Introducing the oasis R package — a R package implementation of OASIS is Automated Statistical Inference for Segmentation (OASIS) currently hosted on github. The OASIS algorithm takes structural brain MRI studies with a FLAIR, T1, T2, and PD volume from patients with multiple sclerosis (MS) and produces OASIS probability maps of MS lesion presence, which can […]
I added my journal club presentations to a github repo here (mostly so I can find them to reuse): https://github.com/emsweene/journal_club Check it out!
Often, it is desirable to submit the same job to a computing cluster, changing only a few variables each time. For example, you may wish to run a simulation where random variables are generated from the same distribution, but each time with a different seed. Here, we will be generating 100 observations from an exponential distribution […]
This post was inspired by reading the book How to Write a Lot and John Muschelli‘s post on the book, fittingly entitled How to Write a Lot. John provides an excellent summary of the book along with his reflections. Here I share 6 tips for writing that have worked well for me: 1) Don’t outline alone. The […]
Over the past year, I have signed up for over 10 Coursera classes. My research involves working with Neuroimaging data and I want to take Coursera classes in order to learn some of the basics of Neuroscience. I’m tired of being in meetings with collaborators and referring to parts of the brain by frantically […]
Just Kids (Patti Smith). This memoir details the close friendship and rise to fame of the author, singer-songwriter Patti Smith, and photographer Robert Mapplethorpe. The pair met in Brooklyn, New York in the late 1960s. I have to be honest and admit that I only read half the book. I loved the beginning — a […]
## This code reads a dicom image, converts it to a nifit and then writes the nifit file. ## Requires the packages oro.dicom and oro.nifti. ## ## Elizabeth Sweeney ## August 26th 2013 library(oro.dicom) library(oro.nifti) dicom <- readDICOM(‘~/folder’, flipud = FALSE) nifti <- dicom2nifti(dicom) writeNIfTI(nifti, filename = “nifti”, verbose = TRUE, gzipped = TRUE)