Continuous process of using, improving and designing the
simplest open source scripted software that depends on the
minimum number of software platforms and is dedicated to
improving the correctness, responsibility, and speed of
neuroimage data analysis.
A way of doing imaging analysis where data is reproducible.
Reading, writing, plotting, and manipulating neuroimaging data in R.
Interactively explore data with R.
Numbers vary, they change from being small 120 to being
large 200. In addition the color of where the numbers are
located change, from a dark gray to a light grey.
Difference between two images
Take difference between the two and see if there are any changes between the two images.
Want to observe if biologically there are any lesions in the brain and where it is located.
There is a difference in seeing where the damaged tissue is from quantifying where it actually is, meaning where it affects and for providing as useful tool for medical practice.
Why using R?
Free, hackable, one platform for processing and analysis, developed for data analysis, has many developed packages, easy interaction with state-of-the-art neuro-imaging software (FSL, ANTS).
Why Structural MRI?
High spatial resolution
Extensive use in clinical and research practice
Reveals anatomic structure of soft tissues
Sensitive to pathology (e.g., brain cancer, MS lesions)
DICOM (Digital Imaging and Communications in Medicine)
Standardize representation of images (.dcm)
Format of files from scanner or hospital PACS (picture
archiving and Communications system).
Two components: Image data (in pixels) and header (meta-data: information about the data) aka. jpeg with a text file.