AIMC Topic: Brain

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The Influence of Brain MRI Defacing Algorithms on Brain-Age Predictions via 3D Convolutional Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
In brain imaging research, it is becoming standard practice to remove the face from the individual's 3D structural MRI scan to ensure data privacy standards are met. Face removal - or 'defacing' - is being advocated for large, multi-site studies wher...

MosaicNet: A deep-learning-based multi-tile biomedical image stitching method.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Multi-tile image stitching aims to merge multiple natural or biomedical images into a single mosaic. This is an essential step in whole-slide imaging and large-scale pathological imaging systems. To tackle this task, a multi-step framework is usually...

A Deep Learning Framework for Skull Stripping in Brain MRI.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Skull-stripping, an important pre-processing step in neuroimage computing, involves the automated removal of non-brain anatomy (such as the skull, eyes, and ears) from brain images to facilitate brain segmentation and analysis. Manual segmentation is...

Fuzzy-Inspired Sensing for Time-Domain Brain Stroke Diagnosis: Disease Retrospective Monitoring Strategy.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
This paper propose a novel disease retrospective monitoring strategy (DRMS) for optimal brain stroke diagnosis. We describe the disease monitoring process using a fuzzy-based model and demonstrate the use of information at different time points to im...

[Research on mild cognitive impairment diagnosis based on Bayesian optimized long-short-term neural network model].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
The recurrent neural network architecture improves the processing ability of time-series data. However, issues such as exploding gradients and poor feature extraction limit its application in the automatic diagnosis of mild cognitive impairment (MCI)...

Machine learning classifiers for electrode selection in the design of closed-loop neuromodulation devices for episodic memory improvement.

Cerebral cortex (New York, N.Y. : 1991)
Successful neuromodulation approaches to alter episodic memory require closed-loop stimulation predicated on the effective classification of brain states. The practical implementation of such strategies requires prior decisions regarding electrode im...

Modern Artificial Neural Networks: Is Evolution Cleverer?

Neural computation
Machine learning tools, particularly artificial neural networks (ANN), have become ubiquitous in many scientific disciplines, and machine learning-based techniques flourish not only because of the expanding computational power and the increasing avai...

Strong Allee Effect Synaptic Plasticity Rule in an Unsupervised Learning Environment.

Neural computation
Synaptic plasticity, or the ability of a brain to change one or more of its functions or structures at the synaptic level, has generated and is still generating a lot of interest from the scientific community especially from neuroscientists. These in...

A high-performance deep-learning-based pipeline for whole-brain vasculature segmentation at the capillary resolution.

Bioinformatics (Oxford, England)
MOTIVATION: Reconstructing and analyzing all blood vessels throughout the brain is significant for understanding brain function, revealing the mechanisms of brain disease, and mapping the whole-brain vascular atlas. Vessel segmentation is a fundament...

[Simulation design and experimental study of magnetic stimulation coil for robot pigeon].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
To explore the feasibility of applying magnetic stimulation technology to the movement control of animal robots, the influence of coil radius, number of turns and other factors on the intensity, depth and focus of magnetic stimulation was simulated a...