Pub Date : 2010-04-14DOI: 10.1109/ISBI.2010.5490354
J. D’hooge
In this review lecture, the above described techniques will be presented from a technical point of view together with the experimental validation and/or clinical findings already available. Pros and contras of the approaches will be discussed.
{"title":"New developments in functional cardiac imaging","authors":"J. D’hooge","doi":"10.1109/ISBI.2010.5490354","DOIUrl":"https://doi.org/10.1109/ISBI.2010.5490354","url":null,"abstract":"In this review lecture, the above described techniques will be presented from a technical point of view together with the experimental validation and/or clinical findings already available. Pros and contras of the approaches will be discussed.","PeriodicalId":250523,"journal":{"name":"2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121170575","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 : 2010-04-14DOI: 10.1109/ISBI.2010.5490411
J. Lefévre, J. F. Mangin
The anatomical variability of the human brain folds remains an unclear and challenging issue. Several hypotheses coexist for explaining the rapid development of cortical sulci and it is clear that understanding their variability would improve the comparison of anatomical and functional data across cohorts of subjects. In this article we propose to extend a model of cortical folding based on reaction-diffusion mechanisms. The originality of our approach lies in the fact that the surface on which these mechanisms take place is deformed iteratively and engenders geometric patterns that can be linked to cortical sulci. We show that some statistic properties of our model can reflect the variability of sulcal structures.
{"title":"A reaction-diffusion model of the human brain development","authors":"J. Lefévre, J. F. Mangin","doi":"10.1109/ISBI.2010.5490411","DOIUrl":"https://doi.org/10.1109/ISBI.2010.5490411","url":null,"abstract":"The anatomical variability of the human brain folds remains an unclear and challenging issue. Several hypotheses coexist for explaining the rapid development of cortical sulci and it is clear that understanding their variability would improve the comparison of anatomical and functional data across cohorts of subjects. In this article we propose to extend a model of cortical folding based on reaction-diffusion mechanisms. The originality of our approach lies in the fact that the surface on which these mechanisms take place is deformed iteratively and engenders geometric patterns that can be linked to cortical sulci. We show that some statistic properties of our model can reflect the variability of sulcal structures.","PeriodicalId":250523,"journal":{"name":"2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114194685","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 : 2010-04-14DOI: 10.1109/ISBI.2010.5490062
Zachary T. Harmany, Roummel F. Marcia, R. Willett
In many medical imaging applications (e.g., SPECT, PET), the data are a count of the number of photons incident on a detector array. When the number of photons is small, the measurement process is best modeled with a Poisson distribution. The problem addressed in this paper is the estimation of an underlying intensity from photon-limited projections where the intensity admits a sparse or low-complexity representation. This approach is based on recent inroads in sparse reconstruction methods inspired by compressed sensing. However, unlike most recent advances in this area, the optimization formulation we explore uses a penalized negative Poisson loglikelihood objective function with nonnegativity constraints (since Poisson intensities are naturally nonnegative). This paper describes computational methods for solving the nonnegatively constrained sparse Poisson inverse problem. In particular, the proposed approach incorporates sequential separable quadratic approximations to the log-likelihood and computationally efficient partition-based multiscale estimation methods.
{"title":"Sparsity-regularized photon-limited imaging","authors":"Zachary T. Harmany, Roummel F. Marcia, R. Willett","doi":"10.1109/ISBI.2010.5490062","DOIUrl":"https://doi.org/10.1109/ISBI.2010.5490062","url":null,"abstract":"In many medical imaging applications (e.g., SPECT, PET), the data are a count of the number of photons incident on a detector array. When the number of photons is small, the measurement process is best modeled with a Poisson distribution. The problem addressed in this paper is the estimation of an underlying intensity from photon-limited projections where the intensity admits a sparse or low-complexity representation. This approach is based on recent inroads in sparse reconstruction methods inspired by compressed sensing. However, unlike most recent advances in this area, the optimization formulation we explore uses a penalized negative Poisson loglikelihood objective function with nonnegativity constraints (since Poisson intensities are naturally nonnegative). This paper describes computational methods for solving the nonnegatively constrained sparse Poisson inverse problem. In particular, the proposed approach incorporates sequential separable quadratic approximations to the log-likelihood and computationally efficient partition-based multiscale estimation methods.","PeriodicalId":250523,"journal":{"name":"2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121649664","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 : 2010-04-14DOI: 10.1109/ISBI.2010.5490088
E. V. Dongen, B. Ginneken
A system for the automatic segmentation of the pulmonary vasculature in thoracic CT scans is presented. The method is based on a vesselness filter and includes a local thresholding procedure to accurately segment vessels of varying diameters. The output of an automatic segmentation of the airways is used to remove false positive detections in the airway walls. The algorithm is tested with a quantitative evaluation framework based on manual classification of well-dispersed local maxima and random points on ten axial sections in a scan. The algorithm has been applied to ten low dose CT scans annotated by two observers. Results show that local thresholding and airway wall removal both improve segmentation performance and that the accuracy of the proposed method approaches the interobserver variability.
