Pub Date : 2008-05-14DOI: 10.1109/ISBI.2008.4541042
G. Rohde, Wei Wang, Tao Peng, R. Murphy
We describe a new approach for elucidating the nonlinear degrees of freedom in a distribution of shapes depicted in digital images. By combining a deformation-based method for measuring distances between two shape configurations together with multidimensional scaling, a method for determining the number of degrees of freedom in a shape distribution is described. In addition, a method for visualizing the most representative modes of variation (underlying shape parameterization) in a nuclei shape distribution is also presented. The novel approach takes into account the nonlinear nature of shape manifolds and is related to the ISOMAP algorithm. We apply the method to the task of analyzing the shape distribution of HeLa cell nuclei and conclude that approximately three parameters are responsible for their shape variation. Excluding differences in size, translation, and orientation, these are: elongation, bending (concavity), and shifts in mass distribution. In addition, results show that, contrary to common intuition, the most likely nuclear shape configuration is not symmetric.
{"title":"Deformation-based nonlinear dimension reduction: Applications to nuclear morphometry","authors":"G. Rohde, Wei Wang, Tao Peng, R. Murphy","doi":"10.1109/ISBI.2008.4541042","DOIUrl":"https://doi.org/10.1109/ISBI.2008.4541042","url":null,"abstract":"We describe a new approach for elucidating the nonlinear degrees of freedom in a distribution of shapes depicted in digital images. By combining a deformation-based method for measuring distances between two shape configurations together with multidimensional scaling, a method for determining the number of degrees of freedom in a shape distribution is described. In addition, a method for visualizing the most representative modes of variation (underlying shape parameterization) in a nuclei shape distribution is also presented. The novel approach takes into account the nonlinear nature of shape manifolds and is related to the ISOMAP algorithm. We apply the method to the task of analyzing the shape distribution of HeLa cell nuclei and conclude that approximately three parameters are responsible for their shape variation. Excluding differences in size, translation, and orientation, these are: elongation, bending (concavity), and shifts in mass distribution. In addition, results show that, contrary to common intuition, the most likely nuclear shape configuration is not symmetric.","PeriodicalId":184204,"journal":{"name":"2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"76 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":"114541813","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.2008.4540947
P. Tylski, M. Dusart, B. Vanderlinden, I. Buvat
In PET-based patient monitoring, tumor changes can be assessed using standardized uptake values (SUV), tumor volume (V), or total lesion glycolysis (TLG). We studied the impact of the SUV, V and TLG estimation methods on the interpretation of tumor changes between 2 PET scans. We also propose a bootstrap approach to assign statistical significance to the observed tumor changes. In 17 tumor changes, the SUV variations were the least dependent on the estimation method compared to the V or TLG changes. In 16/17 cases, SUV changes were significant. In 2 out of these 16 significant cases, at least one SUV index suggested non significant change. Testing the significance of tumor feature changes might reduce errors in interpreting tumor changes.
{"title":"Assigning statistical significance to tumor changes in patient monitoring using FDG pet","authors":"P. Tylski, M. Dusart, B. Vanderlinden, I. Buvat","doi":"10.1109/ISBI.2008.4540947","DOIUrl":"https://doi.org/10.1109/ISBI.2008.4540947","url":null,"abstract":"In PET-based patient monitoring, tumor changes can be assessed using standardized uptake values (SUV), tumor volume (V), or total lesion glycolysis (TLG). We studied the impact of the SUV, V and TLG estimation methods on the interpretation of tumor changes between 2 PET scans. We also propose a bootstrap approach to assign statistical significance to the observed tumor changes. In 17 tumor changes, the SUV variations were the least dependent on the estimation method compared to the V or TLG changes. In 16/17 cases, SUV changes were significant. In 2 out of these 16 significant cases, at least one SUV index suggested non significant change. Testing the significance of tumor feature changes might reduce errors in interpreting tumor changes.","PeriodicalId":184204,"journal":{"name":"2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"18 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":"116251666","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.2008.4541311
J. Falconet, R. Sablong, E. Perrin, H. Saint-Jalmes
Optical characterization of biological tissues is of real interest to improve medical diagnosis and in particular in the detection of precancerous tissues. We propose a new noninvasive method allowing the estimation of the anisotropy factor. This method is based on the image analysis of the Q- element of Stokes vector backscattered from the turbid medium. These Q-element images show specific patterns depending on g. Therefore the use of Fourier Descriptors (FD) on simulated data, to discriminate the specific geometrical features of the Q-element, enabled us to determine a linear relation between the anisotropy factor and six FD. This method was applied on experimental data obtained with calibrated solutions. The anisotropy factor was estimated with a maximum relative error of 13 %.
