Pub Date : 2008-05-14DOI: 10.1109/ISBI.2008.4541167
Telmo Amaral, S. McKenna, K. Robertson, A. Thompson
Breast tissue microarrays facilitate the survey of very large numbers of tumours but their scoring by pathologists is time consuming, typically highly quantised and not without error. Automated segmentation of cells and intra-cellular compartments in such data can be problematic for reasons that include cell overlapping, complex tissue structure, debris, and variable appearance. This paper proposes a computationally efficient approach that uses colour and differential invariants to assign class posterior probabilities to pixels and then performs probabilistic classification of TMA spots using features analogous to the Quickscore system currently used by pathologists. It does not rely on accurate segmentation of individual cells. Classification performance at both pixel and spot levels was assessed using 110 spots from the adjuvant breast cancer (ABC) chemotherapy trial. The use of differential invariants in addition to colour yielded a small improvement in accuracy. Some reasons for classification results in disagreement with pathologist-provided labels are discussed and include noise in the class labels.
{"title":"Classification of breast-tissue microarray spots using colour and local invariants","authors":"Telmo Amaral, S. McKenna, K. Robertson, A. Thompson","doi":"10.1109/ISBI.2008.4541167","DOIUrl":"https://doi.org/10.1109/ISBI.2008.4541167","url":null,"abstract":"Breast tissue microarrays facilitate the survey of very large numbers of tumours but their scoring by pathologists is time consuming, typically highly quantised and not without error. Automated segmentation of cells and intra-cellular compartments in such data can be problematic for reasons that include cell overlapping, complex tissue structure, debris, and variable appearance. This paper proposes a computationally efficient approach that uses colour and differential invariants to assign class posterior probabilities to pixels and then performs probabilistic classification of TMA spots using features analogous to the Quickscore system currently used by pathologists. It does not rely on accurate segmentation of individual cells. Classification performance at both pixel and spot levels was assessed using 110 spots from the adjuvant breast cancer (ABC) chemotherapy trial. The use of differential invariants in addition to colour yielded a small improvement in accuracy. Some reasons for classification results in disagreement with pathologist-provided labels are discussed and include noise in the class labels.","PeriodicalId":184204,"journal":{"name":"2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134454723","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}
Pub Date : 2008-05-14DOI: 10.1109/ISBI.2008.4541099
Shaun Fitch, Trevor Jackson, Péter András, C. Robson
Fluorescent microscopy of biological samples allows non-invasive screening of specific molecular events in-situ. This approach is useful for investigating intricate signalling pathways and in the drug discovery process. The large volumes of data involved in image analysis are a limiting factor. As manual image interpretation relies on expensive manpower automated analysis is a far more appropriate solution. In this paper we discuss our approach to achieve reliable automated segmentation of individual cell nuclei from wide field images taken of prostate cancer cells. We present a novel analysis routine to accurately identify cell nuclei based upon intensity clustering and morphological validation using a data derived geometric model. This approach is shown to consistently outperform the standard analysis technique using real data.
{"title":"Unsupervised segmentation of cell nuclei using geometric models","authors":"Shaun Fitch, Trevor Jackson, Péter András, C. Robson","doi":"10.1109/ISBI.2008.4541099","DOIUrl":"https://doi.org/10.1109/ISBI.2008.4541099","url":null,"abstract":"Fluorescent microscopy of biological samples allows non-invasive screening of specific molecular events in-situ. This approach is useful for investigating intricate signalling pathways and in the drug discovery process. The large volumes of data involved in image analysis are a limiting factor. As manual image interpretation relies on expensive manpower automated analysis is a far more appropriate solution. In this paper we discuss our approach to achieve reliable automated segmentation of individual cell nuclei from wide field images taken of prostate cancer cells. We present a novel analysis routine to accurately identify cell nuclei based upon intensity clustering and morphological validation using a data derived geometric model. This approach is shown to consistently outperform the standard analysis technique using real data.","PeriodicalId":184204,"journal":{"name":"2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130320405","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}
Pub Date : 2008-05-14DOI: 10.1109/ISBI.2008.4540974
Walter Sun, M. Çetin, R. Chan, A. Willsky
We propose a method for recursive segmentation of the left ventricle (LV) across a temporal sequence of magnetic resonance (MR) images. The approach involves a technique for learning the LV boundary dynamics together with a particle-based inference algorithm on a loopy graphical model capturing the temporal periodicity of the heart. The dynamic system state is a low-dimensional representation of the boundary, and boundary estimation involves incorporating curve evolution into state estimation. By formulating the problem as one of state estimation, the segmentation at each particular time is based not only on the data observed at that instant, but also on predictions based on past and future boundary estimates. We assess and demonstrate the effectiveness of the proposed framework on a large data set of breath-hold cardiac MR image sequences.
