Proceedings of SPIE--the International Society for Optical Engineering最新文献

{"title":"From Geometry to Intensity: A Coarse-to-Fine Pipeline for Unsupervised 3D Ultrasound Stitching.","authors":"Xing Yao, Runxuan Yu, Daiwei Lu, Nick DiSanto, Ehsan K Aghdam, Kanyifeechukwu Oguine, Gabriel Arenas, Baris Oguz, Alison Pouch, Nadav Schwartz, Brett C Byram, Ipek Oguz","doi":"10.1117/12.3086611","DOIUrl":"10.1117/12.3086611","url":null,"abstract":"<p><p>Three-dimensional ultrasound (3DUS) stitching aims to expand the field-of-view (FOV) by registering partially overlapping 3DUS volumes acquired from different probe positions. This task is highly challenging due to several intrinsic characteristics of 3DUS imaging, such as sector-shaped FOVs, low image quality, substantial noise, and imaging artifacts, as well as large inter-volume motion. These factors make it difficult for conventional registration methods to accurately identify both global and local geometrical correspondences between image pairs. To address these challenges, we propose a simple yet effective unsupervised pipeline for 3DUS stitching, which consists of three main stages: (1) unsupervised geometric feature extraction, (2) point cloud (PCD)-based coarse registration, and (3) intensity-based fine registration. Extensive quantitative and qualitative evaluations on a 3DUS placenta dataset demonstrate that our method significantly outperforms existing state-of-the-art 3DUS registration frameworks in both accuracy and robustness.</p>","PeriodicalId":74505,"journal":{"name":"Proceedings of SPIE--the International Society for Optical Engineering","volume":"13925 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13331289/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148392865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Theoretical Prediction of Bias in Model-Based Material Decomposition.","authors":"Donghyeon Lee, Xiao Jiang, J Webster Stayman, Grace J Gang","doi":"10.1117/12.3087705","DOIUrl":"10.1117/12.3087705","url":null,"abstract":"<p><p>Spectral imaging has significantly improved the quantitative potential of CT compared to conventional single-energy acquisitions. However, spectral imaging is susceptible to bias, which can result in misclassification of materials and compromised quantitation accuracy. Bias quantification has traditionally relied on empirical approaches which require an ensemble of measurements and yield limited theoretical insights. In this work, we propose a theoretical framework for bias prediction in model-based material decomposition. The proposed method estimates statistical bias, which arises from the nonlinear propagation of noise during the decomposition process, and model mismatch bias, resulting from discrepancies between the assumed forward model and actual data acquisition. We validated the predicted bias with empirical measurements over a wide range of imaging conditions including spectral separation, mAs, and varying amount of mismatches in the spectral responses. Statistical bias prediction shows excellent agreement with empirical measurements except at very low levels of spectral separation and mAs. Model mismatch bias increases with increasing mismatch in spectral responses, and appears to be more sensitive to perturbations in tube potential than effective energy. The theoretical model developed in this work accurately predicts bias in a wide range of imaging conditions, facilitating the design of bias-tolerant spectral systems.</p>","PeriodicalId":74505,"journal":{"name":"Proceedings of SPIE--the International Society for Optical Engineering","volume":"13924 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13128016/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147824420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fusion Annotator: A Platform for Accelerating Consensus-Driven Ground Truth Generation with AI Assistance.","authors":"Suhas K C Kumar, Fatemeh Afsari, Nicholas Lucarelli, Dhiraj Srivastav, Avi Z Rosenberg, Samuel Border, William Clapp, Carrie Phillips, Akshita Gupta, Micheal T Eadon, Yulia A L Strekalova, Pinaki Sarder","doi":"10.1117/12.3087861","DOIUrl":"10.1117/12.3087861","url":null,"abstract":"<p><p>Artificial intelligence now plays a central role in computational pathology, enabling large-scale analysis of whole slide images for segmentation, classification, and quantitative feature extraction. Despite these advances, the development of robust and generalizable models remains constrained by the limited availability of high-quality, expertly annotated datasets. This limitation is particularly acute in renal pathology, where ground-truth generation is challenged by labor-intensive workflows, limited subspecialty expertise, inter-observer variability, heterogeneous imaging protocols, and restricted data accessibility. To address these challenges, we present Fusion Annotator, a cloud-first, pathologist-centered digital annotation platform designed to accelerate and standardize expert-driven dataset creation through consensus-oriented workflows. Unlike conventional desktop-based annotation tools that require local installation and hinder collaborative scalability, Fusion Annotator operates entirely within a web browser, enabling secure multi-institutional access, real-time updates, and centralized data management. The platform integrates with the Computational Renal Pathology