{"title":"Anisotropy factor estimation from backscattered Q elements of stokes vectors","authors":"J. Falconet, R. Sablong, E. Perrin, H. Saint-Jalmes","doi":"10.1109/ISBI.2008.4541311","DOIUrl":"https://doi.org/10.1109/ISBI.2008.4541311","url":null,"abstract":"Optical characterization of biological tissues is of real interest to improve medical diagnosis and in particular in the detection of precancerous tissues. We propose a new noninvasive method allowing the estimation of the anisotropy factor. This method is based on the image analysis of the Q- element of Stokes vector backscattered from the turbid medium. These Q-element images show specific patterns depending on g. Therefore the use of Fourier Descriptors (FD) on simulated data, to discriminate the specific geometrical features of the Q-element, enabled us to determine a linear relation between the anisotropy factor and six FD. This method was applied on experimental data obtained with calibrated solutions. The anisotropy factor was estimated with a maximum relative error of 13 %.","PeriodicalId":184204,"journal":{"name":"2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"22 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":"116281057","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.2008.4540925
M. Uhercik, J. Kybic, H. Liebgott, C. Cachard
We address the problem of fast and accurate localization of miniature surgical instruments like needles or electrodes using 3D ultrasound (US). An algorithm based on maximizing a parallel integral transform (PIP) can automatically localize line-shaped objects in 3D US images with accuracy on the order of hundreds of micrometers. Here we propose to use a multi-resolution to accelerate the algorithm significantly. We use a maximum function for downsampling to preserve the high intensity voxels of a thin electrode. We integrate the multi-resolution pyramid into a hierarchical mesh-grid search of PIP. The experiments with a tissue mimicking phantom and breast biopsy data show that proposed method works well on real US images. The speed-up is threefold compared to original PIP method with the same accuracy 0.4 mm. A further speed-up up to 16 times is reached by an early stopping of the optimization, at the expense of some loss of accuracy.
{"title":"Multi-resolution parallel integral projection for fast localization of a straight electrode in 3D ultrasound images","authors":"M. Uhercik, J. Kybic, H. Liebgott, C. Cachard","doi":"10.1109/ISBI.2008.4540925","DOIUrl":"https://doi.org/10.1109/ISBI.2008.4540925","url":null,"abstract":"We address the problem of fast and accurate localization of miniature surgical instruments like needles or electrodes using 3D ultrasound (US). An algorithm based on maximizing a parallel integral transform (PIP) can automatically localize line-shaped objects in 3D US images with accuracy on the order of hundreds of micrometers. Here we propose to use a multi-resolution to accelerate the algorithm significantly. We use a maximum function for downsampling to preserve the high intensity voxels of a thin electrode. We integrate the multi-resolution pyramid into a hierarchical mesh-grid search of PIP. The experiments with a tissue mimicking phantom and breast biopsy data show that proposed method works well on real US images. The speed-up is threefold compared to original PIP method with the same accuracy 0.4 mm. A further speed-up up to 16 times is reached by an early stopping of the optimization, at the expense of some loss of accuracy.","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":"127894862","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.2008.4541204
Sangeetha Somayajula, Anand A. Joshi, R. Leahy
We propose a scale-space based approach to non-rigid small animal image registration. Scale-space theory is based on generating a family of images by blurring an image with Gaussian kernels of increasing width. This approach can be used to extract features at varying levels of detail from an image. We define the scale-space feature vector at each voxel of an image as a vector of intensities of the scale- space images at that voxel. We generate scale-space images of the target and template images, and extract their corresponding scale- space feature vectors at each voxel. The extracted feature vectors are aligned using mutual information based non-rigid registration to simultaneously align global structure as well as detail in the images. We represent the displacement field in terms of the discrete cosine transform (DCT) basis, and use the Laplacian of the displacement field as a regularizing term. The DCT representation of the displacement field simplifies the Laplacian regularization term to a diagonal, thus reducing computational cost. We apply the scale-space registration algorithm on mouse images obtained from two time points of a longitudinal study, and compare its performance with that of a hierarchical multi-scale approach. The results indicate that scale- space based registration gives better skeletal as well as soft tissue alignment compared to the hierarchical multi-scale approach.
