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1.
Quantitative Analysis of Dynamic ContrastEnhanced and DiffusionWeighted Magnetic Resonance Imaging for Oncology in R
Open Access
Title:
Quantitative Analysis of Dynamic ContrastEnhanced and DiffusionWeighted Magnetic Resonance Imaging for Oncology in R
Author:
Volker J. Schmid
;
Brandon Whitcher
Volker J. Schmid
;
Brandon Whitcher
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Description:
The package dcemriS4 provides a complete set of data analysis tools for quantitative assessment of dynamic contrastenhanced magnetic resonance imaging (DCEMRI). Image processing is provided for the ANALYZE and NIfTI data formats as input with all parameter estimates being output in NIfTI format. Estimation of T1 relaxation from multiple flipa...
The package dcemriS4 provides a complete set of data analysis tools for quantitative assessment of dynamic contrastenhanced magnetic resonance imaging (DCEMRI). Image processing is provided for the ANALYZE and NIfTI data formats as input with all parameter estimates being output in NIfTI format. Estimation of T1 relaxation from multiple flipangle acquisitions, using either constant or spatiallyvarying flip angles, is performed via nonlinear regression. Both literaturebased and datadriven arterial input functions are available and may be combined with a variety of compartmental models. Kinetic parameters are obtained from nonlinear regression, Bayesian estimation via Markov chain Monte Carlo or Bayesian maximum a posteriori estimation. A nonparametric model, using penalized splines, is also available to characterize the contrast agent concentration time curves. Estimation of the apparent diffusion coefficient (ADC) is provided for diffusionweighted imaging. Given the size of multidimensional data sets commonly acquired in imaging studies, care has been taken to maximize computational efficiency and minimize memory usage. All methods are illustrated using both simulated and realworld medical imaging data available in the public domain.
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Publisher:
University of California, Los Angeles
Year of Publication:
20111001T00:00:00Z
Source:
Journal of Statistical Software, Vol 44, Iss 05 (2011)
Journal of Statistical Software, Vol 44, Iss 05 (2011)
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Document Type:
article
Language:
English
Subjects:
contrast ; dcemriS4 ; diffusion ; dynamic ; enhanced ; imaging ; magnetic ; resonance. ; LCC:Statistics ; LCC:HA14737 ; LCC:Social Sciences ; LCC:H ; DOAJ:Statistics ; DOAJ:Mathematics and Statistics ; LCC:Statistics ; LCC:HA14737 ; LCC:Social Sciences ; LCC:H ; DOAJ:Statistics ; DOAJ:Mathematics and Statistics ; LCC:Statistics ; LCC:HA14737 ...
contrast ; dcemriS4 ; diffusion ; dynamic ; enhanced ; imaging ; magnetic ; resonance. ; LCC:Statistics ; LCC:HA14737 ; LCC:Social Sciences ; LCC:H ; DOAJ:Statistics ; DOAJ:Mathematics and Statistics ; LCC:Statistics ; LCC:HA14737 ; LCC:Social Sciences ; LCC:H ; DOAJ:Statistics ; DOAJ:Mathematics and Statistics ; LCC:Statistics ; LCC:HA14737 ; LCC:Social Sciences ; LCC:H ; LCC:Statistics ; LCC:HA14737 ; LCC:Social Sciences ; LCC:H ; LCC:Statistics ; LCC:HA14737 ; LCC:Social Sciences ; LCC:H
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2.
Bayesian AgePeriodCohort Modeling and Prediction  BAMP
Open Access
Title:
Bayesian AgePeriodCohort Modeling and Prediction  BAMP
Author:
Volker J. Schmid
;
Leonhard Held
Volker J. Schmid
;
Leonhard Held
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Description:
The software package BAMP provides a method of analyzing incidence or mortality data on the Lexis diagram, using a Bayesian version of an ageperiodcohort model. A hierarchical model is assumed with a binomial model in the firststage. As smoothing priors for the age, period and cohort parameters random walks of first and second order, with and...
