International Conference on Photonics and Imaging in Biology and Medicine最新文献

Photoacoustic molecular imaging for microvascular system in browning adipose tissues 褐色脂肪组织微血管系统的光声分子成像

International Conference on Photonics and Imaging in Biology and Medicine Pub Date : 2023-07-18 DOI: 10.1117/12.2681769

Ronghe Chen, Sangni Lixu, Tao Chen

{"title":"Photoacoustic molecular imaging for microvascular system in browning adipose tissues","authors":"Ronghe Chen, Sangni Lixu, Tao Chen","doi":"10.1117/12.2681769","DOIUrl":"https://doi.org/10.1117/12.2681769","url":null,"abstract":"At present, approximately one third of adults worldwide are obese or overweight. The phenomenon of adipose browning, that is, adipocyte trans-differentiation from an energy storage role to a heat production role, opens up a new way to reverse obesity. However, current methods for judging whether adipose browning occurs are usually based on invasive histological assessments. Adipose browning has been found to be accompanied by changes in adipose microvascular system. Therefore, our research focused on the above biological feature and used a non-invasive photoacoustic imaging technique that integrates the advantages of optical and acoustic imaging to visualize adipose microvascular system in obese mice treated with cold stimulation in a three-dimensional mode. The results showed that based on hemoglobin components, photoacoustic molecular imaging could not only accurately visually display a full view of increased arteriovenous blood network and enhanced blood oxygen consumption during adipose browning, but also quantitatively analyze it. Moreover, the data was consistent with the results of histological means including hematoxylin-eosin staining and immunofluorescence staining. In summary, we demonstrated the feasibility of photoacoustic molecular imaging for detecting adipose browning. This work will provide a new possibility for non-invasive assessment of adipose browning, which can help researchers and clinicians fight against obesity.","PeriodicalId":110373,"journal":{"name":"International Conference on Photonics and Imaging in Biology and Medicine","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123713423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Limited-angle cherenkov-excited luminescence scanned tomography reconstruction based on spatial attention module 基于空间注意模块的切伦科夫激发有限角度发光扫描层析成像

International Conference on Photonics and Imaging in Biology and Medicine Pub Date : 2023-07-18 DOI: 10.1117/12.2682920

Mengfan Geng, Hu Zhang, Jingyue Zhang, Kebin Jia, Zhonghua Sun, Zhe Li, Jinchao Feng

{"title":"Limited-angle cherenkov-excited luminescence scanned tomography reconstruction based on spatial attention module","authors":"Mengfan Geng, Hu Zhang, Jingyue Zhang, Kebin Jia, Zhonghua Sun, Zhe Li, Jinchao Feng","doi":"10.1117/12.2682920","DOIUrl":"https://doi.org/10.1117/12.2682920","url":null,"abstract":"Cherenkov-Excited Luminescence Scanned Tomography (CELST) is a new emerging imaging modality, which uses the Cherenkov light to excite fluorophores for tomographic imaging. In order to improve the imaging depth and spatial resolution, a rotational CELST was developed to scan the imaging object to produce sinogram data, and a Filtered Back Projection (FBP) was used to recover the distribution of fluorophores. However, the images reconstructed by FBP are usually corrupted by artifacts due to measurements from limited angles. To reduce the artifacts, we propose a deep learning-based reconstruction algorithm (SAM-Unet), which is based on a fully convolutional deep neural network with U-Net structure, and a spatial attention module was added between the encoder and the decoder. The image features extracted by the spatial attention module are transferred to the decoder through a skip connection structure. The effectiveness of the proposed SAM-Unet is verified by numerical experiments, and the results show that the SAM-Unet can improve the mean square error (MSE) (97.5%), Peak Signal-To-Noise Ratio (PSNR) (81.9%) and Structure Similarity Index Measure (SSIM) (63.4%) compared with the FBP algorithm. Compared with the deep learning method U-Net, the MSE improved 39.8%, the PSNR improved 8.0% and SSIM improved 2.6%.","PeriodicalId":110373,"journal":{"name":"International Conference on Photonics and Imaging in Biology and Medicine","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122427629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Label-free analysis of single microparticles and nanoscale exosomes with two-dimensional light scattering technology 二维光散射技术对单个微粒和纳米级外泌体的无标记分析

International Conference on Photonics and Imaging in Biology and Medicine Pub Date : 2023-07-18 DOI: 10.1117/12.2682909