{"title":"Mutual information based non-rigidmouse registration using a scale-space approach","authors":"Sangeetha Somayajula, Anand A. Joshi, R. Leahy","doi":"10.1109/ISBI.2008.4541204","DOIUrl":"https://doi.org/10.1109/ISBI.2008.4541204","url":null,"abstract":"We propose a scale-space based approach to non-rigid small animal image registration. Scale-space theory is based on generating a family of images by blurring an image with Gaussian kernels of increasing width. This approach can be used to extract features at varying levels of detail from an image. We define the scale-space feature vector at each voxel of an image as a vector of intensities of the scale- space images at that voxel. We generate scale-space images of the target and template images, and extract their corresponding scale- space feature vectors at each voxel. The extracted feature vectors are aligned using mutual information based non-rigid registration to simultaneously align global structure as well as detail in the images. We represent the displacement field in terms of the discrete cosine transform (DCT) basis, and use the Laplacian of the displacement field as a regularizing term. The DCT representation of the displacement field simplifies the Laplacian regularization term to a diagonal, thus reducing computational cost. We apply the scale-space registration algorithm on mouse images obtained from two time points of a longitudinal study, and compare its performance with that of a hierarchical multi-scale approach. The results indicate that scale- space based registration gives better skeletal as well as soft tissue alignment compared to the hierarchical multi-scale approach.","PeriodicalId":184204,"journal":{"name":"2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"245 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":"128086058","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.2008.4541106
Lotfi Chaari, J. Pesquet, A. Benazza-Benyahia, P. Ciuciu
To reduce the scanning time in some MRI applications, parallel acquisition techniques with multiple coils have been developed. Then, the full Field of View (FOV) image is reconstructed from the resulting registered subsampled k-space data. To this end, several reconstruction techniques have been proposed such as the widely-used SENSE method. However, the reconstructed image generally presents artifacts especially when perturbations occur in both the measured data and in the estimated coil sensitivity maps. In order to alleviate such shortcomings by limiting the distortions, Tikhonov regularization in the image domain has also been investigated. In this paper, we present a novel algorithm for SENSE reconstruction which proceeds with regularization in the wavelet domain, the hyperparameters being estimated from the data. Experiments carried out on real T1-weighted MRI data at 1.5 T indicate that the proposed algorithm generates reconstructed images with reduced artifacts in comparison with conventional reconstruction techniques.