The software package BAMP provides a method of analyzing incidence or mortality data on the Lexis diagram, using a Bayesian version of an ageperiodcohort model. A hierarchical model is assumed with a binomial model in the firststage. As smoothing priors for the age, period and cohort parameters random walks of first and second order, with and without an additional unstructured component are available. Unstructured heterogeneity can also be included in the model. In order to evaluate the model fit, posterior deviance, DIC and predictive deviances are computed. By projecting the random walk prior into the future, future death rates can be predicted.
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Publisher:
University of California at Los Angeles, Department of Statistics
Year of Publication:
20071001T00:00:00Z
Document Type:
article
Language:
English
Subjects:
Bayesian hierarchical models ; ageperiodcohort models ; prediction ; LCC:Statistics ; LCC:HA14737 ; LCC:Social Sciences ; LCC:H ; DOAJ:Statistics ; DOAJ:Mathematics and Statistics ; LCC:Statistics ; LCC:HA14737 ; LCC:Social Sciences ; LCC:H ; DOAJ:Statistics ; DOAJ:Mathematics and Statistics ; LCC:Statistics ; LCC:HA14737 ; LCC:Social Scien...
Bayesian hierarchical models ; ageperiodcohort models ; prediction ; LCC:Statistics ; LCC:HA14737 ; LCC:Social Sciences ; LCC:H ; DOAJ:Statistics ; DOAJ:Mathematics and Statistics ; LCC:Statistics ; LCC:HA14737 ; LCC:Social Sciences ; LCC:H ; DOAJ:Statistics ; DOAJ:Mathematics and Statistics ; LCC:Statistics ; LCC:HA14737 ; LCC:Social Sciences ; LCC:H ; DOAJ:Statistics ; DOAJ:Mathematics and Statistics ; LCC:Statistics ; LCC:HA14737 ; LCC:Social Sciences ; LCC:H ; DOAJ:Statistics ; DOAJ:Mathematics and Statistics ; LCC:Statistics ; LCC:HA14737 ; LCC:Social Sciences ; LCC:H
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http://www.jstatsoft.org/v21/i08/paper
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3.
Bayesian AgePeriodCohort Modeling and Prediction  BAMP
Title:
Bayesian AgePeriodCohort Modeling and Prediction  BAMP
Author:
Leonhard Held
;
Volker J. Schmid
Leonhard Held
;
Volker J. Schmid
Minimize authors
Description:
The software package BAMP provides a method of analyzing incidence or mortality data on the Lexis diagram, using a Bayesian version of an ageperiodcohort model. A hierarchical model is assumed with a binomial model in the firststage. As smoothing priors for the age, period and cohort parameters random walks of first and second order, with and...
The software package BAMP provides a method of analyzing incidence or mortality data on the Lexis diagram, using a Bayesian version of an ageperiodcohort model. A hierarchical model is assumed with a binomial model in the firststage. As smoothing priors for the age, period and cohort parameters random walks of first and second order, with and without an additional unstructured component are available. Unstructured heterogeneity can also be included in the model. In order to evaluate the model fit, posterior deviance, DIC and predictive deviances are computed. By projecting the random walk prior into the future, future death rates can be predicted.
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4.
Working with the DICOM and NIfTI Data Standards in R
Open Access
Title:
Working with the DICOM and NIfTI Data Standards in R
Author:
Andrew Thorton
;
Volker J. Schmid
;
Brandon Whitcher
Andrew Thorton
;
Volker J. Schmid
;
Brandon Whitcher
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Description:
Two packages, oro.dicom and oro.nifti, are provided for the interaction with and manipulation of medical imaging data that conform to the DICOM standard or ANALYZE/NIfTI formats. DICOM data, from a single file or directory tree, may be uploaded into R using basic data structures: a data frame for the header information and a matrix for the image...
Two packages, oro.dicom and oro.nifti, are provided for the interaction with and manipulation of medical imaging data that conform to the DICOM standard or ANALYZE/NIfTI formats. DICOM data, from a single file or directory tree, may be uploaded into R using basic data structures: a data frame for the header information and a matrix for the image data. A list structure is used to organize multiple DICOM files. The S4 class framework is used to develop basic ANALYZE and NIfTI classes, where NIfTI extensions may be used to extend the fixedbyte NIfTI header. One example of this, that has been implemented, is an XMLbased audit trail tracking the history of operations applied to a data set. The conversion from DICOM to ANALYZE/NIfTI is straightforward using the capabilities of both packages. The S4 classes have been developed to provide a userfriendly interface to the ANALYZE/NIfTI data formats; allowing easy data input, data output, image processing and visualization.
