Pub Date : 2009-06-28DOI: 10.1109/ISBI.2009.5193308
Sila Kurugol, Jennifer G. Dy, M. Rajadhyaksha, D. Brooks
Confocal reflectance microscopy is an emerging modality, for dermatology applications, especially for in-situ and bedside detection of skin cancers. As this technology gains acceptance, automated processing methods become increasingly important to develop. Since the dominant internal feature of the skin is the epidermis/dermis boundary, it has been chosen as the initial target for this development. This boundary is a complex corrugated 3D layer marked by optically subtle changes and features. Indeed, even trained clinicians in an attempt at validation of our early work, were unable to precisely and reliably locate the boundary within optical resolution. Thus here we propose to detect two boundaries, a lower boundary for the epidermis and an upper boundary for the dermis thus trapping the epidermis/dermis boundary. We use a novel combined segmentation/classification approach applied to z-sequences of tiles in the 3D stack. The approach employs a sequential classification on texture features, selected via on-line feature selection, to minimize the labeling required and to cope with high inter- and intra-subject variability and low optical contrast. Initial results indicate the ability of our approach to find these two boundaries successfully for most of the z-sequences from the stack.
{"title":"Localizing the dermis/epidermis boundary in reflectance confocal microscopy images with a hybrid classification algorithm","authors":"Sila Kurugol, Jennifer G. Dy, M. Rajadhyaksha, D. Brooks","doi":"10.1109/ISBI.2009.5193308","DOIUrl":"https://doi.org/10.1109/ISBI.2009.5193308","url":null,"abstract":"Confocal reflectance microscopy is an emerging modality, for dermatology applications, especially for in-situ and bedside detection of skin cancers. As this technology gains acceptance, automated processing methods become increasingly important to develop. Since the dominant internal feature of the skin is the epidermis/dermis boundary, it has been chosen as the initial target for this development. This boundary is a complex corrugated 3D layer marked by optically subtle changes and features. Indeed, even trained clinicians in an attempt at validation of our early work, were unable to precisely and reliably locate the boundary within optical resolution. Thus here we propose to detect two boundaries, a lower boundary for the epidermis and an upper boundary for the dermis thus trapping the epidermis/dermis boundary. We use a novel combined segmentation/classification approach applied to z-sequences of tiles in the 3D stack. The approach employs a sequential classification on texture features, selected via on-line feature selection, to minimize the labeling required and to cope with high inter- and intra-subject variability and low optical contrast. Initial results indicate the ability of our approach to find these two boundaries successfully for most of the z-sequences from the stack.","PeriodicalId":272938,"journal":{"name":"2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"124 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134450233","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 : 2009-06-28DOI: 10.1109/ISBI.2009.5193113
A. Sadeghi-Naini, Rajnikant V. Patel, A. Samani
A novel technique is proposed to construct CT images of the lung in a totally deflated mode using non-rigid registration and extrapolation. This CT image would be very useful in performing tumor ablative procedures (such as brachytherapy) for the treatment of lung cancer. This is because during such procedures the target lung is almost completely deflated whereas pre-operative images are acquired while the lung is partially inflated. This makes pre-operative images very inaccurate. Given that Ultrasound (US) imaging is very sensitive to residual air in a deflated lung, it is not an effective intra-operative imaging modality by itself. One possible approach for image guided lung brachytherapy is registering low quality intra-operative ultrasound images to high quality lung CT image of the deflated lung constructed using the proposed technique. The technique was applied to an ex-vivo porcine lung and the preliminary results were found to be very encouraging.
{"title":"CT image construction of the lung in a totally deflated mode","authors":"A. Sadeghi-Naini, Rajnikant V. Patel, A. Samani","doi":"10.1109/ISBI.2009.5193113","DOIUrl":"https://doi.org/10.1109/ISBI.2009.5193113","url":null,"abstract":"A novel technique is proposed to construct CT images of the lung in a totally deflated mode using non-rigid registration and extrapolation. This CT image would be very useful in performing tumor ablative procedures (such as brachytherapy) for the treatment of lung cancer. This is because during such procedures the target lung is almost completely deflated whereas pre-operative images are acquired while the lung is partially inflated. This makes pre-operative images very inaccurate. Given that Ultrasound (US) imaging is very sensitive to residual air in a deflated lung, it is not an effective intra-operative imaging modality by itself. One possible approach for image guided lung brachytherapy is registering low quality intra-operative ultrasound images to high quality lung CT image of the deflated lung constructed using the proposed technique. The technique was applied to an ex-vivo porcine lung and the preliminary results were found to be very encouraging.","PeriodicalId":272938,"journal":{"name":"2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129105322","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 : 2009-06-28DOI: 10.1109/ISBI.2009.5193262
R. Juang, A. Levchenko, P. Burlina
We present a method for tracking the movement of multiple cells and their lineage. We use the Gaussian Mixture Probability Hypothesis Density (GM-PHD) filter, a multi-target tracking algorithm, to track the motion of multiple cells over time and to keep track of the lineage of cells as they spawn. We describe a spawning model for the GM-PHD filter as well as modifications to the original GM-PHD algorithm to track lineage. Experimental results are provided illustrating the approach for dense cell colonies.