{"title":"Segmentation of the evolving left ventricle by learning the dynamics","authors":"Walter Sun, M. Çetin, R. Chan, A. Willsky","doi":"10.1109/ISBI.2008.4540974","DOIUrl":"https://doi.org/10.1109/ISBI.2008.4540974","url":null,"abstract":"We propose a method for recursive segmentation of the left ventricle (LV) across a temporal sequence of magnetic resonance (MR) images. The approach involves a technique for learning the LV boundary dynamics together with a particle-based inference algorithm on a loopy graphical model capturing the temporal periodicity of the heart. The dynamic system state is a low-dimensional representation of the boundary, and boundary estimation involves incorporating curve evolution into state estimation. By formulating the problem as one of state estimation, the segmentation at each particular time is based not only on the data observed at that instant, but also on predictions based on past and future boundary estimates. We assess and demonstrate the effectiveness of the proposed framework on a large data set of breath-hold cardiac MR image sequences.","PeriodicalId":184204,"journal":{"name":"2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125201218","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}
Pub Date : 2008-05-14DOI: 10.1109/ISBI.2008.4541232
M. Chakravarty, P. Rosa-Neto, S. Broadbent, Alan C. Evans, D. Collins
Pre-operative neurosurgical planning often uses data from functional magnetic resonance imaging (fMRI) to identify areas of eloquent cortex, such as the primary and secondary somatosensory cortices, to be spared during surgery. However, the in-vivo visualization of subcortical neurosurgical targets has typically involved the warping of subcortical atlases or T2- and diffusion-weighted imaging techniques to help define the anatomical borders. We propose a novel vibrotactile stimulation technique to activate the somatosensory pathway, and particularly the sensory thalamus. Experiments were executed on two MRI scanners (1.5T and 3.0T). A sensitivity analysis demonstrated that statistically significant functional activations of the sensory thalamus can be in achieved in clinically acceptable time (32 minutes at 1.5T and 12 minutes at 3.0T), thus enabling this technique to be used for pre-operative planning in patients.
{"title":"Development of FMRI techniques for planning in functional neurosurgery for Parkinson’s disease","authors":"M. Chakravarty, P. Rosa-Neto, S. Broadbent, Alan C. Evans, D. Collins","doi":"10.1109/ISBI.2008.4541232","DOIUrl":"https://doi.org/10.1109/ISBI.2008.4541232","url":null,"abstract":"Pre-operative neurosurgical planning often uses data from functional magnetic resonance imaging (fMRI) to identify areas of eloquent cortex, such as the primary and secondary somatosensory cortices, to be spared during surgery. However, the in-vivo visualization of subcortical neurosurgical targets has typically involved the warping of subcortical atlases or T2- and diffusion-weighted imaging techniques to help define the anatomical borders. We propose a novel vibrotactile stimulation technique to activate the somatosensory pathway, and particularly the sensory thalamus. Experiments were executed on two MRI scanners (1.5T and 3.0T). A sensitivity analysis demonstrated that statistically significant functional activations of the sensory thalamus can be in achieved in clinically acceptable time (32 minutes at 1.5T and 12 minutes at 3.0T), thus enabling this technique to be used for pre-operative planning in patients.","PeriodicalId":184204,"journal":{"name":"2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129172850","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}
Pub Date : 2008-05-14DOI: 10.1109/ISBI.2008.4541187
D. Fiorin, M. Jolly, Charles Florin
This paper describes a method to determine whether two CT volumes overlap in anatomy or not. This is an important problem because radiologists have to manually select which series should be registered together for follow-up exams. This task is becoming more and more tedious as the number of studies and series for each patient increases in large hospital settings, and meta-data is often erroneous, incomplete, or inconsistent, and therefore unreliable. We demonstrate on 40 patients and 100 possible matches that our tool is successful in identifying the overlapping (or registrable) cases automatically. We also show that this is not possible using the residual error after registration.
