","authors":"Luigi Melchiorre , Francesco Anelli , Giansergio Menduni , Andrea Annunziato , Laurine Bodin , Solenn Cozic , Giovanni Magno , Angelo Sampaolo , Francesco Prudenzano , Vincenzo Spagnolo","doi":"10.1016/j.pacs.2025.100689","DOIUrl":"10.1016/j.pacs.2025.100689","url":null,"abstract":"<div><div>In this work, a novel indium fluoride glass 2-input-1-output fiber combiner was designed and fabricated to combine two Interband Cascade Laser (ICL) sources emitting in the mid-infrared wavelength range. To test the combiner performance, a dual-gas quartz-enhanced photoacoustic spectroscopy sensor was demonstrated for the detection of carbon dioxide (CO<sub>2</sub>) and nitric oxide (NO), employing two fiber-coupled ICLs having central emission wavelengths of 4,234 nm and 5,263 nm, respectively. The laser beams were coupled via the fiber combiner and then focused into a commercial acoustic detection module equipped with an input fiber-port, thus resulting in a plug-and-play sensing system. Tens of ppm-level detection limits at 3σ are achieved for both pollutants with a lock-in integration time (τ) of 0.1 s. Finally, an Allan-Werle analysis demonstrated the stability of the sensor, allowing the achievement of detection limit of 13 ppm and 4 ppm at τ = 10 s for CO<sub>2</sub> and NO, respectively.</div></div>","PeriodicalId":56025,"journal":{"name":"Photoacoustics","volume":"42 ","pages":"Article 100689"},"PeriodicalIF":7.1,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11787027/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143082267","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
PhotoacousticsPub Date : 2025-01-11DOI: 10.1016/j.pacs.2025.100684
Zhaoyong Liang , Zongxin Mo , Shuangyang Zhang , Long Chen , Danni Wang , Chaobin Hu , Li Qi
{"title":"Self-supervised light fluence correction network for photoacoustic tomography based on diffusion equation","authors":"Zhaoyong Liang , Zongxin Mo , Shuangyang Zhang , Long Chen , Danni Wang , Chaobin Hu , Li Qi","doi":"10.1016/j.pacs.2025.100684","DOIUrl":"10.1016/j.pacs.2025.100684","url":null,"abstract":"<div><div>Deep learning (DL) shows promise in estimating the absorption coefficient distribution of biological tissue in quantitative photoacoustic tomography (QPAT) imaging, but its application is limited by a lack of ground truth for supervised network training. To address this issue, we propose a DL-based light fluence correction method that only uses the original PAT images for network training. Our self-supervised QPAT network model, which we termed SQPA-Net, introduces light fluence estimation based on diffusion equation to the loss function, and thus guides the model to learn an implicit representation of photoacoustic light transport within tissue. Simulation and small animal imaging experiments demonstrate the effectiveness and efficiency of our method. Compared to current DL-based methods and traditional iterative correction method, the proposed SQPA-Net achieves better light fluence correction results and significantly reduces the processing time.</div></div>","PeriodicalId":56025,"journal":{"name":"Photoacoustics","volume":"42 ","pages":"Article 100684"},"PeriodicalIF":7.1,"publicationDate":"2025-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11786910/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143082269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
PhotoacousticsPub Date : 2025-01-10DOI: 10.1016/j.pacs.2025.100686
Shaoqiang Bi, Xinru Zhang, Zhonghai Zhang, Xuan Liu, Lu Qin, Jingqi Shi, Yiyang Zhao, Zongliang Wang
{"title":"A light-induced thermoelastic spectroscopy using surface mounted device quartz tuning fork","authors":"Shaoqiang Bi, Xinru Zhang, Zhonghai Zhang, Xuan Liu, Lu Qin, Jingqi Shi, Yiyang Zhao, Zongliang Wang","doi":"10.1016/j.pacs.2025.100686","DOIUrl":"10.1016/j.pacs.2025.100686","url":null,"abstract":"<div><div>This paper reported on a system for the detection of trace acetylene (C<sub>2</sub>H<sub>2</sub>) gas utilizing a surface mounted device quartz tuning fork (SMD QTF) in conjunction with light-induced thermoelastic spectroscopy (LITES) and provided a comparative analysis against a conventional plug-in quartz tuning fork (P-QTF). The SMD QTF is a cost-effective standard instrument featuring a transparent glass shell and smaller size, which eliminates the need for stripping shell in LITES and effectively mitigates oxidation of the QTF as well as drift in resonance frequency. The SMD QTF has almost 2–4 times more Q factor than the conventional bare P-QTF. Experiments demonstrated that the signal amplitude of the SMD-QTF was almost 9 times higher than that of the conventional bare P-QTF. Minimum detection limits (MDLs) of 68.11 ppb@220 s (P-QTF) and 40.39 ppb@200 s (Larger SMD QTF) were obtained for both under the same experimental conditions.</div></div>","PeriodicalId":56025,"journal":{"name":"Photoacoustics","volume":"42 ","pages":"Article 100686"},"PeriodicalIF":7.1,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143162046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
PhotoacousticsPub Date : 2025-01-09DOI: 10.1016/j.pacs.2025.100687
Shuyan Zhang , Jingtan Li , Lin Shen , Zhonghao Zhao , Minjun Lee , Kun Qian , Naidi Sun , Bin Hu
