AIMC Topic: Brain

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verified anatomically aware deep learning for real-time electric field simulation.

Journal of neural engineering
Transcranial magnetic stimulation (TMS) has emerged as a prominent non-invasive technique for modulating brain function and treating mental disorders. By generating a high-precision magnetically evoked electric field (E-field) using a TMS coil, it en...

CEST and nuclear Overhauser enhancement imaging with deep learning-extrapolated semisolid magnetization transfer reference: Scan-rescan reproducibility and reliability studies.

Magnetic resonance in medicine
PURPOSE: To develop a novel MR physics-driven, deep-learning, extrapolated semisolid magnetization transfer reference (DeepEMR) framework to provide fast, reliable magnetization transfer contrast (MTC) and CEST signal estimations, and to determine th...

Accuracy of ChatGPT generated diagnosis from patient's medical history and imaging findings in neuroradiology cases.

Neuroradiology
PURPOSE: The noteworthy performance of Chat Generative Pre-trained Transformer (ChatGPT), an artificial intelligence text generation model based on the GPT-4 architecture, has been demonstrated in various fields; however, its potential applications i...

Salient Arithmetic Data Extraction from Brain Activity via an Improved Deep Network.

Sensors (Basel, Switzerland)
Interpretation of neural activity in response to stimulations received from the surrounding environment is necessary to realize automatic brain decoding. Analyzing the brain recordings corresponding to visual stimulation helps to infer the effects of...

Deep learning reconstruction for improving the visualization of acute brain infarct on computed tomography.

Neuroradiology
PURPOSE: This study aimed to investigate the impact of deep learning reconstruction (DLR) on acute infarct depiction compared with hybrid iterative reconstruction (Hybrid IR).

Learning to deep learning: statistics and a paradigm test in selecting a UNet architecture to enhance MRI.

Magma (New York, N.Y.)
OBJECTIVE: This study aims to assess the statistical significance of training parameters in 240 dense UNets (DUNets) used for enhancing low Signal-to-Noise Ratio (SNR) and undersampled MRI in various acquisition protocols. The objective is to determi...

Noise reduction by multiple path neural network using Attention mechanisms with an emphasis on robustness against Errors: A pilot study on brain Diffusion-Weighted images.

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: In deep learning-based noise reduction, larger networks offer advanced and complex functionality by utilizing its greater degree of freedom, but come with increased unpredictability, raising the potential risk of unforeseen errors. Here, we ...

A Semi-Autonomous Stereotactic Brain Biopsy Robotic System With Enhanced Surgical Safety and Surgeon-Robot Collaboration.

IEEE transactions on bio-medical engineering
OBJECTIVE: Despite benefits brought by recent neurosurgical robots, surgical safety and surgeon-robot collaboration remain significant challenges. In this article, we analyze and address these problems in the context of brain biopsy, by proposing a s...

Improved segmentation of basal ganglia from MR images using convolutional neural network with crossover-typed skip connection.

International journal of computer assisted radiology and surgery
PURPOSE: Accurate and automatic segmentation of basal ganglia from magnetic resonance (MR) images is important for diagnosis and treatment of various brain disorders. However, the basal ganglia segmentation is a challenging task because of the class ...

Facemap: a framework for modeling neural activity based on orofacial tracking.

Nature neuroscience
Recent studies in mice have shown that orofacial behaviors drive a large fraction of neural activity across the brain. To understand the nature and function of these signals, we need better computational models to characterize the behaviors and relat...