Biomedical optics express最新文献_第5页

Mask-guided network for finger vein feature extraction and biometric identification. 用于手指静脉特征提取和生物识别的掩膜引导网络。

IF 2.9 2区医学

Biomedical optics express Pub Date : 2024-11-15 eCollection Date: 2024-12-01 DOI: 10.1364/BOE.535390

Haohan Bai, Yubo Tan, Yong-Jie Li

{"title":"Mask-guided network for finger vein feature extraction and biometric identification.","authors":"Haohan Bai, Yubo Tan, Yong-Jie Li","doi":"10.1364/BOE.535390","DOIUrl":"10.1364/BOE.535390","url":null,"abstract":"The problems of complex background, low quality of finger vein images, and poor discriminative features have been the bottleneck of feature extraction and finger vein recognition. To this end, we propose a feature extraction algorithm based on the open-set testing protocol. In order to eliminate the interference of irrelevant areas, this paper proposes the idea of segmentation-assisted classification, that is, using the rough mask of the finger vein to constrain the feature learning process so that the network can focus on the vein area and learn greater weight for the vein. Specifically, the feature maps of the shallow layers of the network are first sent to the feature pyramid module to fuse the primary features of different scales, which are then sent to the spatial attention module to obtain the spatial weight map of the image. Based on the results of several classical vein skeleton extraction algorithms, a weighting method is used to obtain a more accurate mask to constrain the learning of the spatial weight map. Finally, a hybrid loss function combining triplet loss and cross-entropy loss is used to reduce the distance between feature vectors of the same categories and increase the distance between feature vectors of different categories in the Euclidean space, thereby improving feature discriminability. Good recognition results were achieved on the three public data sets of SDUMLA, MMCBNU, and FVUSM, and the values of equal error rate (EER) on them are as low as 2.50%, 0.20%, and 0.14%, respectively.","PeriodicalId":8969,"journal":{"name":"Biomedical optics express","volume":"15 12","pages":"6845-6863"},"PeriodicalIF":2.9,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11640582/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142827319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Imaging of prostate micro-architecture using three-dimensional wide-field optical coherence tomography. 三维宽视场光学相干层析成像前列腺微结构。

IF 2.9 2区医学

Biomedical optics express Pub Date : 2024-11-14 eCollection Date: 2024-12-01 DOI: 10.1364/BOE.537783

Marta K Skrok, Szymon Tamborski, Matt S Hepburn, Qi Fang, Mateusz Maniewski, Marek Zdrenka, Maciej Szkulmowski, Adam Kowalewski, Łukasz Szylberg, Brendan F Kennedy

{"title":"Imaging of prostate micro-architecture using three-dimensional wide-field optical coherence tomography.","authors":"Marta K Skrok, Szymon Tamborski, Matt S Hepburn, Qi Fang, Mateusz Maniewski, Marek Zdrenka, Maciej Szkulmowski, Adam Kowalewski, Łukasz Szylberg, Brendan F Kennedy","doi":"10.1364/BOE.537783","DOIUrl":"10.1364/BOE.537783","url":null,"abstract":"Prostate cancer is a global health issue that requires new diagnostic methods to provide accurate and precise visualization of prostate tissue on the micro-scale. Such methods have the potential to improve nerve-sparing surgery and to provide image guidance during prostate biopsy. In this feasibility study, we assess the potential of en face three-dimensional wide-field optical coherence tomography (OCT), covering a volumetric imaging field-of-view up to 46 × 46 × 1 mm3, to visualize micro-architecture in 18 freshly excised human prostate specimens. In each case, validation of contrast in OCT images is provided by co-registered wide-field histology images. Using this co-registration, we demonstrate that OCT can distinguish between healthy and cancerous glands at different stages, as well as visualize micro-architecture in the prostate, such as epineurium and perineurium in nerves and the tunica intima and tunica media in blood vessels.","PeriodicalId":8969,"journal":{"name":"Biomedical optics express","volume":"15 12","pages":"6816-6833"},"PeriodicalIF":2.9,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11640564/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142827286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Diffractive hyperchromatic objective for chromatic confocal microscopy. 用于彩色共聚焦显微镜的衍射高色差物镜。

IF 2.9 2区医学

Biomedical optics express Pub Date : 2024-11-14 eCollection Date: 2024-12-01 DOI: 10.1364/BOE.543322