{"title":"Structure and oxygen saturation recovery of sparse photoacoustic microscopy images by deep learning","authors":"Shuyan Zhang , Jingtan Li , Lin Shen , Zhonghao Zhao , Minjun Lee , Kun Qian , Naidi Sun , Bin Hu","doi":"10.1016/j.pacs.2025.100687","DOIUrl":"10.1016/j.pacs.2025.100687","url":null,"abstract":"<div><div>Photoacoustic microscopy (PAM) leverages the photoacoustic effect to provide high-resolution structural and functional imaging. However, achieving high-speed imaging with high spatial resolution remains challenging. To address this, undersampling and deep learning have emerged as common techniques to enhance imaging speed. Yet, existing methods rarely achieve effective recovery of functional images. In this study, we propose Mask-enhanced U-net (MeU-net) for recovering sparsely sampled PAM structural and functional images. The model utilizes dual-channel input, processing photoacoustic data from 532 nm and 558 nm wavelengths. Additionally, we introduce an adaptive vascular attention mask module that focuses on vascular information recovery and design a vessel-specific loss function to enhance restoration accuracy. We simulate data from mouse brain and ear imaging under various levels of sparsity (4 ×, 8 ×, 12 ×) and conduct extensive experiments. The results demonstrate that MeU-net significantly outperforms traditional interpolation methods and other representative models in structural information and oxygen saturation recovery.</div></div>","PeriodicalId":56025,"journal":{"name":"Photoacoustics","volume":"42 ","pages":"Article 100687"},"PeriodicalIF":7.1,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11787619/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143082270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
PhotoacousticsPub Date : 2025-01-06DOI: 10.1016/j.pacs.2025.100683
Hanxu Ma , Yanjun Chen , Shunda Qiao , Ying He , Yufei Ma
{"title":"A high sensitive methane QEPAS sensor based on self-designed trapezoidal-head quartz tuning fork and high power diode laser","authors":"Hanxu Ma , Yanjun Chen , Shunda Qiao , Ying He , Yufei Ma","doi":"10.1016/j.pacs.2025.100683","DOIUrl":"10.1016/j.pacs.2025.100683","url":null,"abstract":"<div><div>A high sensitive methane (CH<sub>4</sub>) sensor based on quartz-enhanced photoacoustic spectroscopy (QEPAS) using self-designed trapezoidal-head quartz tuning fork (QTF) and high power diode laser is reported for the first time in this paper. The trapezoidal-head QTF with low resonant frequency (<em>f</em><sub><em>0</em></sub>) of ∼ 9 kHz, serves as the detection element, enabling longer energy accumulation times. A diode laser with an output power of 10 mW is utilized as the excitation source. A Raman fiber amplifier (RFA) is employed to boost the diode laser power to 300 mW to increase the excitation intensity. Acoustic micro-resonators (AmRs) are designed and placed on both sides of the QTF to form an acoustic standing wave cavity, which increases the acoustic wave intensity and enhances the vibration amplitude of the QTF. Additionally, the long-term stability is analyzed by Allan deviation analysis. When the average time of the sensor system is increased to 150 s, the minimum detection limit (MDL) of the CH<sub>4</sub>-QEPAS sensor system can be improved to 15.5 ppb.</div></div>","PeriodicalId":56025,"journal":{"name":"Photoacoustics","volume":"42 ","pages":"Article 100683"},"PeriodicalIF":7.1,"publicationDate":"2025-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11780171/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143082266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
PhotoacousticsPub Date : 2024-11-27DOI: 10.1016/j.pacs.2024.100670
Zilong Li , Jiabin Lin , Yiguang Wang, Jiahong Li, Yubin Cao, Xuan Liu, Wenbo Wan, Qiegen Liu, Xianlin Song
{"title":"Ultra-sparse reconstruction for photoacoustic tomography: Sinogram domain prior-guided method exploiting enhanced score-based diffusion model","authors":"Zilong Li , Jiabin Lin , Yiguang Wang, Jiahong Li, Yubin Cao, Xuan Liu, Wenbo Wan, Qiegen Liu, Xianlin Song","doi":"10.1016/j.pacs.2024.100670","DOIUrl":"10.1016/j.pacs.2024.100670","url":null,"abstract":"<div><div>Photoacoustic tomography, a novel non-invasive imaging modality, combines the principles of optical and acoustic imaging for use in biomedical applications. In scenarios where photoacoustic signal acquisition is insufficient due to sparse-view sampling, conventional direct reconstruction methods significantly degrade image resolution and generate numerous artifacts. To mitigate these constraints, a novel sinogram-domain priors guided extremely sparse-view reconstruction method for photoacoustic tomography boosted by enhanced diffusion model is proposed. The model learns prior information from the data distribution of sinograms under full-ring, 512-projections. In iterative reconstruction, the prior information serves as a constraint in least-squares optimization, facilitating convergence towards more plausible solutions. The performance of the method is evaluated using blood vessel simulation, phantoms, and <em>in vivo</em> experimental data. Subsequently, the transformation of the reconstructed sinograms into the image domain is achieved through the delay-and-sum method, enabling a thorough assessment of the proposed method. The results show that the proposed method demonstrates superior performance compared to the U-Net method, yielding images of markedly higher quality. Notably, for <em>in vivo</em> data under 32 projections, the sinogram structural similarity improved by ∼21 % over U-Net, and the image structural similarity increased by ∼51 % and ∼84 % compared to U-Net and delay-and-sum methods, respectively. The reconstruction in the sinogram domain for photoacoustic tomography enhances sparse-view imaging capabilities, potentially expanding the applications of photoacoustic tomography.</div></div>","PeriodicalId":56025,"journal":{"name":"Photoacoustics","volume":"41 ","pages":"Article 100670"},"PeriodicalIF":7.1,"publicationDate":"2024-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142757340","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}