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Publisher:
University of California, Los Angeles
Year of Publication:
20111001T00:00:00Z
Source:
Journal of Statistical Software, Vol 44, Iss 06 (2011)
Journal of Statistical Software, Vol 44, Iss 06 (2011)
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Document Type:
article
Language:
English
Subjects:
export ; imaging ; import ; medical ; visualization. ; LCC:Statistics ; LCC:HA14737 ; LCC:Social Sciences ; LCC:H ; DOAJ:Statistics ; DOAJ:Mathematics and Statistics ; LCC:Statistics ; LCC:HA14737 ; LCC:Social Sciences ; LCC:H ; DOAJ:Statistics ; DOAJ:Mathematics and Statistics ; LCC:Statistics ; LCC:HA14737 ; LCC:Social Sciences ; LCC:H ; LC...
export ; imaging ; import ; medical ; visualization. ; LCC:Statistics ; LCC:HA14737 ; LCC:Social Sciences ; LCC:H ; DOAJ:Statistics ; DOAJ:Mathematics and Statistics ; LCC:Statistics ; LCC:HA14737 ; LCC:Social Sciences ; LCC:H ; DOAJ:Statistics ; DOAJ:Mathematics and Statistics ; LCC:Statistics ; LCC:HA14737 ; LCC:Social Sciences ; LCC:H ; LCC:Statistics ; LCC:HA14737 ; LCC:Social Sciences ; LCC:H ; LCC:Statistics ; LCC:HA14737 ; LCC:Social Sciences ; LCC:H
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5.
Working with the DICOM Data Standard in R Brandon Whitcher Pfizer Worldwide R&D
Open Access
Title:
Working with the DICOM Data Standard in R Brandon Whitcher Pfizer Worldwide R&D
Author:
Volker J. Schmid
;
Andrew Thornton
Volker J. Schmid
;
Andrew Thornton
Minimize authors
Description:
The package oro.dicom facilitates the interaction with and manipulation of medical imaging data that conform to the DICOM standard. DICOM data, from a single file or single directory or directory tree, may be uploaded into R using basic data structures: a data frame for the header information and a matrix for the image data. A list structure is ...
The package oro.dicom facilitates the interaction with and manipulation of medical imaging data that conform to the DICOM standard. DICOM data, from a single file or single directory or directory tree, may be uploaded into R using basic data structures: a data frame for the header information and a matrix for the image data. A list structure is used to organize multiple DICOM files. The conversion from DICOM to ANALYZE/NIfTI is straightforward using the capabilities of oro.dicom and oro.nifti.
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Contributors:
The Pennsylvania State University CiteSeerX Archives
Year of Publication:
20141204
Source:
http://cran.rproject.org/web/packages/oro.dicom/vignettes/dicom.pdf
http://cran.rproject.org/web/packages/oro.dicom/vignettes/dicom.pdf
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Document Type:
text
Language:
en
Subjects:
export ; imaging ; import ; medical ; visualization
export ; imaging ; import ; medical ; visualization
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Rights:
Metadata may be used without restrictions as long as the oai identifier remains attached to it.
Metadata may be used without restrictions as long as the oai identifier remains attached to it.
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http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.463.3573
http://cran.rproject.org/web/packages/oro.dicom/vignettes/dicom.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.463.3573
http://cran.rproject.org/web/packages/oro.dicom/vignettes/dicom.pdf
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6.
Working with the NIfTI Data Standard in R Brandon Whitcher Mango Solutions
Open Access
Title:
Working with the NIfTI Data Standard in R Brandon Whitcher Mango Solutions
Author:
Volker J. Schmid
;
Ludwigmaximilians Universität München
;
Andrew Thornton
Volker J. Schmid
;
Ludwigmaximilians Universität München
;
Andrew Thornton
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Description:
The package oro.nifti facilitates the interaction with and manipulation of medical imaging data that conform to the ANALYZE, NIfTI and AFNI formats. The S4 class framework is used to develop basic ANALYZE and NIfTI classes, where NIfTI extensions may be used to extend the fixedbyte NIfTI header. One example of this, that has been implemented, i...