{"title":"Tracking cell motion using GM-PHD","authors":"R. Juang, A. Levchenko, P. Burlina","doi":"10.1109/ISBI.2009.5193262","DOIUrl":"https://doi.org/10.1109/ISBI.2009.5193262","url":null,"abstract":"We present a method for tracking the movement of multiple cells and their lineage. We use the Gaussian Mixture Probability Hypothesis Density (GM-PHD) filter, a multi-target tracking algorithm, to track the motion of multiple cells over time and to keep track of the lineage of cells as they spawn. We describe a spawning model for the GM-PHD filter as well as modifications to the original GM-PHD algorithm to track lineage. Experimental results are provided illustrating the approach for dense cell colonies.","PeriodicalId":272938,"journal":{"name":"2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"264 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134369757","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 : 2009-06-28DOI: 10.1109/ISBI.2009.5193094
R. Karim, D. Rueckert, R. Mohiaddin, P. Drivas
This paper describes and evaluates methods to detect pulmonary vein drainages and create detailed vessel trees of each drainage from contrast-enhanced magnetic resonance angiography (MRA). This description of the drainage allow us to determine the highly complex left atrial anatomy in a qualitative and quantitative way. It is beneficial for planning atrial fibrillation ablation procedures. We conclude that our methods permit the creation of drainage trees for the detailed description of the atrial anatomy from cardiac MRA data.
{"title":"Automatic extraction of the left atrial anatomy from MR for atrial fibrillation ablation","authors":"R. Karim, D. Rueckert, R. Mohiaddin, P. Drivas","doi":"10.1109/ISBI.2009.5193094","DOIUrl":"https://doi.org/10.1109/ISBI.2009.5193094","url":null,"abstract":"This paper describes and evaluates methods to detect pulmonary vein drainages and create detailed vessel trees of each drainage from contrast-enhanced magnetic resonance angiography (MRA). This description of the drainage allow us to determine the highly complex left atrial anatomy in a qualitative and quantitative way. It is beneficial for planning atrial fibrillation ablation procedures. We conclude that our methods permit the creation of drainage trees for the detailed description of the atrial anatomy from cardiac MRA data.","PeriodicalId":272938,"journal":{"name":"2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133762538","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 : 2009-06-28DOI: 10.1109/ISBI.2009.5192983
D. E. Freund, N. Bressler, P. Burlina
Age related macular degeneration (AMD) is a condition of the retina that occurs with individuals over 50. AMD is characterized by the formation of drusen in the macula. This condition leads to a deterioration of foveal vision and eventually functional blindness. Automatically screening atrisk individuals may allow the detection of intermediate stage AMD where it is still treatable using anti-VEGH therapy. One of the difficulties in detecting and locating drusen is that their aspect (shape, texture, color, extent) varies significantly, and because of this it is often difficult to build a classifier. To address this difficulty we use a two pronged approach based on (a) multiscale analysis and (b) kernel based anomaly detection. We show experimental results on examples of fundus images taken from healthy and affected patients.
{"title":"Automated detection of drusen in the macula","authors":"D. E. Freund, N. Bressler, P. Burlina","doi":"10.1109/ISBI.2009.5192983","DOIUrl":"https://doi.org/10.1109/ISBI.2009.5192983","url":null,"abstract":"Age related macular degeneration (AMD) is a condition of the retina that occurs with individuals over 50. AMD is characterized by the formation of drusen in the macula. This condition leads to a deterioration of foveal vision and eventually functional blindness. Automatically screening atrisk individuals may allow the detection of intermediate stage AMD where it is still treatable using anti-VEGH therapy. One of the difficulties in detecting and locating drusen is that their aspect (shape, texture, color, extent) varies significantly, and because of this it is often difficult to build a classifier. To address this difficulty we use a two pronged approach based on (a) multiscale analysis and (b) kernel based anomaly detection. We show experimental results on examples of fundus images taken from healthy and affected patients.","PeriodicalId":272938,"journal":{"name":"2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115968765","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 : 2009-06-28DOI: 10.1109/ISBI.2009.5193105
Raja' S. Alomari, Jason J. Corso, V. Chaudhary, G. Dhillon
Lumbar intervertebral disc diseases are among the main causes of lower back pain (LBP). Desiccation is a common disease resulting from various reasons and ultimately most people are affected by desiccation at some age. We propose a probabilistic model that incorporates intervertebral disc appearance and contextual information for automating the diagnosis of lumbar disc desiccation. We utilize a Gibbs distribution for processing localized lumbar intervertebral discs' appearance and contextual information. We use 55 clinical T2-weighted MRI for lumbar area and achieve over 96% accuracy on a cross validation experiment.