Jiabin Chen, Shaobai Li, Wenjun Kang, Shuyuan Guan, Zhihan Hong, Rongguang Liang

引用次数: 0

Fast and customizable image formation model for optical coherence tomography. 快速、可定制的光学相干断层扫描图像形成模型。

IF 2.9 2区医学

Biomedical optics express Pub Date : 2024-11-13 eCollection Date: 2024-12-01 DOI: 10.1364/BOE.534263

Andrea Mazzolani, Callum Macdonald, Peter R T Munro

{"title":"Fast and customizable image formation model for optical coherence tomography.","authors":"Andrea Mazzolani, Callum Macdonald, Peter R T Munro","doi":"10.1364/BOE.534263","DOIUrl":"10.1364/BOE.534263","url":null,"abstract":"Optical coherence tomography (OCT) is a technique that performs high-resolution, three-dimensional, imaging of semi-transparent scattering biological tissues. Models of OCT image formation are needed for applications such as aiding image interpretation and validating OCT signal processing techniques. Existing image formation models generally trade off between model realism and computation time. In particular, the most realistic models tend to be highly computationally demanding, which becomes a limiting factor when simulating C-scan generation. Here we present an OCT image formation model based on the first-order Born approximation that is significantly faster than existing models, whilst maintaining a high degree of realism. This model is made more powerful because it is amenable to simulation of phase sensitive OCT, thus making it applicable to scenarios where sample displacement is of interest, such as optical coherence elastography (OCE) or Doppler OCT. The low computational cost of the model also makes it suitable for creating large OCT data sets needed for training deep learning OCT signal processing models. We present details of our novel image formation model and demonstrate its accuracy and computational efficiency.","PeriodicalId":8969,"journal":{"name":"Biomedical optics express","volume":"15 12","pages":"6783-6798"},"PeriodicalIF":2.9,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11640576/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142827282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Embedded CPU-GPU pupil tracking. 嵌入式CPU-GPU瞳孔跟踪。

IF 2.9 2区医学

Biomedical optics express Pub Date : 2024-11-13 eCollection Date: 2024-12-01 DOI: 10.1364/BOE.541421

Bartlomiej Kowalski, Xiaojing Huang, Alfredo Dubra

{"title":"Embedded CPU-GPU pupil tracking.","authors":"Bartlomiej Kowalski, Xiaojing Huang, Alfredo Dubra","doi":"10.1364/BOE.541421","DOIUrl":"10.1364/BOE.541421","url":null,"abstract":"We explore camera-based pupil tracking using high-level programming in computing platforms with end-user discrete and integrated central processing units (CPUs) and graphics processing units (GPUs), seeking low calculation latencies previously achieved with specialized hardware and programming (Kowalski et al., [Biomed. Opt. Express12, 6496 (2021)10.1364/BOE.433766]. Various desktop and embedded computers were tested, some with two operating systems, using the traditional sequential pupil tracking paradigm, in which the processing of the camera image only starts after it is fully downloaded to the computer. The pupil tracking was demonstrated using two Scheimpflug optical setups, telecentric in both image and object spaces, with different optical magnifications and nominal diffraction-limited performance over an ∼18 mm full field of view illuminated with 940 nm light. Eye images from subjects with different iris and skin pigmentation captured at this wavelength suggest that the proposed pupil tracking does not suffer from ethnic bias. The optical axis of the setups is tilted at 45° to facilitate integration with other instruments without the need for beam splitting. Tracking with ∼0.9-4.4 µm precision and safe light levels was demonstrated using two complementary metal-oxide-semiconductor cameras with global shutter, operating at 438 and 1,045 fps with an ∼500 × 420 pixel region of interest (ROI), and at 633 and 1,897 fps with ∼315 × 280 pixel ROI. For these image sizes, the desktop computers achieved calculation times as low as 0.5 ms, while low-cost embedded computers delivered calculation times in the 0.8-1.3 ms range.","PeriodicalId":8969,"journal":{"name":"Biomedical optics express","volume":"15 12","pages":"6799-6815"},"PeriodicalIF":2.9,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11640584/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142827280","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Structural diversity of Alzheimer-related protein aggregations revealed using photothermal ratio-metric micro-spectroscopy. 利用光热比值微光谱学揭示阿尔茨海默氏症相关蛋白质聚集的结构多样性。

IF 2.9 2区医学

Biomedical optics express Pub Date : 2024-11-11 eCollection Date: 2024-12-01 DOI: 10.1364/BOE.537461