{"title":"On the registrability of two CT volumes","authors":"D. Fiorin, M. Jolly, Charles Florin","doi":"10.1109/ISBI.2008.4541187","DOIUrl":"https://doi.org/10.1109/ISBI.2008.4541187","url":null,"abstract":"This paper describes a method to determine whether two CT volumes overlap in anatomy or not. This is an important problem because radiologists have to manually select which series should be registered together for follow-up exams. This task is becoming more and more tedious as the number of studies and series for each patient increases in large hospital settings, and meta-data is often erroneous, incomplete, or inconsistent, and therefore unreliable. We demonstrate on 40 patients and 100 possible matches that our tool is successful in identifying the overlapping (or registrable) cases automatically. We also show that this is not possible using the residual error after registration.","PeriodicalId":184204,"journal":{"name":"2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129107957","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}
Pub Date : 2008-05-14DOI: 10.1109/ISBI.2008.4541289
Hui Sun, B. Avants, Alejandro F Frangi, S. Ordas, J. Gee, Paul Yushkevich
The cm-rep (continuous medial representation) is a powerful shape representation method that models a 3D object by describing its medial axis (skeleton) and boundary as continuous parametric manifolds. It provides parametrization of the entire interior of the object, which can be used for combined statistical analysis of shape and appearance. This paper extends the cm-rep to more complex shapes with multi-figures, i.e., shapes whose skeletons have branches. Along the branching curves, the equality constraints enforced by the medial geometry are implemented as soft penalties in the deformable model. The remaining small violations are corrected by local adjustments. As a proof of concept, the branching continuous medial representation is applied to a 2-chamber heart model data set consisting of 428 cardiac shapes from 90 subjects. The results show that our model can capture the heart shape accurately.
{"title":"Branching medial models for cardiac shape representation","authors":"Hui Sun, B. Avants, Alejandro F Frangi, S. Ordas, J. Gee, Paul Yushkevich","doi":"10.1109/ISBI.2008.4541289","DOIUrl":"https://doi.org/10.1109/ISBI.2008.4541289","url":null,"abstract":"The cm-rep (continuous medial representation) is a powerful shape representation method that models a 3D object by describing its medial axis (skeleton) and boundary as continuous parametric manifolds. It provides parametrization of the entire interior of the object, which can be used for combined statistical analysis of shape and appearance. This paper extends the cm-rep to more complex shapes with multi-figures, i.e., shapes whose skeletons have branches. Along the branching curves, the equality constraints enforced by the medial geometry are implemented as soft penalties in the deformable model. The remaining small violations are corrected by local adjustments. As a proof of concept, the branching continuous medial representation is applied to a 2-chamber heart model data set consisting of 428 cardiac shapes from 90 subjects. The results show that our model can capture the heart shape accurately.","PeriodicalId":184204,"journal":{"name":"2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131885299","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}
Pub Date : 2008-05-14DOI: 10.1109/ISBI.2008.4541089
K. Majidi, J. Brankov, M. Wernick
Multiple-Image Radiography (MIR) is an analyzer-based phase-sensitive x-ray imaging method, which is a potential alternative to conventional radiography. MIR simultaneously generates three planar images containing information about scattering, refraction and absorption properties of the object. These parametric images are acquired by sampling the angular intensity profile of the beam passing through the object at different positions of the analyzer crystal. Like many of the modern imaging techniques, MIR is a computing imaging method and the noise in MIR, in addition to the imaging conditions, depends also on the estimation of the parameters. In this work, we use Cramer-Rao lower bound to quantify the noise in MIR estimated images and investigate the effect of different sampling strategies at the analyzer on this bound. We also evaluate the performance of an estimator with respect to this bound.
{"title":"Sampling strategies in multiple-image radiography","authors":"K. Majidi, J. Brankov, M. Wernick","doi":"10.1109/ISBI.2008.4541089","DOIUrl":"https://doi.org/10.1109/ISBI.2008.4541089","url":null,"abstract":"Multiple-Image Radiography (MIR) is an analyzer-based phase-sensitive x-ray imaging method, which is a potential alternative to conventional radiography. MIR simultaneously generates three planar images containing information about scattering, refraction and absorption properties of the object. These parametric images are acquired by sampling the angular intensity profile of the beam passing through the object at different positions of the analyzer crystal. Like many of the modern imaging techniques, MIR is a computing imaging method and the noise in MIR, in addition to the imaging conditions, depends also on the estimation of the parameters. In this work, we use Cramer-Rao lower bound to quantify the noise in MIR estimated images and investigate the effect of different sampling strategies at the analyzer on this bound. We also evaluate the performance of an estimator with respect to this bound.","PeriodicalId":184204,"journal":{"name":"2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"274 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133280281","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}
Pub Date : 2008-05-14DOI: 10.1109/ISBI.2008.4541021
E. Gedamu, Abraham Gedamu, D. Arnold, D. Collins
Movement during the acquisition of magnetic resonance images can cause artifacts that interfere with subsequent image analysis. In this paper we address the problem of inter-packet motion and provide a method to minimize errors associated with this artifact. The procedure is based on an iterative packet-to-volume registration process and does not require complementary information such as multimodal acquisitions or protocols that provide redundant volume data. A Kaiser-Bessel function is used to interpolate missing data. Experiments with simulated data demonstrate that the packet-to-volume registration improves greatly after a single iteration and maintains improvement for the following iterations, while experiments with real data demonstrate a substantial reduction in associated artifacts and improvement in quality. In both cases anatomical integrity is preserved after reconstruction.