The package oro.nifti facilitates the interaction with and manipulation of medical imaging data that conform to the ANALYZE, NIfTI and AFNI formats. The S4 class framework is used to develop basic ANALYZE and NIfTI classes, where NIfTI extensions may be used to extend the fixedbyte NIfTI header. One example of this, that has been implemented, is an XMLbased “audit trail ” tracking the history of operations applied to a data set. The conversion from DICOM to ANALYZE/NIfTI is straightforward using the capabilities of oro.dicom. The S4 classes have been developed to provide a userfriendly interface to the ANALYZE/NIfTI data formats; allowing easy data input, data output, image processing and visualization. Keywords:˜export, imaging, import, medical, visualization. 1.
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Year of Publication:
20130724
Source:
http://cran.rproject.org/web/packages/oro.nifti/vignettes/nifti.pdf
http://cran.rproject.org/web/packages/oro.nifti/vignettes/nifti.pdf
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7.
Working with the DICOM Data Standard in R Brandon Whitcher Mango Solutions
Open Access
Title:
Working with the DICOM Data Standard in R Brandon Whitcher Mango Solutions
Author:
Volker J. Schmid
;
Ludwigmaximilians Universität München
;
Andrew Thornton
Volker J. Schmid
;
Ludwigmaximilians Universität München
;
Andrew Thornton
Minimize authors
Description:
The package oro.dicom facilitates the interaction with and manipulation of medical imaging data that conform to the DICOM standard. DICOM data, from a single file or single directory or directory tree, may be uploaded into R using basic data structures: a data frame for the header information and a matrix for the image data. A list structure is ...
The package oro.dicom facilitates the interaction with and manipulation of medical imaging data that conform to the DICOM standard. DICOM data, from a single file or single directory or directory tree, may be uploaded into R using basic data structures: a data frame for the header information and a matrix for the image data. A list structure is used to organize multiple DICOM files. The conversion from DICOM to ANALYZE/NIfTI is straightforward using the capabilities of oro.dicom and oro.nifti. Keywords:˜export, imaging, import, medical, visualization. 1.
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20130724
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http://cran.at.rproject.org/web/packages/oro.dicom/vignettes/dicom.pdf
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8.
resonance
Open Access
Title:
resonance
Author:
Volker J Schmid
;
On Whitcher
;
Guangzhong Yang
Volker J Schmid
;
On Whitcher
;
Guangzhong Yang
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Description:
A Bayesian framework for pharmacokinetic modelling in dynamic contrastenhanced magnetic
A Bayesian framework for pharmacokinetic modelling in dynamic contrastenhanced magnetic
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The Pennsylvania State University CiteSeerX Archives
Year of Publication:
20080701
Source:
http://www.maths.leeds.ac.uk/statistics/workshop/lasr2006/proceedings/
schmid
2.pdf
http://www.maths.leeds.ac.uk/statistics/workshop/lasr2006/proceedings/
schmid
2.pdf
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http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.107.3845
http://www.maths.leeds.ac.uk/statistics/workshop/lasr2006/proceedings/schmid2.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.107.3845
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9.
dcemriS4: A Package for Medical Image Analysis
Open Access
Title:
dcemriS4: A Package for Medical Image Analysis
Author:
Brandon Whitcher
;
Volker J. Schmid
Brandon Whitcher
;
Volker J. Schmid
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Description:
Quantitative analysis of perfusion imaging using dynamic contrastenhanced MRI (DCEMRI) is achieved through a series of processing steps, starting with the raw data acquired from the MRI scanner, and involves a combination of physics, mathematics, engineering and statistics. The purpose of the dcemriS4 package is to provide a collection of func...