{"title":"Desiccation diagnosis in lumbar discs from clinical MRI with a probabilistic model","authors":"Raja' S. Alomari, Jason J. Corso, V. Chaudhary, G. Dhillon","doi":"10.1109/ISBI.2009.5193105","DOIUrl":"https://doi.org/10.1109/ISBI.2009.5193105","url":null,"abstract":"Lumbar intervertebral disc diseases are among the main causes of lower back pain (LBP). Desiccation is a common disease resulting from various reasons and ultimately most people are affected by desiccation at some age. We propose a probabilistic model that incorporates intervertebral disc appearance and contextual information for automating the diagnosis of lumbar disc desiccation. We utilize a Gibbs distribution for processing localized lumbar intervertebral discs' appearance and contextual information. We use 55 clinical T2-weighted MRI for lumbar area and achieve over 96% accuracy on a cross validation experiment.","PeriodicalId":272938,"journal":{"name":"2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115946333","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 : 2009-06-28DOI: 10.1109/ISBI.2009.5192984
Sang Ho Lee, Jong Hyo Kim, J. Park, Y. Jung, W. Moon
This study was designed to characterize the spatio-temporal properties of intratumoral enhancement patterns by using voxel-wise temporal enhancement spectra and morphometry of their spatial distributions in dynamic contrast-enhanced (DCE) breast MRI. Discrete Fourier transformation (DFT) and singular value decomposition (SVD) were used to extract the temporal enhancement features for comparison, generating 4D spectral maps. The spatial variations of DFT and SVD-based eigen spectra within tumor were captured by 3D moment descriptors, respectively. Differentiation between benign and malignant tumors was carried out using least squares support vector machine (LS-SVM) with a radial basis function (RBF) kernel and leave-one-out cross validation was used for performance evaluation. Using DFT, the sensitivity, specificity and area under ROC curve were 84.8%, 64.4% and 0.728. Using SVD, the corresponding values were 100%, 86.7% and 0.935. Combination of SVD and 3D moments yields higher performance in tumor differentiation than that of DFT and 3D moments.
{"title":"Characterizing time-intensity curves for spectral morphometric analysis of intratumoral enhancement patterns in breast DCE-MRI: Comparison between differentiation performance of temporal model parameters based on DFT and SVD","authors":"Sang Ho Lee, Jong Hyo Kim, J. Park, Y. Jung, W. Moon","doi":"10.1109/ISBI.2009.5192984","DOIUrl":"https://doi.org/10.1109/ISBI.2009.5192984","url":null,"abstract":"This study was designed to characterize the spatio-temporal properties of intratumoral enhancement patterns by using voxel-wise temporal enhancement spectra and morphometry of their spatial distributions in dynamic contrast-enhanced (DCE) breast MRI. Discrete Fourier transformation (DFT) and singular value decomposition (SVD) were used to extract the temporal enhancement features for comparison, generating 4D spectral maps. The spatial variations of DFT and SVD-based eigen spectra within tumor were captured by 3D moment descriptors, respectively. Differentiation between benign and malignant tumors was carried out using least squares support vector machine (LS-SVM) with a radial basis function (RBF) kernel and leave-one-out cross validation was used for performance evaluation. Using DFT, the sensitivity, specificity and area under ROC curve were 84.8%, 64.4% and 0.728. Using SVD, the corresponding values were 100%, 86.7% and 0.935. Combination of SVD and 3D moments yields higher performance in tumor differentiation than that of DFT and 3D moments.","PeriodicalId":272938,"journal":{"name":"2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"139 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116036883","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 : 2009-06-28DOI: 10.1109/ISBI.2009.5193263
Q. Xue, M. Leake
Automated tracking of fluorescent particles in living cells is vital for subcellular stoichoimetry analysis [1, 2]. Here, a new automatic tracking algorithm is described to track multiple particles, based on minimal path optimization. After linking feature points frame-by-frame, spatio-temporal data from time-lapse microscopy are combined together to construct a transformed 3D volume. The trajectories are then generated from the minimal energy path as defined by the solution of the time-dependent partial differential equation using a gray weighted distance transform dynamic programming method. Results from simulated and experimental data demonstrate that our novel automatic method gives sub-pixel accuracy even for very noisy images.
