YoVDO

Introduction to Neurohacking In R

Offered By: Johns Hopkins University via Coursera

Tags

Programming Courses R Programming Courses

Course Description

Overview

Neurohacking describes how to use the R programming language (https://cran.r-project.org/) and its associated package to perform manipulation, processing, and analysis of neuroimaging data. We focus on publicly-available structural magnetic resonance imaging (MRI). We discuss concepts such as inhomogeneity correction, image registration, and image visualization. By the end of this course, you will be able to: Read/write images of the brain in the NIfTI (Neuroimaging Informatics Technology Initiative) format Visualize and explore these images Perform inhomogeneity correction, brain extraction, and image registration (within a subject and to a template).

Syllabus

  • Introduction
  • Neuroimaging: Formats and Visualization
    • In this section, we will discuss different formats that brain images come in, as well as some of the commonly done magnetic resonance imaging (MRI) scans.
  • Image Processing
    • In this section, we will discuss the steps done to process brain MRI data. We will discuss inhomogeneity correction, brain extraction or skull stripping, and various image registration techniques.
  • Extended Image Processing
    • In this section, we will discuss the different types of registration and how one would go through processing a multi-sequence MRI scan, as well as wrapper functions that make the process much easier. We also cover interactive exploration of brain image data and tissue-level (white/gray matter and cerebrospinal fluid (CSF)) segmentation from a T1-weighted image.

Taught by

Dr. Elizabeth Sweeney , Ciprian M. Crainiceanu and John Muschelli III

Tags

Related Courses

Statistics One
Princeton University via Coursera
Introduction to Computational Finance and Financial Econometrics
University of Washington via Coursera
Curso Práctico de Bioestadística con R
Universidad San Pablo CEU via Miríadax
Análisis Estadístico de datos con R
Universidad Católica de Murcia via Miríadax
Data Analysis with R
Facebook via Udacity