Academic Background It is widely recognized that the cognitive function of patients with high-grade glioma is affected by the location and volume of the tumor. However, research on how to accurately predict individual patients’ cognitive function for personalized treatment decisions before and after surgery remains limited. Currently, most studies ...
Neuroinformatics Research: 3D Modeling of Neuroanatomy with Multi-Camera System Academic Background The surgical anatomy of the central nervous system, including the skull and spine, has an extremely complex three-dimensional (3D) structure, making it difficult for learners to fully understand the intricate relationships between various structures....
MRQA: Addressing the Widespread Problem of MRI Protocol Non-Compliance Background In recent years, large-scale neuroimaging datasets have played a crucial role in studying brain-behavior relationships, such as the Alzheimer’s Disease Neuroimaging Initiative (ADNI), Human Connectome Project (HCP), and Adolescent Brain Cognitive Development (ABCD) st...
Image Classification Based on Bayesian Tensor Modeling for Alzheimer’s Disease Introduction Neuroimaging research is a crucial component of contemporary neuroscience, significantly enhancing our understanding of brain structure and function. Through these non-invasive visualization techniques, researchers can more accurately predict the risk of cer...
Identifying Diagnostic Biomarkers for Autism Spectrum Disorder using the PED Algorithm In the field of neuroinformatics, research on Autism Spectrum Disorder (ASD) predominantly focuses on the bidirectional connectivity between brain regions, with fewer studies addressing higher-order interaction anomalies among brain regions. To explore the comple...
Using fMRI to Guide TMS Target Selection: Reliability and Sensitivity of 3T and 1.5T fMRI Metrics [DOI: 10.1007/s12021-024-09667-5], published in Neuroinformatics Background Introduction The early application of functional magnetic resonance imaging (fMRI) mainly focused on inferring cognitive processes. However, modern medicine is gradually extend...
Research Report on the Enhanced Spatial Fuzzy C-Means Algorithm for Brain Tissue Segmentation Academic Background Magnetic Resonance Imaging (MRI) plays a vital role in neurology, particularly in the precise segmentation of brain tissue. Accurate tissue segmentation is crucial for diagnosing brain injuries and neurodegenerative diseases. Segmenting...
MRIO: A Magnetic Resonance Imaging Acquisition and Analysis Ontology Magnetic Resonance Imaging (MRI) is a biomedical imaging technology used to non-invasively visualize internal structures of tissues in three-dimensional space. MRI is widely used in studying the structure and function of the human brain and is a powerful tool for diagnosing neurol...
Gender Differences in Acute Axonal Pathology Following Experimental Concussion Academic Background Each year, approximately 50 million people worldwide suffer from concussions, also known as mild traumatic brain injuries (TBI). However, for more than 15% of patients, this “mild” brain injury can lead to lasting neurocognitive dysfunction. The exist...
Neurohackademy: Combining Online and Offline Neurological Informatics Education Background Introduction In recent years, human neuroscience has entered an era of big data. Due to initiatives like the Human Connectome Project and the Adolescent Brain Cognitive Development (ABCD) study, scientists have acquired datasets of previously unimaginable sca...