{"title":"MRI inter-packet movement correction for images acquired with non-complementary data","authors":"E. Gedamu, Abraham Gedamu, D. Arnold, D. Collins","doi":"10.1109/ISBI.2008.4541021","DOIUrl":"https://doi.org/10.1109/ISBI.2008.4541021","url":null,"abstract":"Movement during the acquisition of magnetic resonance images can cause artifacts that interfere with subsequent image analysis. In this paper we address the problem of inter-packet motion and provide a method to minimize errors associated with this artifact. The procedure is based on an iterative packet-to-volume registration process and does not require complementary information such as multimodal acquisitions or protocols that provide redundant volume data. A Kaiser-Bessel function is used to interpolate missing data. Experiments with simulated data demonstrate that the packet-to-volume registration improves greatly after a single iteration and maintains improvement for the following iterations, while experiments with real data demonstrate a substantial reduction in associated artifacts and improvement in quality. In both cases anatomical integrity is preserved after reconstruction.","PeriodicalId":184204,"journal":{"name":"2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133496792","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}
Pub Date : 2008-05-14DOI: 10.1109/ISBI.2008.4541020
L. Wen, M. Bewley, S. Eberl, M. Fulham, D. Feng
It remains a challenge to identify the different types of dementia and separate these from various subtypes from the normal effects of ageing. In this paper the potential of parametric images from FDG-PET studies to aid the classification of dementia using data mining techniques was investigated. Scalar, joint, histogram and voxel-level features were used in the investigation with principal component analysis (PCA) for dimensionality reduction. The logistic regression model and the additive logistic regression model were applied in the classification. The results show that cerebral metabolic rate of glucose consumption (CMRGlc) was efficient in the classification of dementia and data mining using voxel-level features with PCA and the logistic regression model method achieving the best classification.
{"title":"Classification of dementia from FDG-PET parametric images using data mining","authors":"L. Wen, M. Bewley, S. Eberl, M. Fulham, D. Feng","doi":"10.1109/ISBI.2008.4541020","DOIUrl":"https://doi.org/10.1109/ISBI.2008.4541020","url":null,"abstract":"It remains a challenge to identify the different types of dementia and separate these from various subtypes from the normal effects of ageing. In this paper the potential of parametric images from FDG-PET studies to aid the classification of dementia using data mining techniques was investigated. Scalar, joint, histogram and voxel-level features were used in the investigation with principal component analysis (PCA) for dimensionality reduction. The logistic regression model and the additive logistic regression model were applied in the classification. The results show that cerebral metabolic rate of glucose consumption (CMRGlc) was efficient in the classification of dementia and data mining using voxel-level features with PCA and the logistic regression model method achieving the best classification.","PeriodicalId":184204,"journal":{"name":"2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"3 7","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132581104","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}
Pub Date : 2008-05-14DOI: 10.1109/ISBI.2008.4541086
P. Orlowski, J. Noble, Y. Ventikos, J. Byrne, P. Summers
A novel image-based patient-specific simulation method has been developed incorporating computational fluid dynamics (CFD) and porous media principles which presents, for the first time, patient-specific blood flow through an arteriovenous malformation of the brain (BAVM). The new approach constructs an image-based geometric model of a malformation where the BAVM nidus is modelled as a porous medium. The method has been applied to a brain BAVM case with two feeding and four draining vessels. A qualitative comparison of the simulation results with blood flow imaging data shows the promise of the approach and suggests that the method may find application in planning for BAVM treatment.
{"title":"Image-based simulation of brain arteriovenous malformation hemodynamics","authors":"P. Orlowski, J. Noble, Y. Ventikos, J. Byrne, P. Summers","doi":"10.1109/ISBI.2008.4541086","DOIUrl":"https://doi.org/10.1109/ISBI.2008.4541086","url":null,"abstract":"A novel image-based patient-specific simulation method has been developed incorporating computational fluid dynamics (CFD) and porous media principles which presents, for the first time, patient-specific blood flow through an arteriovenous malformation of the brain (BAVM). The new approach constructs an image-based geometric model of a malformation where the BAVM nidus is modelled as a porous medium. The method has been applied to a brain BAVM case with two feeding and four draining vessels. A qualitative comparison of the simulation results with blood flow imaging data shows the promise of the approach and suggests that the method may find application in planning for BAVM treatment.","PeriodicalId":184204,"journal":{"name":"2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121037373","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}
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