Siming Wang, Wenhao Zhang, Pengcheng Fu, Yan Zhong, Kiryl D Piatkevich, Delong Zhang, Hyeon Jeong Lee

{"title":"Structural diversity of Alzheimer-related protein aggregations revealed using photothermal ratio-metric micro-spectroscopy.","authors":"Siming Wang, Wenhao Zhang, Pengcheng Fu, Yan Zhong, Kiryl D Piatkevich, Delong Zhang, Hyeon Jeong Lee","doi":"10.1364/BOE.537461","DOIUrl":"10.1364/BOE.537461","url":null,"abstract":"The crucial link between pathological protein aggregations and lipids in Alzheimer's disease pathogenesis is increasingly recognized, yet its spatial dynamics remain challenging for labeling-based microscopy. Here, we demonstrate photothermal ratio-metric infrared spectro-microscopy (PRISM) to investigate the in situ structural and molecular compositions of pathological features in brain tissues at submicron resolution. By identifying the vibrational spectroscopic signatures of protein secondary structures and lipids, PRISM tracks the structural dynamics of pathological proteins, including amyloid and hyperphosphorylated Tau (pTau). Amyloid-associated lipid features in major brain regions were observed, notably the enrichment of lipid-dissociated plaques in the hippocampus. Spectroscopic profiling of pTau revealed significant heterogeneity in phosphorylation levels and a distinct lipid-pTau relationship that contrasts with the anticipated lipid-plaque correlation. Beyond in vitro studies, our findings provide direct visualization evidence of aggregate-lipid interactions across the brain, offering new insights into mechanistic and therapeutic research of neurodegenerative diseases.","PeriodicalId":8969,"journal":{"name":"Biomedical optics express","volume":"15 12","pages":"6768-6782"},"PeriodicalIF":2.9,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11640567/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142827335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Tissue-probe contact assessment during robotic surgery using single-fiber reflectance spectroscopy. 利用单纤维反射光谱仪评估机器人手术过程中组织与探针的接触情况。

IF 2.9 2区医学

Biomedical optics express Pub Date : 2024-11-11 eCollection Date: 2024-12-01 DOI: 10.1364/BOE.534558

Lotte M de Roode, Lisanne L de Boer, Henricus J C M Sterenborg, Theo J M Ruers

{"title":"Tissue-probe contact assessment during robotic surgery using single-fiber reflectance spectroscopy.","authors":"Lotte M de Roode, Lisanne L de Boer, Henricus J C M Sterenborg, Theo J M Ruers","doi":"10.1364/BOE.534558","DOIUrl":"10.1364/BOE.534558","url":null,"abstract":"The introduction of robotic surgery has improved minimally invasive surgery, and now robotic surgery is used in several areas of surgical oncology. Several optical techniques can be used to discriminate cancer from healthy tissue based on their optical properties. These technologies can also be employed with a small fiber-optic probe during minimally invasive surgery; however, for acquiring reliable measurements, some optical techniques require the fiber-optic probe to be in direct contact with the tissue. The lack of tactile feedback in robotic surgery makes assessing tissue-probe contact suitable for optical contact measurements challenging for the surgeon. In this study, we investigated the use of single fiber reflectance (SFR) to determine tissue-probe contact adequately. A machine learning-based algorithm was developed to classify if direct tissue-probe contact was present during the measurement in an ex-vivo tissue setup. Using this classification algorithm, an average accuracy of 93.9% was achieved for assessing probe-tissue contact, suggesting that this technique can be utilized to assess tissue-probe contact in an in vivo clinical setting.","PeriodicalId":8969,"journal":{"name":"Biomedical optics express","volume":"15 12","pages":"6756-6767"},"PeriodicalIF":2.9,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11640583/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142827340","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Cerebral blood flow patterns induced by photoactivation based on laser speckle contrast imaging. 基于激光斑点对比成像的光激活诱导脑血流模式。

IF 2.9 2区医学

Biomedical optics express Pub Date : 2024-11-08 eCollection Date: 2024-12-01 DOI: 10.1364/BOE.541444

Xuan Zhu, Liang Shi, Pengcheng Li, Jinling Lu

引用次数: 0

Accurate attenuation characterization in optical coherence tomography using multi-reference phantoms and deep learning. 光学相干层析成像中使用多参考幻影和深度学习的精确衰减表征。

