AIMC Topic: Hippocampus
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Identification and cognitive function prediction of Alzheimer's disease based on multivariate pattern analysis of hippocampal volumes.
Journal of Alzheimer's disease : JAD
Nov 25, 2024
BACKGROUND: Alzheimer's disease (AD) is strongly associated with slowly progressive hippocampal atrophy. Elucidating the relationships between local morphometric changes and disease status for early diagnosis could be aided by machine learning algori...
Machine learning localization to identify the epileptogenic side in mesial temporal lobe epilepsy.
Magnetic resonance imaging
Oct 18, 2024
BACKGROUND: Mesial temporal sclerosis (MTS) is the most common pathology associated with drug-resistant mesial temporal lobe epilepsy (mTLE) in adults. Most atrophic hippocampi can be identified using MRI based on standard epilepsy protocols; however...
Graphene Microelectrode Arrays, 4D Structured Illumination Microscopy, and a Machine Learning Spike Sorting Algorithm Permit the Analysis of Ultrastructural Neuronal Changes During Neuronal Signaling in a Model of Niemann-Pick Disease Type C.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Sep 28, 2024
Simultaneously recording network activity and ultrastructural changes of the synapse is essential for advancing understanding of the basis of neuronal functions. However, the rapid millisecond-scale fluctuations in neuronal activity and the subtle su...
Deep learning for contour quality assurance for RTOG 0933: In-silico evaluation.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Aug 31, 2024
PURPOSE: To validate a CT-based deep learning (DL) hippocampal segmentation model trained on a single-institutional dataset and explore its utility for multi-institutional contour quality assurance (QA).
Heatstroke death identification using ATR-FTIR spectroscopy combined with a novel multi-organ machine learning approach.
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Aug 27, 2024
With global warming, the number of deaths due to heatstroke has drastically increased. Nevertheless, there are still difficulties with the forensic assessment of heatstroke deaths, including the absence of particular organ pathological abnormalities ...
Automatic deep learning segmentation of the hippocampus on high-resolution diffusion magnetic resonance imaging and its application to the healthy lifespan.
NMR in biomedicine
Aug 13, 2024
Diffusion tensor imaging (DTI) can provide unique contrast and insight into microstructural changes with age or disease of the hippocampus, although it is difficult to measure the hippocampus because of its comparatively small size, location, and sha...
Fully Automated Hippocampus Segmentation using T2-informed Deep Convolutional Neural Networks.
NeuroImage
Aug 3, 2024
Hippocampal atrophy (tissue loss) has become a fundamental outcome parameter in clinical trials on Alzheimer's disease. To accurately estimate hippocampus volume and track its volume loss, a robust and reliable segmentation is essential. Manual hippo...
Random effects during training: Implications for deep learning-based medical image segmentation.
Computers in biology and medicine
Aug 2, 2024
BACKGROUND: A single learning algorithm can produce deep learning-based image segmentation models that vary in performance purely due to random effects during training. This study assessed the effect of these random performance fluctuations on the re...
DSnet: a new dual-branch network for hippocampus subfield segmentation.
Scientific reports
Jul 3, 2024
The hippocampus is a critical component of the brain and is associated with many neurological disorders. It can be further subdivided into several subfields, and accurate segmentation of these subfields is of great significance for diagnosis and rese...
Bio-inspired computational memory model of the Hippocampus: An approach to a neuromorphic spike-based Content-Addressable Memory.
Neural networks : the official journal of the International Neural Network Society
Jun 20, 2024
The brain has computational capabilities that surpass those of modern systems, being able to solve complex problems efficiently in a simple way. Neuromorphic engineering aims to mimic biology in order to develop new systems capable of incorporating s...
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