Pub Date : 2014-07-31DOI: 10.1109/ISBI.2014.6868085
B. D. Senneville, Y. Regard, C. Moonen, M. Ries
Real-time motion estimation has a growing interest for the guidance of interventional procedures in mobile organs. For this purpose, combined magnetic resonance (MR) imaging and ultrasound (US) echography systems can now provide both MR- and US- images, which can be exploited simultaneously for improved target tracking. For this purpose, two tracking strategies can be investigated: While indirect tracking methods rely on a calibration obtained prior to the intervention, direct tracking methods perform the target localization directly on the continuously acquired position. The current paper describes real-time methodological developments designed for the guidance of non-invasive interventional procedures, using a combined MR/US imaging system: A GPU (Graphics Processing Unit) optimized processing pipeline is proposed for both direct and indirect approaches, in conjunction with simultaneous high-frame-rate MR and echography. Experiments on a moving ex-vivo target were performed with MR-guided HIFU (High Intensity Focused Ultrasound) during continuous ultrasound echography. Real-time US echography-based tracking during MR-guided HIFU heating was achieved with heated area dimensions similar to those obtained for a static target.
{"title":"Combined ultrasound echography and magnetic resonance imaging guidance for direct and indirect target tracking","authors":"B. D. Senneville, Y. Regard, C. Moonen, M. Ries","doi":"10.1109/ISBI.2014.6868085","DOIUrl":"https://doi.org/10.1109/ISBI.2014.6868085","url":null,"abstract":"Real-time motion estimation has a growing interest for the guidance of interventional procedures in mobile organs. For this purpose, combined magnetic resonance (MR) imaging and ultrasound (US) echography systems can now provide both MR- and US- images, which can be exploited simultaneously for improved target tracking. For this purpose, two tracking strategies can be investigated: While indirect tracking methods rely on a calibration obtained prior to the intervention, direct tracking methods perform the target localization directly on the continuously acquired position. The current paper describes real-time methodological developments designed for the guidance of non-invasive interventional procedures, using a combined MR/US imaging system: A GPU (Graphics Processing Unit) optimized processing pipeline is proposed for both direct and indirect approaches, in conjunction with simultaneous high-frame-rate MR and echography. Experiments on a moving ex-vivo target were performed with MR-guided HIFU (High Intensity Focused Ultrasound) during continuous ultrasound echography. Real-time US echography-based tracking during MR-guided HIFU heating was achieved with heated area dimensions similar to those obtained for a static target.","PeriodicalId":440405,"journal":{"name":"2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI)","volume":"182 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126954274","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 : 2014-07-31DOI: 10.1109/ISBI.2014.6868005
J. Lötjönen, C. Ledig, J. Koikkalainen, R. Wolz, L. Thurfjell, H. Soininen, S. Ourselin, D. Rueckert
The boundary shift integral (BSI) is a widely used method for measuring atrophy rate, dynamic changes of the gray-matter and cerebrospinal fluid boundaries in magnetic resonance images. BSI is based on intensity differences on this boundary region. This work extends the method in two respects: 1) Instead of using only intensity information on the boundary region, a probabilistic approach is proposed in which also other characteristics of the boundary region can be used. 2) The use of the probabilistic model enables to measure changes between any structures or combination of structures in the image. The performance of the extended BSI is verified against standard BSI in the ADNI and AIBL cohorts. The area-under-the-curve is clearly above 90 % in both cohorts when comparing the classification between cognitively normal and Alzheimer's disease groups. The accuracies of the extended BSI were higher than the standard BSI between these groups.