Suite, leveraging open-source machine learning models to pre-identify regions of interest and functional tissue units, thereby reducing manual annotation burden. Fusion Annotator supports customizable descriptor schemas tailored to specific disease cohorts and study objectives, enabling structured and flexible annotation protocols. Additional features include reference image guidance to support annotator training, multi-expert annotation to facilitate consensus building, and iterative refinement informed by continuous feedback from practicing renal pathologists. The platform is currently being used to generate expert-annotated datasets for focal segmental glomerulosclerosis, diabetic nephropathy, and renal transplant cohorts. Fusion Annotator provides an extensible pathway for producing high-quality renal pathology datasets to support scalable AI development in computational pathology.</p>","PeriodicalId":74505,"journal":{"name":"Proceedings of SPIE--the International Society for Optical Engineering","volume":"13932 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13186582/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147984551","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Characteristics of trainee interpretation time during simulated screening mammography.","authors":"L R Salkowski, L R Murphy, E M Yüksel, N A Fellinger, E A Krupinski, A M Fowler, H A Vlach, C S Green, M A Elezaby","doi":"10.1117/12.3085064","DOIUrl":"10.1117/12.3085064","url":null,"abstract":"<p><strong>Purpose: </strong>Efficiency in screening mammogram interpretation is complex and involves the time to view the images and report the findings. The purpose of this study was to evaluate the factors impacting the interpretation time of screening mammograms by radiology residents.</p><p><strong>Materials and methods: </strong>In this IRB-approved prospective study, radiology residents performed screening mammography simulations during their breast imaging rotations. The research simulation space replicated the clinical practice area without the interruptions. Residents interpreted 50 enriched screening mammograms and completed eye tracking on the first ten cases (six digital breast tomosynthesis (DBT) and four full-field digital mammogram (FFDM) cases). The amount of time to interpret (visual inspection) and report the 10 eye-tracking cases (electronic reporting) was evaluated and compared based on the breast imaging rotation (first, second, or third) and postgraduate year level (PGY). We present the time for each of the 10 eye tracking cases that were subdivided into visual inspection time of the mammogram and reporting time. Comparisons were performed with t-test and significance at p≤0.05.</p><p><strong>Results: </strong>25 residents performed the simulation with eye tracking: 14 residents during their first rotation, 7 in their second, and 4 in their third. There were 5 PGY2, 8 PGY3, 7 PGY4 and 5 PGY5 residents.The average overall interpretation time for 50 cases was 4.12 hours (SD=1.26), and 1.35 hours for the 10 eye tracking cases. For the eye-tracking cases, the average visual inspection time per case was 2.13 minutes with a reporting time of 3.08 minutes for an overall interpretation time of 5.21 minutes per case.For eye-tracking cases, the overall interpretation time significantly decreased from those completing their first (6.0 min) to third (4.2 min) breast rotation (p<0.001) and from PGY2 (6.6 min) to PGY5 (4.8 min) (p=0.004). The visual inspection time significantly decreased from PGY2 (2.6 min) compared to PGY5 (1.8 min) (p=0.001) level and from the first to the third rotation (p=0.021).No significant differences were observed for overall interpretation time between DBT (5.29 min) and FFDM (5.69 min) (p=0.319) or visual inspection time per case for DBT (2.20 min) and FFDM (2.03 min) (p=0.335).</p><p><strong>Conclusion: </strong>Interpretation time for screening mammography decreases with increasing PGY level and the number of breast imaging rotations, which is likely due to experience and confidence with the types of exams. No difference was noted between DBT and FFDM average times.</p>","PeriodicalId":74505,"journal":{"name":"Proceedings of SPIE--the International Society for Optical Engineering","volume":"13928 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13160490/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147936086","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Phenotype discovery of traumatic brain injury segmentations from heterogeneous multi-site data.","authors":"Adam M Saunders, Michael E Kim, Gaurav Rudravaram, Lucas W Remedios, Chloe Cho, Elyssa M McMaster, Daniel R Gillis, Yihao Liu, Lianrui Zuo, Bennett A Landman, Tonia S Rex","doi":"10.1117/12.3085847","DOIUrl":"10.1117/12.3085847","url":null,"abstract":"<p><p>Traumatic brain injury (TBI) is intrinsically heterogeneous, and typical clinical outcome measures like the Glasgow Coma Scale complicate this diversity. The large variability in severity and patient outcomes render it difficult to link structural damage to functional deficits. The Federal Interagency Traumatic Brain Injury Research (FITBIR) repository contains large-scale multi-site magnetic resonance imaging data of varying resolutions and acquisition parameters (25 shared studies with 7,693 sessions that have age, sex and TBI status defined - 5,811 TBI and 1,882 