AIMC Topic: Brain

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Neuromorphic Sentiment Analysis Using Spiking Neural Networks.

Sensors (Basel, Switzerland) Sep 6, 2023
Over the past decade, the artificial neural networks domain has seen a considerable embracement of deep neural networks among many applications. However, deep neural networks are typically computationally complex and consume high power, hindering the...
Humans Neural Networks, Computer Autonomous Vehicles Databases, Factual Sentiment Analysis Brain
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Uncertainty-Aware Multi-Dimensional Mutual Learning for Brain and Brain Tumor Segmentation.

IEEE journal of biomedical and health informatics Sep 6, 2023
Existing segmentation methods for brain MRI data usually leverage 3D CNNs on 3D volumes or employ 2D CNNs on 2D image slices. We discovered that while volume-based approaches well respect spatial relationships across slices, slice-based methods typic...
Uncertainty Brain Neoplasms Image Processing, Computer-Assisted Humans Neural Networks, Computer Brain Reproducibility of Results
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Fast deep learning reconstruction techniques for preclinical magnetic resonance fingerprinting.

NMR in biomedicine Sep 5, 2023
We propose a deep learning (DL) model and a hyperparameter optimization strategy to reconstruct T and T maps acquired with the magnetic resonance fingerprinting (MRF) methodology. We applied two different MRF sequence routines to acquire images of ex...
Image Processing, Computer-Assisted Magnetic Resonance Imaging Brain Deep Learning Magnetic Resonance Spectroscopy Phantoms, Imaging Prospective Studies
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Comparison of four synthetic CT generators for brain and prostate MR-only workflow in radiotherapy.

Radiation oncology (London, England) Sep 5, 2023
BACKGROUND: The interest in MR-only workflows is growing with the introduction of artificial intelligence in the synthetic CT generators converting MR images into CT images. The aim of this study was to evaluate several commercially available sCT gen...
Prostate Pelvis Workflow Tomography, X-Ray Computed Male Artificial Intelligence Brain Humans
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Improved prediction of behavioral and neural similarity spaces using pruned DNNs.

Neural networks : the official journal of the International Neural Network Society Sep 4, 2023
Deep Neural Networks (DNNs) have become an important tool for modeling brain and behavior. One key area of interest has been to apply these networks to model human similarity judgements. Several previous works have used the embeddings from the penult...
Humans Neural Networks, Computer Brain
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Synchronization in STDP-driven memristive neural networks with time-varying topology.

Journal of biological physics Sep 1, 2023
Synchronization is a widespread phenomenon in the brain. Despite numerous studies, the specific parameter configurations of the synaptic network structure and learning rules needed to achieve robust and enduring synchronization in neurons driven by s...
Neural Networks, Computer Brain Neurons Synapses Neuronal Plasticity Models, Neurological
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HybridSNN: Combining Bio-Machine Strengths by Boosting Adaptive Spiking Neural Networks.

IEEE transactions on neural networks and learning systems Sep 1, 2023
Spiking neural networks (SNNs), inspired by the neuronal network in the brain, provide biologically relevant and low-power consuming models for information processing. Existing studies either mimic the learning mechanism of brain neural networks as c...
Neural Networks, Computer Brain Neurons Machine Learning Algorithms
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Deep Learning-Based Versus Iterative Image Reconstruction for Unenhanced Brain CT: A Quantitative Comparison of Image Quality.

Tomography (Ann Arbor, Mich.) Aug 31, 2023
This exploratory retrospective study aims to quantitatively compare the image quality of unenhanced brain computed tomography (CT) reconstructed with an iterative (AIDR-3D) and a deep learning-based (AiCE) reconstruction algorithm. After a preliminar...
Humans Retrospective Studies Brain Tomography, X-Ray Computed Deep Learning Image Processing, Computer-Assisted
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Hierarchical growth in neural networks structure: Organizing inputs by Order of Hierarchical Complexity.

PloS one Aug 31, 2023
Several studies demonstrate that the structure of the brain increases in hierarchical complexity throughout development. We tested if the structure of artificial neural networks also increases in hierarchical complexity while learning a developing ta...
Biological Evolution Brain Neural Networks, Computer Records Computer Simulation
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Geometric evaluations of CT and MRI based deep learning segmentation for brain OARs in radiotherapy.

Physics in medicine and biology Aug 29, 2023
Deep-learning auto-contouring (DL-AC) promises standardisation of organ-at-risk (OAR) contouring, enhancing quality and improving efficiency in radiotherapy. No commercial models exist for OAR contouring based on brain magnetic resonance imaging (MRI...
Organs at Risk Radiotherapy Planning, Computer-Assisted Head and Neck Neoplasms Magnetic Resonance Imaging Retrospective Studies Humans Deep Learning Tomography, X-Ray Computed Brain Image Processing, Computer-Assisted
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