AIMC Topic: Brain

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NeoSLAM: Long-Term SLAM Using Computational Models of the Brain.

Sensors (Basel, Switzerland)
Simultaneous Localization and Mapping (SLAM) is a fundamental problem in the field of robotics, enabling autonomous robots to navigate and create maps of unknown environments. Nevertheless, the SLAM methods that use cameras face problems in maintaini...

Deep learning-assisted mass spectrometry imaging for preliminary screening and pre-classification of psychoactive substances.

Talanta
Currently, it is of great urgency to develop a rapid pre-classification and screening method for suspected drugs as the constantly springing up of new psychoactive substances. In most researches, psychoactive substances classification approaches depe...

White matter diffusion estimates in obsessive-compulsive disorder across 1653 individuals: machine learning findings from the ENIGMA OCD Working Group.

Molecular psychiatry
White matter pathways, typically studied with diffusion tensor imaging (DTI), have been implicated in the neurobiology of obsessive-compulsive disorder (OCD). However, due to limited sample sizes and the predominance of single-site studies, the gener...

Safety and efficacy of frameless stereotactic robot-assisted intraparenchymal brain lesion biopsies versus image-guided biopsies: a bicentric comparative study.

Acta neurochirurgica
PURPOSE: User-friendly robotic assistance and image-guided tools have been developed in the past decades for intraparenchymal brain lesion biopsy. These two methods are gradually becoming well accepted and are performed at the discretion of the neuro...

NPB-REC: A non-parametric Bayesian deep-learning approach for undersampled MRI reconstruction with uncertainty estimation.

Artificial intelligence in medicine
The ability to reconstruct high-quality images from undersampled MRI data is vital in improving MRI temporal resolution and reducing acquisition times. Deep learning methods have been proposed for this task, but the lack of verified methods to quanti...

Phase Aberration Correction for In Vivo Ultrasound Localization Microscopy Using a Spatiotemporal Complex-Valued Neural Network.

IEEE transactions on medical imaging
Ultrasound Localization Microscopy (ULM) can map microvessels at a resolution of a few micrometers ( [Formula: see text]). Transcranial ULM remains challenging in presence of aberrations caused by the skull, which lead to localization errors. Herein,...

Two is better than one: longitudinal detection and volumetric evaluation of brain metastases after Stereotactic Radiosurgery with a deep learning pipeline.

Journal of neuro-oncology
PURPOSE: Close MRI surveillance of patients with brain metastases following Stereotactic Radiosurgery (SRS) treatment is essential for assessing treatment response and the current disease status in the brain. This follow-up necessitates the compariso...

Assessment of brain tumor detection techniques and recommendation of neural network.

Biomedizinische Technik. Biomedical engineering
OBJECTIVES: Brain tumor classification is amongst the most complex and challenging jobs in the computer domain. The latest advances in brain tumor detection systems (BTDS) are presented as they can inspire new researchers to deliver new architectures...

Unraveling motor imagery brain patterns using explainable artificial intelligence based on Shapley values.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Motor imagery (MI) based brain-computer interfaces (BCIs) are widely used in rehabilitation due to the close relationship that exists between MI and motor execution (ME). However, the underlying brain mechanisms of MI remain...