{"title":"Extended boundary shift integral","authors":"J. Lötjönen, C. Ledig, J. Koikkalainen, R. Wolz, L. Thurfjell, H. Soininen, S. Ourselin, D. Rueckert","doi":"10.1109/ISBI.2014.6868005","DOIUrl":"https://doi.org/10.1109/ISBI.2014.6868005","url":null,"abstract":"The boundary shift integral (BSI) is a widely used method for measuring atrophy rate, dynamic changes of the gray-matter and cerebrospinal fluid boundaries in magnetic resonance images. BSI is based on intensity differences on this boundary region. This work extends the method in two respects: 1) Instead of using only intensity information on the boundary region, a probabilistic approach is proposed in which also other characteristics of the boundary region can be used. 2) The use of the probabilistic model enables to measure changes between any structures or combination of structures in the image. The performance of the extended BSI is verified against standard BSI in the ADNI and AIBL cohorts. The area-under-the-curve is clearly above 90 % in both cohorts when comparing the classification between cognitively normal and Alzheimer's disease groups. The accuracies of the extended BSI were higher than the standard BSI between these groups.","PeriodicalId":440405,"journal":{"name":"2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117023828","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 : 2014-07-31DOI: 10.1109/ISBI.2014.6867838
S. Johnston, G. Johnson, C. Badea
While helical scanning is well established in the clinical arena, most micro-CT scanners use circular cone beam trajectories and approximate reconstructions based on a filtered backprojection (FBP) algorithm. This may be sufficient for some applications, but in studies of larger animals, such as rats, the size of the detector can constrain the field of view and extend scan time. To address this problem, we have designed and implemented helical scanning and reconstruction procedures for an in-house-developed dual source cone-beam micro-CT system. The reconstruction uses a simultaneous algebraic reconstruction technique combined with total variation regularization (SART-TV). We implemented this algorithm on a graphics processing unit (GPU) to reduce run time. The results demonstrate the speed and accuracy of the GPU-based SART-TV algorithm. The helical scan enables the reconstruction of volumes with extended field of view for whole body micro-CT imaging of large rodents.
{"title":"Helical dual source cone-beam micro-CT","authors":"S. Johnston, G. Johnson, C. Badea","doi":"10.1109/ISBI.2014.6867838","DOIUrl":"https://doi.org/10.1109/ISBI.2014.6867838","url":null,"abstract":"While helical scanning is well established in the clinical arena, most micro-CT scanners use circular cone beam trajectories and approximate reconstructions based on a filtered backprojection (FBP) algorithm. This may be sufficient for some applications, but in studies of larger animals, such as rats, the size of the detector can constrain the field of view and extend scan time. To address this problem, we have designed and implemented helical scanning and reconstruction procedures for an in-house-developed dual source cone-beam micro-CT system. The reconstruction uses a simultaneous algebraic reconstruction technique combined with total variation regularization (SART-TV). We implemented this algorithm on a graphics processing unit (GPU) to reduce run time. The results demonstrate the speed and accuracy of the GPU-based SART-TV algorithm. The helical scan enables the reconstruction of volumes with extended field of view for whole body micro-CT imaging of large rodents.","PeriodicalId":440405,"journal":{"name":"2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI)","volume":"364 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132524273","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 : 2014-07-31DOI: 10.1109/ISBI.2014.6867870
A. Crimi, M. Makhinya, U. Baumann, G. Székely, O. Goksel
Information concerning central venous pressure (CVP) is crucial in clinical situations, such as cardiac failure, volume overload, and sepsis. The measurement of CVP, however, requires insertion of a catheter through a vein up a vena cava - close to the heart - with related cost and risk of complications. Peripheral venous pressure (PVP) measurement is a technique which allows indirect assessment of CVP without catheterization. However, PVP measurement is cumbersome since it requires several devices, trained medical personnel, and is difficult to perform repeatably. Aiming at an automatic venous pressure measurement system via image-processing, we introduce in this paper a robust vessel tracking algorithm fit for this purpose. The proposed algorithm addresses the challenge of tracking compressed vessels, which is essential for this venous pressure measurement technique. Given this tracking algorithm, initial PVP measurements on healthy volunteers are reported.