controls). To reveal shared pathways of injury of TBI through imaging, we analyzed T1-weighted images from these sessions by first harmonizing to a local dataset and segmenting 132 regions of interest (ROIs) in the brain. After running quality assurance, calculating the volumes of the ROIs, and removing outliers, we calculated the z-scores of volumes for all participants relative to the mean and standard deviation of the controls. We regressed out sex, age, and total brain volume with a multivariate linear regression, and we found significant differences in 37 ROIs between subjects with TBI and controls (<i>p</i> < 0.05 with independent <i>t</i>-tests with false discovery rate correction). We found that differences originated in 1) the brainstem, occipital pole and structures posterior to the orbit, 2) subcortical gray matter and insular cortex, and 3) cerebral and cerebellar white matter using independent component analysis and clustering the component loadings of those with TBI.</p>","PeriodicalId":74505,"journal":{"name":"Proceedings of SPIE--the International Society for Optical Engineering","volume":"13925 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13245470/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148213580","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A multi-channel fluorescence endoscope for pre-operative assessment of epithelial ovarian cancer.","authors":"Sanjana Pannem, Jonathan Elliott, Keith Paulsen, Kimberley S Samkoe","doi":"10.1117/12.3078511","DOIUrl":"10.1117/12.3078511","url":null,"abstract":"<p><p>Determining if a patient with epithelial ovarian cancer is eligible for surgical resection is difficult due to late-stage diagnosis and metastases. This often leads to patients receiving unnecessary surgery and delays in adjuvant therapies; thereby, increasing healthcare costs and decreasing therapeutic efficacy. We aim to utilize Paired Agent Imaging (PAI), a fluorescence molecular imaging technique, to pre-operatively assess tumor burden and determine an individual's eligibility for surgery. We developed a multi-channel optical endoscope with PAI to enhance tumor visualization and guide treatment planning. The system is tested on fluorescent dye solutions to evaluate its linear detection range and system sensitivity to fluorophore concentration.</p>","PeriodicalId":74505,"journal":{"name":"Proceedings of SPIE--the International Society for Optical Engineering","volume":"13838 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13175120/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147965508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Joint Cone-Beam CT Reconstruction and Rigid Motion Compensation Using A Differentiable Projector.","authors":"Xin Wang, Xiao Jiang, Yue Fan, Wojciech Zbijewski, J Webster Stayman","doi":"10.1117/12.3087735","DOIUrl":"10.1117/12.3087735","url":null,"abstract":"<p><strong>Purpose: </strong>To develop and assess the feasibility of integrating model-based CBCT reconstruction with rigid motion estimation, using only a projection-domain data fidelity objective coupled with a differentiable forward projector.</p><p><strong>Methods: </strong>We propose a joint image reconstruction and motion estimation framework that integrates motion compensation directly into a model-based iterative reconstruction (MBIR) scheme. Rigid motion with six degrees of freedom (DoF) is modeled as geometric perturbations that alter the projection geometry and thereby affect the estimated projections. To enable gradient-based optimization, a differentiable forward projector with an analytical gradient formulation is employed, allowing efficient backpropagation of the loss between the estimated and measured projections. Within this differentiable framework, the motion parameters and attenuation volume are optimized simultaneously. To evaluate the proposed method, we conducted both simulation and physical phantom studies. In the simulation study, we assessed performance under jerk motion with progressively increasing motion amplitudes, ranging from 1 mm to 10 mm in translation and from 0.02 rad to 0.2 rad in rotation. Reconstruction accuracy was quantified using structural similarity index (SSIM) relative to motion-free ground truth. In the physical phantom study, a jerk motion of 5 mm translation and 0.1 rad rotation was applied during scanning. Motion-free, motion-corrupted, and motion-compensated reconstructions were displayed side-by-side for qualitative comparison, enabling visual assessment of motion artifact reduction.</p><p><strong>Results: </strong>The experimental results demonstrate that the proposed motion compensation method substantially enhances image quality across a range of motion amplitudes. Qualitative evaluation reveal that even under significant translational and rotational motion, the method effectively recovers anatomical structures with minimal residual errors. In simulation studies, SSIM values improved by 18%, 37%, and 48% for motion amplitudes (3 mm, 0.06 rad), (6 mm, 0.12 rad), and (9 mm, 0.18 rad), respectively. Reconstructions from physical bench data further confirm efficacy, showing restored sharpness and anatomical continuity across coronal and sagittal planes.</p><p><strong>Conclusion: </strong>The discrepancy between the estimated and acquired projections serves as a sufficient objective for jointly estimating both the image volume and motion parameters, potentially avoiding the need for image-based sharpness criteria.