Quantitative analysis of perfusion imaging using dynamic contrastenhanced MRI (DCEMRI) is achieved through a series of processing steps, starting with the raw data acquired from the MRI scanner, and involves a combination of physics, mathematics, engineering and statistics. The purpose of the dcemriS4 package is to provide a collection of functions that move the
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Year of Publication:
20110626
Source:
http://cran.at.rproject.org/web/packages/dcemriS4/vignettes/dcemriS4.pdf
http://cran.at.rproject.org/web/packages/dcemriS4/vignettes/dcemriS4.pdf
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http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.193.1327
http://cran.at.rproject.org/web/packages/dcemriS4/vignettes/dcemriS4.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.193.1327
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10.
ABSTRACT Attenuation resilient AIF estimation based on hierarchical
Open Access
Title:
ABSTRACT Attenuation resilient AIF estimation based on hierarchical
Author:
Volker J Schmid
;
Peter D Gatehouse
;
Guangzhong Yang
Volker J Schmid
;
Peter D Gatehouse
;
Guangzhong Yang
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Description:
Bayesian modelling for first pass myocardial perfusion MRI Nonlinear attenuation of the Arterial Input Function (AIF) is a major problem in firstpass MR perfusion imaging due to the high concentration of the contrast agent in the blood pool. This paper presents a technique to reconstruct the true AIF using signal intensities in the myocardium ...
Bayesian modelling for first pass myocardial perfusion MRI Nonlinear attenuation of the Arterial Input Function (AIF) is a major problem in firstpass MR perfusion imaging due to the high concentration of the contrast agent in the blood pool. This paper presents a technique to reconstruct the true AIF using signal intensities in the myocardium and the attenuated AIF based on a Hierarchical Bayesian Model (HBM). With the proposed method, both the AIF and the response function are modeled as smoothed functions by using Bayesian penalty splines (PSplines). The derived AIF is then used to estimate the impulse response of the myocardium based on deconvolution analysis. The proposed technique is validated both with simulated data using the MMID4 model and ten in vivo data sets for estimating myocardial perfusion reserve rates. The results demonstrate the ability of the proposed technique in accurately reconstructing the desired AIF for myocardial perfusion quantification. The method does not involve any MRI pulse sequence modification, and thus is expected to have wider clinical impact. HIERARCHICAL BAYESIAN MODEL We propose a Hierarchical Bayesian Model (HBM) for the reconstruction of the AIF, where both the AIF and the response function are modelled as smoothed functions by using Bayesian penalty splines (PSplines) [2]. Since the information from the myocardium is sparse, a relatively informative prior model is used for the response function. Subsequently, the derived AIF can be used in existing myocardial impulse response estimation techniques based on deconvolution analysis Y signal in myocardial tissue S true contrast conc. intissue f response in myoc. tissue β spline parameters φ smoothness parameters Z signal in LV blood pool A true AIF γ spline parameters ψ smoothness parameters
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Year of Publication:
20080701
Source:
http://pangast.de/
volker
schmid
/media/directory/uploads/6c8349cc7260ae62e3b1396831a8398f.pdf
http://pangast.de/
volker
schmid
/media/directory/uploads/6c8349cc7260ae62e3b1396831a8398f.pdf
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en
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310 Collections of general statistics
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http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.86.7605
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(13) Schmid, Volker J.
(9) The Pennsylvania State University CiteSeerX...
(9) Volker J. Schmid
(4) Brandon Whitcher
(3) Andrew Thornton
(3) Gertheiss, Jan
(3) Ludwigmaximilians Universität München
(3) Schmid, Volker
(3) Sommer, Julia C.
