AIMC Topic: Brain

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Multi-Level Functional Connectivity Fusion Classification Framework for Brain Disease Diagnosis.

IEEE journal of biomedical and health informatics
Brain disease diagnosis is a new hotspot in the cross research of artificial intelligence and neuroscience. Quantitative analysis of functional magnetic resonance imaging (fMRI) data can provide valuable biomarkers that contributes to clinical diagno...

NPBDREG: Uncertainty assessment in diffeomorphic brain MRI registration using a non-parametric Bayesian deep-learning based approach.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Quantification of uncertainty in deep-neural-networks (DNN) based image registration algorithms plays a critical role in the deployment of image registration algorithms for clinical applications such as surgical planning, intraoperative guidance, and...

Validation of deep learning-based nonspecific estimates for amyloid burden quantification with longitudinal data.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: To validate our previously proposed method of quantifying amyloid-beta (Aβ) load using nonspecific (NS) estimates generated with convolutional neural networks (CNNs) using [F]Florbetapir scans from longitudinal and multicenter ADNI data.

Contrastive machine learning reveals the structure of neuroanatomical variation within autism.

Science (New York, N.Y.)
Autism spectrum disorder (ASD) is highly heterogeneous. Identifying systematic individual differences in neuroanatomy could inform diagnosis and personalized interventions. The challenge is that these differences are entangled with variation because ...

Lag Synchronization of Noisy and Nonnoisy Multiple Neurobiological Coupled FitzHugh-Nagumo Networks with and without Delayed Coupling.

Computational intelligence and neuroscience
This paper presents a methodology for synchronizing noisy and nonnoisy multiple coupled neurobiological FitzHugh-Nagumo (FHN) drive and slave neural networks with and without delayed coupling, under external electrical stimulation (EES), external dis...

Scan-Specific Generative Neural Network for MRI Super-Resolution Reconstruction.

IEEE transactions on medical imaging
The interpretation and analysis of Magnetic resonance imaging (MRI) benefit from high spatial resolution. Unfortunately, direct acquisition of high spatial resolution MRI is time-consuming and costly, which increases the potential for motion artifact...

Deep Diffusion MRI Registration (DDMReg): A Deep Learning Method for Diffusion MRI Registration.

IEEE transactions on medical imaging
In this paper, we present a deep learning method, DDMReg, for accurate registration between diffusion MRI (dMRI) datasets. In dMRI registration, the goal is to spatially align brain anatomical structures while ensuring that local fiber orientations r...

Neuromorphic Time-Multiplexed Reservoir Computing With On-the-Fly Weight Generation for Edge Devices.

IEEE transactions on neural networks and learning systems
The human brain has evolved to perform complex and computationally expensive cognitive tasks, such as audio-visual perception and object detection, with ease. For instance, the brain can recognize speech in different dialects and perform other cognit...

Programming Molecular Systems To Emulate a Learning Spiking Neuron.

ACS synthetic biology
Hebbian theory seeks to explain how the neurons in the brain adapt to stimuli to enable learning. An interesting feature of Hebbian learning is that it is an unsupervised method and, as such, does not require feedback, making it suitable in contexts ...

Deep learning-based automated segmentation of eight brain anatomical regions using head CT images in PET/CT.

BMC medical imaging
OBJECTIVE: We aim to propose a deep learning-based method of automated segmentation of eight brain anatomical regions in head computed tomography (CT) images obtained during positron emission tomography/computed tomography (PET/CT) scans. The brain r...