</p>","PeriodicalId":74505,"journal":{"name":"Proceedings of SPIE--the International Society for Optical Engineering","volume":"13924 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13095155/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147791635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hallucination at low radiation dose: Evaluation of two deep-learning reconstruction methods in high-resolution chest CT.","authors":"Zhongxing Zhou, Alex Bratt, Chi Wan Koo, Patricia J Mergo, Prabhakar Rajiah, Catherine Liang, Scott S Hsieh, Cynthia H McCollough, Lifeng Yu","doi":"10.1117/12.3087772","DOIUrl":"10.1117/12.3087772","url":null,"abstract":"<p><p>Deep learning reconstruction (DLR) methods can generate false anatomical structures (\"hallucinations\") by interpreting noise or artifacts, especially at low radiation doses. This study assessed how dose reduction affects hallucinations in two DLR algorithms (DLR1 and DLR2) for high-resolution chest CT scans, specifically for interstitial lung disease (ILD). Full-dose projection data from a photon-counting detector CT scanner were simulated at 25% and 8% dose levels, with 8% approaching chest X-ray doses. Thirty image series (5 patients × 3 doses × 2 DLRs) were independently assessed by four thoracic radiologists under two references: routine reconstruction with a medium-sharp kernel (Qr56-IR3) and the sharpest quantitative kernel (Qr89-IR4). Images were rated on 5-point Likert scales for hallucination presence. DLR2 showed superior hallucination suppression versus DLR1 at 25% and 8% doses (p < 0.01), with comparable hallucination scores at full dose. Radiation dose reduction induces hallucinations in DLR images, with effects depending on algorithm. DLR2 consistently minimized hallucinations better than DLR1 at reduced doses.</p>","PeriodicalId":74505,"journal":{"name":"Proceedings of SPIE--the International Society for Optical Engineering","volume":"13924 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13193233/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148019275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In vitro effects of Taurine on Taxol-induced mitochondrial dysfunction.","authors":"Rozhin Penjweini, Katie A Link, Jasmine Su, Dan L Sackett, Jay R Knutson","doi":"10.1117/12.3091945","DOIUrl":"10.1117/12.3091945","url":null,"abstract":"<p><p>Mitochondria are intricately involved with essential functions in normal and cancer cells and, as such, mitochondria are a natural target for chemotherapeutic drugs. We previously showed that Taxol, even at low doses, adversely effects mitochondrial energetics, function, and intracellular migration patterns. We observed (by multiple optical means) suppression of oxidative phosphorylation (OXPHOS) and decreased adenosine triphosphate (ATP) production, increased reactive oxygen species (ROS) generation (both immediately and integrated over time), increased mitotic fraction, and the release of LDH and cytochrome <i>c</i> in Taxol-treated cells. Moreover, we observed more random (less ordered) motion of the mitochondria as well as altered mitochondrial morphology and lessened association with microtubules. Recently, several in vitro and in vivo studies have demonstrated the beneficial effects of taurine (a very abundant non-protein amino acid in most tissues, particularly in the heart, retina, brain and muscles) in maintaining mitochondrial functions. Intracellular concentrations of taurine in tissues range from 5-50 mM, but most culture conditions have little or no taurine. In this study, we show how taurine supplementation alters the impact of Taxol treatment in a variety of cell lines with varying glycolytic profiles. A549 (non-small cell lung epithelial cancer cell line), A549-<i>ρ</i> ⁰ (mitochondrial DNA-depleted derivative of A549), BEAS-2B (a non-cancer cell line derived from normal bronchial epithelium), as well as T98G (glioblastoma cell line) cells are used in this study.</p>","PeriodicalId":74505,"journal":{"name":"Proceedings of SPIE--the International Society for Optical Engineering","volume":"13856 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13007989/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147517356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"On-glass Interference Confocal Reflectance Microscopy for Collagen Fibril Diameter Measurement.","authors":"Eric P Hall, Jeffrey Ruberti, Charles A DiMarzio","doi":"10.1117/12.3081844","DOIUrl":"10.1117/12.3081844","url":null,"abstract":"<p><p>Previously, our group demonstrated using interference confocal reflectance microscopy (I-CRM) to measure collagen fibril diameters when suspended. An equally popular but optically unique challenge is presented when imaging collagen on glass, which is used for studying early stage fibril development. In this short manuscript, we present interference confocal reflectance microscopy as an alternative to atomic force microscopy for quantifying collagen fibrils below 50nm.</p>","PeriodicalId":74505,"journal":{"name":"Proceedings of SPIE--the International Society for Optical Engineering","volume":"13857 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13215243/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148058840","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}