Важная информация
Резюме
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).
Программа
- Week 1 - Introduction
- Week 2 - 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. - Week 3 - 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. - Week 4 - 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 a...
Пользователи
Dr. Elizabeth Sweeney
Rice Academy Postdoctoral Fellow
Biostatistics
Ciprian M. Crainiceanu
Professor
Biostatstics
John Muschelli III
Assistant Scientist
Biostatistics
Разработчик
Платформа
Coursera - это цифровая компания, предлагающая массовые открытые онлайн-курсы, основанные учителями компьютеров Эндрю Нгом и Стэнфордским университетом Дафни Коллер, расположенные в Маунтин-Вью, штат Калифорния.
Coursera работает с ведущими университетами и организациями, чтобы сделать некоторые из своих курсов доступными в Интернете, и предлагает курсы по многим предметам, включая: физику, инженерию, гуманитарные науки, медицину, биологию, социальные науки, математику, бизнес, информатику, цифровой маркетинг, науку о данных и другие предметы.
