NINS_QC: A Data Quality Checker in Neuroimaging

Evaluation of data quality always remains labor-intensive, but it is a critical prerequisite in clinical neuroscience research to ensure the reliability and reproducibility of research outcomes. The unavailability of quality control (QC) pipelines on a single platform for multimodal neuroimaging data has been a limiting factor in extensive brain research. Moreover, existing QC pipelines primarily involve MRI-based data only. In this context, we developed a neuroimaging and neurospectroscopy (NINS) QC platform "NINS_QC" for multimodal neuroimaging (MRI, fMRI, DTI, MRS) and neuropsychological data. NINS_QC is a transparent and user-friendly framework that can be distributed as a standalone or in the form of a downloadable executable file. This allows local processing of multimodal neuroimaging data and is well-suited for environments with stringent data privacy requirements. The presence of metrics-based analysis, along with visual-based assessment, has added one more attribute to this platform.