Zhuo Wang, Aishi Wang, Qiao Liu, Shuanglian Wang, Xuantao Su

{"title":"Label-free analysis of single microparticles and nanoscale exosomes with two-dimensional light scattering technology","authors":"Zhuo Wang, Aishi Wang, Qiao Liu, Shuanglian Wang, Xuantao Su","doi":"10.1117/12.2682909","DOIUrl":"https://doi.org/10.1117/12.2682909","url":null,"abstract":"Liver cancer is one of the most common digestive system malignancies with an average five-year survival rate of less than 20%, while traditional methods are often unautomated, labeling required, and limited for early liver cancer detection. Exosomes are a type of extracellular vesicles with a diameter of 40-150 nm, which play important role in disease diagnosis and treatment. It is of interest to develop a label-free optical system for the analysis of nanoscale exosomes. Here, we developed a label-free two-dimensional (2D) light scattering acquisition system for the measurements of microparticles and the exosomes derived from the normal liver cells. By adjusting the thickness of the light sheet for illumination in our system, nanoparticles down to 41 nm are detected. The visualization and accurate particle size analysis of liver cell exosomes are then performed by our 2D light scattering technology. Our method is expected to have important applications in the quantitative analysis field of cellular and extracellular structures that may find potential applications in clinics such as for early cancer diagnosis.","PeriodicalId":110373,"journal":{"name":"International Conference on Photonics and Imaging in Biology and Medicine","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114182291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Determination of birefringence of myocardial tissue based on PS-OCT with circularly polarized light as reference 以圆偏振光为参比的PS-OCT测定心肌组织双折射

International Conference on Photonics and Imaging in Biology and Medicine Pub Date : 2023-07-18 DOI: 10.1117/12.2683117

Wangbiao Li, Ke Li, Dezi Li, Haiyu Chen, Wenliang Cao, Shufeng Zhuo, Hui Li, Zhifang Li

{"title":"Determination of birefringence of myocardial tissue based on PS-OCT with circularly polarized light as reference","authors":"Wangbiao Li, Ke Li, Dezi Li, Haiyu Chen, Wenliang Cao, Shufeng Zhuo, Hui Li, Zhifang Li","doi":"10.1117/12.2683117","DOIUrl":"https://doi.org/10.1117/12.2683117","url":null,"abstract":"In this study, the modified spectral domain polarization-sensitive optical coherence tomography (SD PS-OCT) is proposed for determining the birefringence of the myocardial tissue. In this modified SD PS-OCT, the circular polarization state of light was generated before entering the beam splitter. Thus, the polarization states in the reference and sample arms are both circular, and the symmetry between them is good without using additional Quarter-Wave Plate (QWP), which reduce the dispersion effect. The results demonstrated that theoretical analysis for determination of birefringence including the phase retardance and the fast axis orientation based on Stokes parameters of backscattered from biological tissue, which is different from the traditional SD PS-OCT. In addition, the phase retardance and the fast axis orientation was used to differentiate the myocaridal tissue in the diastole of the cardiac cycle the from that in the systole of the cardiac cycle. The findings suggest that the SD PS-OCT be a potential tool for the real-time monitoring the change of the myocardial wall during the cardiac cycle.","PeriodicalId":110373,"journal":{"name":"International Conference on Photonics and Imaging in Biology and Medicine","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124821505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimization design of the coupling scheme of the pulse laser output through the hysteroscope observation channel 宫腔镜观察通道脉冲激光输出耦合方案的优化设计

International Conference on Photonics and Imaging in Biology and Medicine Pub Date : 2023-07-18 DOI: 10.1117/12.2682773

Jinrui Wang, Chuanhui Ge, Guansong Zou, Feiyang Wang, Xiaoman Zhang, Shulian Wu, Hengchang Guo, Huan Yi, Yulong Zhang, Hui Li

引用次数: 0

A deep learning-based algorithm for three-dimensional dose prediction 基于深度学习的三维剂量预测算法

International Conference on Photonics and Imaging in Biology and Medicine Pub Date : 2023-07-18 DOI: 10.1117/12.2685094

Mengjia Xue, Tianrui Liu, Yizhen Xie, Meiya Dong, Xiuping Liu

引用次数: 0

Semi-automatic segmentation of coronary vessels based on improved livewire algorithm 基于改进livewire算法的冠状血管半自动分割

International Conference on Photonics and Imaging in Biology and Medicine Pub Date : 2023-07-18 DOI: 10.1117/12.2683104