{"title":"Autocalibrated regularized parallel mri reconstruction in the wavelet domain","authors":"Lotfi Chaari, J. Pesquet, A. Benazza-Benyahia, P. Ciuciu","doi":"10.1109/ISBI.2008.4541106","DOIUrl":"https://doi.org/10.1109/ISBI.2008.4541106","url":null,"abstract":"To reduce the scanning time in some MRI applications, parallel acquisition techniques with multiple coils have been developed. Then, the full Field of View (FOV) image is reconstructed from the resulting registered subsampled k-space data. To this end, several reconstruction techniques have been proposed such as the widely-used SENSE method. However, the reconstructed image generally presents artifacts especially when perturbations occur in both the measured data and in the estimated coil sensitivity maps. In order to alleviate such shortcomings by limiting the distortions, Tikhonov regularization in the image domain has also been investigated. In this paper, we present a novel algorithm for SENSE reconstruction which proceeds with regularization in the wavelet domain, the hyperparameters being estimated from the data. Experiments carried out on real T1-weighted MRI data at 1.5 T indicate that the proposed algorithm generates reconstructed images with reduced artifacts in comparison with conventional reconstruction techniques.","PeriodicalId":184204,"journal":{"name":"2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"4 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":"128114492","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.2008.4541306
J. Ross, N. Subramanian, S. Solomon
Hepatic embolization is a procedure designed to cut off blood supply to liver tumors, either hepatocellular carcinomas (HCC) or metastases from other parts of the body. While it often serves as a palliative treatment, it can also be indicated as a precursor to liver resection and liver transplants. The procedure itself is conducted under fluoroscopic X-ray guidance. Contrast agent is administered to opacify the vasculature and to indicate the arterial branches that feed the treatment target. These supply routes are then blocked by embolic agents, cutting off the tumor's blood supply. While methods exist to enhance fluoroscopic images and reduce the dependency on contrast agent, they are typically confounded by patient respiratory motion and are hence not effective for abdominal interventions. This paper presents an appearance based tracking algorithm that quickly and accurately compensates for the liver's bulk motion due to respiration, thereby enabling the application of fluoroscopic augmentations (i.e. image overlays) for hepatic embolization procedures. To quantify the accuracy of our algorithm, we manually identified vascular and artificial landmarks in fluoroscopy sequences acquired from three patients during free breathing. The average postmotion compensation landmark misalignment was 1.9 mm, with the maximum landmark misalignment not exceeding 5.5 mm.
{"title":"Motion correction for augmented fluoroscopy - application to liver embolization","authors":"J. Ross, N. Subramanian, S. Solomon","doi":"10.1109/ISBI.2008.4541306","DOIUrl":"https://doi.org/10.1109/ISBI.2008.4541306","url":null,"abstract":"Hepatic embolization is a procedure designed to cut off blood supply to liver tumors, either hepatocellular carcinomas (HCC) or metastases from other parts of the body. While it often serves as a palliative treatment, it can also be indicated as a precursor to liver resection and liver transplants. The procedure itself is conducted under fluoroscopic X-ray guidance. Contrast agent is administered to opacify the vasculature and to indicate the arterial branches that feed the treatment target. These supply routes are then blocked by embolic agents, cutting off the tumor's blood supply. While methods exist to enhance fluoroscopic images and reduce the dependency on contrast agent, they are typically confounded by patient respiratory motion and are hence not effective for abdominal interventions. This paper presents an appearance based tracking algorithm that quickly and accurately compensates for the liver's bulk motion due to respiration, thereby enabling the application of fluoroscopic augmentations (i.e. image overlays) for hepatic embolization procedures. To quantify the accuracy of our algorithm, we manually identified vascular and artificial landmarks in fluoroscopy sequences acquired from three patients during free breathing. The average postmotion compensation landmark misalignment was 1.9 mm, with the maximum landmark misalignment not exceeding 5.5 mm.","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":"132248068","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.2008.4541144
B. Jeurissen, A. Leemans, J. Tournier, Jan Sijbers
Constrained spherical deconvolution (CSD) is a new reconstruction technique that extracts white matter fiber orientations from diffusion weighted MRI data of the brain. However, since these orientations are estimated from noisy data, they are subject to errors, which propagate during fiber tractography. Therefore, it is important to estimate the uncertainty associated with the fiber orientations. In this work, we investigate the performance of a statistical method called the bootstrap, when estimating confidence intervals for CSD fiber orientations. The bootstrap is a nonparametric statistical technique based on data resampling. We used Monte Carlo simulations to measure both its accuracy and precision when applied to CSD. Also, we evaluated an alternative method called the bootknife, which aims to increase the precision of the bootstrap.
