BrAInXplore: Automated 3D Delineation and Structural Analysis of Brain MRI Data

Magnetic Resonance Imaging (MRI) is fundamental for the diagnosis of neurological disorders, as by isolating specific regions of the brain allows easier detection of possible anatomical alterations. In recent years, the use of deep learning (DL) approaches spread in clinics for automated and accurate segmentation of brain tissues and structures. This work presents BrAInXplore, a DL-based graphical user interface (GUI) designed for automated anatomical delineation, 3D reconstruction, and qualitative and quantitative brain MRI analysis. The tool integrates a previously developed DL segmentation algorithm into a user-friendly and extensible framework. BrAInXplore is mainly structured in two windows: the main window, which serves as the main application interface, and an operating window, called "3D Viewer", which performs 3D reconstruction of brain tissues and structures from MRI data. The GUI automatically delineates and visualizes in 3D six anatomical components (grey matter, white matter, basal ganglia, cerebellum, ventricles, and brainstem), also providing their volumes. BrAInXplore can handle both labelled and blind input data, depending on whether annotations on brain anatomical components are available or not. The GUI may find application in both research and educational contexts. Moreover, its design ensures extensibility and ease of modification, allowing for future improvements.