similar to: dcemri: A package for medical image analysis

dcemriS4: A package for medical image anlaysis The dcemriS4 package is a major update, and S4 implementation, of the dcemri package.? All previous functionality has been replicated, for DCE-MRI and DWI, with specific emphasis on cancer imaging applications.? Additional major features include: ? o S4 classes for NIfTI and Analyze data formats that merges header and data information o

dcemriS4: A package for medical image anlaysis The dcemriS4 package is a major update, and S4 implementation, of the dcemri package.? All previous functionality has been replicated, for DCE-MRI and DWI, with specific emphasis on cancer imaging applications.? Additional major features include: ? o S4 classes for NIfTI and Analyze data formats that merges header and data information o

I am trying to use the survfit() function with the newdata argument to produce predicted survivor curves for a particular covariate profile. The main purpose of the plot will be to visualise the effect of snp1, coded 0 and 1. In my Cox model I have stratified by one variable, edu, and so I know I will automatically get a separate curve for each strata. My problem is how to deal with the

Dear R users, I am curious to know if someone has connected R with the Insight Segmentation and Registration Toolkit (www.itk.org). From the website... ITK is an open-source, cross-platform system that provides developers with an extensive suite of software tools for image analysis. Developed through extreme programming methodologies, ITK employs leading-edge algorithms for registering and

R-help, I am trying to perform a basic anlaysis of the BreastCancer data from "mlbench" using the svm() function in "e1071". I use the following code library("e1071") library("mlbench") data(BreastCancer) BC <- subset(BreastCancer, select=-Id) pairs(BC) model <- svm(Class ~ ., data=BC, cross=10) ## plot(model, BC, ) tobj <- tune.svm(Class ~ .,

TOP Institute Pharma (TI Pharma) has granted our proposal to set up a mechanism-based PKPD modelling platform. This platform focuses on the transfer of knowledge from academia to the pharmaceutical industry and is a collaborative effort of four excellent academic institutes and six leading global pharmaceutical industries. Unique to this platform is the availability of shared databases on

The first release of "RNiftyReg", an R package for registration (alignment and resampling) of medical images, is now available on CRAN [1]. It may also be useful for other 3D array-like data sets. RNiftyReg is built on top of the NiftyReg library [2], and is written in a mixture of C, C++ and R. It currently supports 3D rigid-body and affine registration, and support for 2D and nonlinear

The first release of "RNiftyReg", an R package for registration (alignment and resampling) of medical images, is now available on CRAN [1]. It may also be useful for other 3D array-like data sets. RNiftyReg is built on top of the NiftyReg library [2], and is written in a mixture of C, C++ and R. It currently supports 3D rigid-body and affine registration, and support for 2D and nonlinear

Dear all, There have been some recent major updates to the TractoR and RNiftyReg packages, which are available for medical image analysis applications. If you use R for these purposes, I hope you will find the updates useful. RNiftyReg is an image registration package, which provides a clean R-like interface to the NiftyReg library developed at University College London [1]. It is aimed at

Dear all, There have been some recent major updates to the TractoR and RNiftyReg packages, which are available for medical image analysis applications. If you use R for these purposes, I hope you will find the updates useful. RNiftyReg is an image registration package, which provides a clean R-like interface to the NiftyReg library developed at University College London [1]. It is aimed at

Dear all, The "tractor.base" package has recently been added to CRAN. This package provides functions to read, write, visualise and manipulate magnetic resonance images. The standard Analyze, NIfTI and DICOM file formats are supported (read-only for DICOM), and all metadata is stored with the image data internally. The code can be used to visualise image slices or maximum intensity

Dear all, The "tractor.base" package has recently been added to CRAN. This package provides functions to read, write, visualise and manipulate magnetic resonance images. The standard Analyze, NIfTI and DICOM file formats are supported (read-only for DICOM), and all metadata is stored with the image data internally. The code can be used to visualise image slices or maximum intensity

Hi, there: As you all know, correlation is not a very robust procedure. Sometimes correlation could be driven by a few outliers. There are a few ways to improve the robustness of correlation (pearson correlation), either by outlier removal procedure, or resampling technique. I am wondering if there is any R package or R code that have incorporated outlier removal or resampling procedure in

Dear R users, Has anyone implemented a "matrix log" function in R similar to the function logm() in Matlab? I did a quick R site search and browsed the contributed packages to no avail. The octave function is far too simplistic and fails for the Matlab test matrix. Ideally, the code of Cheng, Higham, and Laub (2001) or something similar could be utilized. Just checking before I

Magazine: Pharmaceutical Manufacturing Date: Nov/Dec 2009 Title: What Your ICH Q8 Design Space Needs: A Multivariate Predictive Distribution Author: Peterson, John J. Company: GlaxoSmithKline Pharmaceuticals Summary: Multivariate Predicitive distibution quantifies the level of QA in a design space. "Parametric Bootstrapping" can help simplify early analysis and compliment Bayesian

Dear R users, I am looking for code to perform a permutation version of the multivariate two-sample test (difference in means). I am aware of F. Pesarin's book and website, but his single S-Plus function does not work in R (for various reasons). Has anyone adapted (or added to) PermutationTestMeans() so that it does work in R? Or do you know of an alternative implementation that does

The package DICOM is a first attempt at a set of routines to import and summarize medical imaging data that conforms to the DICOM standard. This is now the industry standard for a wide variety of medical imaging equipment (e.g., PET, MRI, CT, etc.). Please see http://medical.nema.org for more information about the DICOM standard. A simple list structure holds the separate header and image

The package DICOM is a first attempt at a set of routines to import and summarize medical imaging data that conforms to the DICOM standard. This is now the industry standard for a wide variety of medical imaging equipment (e.g., PET, MRI, CT, etc.). Please see http://medical.nema.org for more information about the DICOM standard. A simple list structure holds the separate header and image

waveslim 1.4 has recently been uploaded to CRAN and is fully compatible with Rv2.0. Besides ensuring usability with the most recent version of R, two additional "flavors" of wavelet methodology have been added to the package: (1) Hilbert wavelet pairs and (2) the dual-tree complex wavelet transform [only 1D and 2D ported from Matlab code by Selesnick]. The dual-tree CWT code has

waveslim 1.4 has recently been uploaded to CRAN and is fully compatible with Rv2.0. Besides ensuring usability with the most recent version of R, two additional "flavors" of wavelet methodology have been added to the package: (1) Hilbert wavelet pairs and (2) the dual-tree complex wavelet transform [only 1D and 2D ported from Matlab code by Selesnick]. The dual-tree CWT code has