{"title":"Estimation of uncertainty in constrained spherical deconvolution fiber orientations","authors":"B. Jeurissen, A. Leemans, J. Tournier, Jan Sijbers","doi":"10.1109/ISBI.2008.4541144","DOIUrl":"https://doi.org/10.1109/ISBI.2008.4541144","url":null,"abstract":"Constrained spherical deconvolution (CSD) is a new reconstruction technique that extracts white matter fiber orientations from diffusion weighted MRI data of the brain. However, since these orientations are estimated from noisy data, they are subject to errors, which propagate during fiber tractography. Therefore, it is important to estimate the uncertainty associated with the fiber orientations. In this work, we investigate the performance of a statistical method called the bootstrap, when estimating confidence intervals for CSD fiber orientations. The bootstrap is a nonparametric statistical technique based on data resampling. We used Monte Carlo simulations to measure both its accuracy and precision when applied to CSD. Also, we evaluated an alternative method called the bootknife, which aims to increase the precision of the bootstrap.","PeriodicalId":184204,"journal":{"name":"2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"752 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":"132486489","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.2008.4541131
M. Liebling, J. Vermot, S. Fraser
We present a time-lapse collection and reconstruction technique that allows following embryonic heart development at any computationally halted heart contraction state. The central idea is to image at least one full heartbeat at a fast frame rate, resulting in a two-dimensional plus time (2D+T) data set, and repeat this operation every few minutes over several hours for multiple axial positions. The acquired data are five dimensional (X, Y, and Z in space, 'fast' and 'slow' dimensions in time). The (2D+T) image series are then synchronized to their neighbors in the axial and development time dimensions using a non-rigid registration algorithm (constrained such as to leave all but the fast time dimension unchanged). The algorithm proceeds recursively over the different axial positions and developmental stages. We successfully applied this procedure to image the development of the embryonic zebrafish heart between 32 and 44 hours post fertilization (hpf).
{"title":"Double time-scale image reconstruction of the beating and developing embryonic zebrafish heart","authors":"M. Liebling, J. Vermot, S. Fraser","doi":"10.1109/ISBI.2008.4541131","DOIUrl":"https://doi.org/10.1109/ISBI.2008.4541131","url":null,"abstract":"We present a time-lapse collection and reconstruction technique that allows following embryonic heart development at any computationally halted heart contraction state. The central idea is to image at least one full heartbeat at a fast frame rate, resulting in a two-dimensional plus time (2D+T) data set, and repeat this operation every few minutes over several hours for multiple axial positions. The acquired data are five dimensional (X, Y, and Z in space, 'fast' and 'slow' dimensions in time). The (2D+T) image series are then synchronized to their neighbors in the axial and development time dimensions using a non-rigid registration algorithm (constrained such as to leave all but the fast time dimension unchanged). The algorithm proceeds recursively over the different axial positions and developmental stages. We successfully applied this procedure to image the development of the embryonic zebrafish heart between 32 and 44 hours post fertilization (hpf).","PeriodicalId":184204,"journal":{"name":"2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"130 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":"134543077","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.2008.4541270
F. Beekman, F. V. D. Have, B. Vastenhouw, W. Branderhorst, A. Linden, M. Smidt
We demonstrate new technologies for SPECT imaging with unsurpassed resolution in mice and rats. Results of the imaging of living animals will be shown. In addition development of detectors for next generation systems with an even higher resolution will be shown.
{"title":"Imaging dynamics of organs and drugs at sub-half-mm and sub-minute resolution using focusing pinhole SPECT","authors":"F. Beekman, F. V. D. Have, B. Vastenhouw, W. Branderhorst, A. Linden, M. Smidt","doi":"10.1109/ISBI.2008.4541270","DOIUrl":"https://doi.org/10.1109/ISBI.2008.4541270","url":null,"abstract":"We demonstrate new technologies for SPECT imaging with unsurpassed resolution in mice and rats. Results of the imaging of living animals will be shown. In addition development of detectors for next generation systems with an even higher resolution will be shown.","PeriodicalId":184204,"journal":{"name":"2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"122 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":"126575960","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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