{"title":"Vessel tracking for ultrasound-based venous pressure measurement","authors":"A. Crimi, M. Makhinya, U. Baumann, G. Székely, O. Goksel","doi":"10.1109/ISBI.2014.6867870","DOIUrl":"https://doi.org/10.1109/ISBI.2014.6867870","url":null,"abstract":"Information concerning central venous pressure (CVP) is crucial in clinical situations, such as cardiac failure, volume overload, and sepsis. The measurement of CVP, however, requires insertion of a catheter through a vein up a vena cava - close to the heart - with related cost and risk of complications. Peripheral venous pressure (PVP) measurement is a technique which allows indirect assessment of CVP without catheterization. However, PVP measurement is cumbersome since it requires several devices, trained medical personnel, and is difficult to perform repeatably. Aiming at an automatic venous pressure measurement system via image-processing, we introduce in this paper a robust vessel tracking algorithm fit for this purpose. The proposed algorithm addresses the challenge of tracking compressed vessels, which is essential for this venous pressure measurement technique. Given this tracking algorithm, initial PVP measurements on healthy volunteers are reported.","PeriodicalId":440405,"journal":{"name":"2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI)","volume":"146 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132579786","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 : 2014-07-31DOI: 10.1109/ISBI.2014.6868046
K. Martínez, Anand A. Joshi, S. Madsen, Shantanu H. Joshi, S. Karama, F. J. Román, Julio Villalón, M. Burgaleta, P. Thompson, R. Colom
Neuroimaging techniques are now widely used to understand relationships between brain features and cognitive performance. Nevertheless, studies do not always implicate the same anatomical neural networks in intellectual function. Here we used T1-weighted brain MRI scans obtained from a sample of 82 healthy young adults to study four potential sources of variability affecting the reproducibility of brain-cognition relationships: the neuroimaging protocol used, different measures of cortical gray matter, the nature of the cognitive measurement, and sample characteristics. We found that brain networks implicated in individual differences in cognition were not consistent when derived from different gray matter measures, or from different surface-based processing pipelines, even in equivalent samples of participants. Differences in the networks associated with cognition may reflect differences in the methods used to analyze them; in addition, different individuals may reach equivalent psychological goals through disparate brain networks.
{"title":"Reproducibility of brain-cognition relationships using different cortical surface-based analysis protocols","authors":"K. Martínez, Anand A. Joshi, S. Madsen, Shantanu H. Joshi, S. Karama, F. J. Román, Julio Villalón, M. Burgaleta, P. Thompson, R. Colom","doi":"10.1109/ISBI.2014.6868046","DOIUrl":"https://doi.org/10.1109/ISBI.2014.6868046","url":null,"abstract":"Neuroimaging techniques are now widely used to understand relationships between brain features and cognitive performance. Nevertheless, studies do not always implicate the same anatomical neural networks in intellectual function. Here we used T1-weighted brain MRI scans obtained from a sample of 82 healthy young adults to study four potential sources of variability affecting the reproducibility of brain-cognition relationships: the neuroimaging protocol used, different measures of cortical gray matter, the nature of the cognitive measurement, and sample characteristics. We found that brain networks implicated in individual differences in cognition were not consistent when derived from different gray matter measures, or from different surface-based processing pipelines, even in equivalent samples of participants. Differences in the networks associated with cognition may reflect differences in the methods used to analyze them; in addition, different individuals may reach equivalent psychological goals through disparate brain networks.","PeriodicalId":440405,"journal":{"name":"2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132857776","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 : 2014-07-31DOI: 10.1109/ISBI.2014.6868117
M. Radojević, Ihor Smal, W. Niessen, E. Meijering
Quantitative analysis of neuronal cell morphology from microscopic image data requires accurate reconstruction of the axonal and dendritic trees. The most critical points to be detected in this process are the bifurcations. Here we present a new method for fully automatic detection of bifurcations in microscopic images. The proposed method models the essential characteristics of bifurcations and employs fuzzy rule based reasoning to decide whether the extracted image features indicate the presence of a bifurcation. Algorithm tests on synthetic image data show high noise immunity and experiments with real fluorescence microscopy data exhibit average recall and precision of 90.4% and 90.5% respectively.
{"title":"Fuzzy logic based detection of neuron bifurcations in microscopy images","authors":"M. Radojević, Ihor Smal, W. Niessen, E. Meijering","doi":"10.1109/ISBI.2014.6868117","DOIUrl":"https://doi.org/10.1109/ISBI.2014.6868117","url":null,"abstract":"Quantitative analysis of neuronal cell morphology from microscopic image data requires accurate reconstruction of the axonal and dendritic trees. The most critical points to be detected in this process are the bifurcations. Here we present a new method for fully automatic detection of bifurcations in microscopic images. The proposed method models the essential characteristics of bifurcations and employs fuzzy rule based reasoning to decide whether the extracted image features indicate the presence of a bifurcation. Algorithm tests on synthetic image data show high noise immunity and experiments with real fluorescence microscopy data exhibit average recall and precision of 90.4% and 90.5% respectively.","PeriodicalId":440405,"journal":{"name":"2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132003463","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 : 2014-07-31DOI: 10.1109/ISBI.2014.6868051
Guang Yang, F. Raschke, T. Barrick, F. Howe
Proton magnetic resonance spectroscopy (1H MRS) provides non-invasive information on brain tumour biochemistry. Many studies have shown that 1H MRS can be used in an objective decision support system, which gives additional diagnosis and prognostic information to the data obtained using conventional radiological modalities. Fully automatic analyses of 1H MRS have been previously applied and can be separated into two types: (i) model dependent signal quantification followed by pattern recognition (PR), or (ii) model independent PR methods. However, there is not yet a consensus as to the best techniques of MRS post-processing or feature extraction to be used for optimum classification. In this study, we analysed the single-voxel MRS acquisitions of 74 patients with histologically diagnosed brain tumours. Our classification results show that the model independent nonlinear manifold learning method can produce superior results to those of using model dependent metabolite quantification.
