Introduction

Introduction

About Preprocessing

MRI preprocessing involves a series of steps to prepare raw MRI data for analysis. Preprocessing is crucial for enhancing image quality, reducing artifacts, and ensuring consistency across scans.

This process typically includes noise reduction, motion correction, and normalization to align images to a standard space. Key steps may also involve skull stripping to remove non-brain tissues and intensity normalization to standardize signal ranges. For small animals (e.g., rats), common preprocessing steps include bias correction, normalization, registration, and segmentation.

Despite the abundance of resources on human brain MRI preprocessing, similar guides for rats are rare. Therefore, this wiki page aims to provide a comprehensive tutorial on rat brain preprocessing steps, primarily using 3D Slicer along with other supporting software.

##Prerequisites

• Basic understanding of MRI data
• Basic software usage skills

###Advanced Prerequisites

These are not required unless you want to use scripts instead of user interface.

• Basic Python skills

Software

• 3D Slicer -- 3D Slicer ANTs registration extension

General Pipeline

• Slice Plane Orientation Correction -> Rigid registration -> Skull-stripping -> Registration -> Segmentation