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Introduction to Neurohacking In R

Курс от Johns Hopkins University

Средний≈ 17.9 чАнглийский

О курсе

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).

Навыки, которые вы освоите

Magnetic Resonance Imaging R Programming Image Analysis Medical Imaging Scientific Visualization Package and Software Management Data Preprocessing Data Import/Export Data Transformation Data Manipulation Image Quality R (Software)Software Visualization Radiology Data Processing Neurology

Программа курса

4 модулей · 58 учебных материалов

01Introduction5 материалов

Welcome to the Course

Meet the TeamВидео SyllabusЧтение

1.1 Neurohacking and Neuroimaging

IntroductionВидео Structural MRI and RВидео

Theme 1 Quiz

Учитесь у экспертов

Dr. Elizabeth Sweeney

Rice Academy Postdoctoral Fellow

Ciprian M. Crainiceanu

Professor

John Muschelli III

Assistant Scientist

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Обучение на Coursera

≈ 17.9 ч

4 модулей

Язык: Английский

Субтитры: Арабский, Французский, Бенгальский, Украинский, Китайский (Китай), Греческий, Итальянский, Бразильский португальский, Нидерландский, Корейский, Немецкий, Пушту, Урду, Русский, Тайский, Индонезийский, Шведский, Турецкий, Азербайджанский, Испанский, Дари, Хинди, Японский, Казахский, Венгерский, Польский

Introduction to Neurohacking In R

О курсе

Навыки, которые вы освоите

Программа курса

Welcome to the Course

1.1 Neurohacking and Neuroimaging

Theme 1 Quiz

Учитесь у экспертов

Dr. Elizabeth Sweeney

Ciprian M. Crainiceanu

John Muschelli III

2.1 Data Structures and Operations

2.2 The NIfTI Format

2.3 Basic Visualization

2.4 Basic Data Manipulation

2.5 Transformations and Smoothing

2.6 Basic MRI Contrasts

3.1 Preprocessing

3.2 Image Registration: Background

3.3 fslr: System Requirements

3.4 Inhomogeneity Correction using fslr

3.5 Brain Extraction Using fslr

3.6 Image Registration Using fslr

3.7 ANTsR: R Package Wrapper for ANTs

3.8 Basic Data Manipulation with ANTsR

3.9 Pre-Processing with ANTSR

4.1 Image Registration: Extensions

4.2 FSLR Co-Registration

4.3 ANTSR Co-Registration

4.4 Wrapper Functions for Processing Pipelines

4.5 Across-Visit Co-Registration of T1 Images

4.6 Rigid Registration to a Template

4.7 Affine Registration of T1 to Template

4.8 Nonlinear Registration of T1 to Template

4.9 Getting ROI Anatomic Information from Non-Linear Registration

4.10 Tissue-Level Segmentation

Bonus Lesson: Papayar: Interactively Viewing Images in R