{"title":"Automatic segmentation of pulmonary vasculature in thoracic CT scans with local thresholding and airway wall removal","authors":"E. V. Dongen, B. Ginneken","doi":"10.1109/ISBI.2010.5490088","DOIUrl":"https://doi.org/10.1109/ISBI.2010.5490088","url":null,"abstract":"A system for the automatic segmentation of the pulmonary vasculature in thoracic CT scans is presented. The method is based on a vesselness filter and includes a local thresholding procedure to accurately segment vessels of varying diameters. The output of an automatic segmentation of the airways is used to remove false positive detections in the airway walls. The algorithm is tested with a quantitative evaluation framework based on manual classification of well-dispersed local maxima and random points on ten axial sections in a scan. The algorithm has been applied to ten low dose CT scans annotated by two observers. Results show that local thresholding and airway wall removal both improve segmentation performance and that the accuracy of the proposed method approaches the interobserver variability.","PeriodicalId":250523,"journal":{"name":"2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114010732","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 : 2010-04-14DOI: 10.1109/ISBI.2010.5490291
Yu Wang, B. Roysam
There is a continued need for improved automated algorithms for tracking the movement of C. elegans worms from time-lapse image sequences, computing measurements, and identifying specific states of worm locomotion. The tracking and locomotion state recognition have been addressed sequentially in the prior literature. However, knowing the locomotion state can help predict worm dynamics while improved worm tracking can allow one to infer worm locomotion state more accurately. To exploit this obvious but unexploited synergy, this paper presents a 3-level model for simultaneous tracking and locomotion state recognition. Use of this model is shown to result in improved tracking performance compared to previously reported methods.
{"title":"Joint tracking and locomotion state recognition of C. elegans from time-lapse image sequences","authors":"Yu Wang, B. Roysam","doi":"10.1109/ISBI.2010.5490291","DOIUrl":"https://doi.org/10.1109/ISBI.2010.5490291","url":null,"abstract":"There is a continued need for improved automated algorithms for tracking the movement of C. elegans worms from time-lapse image sequences, computing measurements, and identifying specific states of worm locomotion. The tracking and locomotion state recognition have been addressed sequentially in the prior literature. However, knowing the locomotion state can help predict worm dynamics while improved worm tracking can allow one to infer worm locomotion state more accurately. To exploit this obvious but unexploited synergy, this paper presents a 3-level model for simultaneous tracking and locomotion state recognition. Use of this model is shown to result in improved tracking performance compared to previously reported methods.","PeriodicalId":250523,"journal":{"name":"2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"138 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124322586","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 : 2010-04-14DOI: 10.1109/ISBI.2010.5490279
An Liu, Kang Li, T. Kanade
We propose a fully-automated mitosis event detector using hidden conditional random fields for cell populations imaged with time-lapse phase contrast microscopy. The method consists of two stages that jointly optimize recall and precision. First, we apply model-based microscopy image preconditioning and volumetric segmentation to identify candidate spatiotemporal sub-regions in the input image sequence where mitosis potentially occurred. Then, we apply a learned hidden conditional random field classifier to classify each candidate sequence as mitosis or not. The proposed detection method achieved 95% precision and 85% recall in very challenging image sequences of multipolar-shaped C3H10T1/2 mesenchymal stem cells. The superiority of the method was further demonstrated by comparisons with conditional random field and support vector machine classifiers. Moreover, the proposed method does not depend on empirical parameters, ad hoc image processing, or cell tracking; and can be straightforwardly adapted to different cell types.