{"title":"A novel multiple particle tracking algorithm for noisy in vivo data by minimal path optimization within the spatio-temporal volume","authors":"Q. Xue, M. Leake","doi":"10.1109/ISBI.2009.5193263","DOIUrl":"https://doi.org/10.1109/ISBI.2009.5193263","url":null,"abstract":"Automated tracking of fluorescent particles in living cells is vital for subcellular stoichoimetry analysis [1, 2]. Here, a new automatic tracking algorithm is described to track multiple particles, based on minimal path optimization. After linking feature points frame-by-frame, spatio-temporal data from time-lapse microscopy are combined together to construct a transformed 3D volume. The trajectories are then generated from the minimal energy path as defined by the solution of the time-dependent partial differential equation using a gray weighted distance transform dynamic programming method. Results from simulated and experimental data demonstrate that our novel automatic method gives sub-pixel accuracy even for very noisy images.","PeriodicalId":272938,"journal":{"name":"2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115196831","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 : 2009-06-28DOI: 10.1109/ISBI.2009.5193255
O. Dzyubachyk, W. A. Cappellen, J. Essers, W. Niessen, E. Meijering
The ultimate aim of many live-cell fluorescence microscopy imaging experiments is the quantitative analysis of the spatial structure and temporal behavior of intracellular objects. This requires finding the precise geometrical correspondence between the time frames for each individual cell and performing intracellular segmentation. In a previous paper we have developed a powerful multi-level-set based algorithm for automated cell segmentation and tracking of many cells in time-lapse images. In this paper, we propose approaches to exploit the output of this algorithm for the subsequent tasks of cell motion correction and intracellular segmentation. Both tasks are formulated as energy minimization problems and are solved efficiently and effectively by distance-transform and graph-cut based algorithms. The potential of the proposed approaches for intracellular analysis is demonstrated by successful experiments on biological image data showing PCNA-foci and nucleoli in HeLa cells.
{"title":"Energy minimization methods for cell motion correction and intracellular analysis in live-cell fluorescence microscopy","authors":"O. Dzyubachyk, W. A. Cappellen, J. Essers, W. Niessen, E. Meijering","doi":"10.1109/ISBI.2009.5193255","DOIUrl":"https://doi.org/10.1109/ISBI.2009.5193255","url":null,"abstract":"The ultimate aim of many live-cell fluorescence microscopy imaging experiments is the quantitative analysis of the spatial structure and temporal behavior of intracellular objects. This requires finding the precise geometrical correspondence between the time frames for each individual cell and performing intracellular segmentation. In a previous paper we have developed a powerful multi-level-set based algorithm for automated cell segmentation and tracking of many cells in time-lapse images. In this paper, we propose approaches to exploit the output of this algorithm for the subsequent tasks of cell motion correction and intracellular segmentation. Both tasks are formulated as energy minimization problems and are solved efficiently and effectively by distance-transform and graph-cut based algorithms. The potential of the proposed approaches for intracellular analysis is demonstrated by successful experiments on biological image data showing PCNA-foci and nucleoli in HeLa cells.","PeriodicalId":272938,"journal":{"name":"2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123751993","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 : 2009-06-28DOI: 10.1109/ISBI.2009.5193309
P. Besson, C. Delmaire, V. Thuc, S. Lehéricy, F. Pasquier, X. Leclerc
The graph theory is increasingly used and provides powerful tools for studying complex biological networks problems. They were able to characterize the small-worldness of the brain connectivity network and were accurate enough to observe topological differences between healthy and diseased brain graphs. However, these methods relied on topological characteristics implying that differences could be observed between two groups only if corresponding graphs topologies were different.
{"title":"Graph wavelet applied to human brain connectivity","authors":"P. Besson, C. Delmaire, V. Thuc, S. Lehéricy, F. Pasquier, X. Leclerc","doi":"10.1109/ISBI.2009.5193309","DOIUrl":"https://doi.org/10.1109/ISBI.2009.5193309","url":null,"abstract":"The graph theory is increasingly used and provides powerful tools for studying complex biological networks problems. They were able to characterize the small-worldness of the brain connectivity network and were accurate enough to observe topological differences between healthy and diseased brain graphs. However, these methods relied on topological characteristics implying that differences could be observed between two groups only if corresponding graphs topologies were different.","PeriodicalId":272938,"journal":{"name":"2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124788158","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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