{"title":"Classification of brain tumour 1H MR spectra: Extracting features by metabolite quantification or nonlinear manifold learning?","authors":"Guang Yang, F. Raschke, T. Barrick, F. Howe","doi":"10.1109/ISBI.2014.6868051","DOIUrl":"https://doi.org/10.1109/ISBI.2014.6868051","url":null,"abstract":"Proton magnetic resonance spectroscopy (1H MRS) provides non-invasive information on brain tumour biochemistry. Many studies have shown that 1H MRS can be used in an objective decision support system, which gives additional diagnosis and prognostic information to the data obtained using conventional radiological modalities. Fully automatic analyses of 1H MRS have been previously applied and can be separated into two types: (i) model dependent signal quantification followed by pattern recognition (PR), or (ii) model independent PR methods. However, there is not yet a consensus as to the best techniques of MRS post-processing or feature extraction to be used for optimum classification. In this study, we analysed the single-voxel MRS acquisitions of 74 patients with histologically diagnosed brain tumours. Our classification results show that the model independent nonlinear manifold learning method can produce superior results to those of using model dependent metabolite quantification.","PeriodicalId":440405,"journal":{"name":"2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134359800","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 : 2014-07-31DOI: 10.1109/ISBI.2014.6868082
W. Cong, Ge Wang
Nanophosphors emit near-infrared (NIR) light upon X-ray excitation, and can be functionalized as optical probes for in vivo molecular imaging. X-ray luminescence computed tomography (XLCT) combines the high sensitivity optical imaging with the high spatial resolution X-ray imaging to visualize specific molecular and cellular targets, pathways and therapeutic responses. In this paper, we propose an X-ray fan-beam luminescence tomography to quantify a spatial distribution of nanophosphors in a biological object. A practical imaging system is designed for the X-ray fan-beam luminescence imaging in which the X-ray tube is collimated into a fan-beam X-rays to excite nanophosphors on a cross-section of the object. The excited nanophosphors would emit NIR light to be detected on the external surface of the object. The measured NIR light signal (2D) is used to reconstruct a nanoparticle distribution (2D) on the cross-section. In this imaging mode, the dimensionality of measurable data matches to that of the nanophosphors image to be reconstructed, allowing an accurate and reliable image reconstruction. The numerical experiments are performed to demonstrate the feasibility and merits of the proposed approach.
{"title":"X-ray fan-beam luminescence tomography","authors":"W. Cong, Ge Wang","doi":"10.1109/ISBI.2014.6868082","DOIUrl":"https://doi.org/10.1109/ISBI.2014.6868082","url":null,"abstract":"Nanophosphors emit near-infrared (NIR) light upon X-ray excitation, and can be functionalized as optical probes for in vivo molecular imaging. X-ray luminescence computed tomography (XLCT) combines the high sensitivity optical imaging with the high spatial resolution X-ray imaging to visualize specific molecular and cellular targets, pathways and therapeutic responses. In this paper, we propose an X-ray fan-beam luminescence tomography to quantify a spatial distribution of nanophosphors in a biological object. A practical imaging system is designed for the X-ray fan-beam luminescence imaging in which the X-ray tube is collimated into a fan-beam X-rays to excite nanophosphors on a cross-section of the object. The excited nanophosphors would emit NIR light to be detected on the external surface of the object. The measured NIR light signal (2D) is used to reconstruct a nanoparticle distribution (2D) on the cross-section. In this imaging mode, the dimensionality of measurable data matches to that of the nanophosphors image to be reconstructed, allowing an accurate and reliable image reconstruction. The numerical experiments are performed to demonstrate the feasibility and merits of the proposed approach.","PeriodicalId":440405,"journal":{"name":"2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133235134","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 : 2014-07-31DOI: 10.1109/ISBI.2014.6867884
R. Tournemenne, Christel Ducroz, J. Olivo-Marin, A. Dufour
Amoeboid cell motility is characterised by the emission of protrusions at the cellular surface (also known as “blebs”). Detection and counting of these protrusions is a crucial step towards the understanding of the deformation and motility machinery. We propose an automated technique to detect protrusions at the surface of cells observed in 3D fluorescence microscopy using over-complete spherical wavelets. The framework permits intuitive manipulation of wavelets on the sphere, thanks to a straightforward analogy with traditional wavelets on the plane. We illustrate detection results on a real data set of protruding cells, indicating the reliability of the method. Moreover, the flexibility of the approach makes it easily amenable to other shape analysis problems.