{"title":"Mitosis sequence detection using hidden conditional random fields","authors":"An Liu, Kang Li, T. Kanade","doi":"10.1109/ISBI.2010.5490279","DOIUrl":"https://doi.org/10.1109/ISBI.2010.5490279","url":null,"abstract":"We propose a fully-automated mitosis event detector using hidden conditional random fields for cell populations imaged with time-lapse phase contrast microscopy. The method consists of two stages that jointly optimize recall and precision. First, we apply model-based microscopy image preconditioning and volumetric segmentation to identify candidate spatiotemporal sub-regions in the input image sequence where mitosis potentially occurred. Then, we apply a learned hidden conditional random field classifier to classify each candidate sequence as mitosis or not. The proposed detection method achieved 95% precision and 85% recall in very challenging image sequences of multipolar-shaped C3H10T1/2 mesenchymal stem cells. The superiority of the method was further demonstrated by comparisons with conditional random field and support vector machine classifiers. Moreover, the proposed method does not depend on empirical parameters, ad hoc image processing, or cell tracking; and can be straightforwardly adapted to different cell types.","PeriodicalId":250523,"journal":{"name":"2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126359015","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 : 2010-04-14DOI: 10.1109/ISBI.2010.5490149
Cheng Yao, J. Simpson, T. Schaeffter, G. Penney
This paper presents a novel method for compounding large numbers of multi-view 3D echocardiography volumes based on feature consistency. Our proposed method directly addresses issues involved with reducing the effects of echocardiography artefacts in the final compounded volume. Quantitative validation experiments are carried out using an echocardiography heart phantom. Images are acquired through various intervening layers of soft-tissue and hard-tissue mimicking material. We use images acquired of the phantom with no intervening material as high-quality reference “gold-standard” images, and then investigate the effects of the introduced soft tissue and strongly reflecting boundaries images on image quality. Our compounding method is compared to the original, uncompounded, echocardiography images, and to images compounded using a published phase-based method. In addition we present qualitative results from a volunteer and a patient dataset. Results show the artefact has been detected and reduced, and a coherent compounded image is produced using large numbers of multi-view 3D volumes.
{"title":"Spatial compounding of large numbers of multi-view 3D echocardiography images using feature consistency","authors":"Cheng Yao, J. Simpson, T. Schaeffter, G. Penney","doi":"10.1109/ISBI.2010.5490149","DOIUrl":"https://doi.org/10.1109/ISBI.2010.5490149","url":null,"abstract":"This paper presents a novel method for compounding large numbers of multi-view 3D echocardiography volumes based on feature consistency. Our proposed method directly addresses issues involved with reducing the effects of echocardiography artefacts in the final compounded volume. Quantitative validation experiments are carried out using an echocardiography heart phantom. Images are acquired through various intervening layers of soft-tissue and hard-tissue mimicking material. We use images acquired of the phantom with no intervening material as high-quality reference “gold-standard” images, and then investigate the effects of the introduced soft tissue and strongly reflecting boundaries images on image quality. Our compounding method is compared to the original, uncompounded, echocardiography images, and to images compounded using a published phase-based method. In addition we present qualitative results from a volunteer and a patient dataset. Results show the artefact has been detected and reduced, and a coherent compounded image is produced using large numbers of multi-view 3D volumes.","PeriodicalId":250523,"journal":{"name":"2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127995711","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 : 2010-04-14DOI: 10.1109/ISBI.2010.5490124
Nicolas Schmidt, G. Peyré, Y. Frégnac, P. Roland
This paper introduces a mathematical model of the spatio-temporal patterns of visually evoked activity observed using Voltage-Sensitive Dye Imaging (VSDI) of the visual cortex. The cortical activity is described using a linear superposition of waves traveling with different speeds. This model improves the quality of the wave detection and still respects the previous approaches, as it integrates several biologically plausible constraints: 1) separability of the sources in terms of cortical location; 2) separability of the waves in terms of propagation speed, and 3) additivity of the depolarizing effects of the waves. Under these assumptions, a traveling component analysis algorithm performs a full separation of the set of waves and recovers the locations of the neural sources. Both features could help to better understand the dynamics of evoked activity in cortical sensory networks.