(3) Whitcher, Brandon
(2) Abbaneo, Duccio
(2) Abbas, M
(2) Adam, Wolfgang
(2) Adler, Volker
(2) Affolder, K
(2) Affolder, T
(2) Ageron, Michel
(2) Agram, JeanLaurent
(2) Ahmed, Ijaz
(2) Akhtar, I
(2) Alagoz, Enver
(2) Albergo, Sebastiano
(2) Albert, Eric
(2) Allen, Andrea
(2) Ambroglini, Filippo
(2) Amsler, Claude
(2) Anagnostou, Georgios
(2) Anghel, Ioana Maria
(2) Anttila, Erkki
(2) Avanzini, Carlo
(2) Azzi, Patrizia
(2) Azzurri, Paolo
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(2) Berretta, Luca
(2) Berst, JeanDaniel
(2) Betchart, Burton
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(2) Bianucci, S
(2) Biasini, Maurizio
(2) Bilei, Gian Mario
(2) Bisello, Dario
(2) Blaes, Reiner
(2) Bloch, Christoph
(2) Blum, P
(2) Boccali, Tommaso
(2) Bocci, Andrea
(2) Bock, E
(2) Bonnet, JeanLuc
(2) Bonnevaux, Alain
(2) Borgia, Maria Assunta
(2) Borrello, Laura
(2) Bosi, Filippo
(2) Boudoul, Gaelle
(2) Bouhali, Othmane
(2) Bracci, Fabrizio
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(2) Cardaci, Marco
(2) Cariola, P
(2) Castaldi, Rino
(2) Castello, Roberto
(2) Cattai, Ariella
(2) Cazzola, Ugo
(2) Ceccanti, Marco
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(5) technische reports
(4) imaging
(3) computer science computer vision and pattern...
(3) ddc 500
(3) doaj mathematics and statistics
(3) doaj statistics
(3) lcc h
(3) lcc ha1 4737
(3) lcc social sciences
(3) lcc statistics
(3) statistics methodology
(2) dcemris4
(2) ddc 510
(2) detectors and experimental techniques
(2) diffusion
(2) dynamic
(2) enhanced
(2) export
(2) import
(2) magnetic
(2) medical
(2) physics medical physics
(2) statistics applications
(2) visualization
(1) age period cohort models
(1) asteroseismology
(1) astrophysique
(1) barr body
(1) bayesian hierarchical models
(1) binaries general
(1) biological sciences
(1) biology
(1) chromatin domain
(1) chromosome territory
(1) computational neuroscience
(1) contrast
(1) ct
(1) ddc 000
(1) ddc 350
(1) ddc 570
(1) ddc 610
(1) dermatologic agents administration dosage...
(1) diffusion weighted imaging
(1) dk atira pure core keywords 559922418
(1) dk atira pure core keywords biology
(1) dynamic contrastenhanced magnetic resonance...
(1) ecosystems research
(1) evidence based medicine
(1) functional magnetic resonance imaging
(1) germany
(1) humans
(1) inactive x chromosome
(1) interchromatin compartment
(1) mathematics ddc 500
(1) medizin
(1) prediction
(1) preface 3
(1) psoriasis drug therapy physiopathology
(1) quantitative biology biomolecules
(1) research
(1) research article
(1) resonance
(1) saf a
(1) severity of illness index
(1) stars individual kic5006817
(1) stars rotation
(1) stars solar type
(1) statistics machine learning
(1) sun oscillations
(1) super resolution microscopy
(1) x chromosome inactivation
(1) xist rna
(1) ˜contrast
Subject:
Dewey Decimal Classification (DDC)
(10) Statistics [31*]
(4) Computer science, knowledge & systems [00*]
(2) Life sciences; biology [57*]
(2) Animals (Zoology) [59*]
(2) Medicine & health [61*]
(1) Magazines, journals & serials [05*]
(1) Public administration & military science [35*]
(1) Science [50*]
(1) Plants (Botany) [58*]
(1) Engineering [62*]
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(7) 2011
(6) 2010
(6) 2012
(5) 2008
(5) 2013
(4) 2014
(3) 2007
(1) 1992
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(1) LeibnizOpen
(1) RePEc.org
(1) Bochum Univ. (RUB): Campus Research Bibliography
(1) Lüneburg Univ.: Forschungsindex FOX
(1) Michigan Univ.: Deep Blue
(1) Basel Univ.: edoc
(1) WallonieBruxelles Académie Univ.: DIfusion
(1) Geneva Univ.: Archive ouverte
(1) Manchester Univ.: eScholar Services
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(28) English
(9) Unknown
(1) German
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(20) Text
(7) Article, Journals
(7) Reports, Papers, Lectures
(4) Unknown
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(24) Open Access
(14) Unknown
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