SWADESH: a multimodal multi-disease brain imaging and neuropsychological database and data analytics platform.

Multimodal neuroimaging data of various brain disorders provides valuable information to understand brain function in health and disease. Various neuroimaging-based databases have been developed that mainly consist of volumetric magnetic resonance imaging (MRI) data. We present the comprehensive web-based neuroimaging platform "SWADESH" for hosting multi-disease, multimodal neuroimaging, and neuropsychological data along with analytical pipelines.

Brain Imaging Databases.

The availability of neuroimaging-based databases is helping immensely to understand the brain function in healthy and diseased conditions. This viewpoint highlights the objectives, commonalities, and differences within these existing databases and pointers for researchers to choose a particular database. We introduce a multimodal multidisease database, SWADESH, and its comparison with the existing databases.

Ultra-Wide Band Gap GaO-on-SiC MOSFETs.

Ultra-wide band gap semiconductor devices based on β-phase gallium oxide (GaO) offer the potential to achieve higher switching performance and efficiency and lower manufacturing cost than that of today's wide band gap power electronics. However, the most critical challenge to the commercialization of GaO electronics is overheating, which impacts the device performance and reliability. We fabricated a GaO/4H-SiC composite wafer using a fusion-bonding method.

PRATEEK: Integration of Multimodal Neuroimaging Data to Facilitate Advanced Brain Research.

Background: In vivo neuroimaging modalities such as magnetic resonance imaging (MRI), functional MRI (fMRI), magnetoencephalography (MEG), magnetic resonance spectroscopy (MRS), and quantitative susceptibility mapping (QSM) are useful techniques to understand brain anatomical structure, functional activity, source localization, neurochemical profiles, and tissue susceptibility respectively. Integrating unique and distinct information from these neuroimaging modalities will further help to enhance the understanding of complex neurological diseases.

Objective: To develop a processing scheme for multimodal data integration in a seamless manner on healthy young population, thus establishing a generalized framework for various clinical conditions (e.

ANSH: Multimodal Neuroimaging Database Including MR Spectroscopic Data From Each Continent to Advance Alzheimer's Disease Research.

Alzheimer's disease (AD) is a devastating neurodegenerative disorder affecting millions of people worldwide. The etiology of AD is not known, and intense research involving multimodal neuroimaging data (e.g.

BRAHMA: Population specific T1, T2, and FLAIR weighted brain templates and their impact in structural and functional imaging studies.

Differences in brain morphology across population groups necessitate creation of population-specific Magnetic Resonance Imaging (MRI) brain templates for interpretation of neuroimaging data. Variations in the neuroanatomy in a genetically heterogeneous population make the development of a population-specific brain template for the Indian subcontinent imperative. A dataset of high-resolution 3D T1, T2-weighted, and FLAIR images acquired from a group of 113 volunteers (M/F - 56/57, mean age-28.