ABSTRACT
In neuroimaging, preprocessing typically refers to the set of operations or steps following image data acquisition, which involve image and signal processing procedures designed to denoise, clean and normalize data for subsequent analysis, thereby improving the quality of results (e.g., for details with functional Magnetic Resonance Imaging (fMRI) see (147) and Chapter 6). As shown in Figure 10.1, neuroimaging studies can be thought of as an experimental pipeline with decisions made at multiple stages, from subject selection through data analysis, including the evaluation of pipeline efficacy using performance metrics. The preprocessing of neuroimaging data occurs at stage 4 within this pipeline; moreover, this stage can be considered a “sub-pipeline”, in which multiple preprocessing decisions are made.