{"title":"3D shape analysis using overcomplete spherical wavelets: Application to BLEB detection in cell biology","authors":"R. Tournemenne, Christel Ducroz, J. Olivo-Marin, A. Dufour","doi":"10.1109/ISBI.2014.6867884","DOIUrl":"https://doi.org/10.1109/ISBI.2014.6867884","url":null,"abstract":"Amoeboid cell motility is characterised by the emission of protrusions at the cellular surface (also known as “blebs”). Detection and counting of these protrusions is a crucial step towards the understanding of the deformation and motility machinery. We propose an automated technique to detect protrusions at the surface of cells observed in 3D fluorescence microscopy using over-complete spherical wavelets. The framework permits intuitive manipulation of wavelets on the sphere, thanks to a straightforward analogy with traditional wavelets on the plane. We illustrate detection results on a real data set of protruding cells, indicating the reliability of the method. Moreover, the flexibility of the approach makes it easily amenable to other shape analysis problems.","PeriodicalId":440405,"journal":{"name":"2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133512934","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 : 2014-07-31DOI: 10.1109/ISBI.2014.6867942
Zhichao Lian, Xiang Li, Jianchuan Xing, Jinglei Lv, Xi Jiang, Dajiang Zhu, Shu Zhang, Jiansong Xu, M. Potenza, Tianming Liu, Jing Zhang
Multiple recent neuroimaging studies have demonstrated that the human brain's function undergoes remarkable temporal dynamics. However, quantitative characterization and modeling of such functional dynamics have been rarely explored. To fill this gap, we presents a novel Bayesian connectivity change point model (BCCPM), to analyze the joint probabilities among the nodes of brain networks between different time periods and statistically determine the boundaries of temporal blocks to estimate the change points. Intuitively, the determined change points represent the transitions of functional interaction patterns within the brain networks and can be used to investigate temporal functional brain dynamics. The BCCPM has been evaluated and validated by synthesized data. Also, the BCCPM has been applied to a real block-design task-based fMRI dataset and interesting results were obtained.
{"title":"Exploring functional brain dynamics via a Bayesian connectivity change point model","authors":"Zhichao Lian, Xiang Li, Jianchuan Xing, Jinglei Lv, Xi Jiang, Dajiang Zhu, Shu Zhang, Jiansong Xu, M. Potenza, Tianming Liu, Jing Zhang","doi":"10.1109/ISBI.2014.6867942","DOIUrl":"https://doi.org/10.1109/ISBI.2014.6867942","url":null,"abstract":"Multiple recent neuroimaging studies have demonstrated that the human brain's function undergoes remarkable temporal dynamics. However, quantitative characterization and modeling of such functional dynamics have been rarely explored. To fill this gap, we presents a novel Bayesian connectivity change point model (BCCPM), to analyze the joint probabilities among the nodes of brain networks between different time periods and statistically determine the boundaries of temporal blocks to estimate the change points. Intuitively, the determined change points represent the transitions of functional interaction patterns within the brain networks and can be used to investigate temporal functional brain dynamics. The BCCPM has been evaluated and validated by synthesized data. Also, the BCCPM has been applied to a real block-design task-based fMRI dataset and interesting results were obtained.","PeriodicalId":440405,"journal":{"name":"2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI)","volume":"36 11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124516110","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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