Publications by authors named "Kei Kamiya"
Segmentation and Volume Estimation of the Habenula Using Deep Learning in Patients With Depression.
Biol Psychiatry Glob Open Sci
July 2024
Background: The habenula is involved in the pathophysiology of depression. However, its small structure limits the accuracy of segmentation methods, and the findings regarding its volume have been inconsistent. This study aimed to create a highly accurate habenula segmentation model using deep learning, test its generalizability to clinical magnetic resonance imaging, and examine differences between healthy participants and patients with depression.
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- - This study focuses on creating a prediction model for amyloid-beta deposition in Alzheimer's disease using advanced MRI techniques and diverse patient data, including those with various cognitive disorders and healthy controls.
- - The research utilized a data-driven algorithm analyzing structural MR images, cognitive test results, and apolipoprotein E status, achieving an impressive accuracy of 89.8% in detecting amyloid-beta positivity.
- - The findings suggest that a specific gray matter volume pattern related to Alzheimer's significantly impacts prediction accuracy, highlighting the potential of MRI-based machine learning as a diagnostic tool for various neurological and psychiatric conditions.
Aim: Healthy older drivers may be at high risk of fatal traffic accidents. Our recent study showed that volumetric alterations in gray matter in the brain regions within the dorsal attention network (DAN) were strongly related to the risk of unsafe driving in healthy older people. However, the relationship between white matter (WM) structural connectivity and driving ability in healthy older people is still unclear.
View Article and Find Full Text PDFAim: Parents have significant genetic and environmental influences, which are known as intergenerational effects, on the cognition, behavior, and brain of their offspring. These intergenerational effects are observed in patients with mood disorders, with a particularly strong association of depression between mothers and daughters. The main purpose of our study was to investigate female-specific intergenerational transmission patterns in the human brain among patients with depression and their never-depressed offspring.
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- Traffic accidents involving older drivers are on the rise, with many being cognitively normal, highlighting the need to identify those at high risk of causing fatal accidents.
- A study enrolled 32 healthy older individuals to assess their driving abilities using an on-road test and machine learning techniques, leading to an 87.5% accuracy in classifying safe versus unsafe drivers.
- Key cortical regions linked to attention, decision making, and working memory were identified as crucial factors in unsafe driving behavior among older adults.