IF 2.9 2区医学

Biomedical optics express Pub Date : 2024-11-06 eCollection Date: 2024-12-01 DOI: 10.1364/BOE.543606

Nian Peng, Chengli Xu, Yi Shen, Wu Yuan, Xiaoyu Yang, Changhai Qi, Haixia Qiu, Ying Gu, Defu Chen

{"title":"Accurate attenuation characterization in optical coherence tomography using multi-reference phantoms and deep learning.","authors":"Nian Peng, Chengli Xu, Yi Shen, Wu Yuan, Xiaoyu Yang, Changhai Qi, Haixia Qiu, Ying Gu, Defu Chen","doi":"10.1364/BOE.543606","DOIUrl":"10.1364/BOE.543606","url":null,"abstract":"The optical attenuation coefficient (AC), a crucial tissue parameter indicating the rate of light attenuation within a medium, enables quantitative analysis of tissue properties and facilitates tissue differentiation. Despite its growing clinical significance, accurate quantification of AC from optical coherence tomography (OCT) signals remains a pressing concern. This study comprehensively investigates the factors influencing the accuracy of quantitative AC extraction among existing OCT-based AC extraction algorithms. Subsequently, we propose an approach, the Multi-Reference Phantom Driven Network (MR-Net), which leverages multi-reference phantoms and deep learning to implicitly model factors affecting OCT signal propagation, thereby automatically regressing AC. Using a dataset from Intralipid and silicone-TiO2 phantoms with known AC values obtained from a collimated transmission system and imaged with a 1300 nm swept-source OCT system, we conducted a thorough comparison focusing on data length, out-of-focus distance, and reference phantoms' attenuation among existing OCT-based AC extraction algorithms. By leveraging this extensive dataset, MR-Net can automatically model the complex physical effects in the transmission process of OCT signals, significantly enhancing the accuracy of AC predictions. MR-Net outperforms other algorithms in all metrics, achieving an average relative error of only 10.43% for calculating attenuation samples, significantly lower than the lowest value of 23.72% achieved by other algorithms. This method offers a quantitative framework for disease diagnosis, ultimately contributing to more accurate and effective tissue characterization in clinical settings.","PeriodicalId":8969,"journal":{"name":"Biomedical optics express","volume":"15 12","pages":"6697-6714"},"PeriodicalIF":2.9,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11640581/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142827112","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

BreakNet: discontinuity-resilient multi-scale transformer segmentation of retinal layers. BreakNet：视网膜层的间断弹性多尺度变压器分割。

IF 2.9 2区医学

Biomedical optics express Pub Date : 2024-11-06 eCollection Date: 2024-12-01 DOI: 10.1364/BOE.538904

Razieh Ganjee, Bingjie Wang, Lingyun Wang, Chengcheng Zhao, José-Alain Sahel, Shaohua Pi

{"title":"BreakNet: discontinuity-resilient multi-scale transformer segmentation of retinal layers.","authors":"Razieh Ganjee, Bingjie Wang, Lingyun Wang, Chengcheng Zhao, José-Alain Sahel, Shaohua Pi","doi":"10.1364/BOE.538904","DOIUrl":"10.1364/BOE.538904","url":null,"abstract":"Visible light optical coherence tomography (vis-OCT) is gaining traction for retinal imaging due to its high resolution and functional capabilities. However, the significant absorption of hemoglobin in the visible light range leads to pronounced shadow artifacts from retinal blood vessels, posing challenges for accurate layer segmentation. In this study, we present BreakNet, a multi-scale Transformer-based segmentation model designed to address boundary discontinuities caused by these shadow artifacts. BreakNet utilizes hierarchical Transformer and convolutional blocks to extract multi-scale global and local feature maps, capturing essential contextual, textural, and edge characteristics. The model incorporates decoder blocks that expand pathways to enhance the extraction of fine details and semantic information, ensuring precise segmentation. Evaluated on rodent retinal images acquired with prototype vis-OCT, BreakNet demonstrated superior performance over state-of-the-art segmentation models, such as TCCT-BP and U-Net, even when faced with limited-quality ground truth data. Our findings indicate that BreakNet has the potential to significantly improve retinal quantification and analysis.","PeriodicalId":8969,"journal":{"name":"Biomedical optics express","volume":"15 12","pages":"6725-6738"},"PeriodicalIF":2.9,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11640562/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142827200","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0