Human activities such as food production, mining, transportation, and construction have extensively modified Earth's land and marine environments, causing biodiversity loss, water pollution, soil erosion, and climate change. However, studying spatial...
BACKGROUND: Contour delineation, a crucial process in radiation oncology, is time-consuming and inaccurate due to inter-observer variation has been a critical issue in this process. An atlas-based automatic segmentation was developed to improve the d...
Understanding the basis of brain function requires knowledge of cortical operations over wide spatial scales and the quantitative analysis of brain activity in well-defined brain regions. Matching an anatomical atlas to brain functional data requires...
The efficacy and safety of drugs are widely known to be determined by their interactions with multiple molecules of pharmacological importance, and it is therefore essential to systematically depict the molecular atlas and pharma-information of studi...
Human endogenous retroviruses (HERVs), as remnants of ancient exogenous retrovirus infected and integrated into germ cells, comprise ∼8% of the human genome. These HERVs have been implicated in numerous diseases, and extensive research has been condu...
The central nervous system (CNS) comprises a diverse range of brain cell types with distinct functions and gene expression profiles. Although single-cell RNA sequencing (scRNA-seq) provides new insights into the brain cell atlases, integrating large-...
Translational magnetic resonance imaging of the rodent brain provides invaluable information for preclinical drug development. However, the automated segmentation of such images for quantitative analyses is limited compared to human brain imaging mai...
This study introduces OpenMAP-T1, a deep-learning-based method for rapid and accurate whole-brain parcellation in T1- weighted brain MRI, which aims to overcome the limitations of conventional normalization-to-atlas-based approaches and multi-atlas l...
IEEE transactions on neural networks and learning systems
37339027
Functional connectivity network (FCN) data from functional magnetic resonance imaging (fMRI) is increasingly used for the diagnosis of brain disorders. However, state-of-the-art studies used to build the FCN using a single brain parcellation atlas at...