{"title":"Separation of traveling waves in cortical networks using optical imaging","authors":"Nicolas Schmidt, G. Peyré, Y. Frégnac, P. Roland","doi":"10.1109/ISBI.2010.5490124","DOIUrl":"https://doi.org/10.1109/ISBI.2010.5490124","url":null,"abstract":"This paper introduces a mathematical model of the spatio-temporal patterns of visually evoked activity observed using Voltage-Sensitive Dye Imaging (VSDI) of the visual cortex. The cortical activity is described using a linear superposition of waves traveling with different speeds. This model improves the quality of the wave detection and still respects the previous approaches, as it integrates several biologically plausible constraints: 1) separability of the sources in terms of cortical location; 2) separability of the waves in terms of propagation speed, and 3) additivity of the depolarizing effects of the waves. Under these assumptions, a traveling component analysis algorithm performs a full separation of the set of waves and recovers the locations of the neural sources. Both features could help to better understand the dynamics of evoked activity in cortical sensory networks.","PeriodicalId":250523,"journal":{"name":"2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125681860","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 : 2010-04-14DOI: 10.1109/ISBI.2010.5490084
M. Marim, M. Atlan, E. Angelini, J. Olivo-Marin
This paper describes an original microscopy imaging framework successfully employing Compressed Sensing for digital holography. Our approach combines a sparsity minimization algorithm to reconstruct the image and digital holography to perform quadrature-resolved random measurements of an optical field in a diffraction plane. Compressed Sensing is a recent theory establishing that near-exact recovery of an unknown sparse signal is possible from a small number of non-structured measurements. We demonstrate with practical experiments on holographic microscopy images of cerebral blood flow that our CS approach enables optimal reconstruction from a very limited number of measurements while being robust to high noise levels.
{"title":"Compressed sensing for digital holographic microscopy","authors":"M. Marim, M. Atlan, E. Angelini, J. Olivo-Marin","doi":"10.1109/ISBI.2010.5490084","DOIUrl":"https://doi.org/10.1109/ISBI.2010.5490084","url":null,"abstract":"This paper describes an original microscopy imaging framework successfully employing Compressed Sensing for digital holography. Our approach combines a sparsity minimization algorithm to reconstruct the image and digital holography to perform quadrature-resolved random measurements of an optical field in a diffraction plane. Compressed Sensing is a recent theory establishing that near-exact recovery of an unknown sparse signal is possible from a small number of non-structured measurements. We demonstrate with practical experiments on holographic microscopy images of cerebral blood flow that our CS approach enables optimal reconstruction from a very limited number of measurements while being robust to high noise levels.","PeriodicalId":250523,"journal":{"name":"2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115844381","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 : 2010-04-14DOI: 10.1109/ISBI.2010.5490198
E. Robinson, D. Rueckert, A. Hammers, A. Edwards
In this paper we describe a framework for creating a probabilistic white matter atlas from diffusion MR images. The approach is based on sampling from the posterior distributions of the parameters of the local model of diffusion and transforming them to a common coordinate space using non-rigid registration. These transformed distributions are then combined to form population distributions of the local fibre direction at each voxel from which a large number of samples are drawn to create an atlas. Next a fibre tract atlas is created by performing probabilistic tractography, between 83 anatomical regions of interest, where the resulting tracts represent the most likely trajectory of pathways for the population. The atlas is created for an entire population 171 subjects ranging from 20–90 years. Statistical comparison of FA in the atlas co-ordinate space allows comparison of diffusion properties across the population without bias from differences in the anatomy. We perform permutation testing of FA within tracts propagated from the temporal lobe and demonstrate significant differences between male and female populations.
{"title":"Probabilistic white matter and fiber tract atlas construction","authors":"E. Robinson, D. Rueckert, A. Hammers, A. Edwards","doi":"10.1109/ISBI.2010.5490198","DOIUrl":"https://doi.org/10.1109/ISBI.2010.5490198","url":null,"abstract":"In this paper we describe a framework for creating a probabilistic white matter atlas from diffusion MR images. The approach is based on sampling from the posterior distributions of the parameters of the local model of diffusion and transforming them to a common coordinate space using non-rigid registration. These transformed distributions are then combined to form population distributions of the local fibre direction at each voxel from which a large number of samples are drawn to create an atlas. Next a fibre tract atlas is created by performing probabilistic tractography, between 83 anatomical regions of interest, where the resulting tracts represent the most likely trajectory of pathways for the population. The atlas is created for an entire population 171 subjects ranging from 20–90 years. Statistical comparison of FA in the atlas co-ordinate space allows comparison of diffusion properties across the population without bias from differences in the anatomy. We perform permutation testing of FA within tracts propagated from the temporal lobe and demonstrate significant differences between male and female populations.","PeriodicalId":250523,"journal":{"name":"2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132461241","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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