Jessica Dong, Zhengguo Dai, Tianwu Xie, Xin Yi

引用次数: 0

Label-free blood analysis utilizing contrast-enhanced defocusing imaging with machine vision 利用机器视觉对比度增强散焦成像的无标签血液分析

International Conference on Photonics and Imaging in Biology and Medicine Pub Date : 2023-07-18 DOI: 10.1117/12.2682246

Duan Chen, Ning Li, Xiuli Liu, Shaoqun Zeng, Xiaohua Lv, Li Chen, Yu-Xiang Xiao, Qinglei Hu

{"title":"Label-free blood analysis utilizing contrast-enhanced defocusing imaging with machine vision","authors":"Duan Chen, Ning Li, Xiuli Liu, Shaoqun Zeng, Xiaohua Lv, Li Chen, Yu-Xiang Xiao, Qinglei Hu","doi":"10.1117/12.2682246","DOIUrl":"https://doi.org/10.1117/12.2682246","url":null,"abstract":"Blood analysis, through the complete blood count, remains the most fundamental medical test for diagnosing broad diseases. Even so, it is still limited to central laboratories with sophisticated facilities and skilled professionals. Here, we propose a simple, machine-vision-aided, label-free blood analysis technique via a regular microscope utilizing contrast-enhance defocus imaging, i.e., defocusing imaging under 415 nm, small aperture illumination. We have shown that this technique can simultaneously obtain leucocytes’ optical phase and erythrocytes’ spectrophotometric information, making it feasible to realize five-part leucocyte differential and hemoglobin quantification with machine vision. The reliability was verified by comparing the quantified results with clinical reference results, which indicates significant linear correlations (significance levels ⪅ 0.0001 and Pearson coefficients ⪆ 0.90). We also show that the virtual staining of the label-free blood cell images can be performed with a generative adversarial network to mimic conventional Wright-Giemsa images, facilitating this technique’s medical translation. This study reports a simple, easy-to-use, quick, reliable blood analysis technique that may lead to a reformation in the blood analysis field. We emphasize this technique’s great potential for early screening of various diseases, including anemia, leukemia, and neglected tropical diseases, especially in resource-limited settings.","PeriodicalId":110373,"journal":{"name":"International Conference on Photonics and Imaging in Biology and Medicine","volume":"309 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131931159","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Processing and analysis of motion-blur images in light scattering flow cytometry 光散射流式细胞术中运动模糊图像的处理与分析

International Conference on Photonics and Imaging in Biology and Medicine Pub Date : 2023-07-18 DOI: 10.1117/12.2682917

F. Yuan, Zhiwen Wang, Qiao Liu, Xuantao Su

引用次数: 0

Application of image segmentation technology in TCM eye diagnosis 图像分割技术在中医眼科诊断中的应用

International Conference on Photonics and Imaging in Biology and Medicine Pub Date : 2023-07-18 DOI: 10.1117/12.2679810

Hong Peng, N. Niu, Yilin Zhang, Guanjun Wang, Chenyang Xue, Mengxing Huang

{"title":"Application of image segmentation technology in TCM eye diagnosis","authors":"Hong Peng, N. Niu, Yilin Zhang, Guanjun Wang, Chenyang Xue, Mengxing Huang","doi":"10.1117/12.2679810","DOIUrl":"https://doi.org/10.1117/12.2679810","url":null,"abstract":"Image segmentation is a critical technology in many fields, such as image processing, pattern recognition, and artificial intelligence. It is also the first and critical step in computer vision technology. Tongue diagnosis combined with deep learning for segmentation and extracting pathological features is relatively mature, but deep learning combined with TCM visualization is sporadic. First, We used the U2Net network1 for segmentation extraction of the sclera in this study. Where the U2Net1 network1 (based on PyTorch) relies on the extensive use of data enhancements to use the available annotation samples more efficiently, and compared with the U-Net network, the U2Net network1 updates an RSU module, each RSU module is a small U-net network,merging multiple U-Net outputs to get the merged Mask target. Finally, we applied classical CNN networks to evaluate the segmentation effect, introducing different evaluation metrics such as Miou, Precision, and Recall. We used the publicly available dataset UBIVIS.V12 for our experiments, where our Miou was as high as 97.3%, and U2Net achieved better results among all the networks, which laid the foundation for our subsequent segmentation and extraction of blood filament features.","PeriodicalId":110373,"journal":{"name":"International Conference on Photonics and Imaging in Biology and Medicine","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116004390","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0