AIMC Topic: Magnetic Resonance Imaging

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Classification of Task-State fMRI Data Based on Circle-EMD and Machine Learning.

Computational intelligence and neuroscience
In the research work of the brain-computer interface and the function of human brain work, the state classification of multitask state fMRI data is a problem. The fMRI signal of the human brain is a nonstationary signal with many noise effects and in...

Probing the neural dynamics of mnemonic representations after the initial consolidation.

NeuroImage
Memories are not stored as static engrams, but as dynamic representations affected by processes occurring after initial encoding. Previous studies revealed changes in activity and mnemonic representations in visual processing areas, parietal lobe, an...

Deep adaptive registration of multi-modal prostate images.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Artificial intelligence, especially the deep learning paradigm, has posed a considerable impact on cancer imaging and interpretation. For instance, fusing transrectal ultrasound (TRUS) and magnetic resonance (MR) images to guide prostate cancer biops...

Predictive Modeling of NMR Chemical Shifts without Using Atomic-Level Annotations.

Journal of chemical information and modeling
Recently, machine learning has been successfully applied to the prediction of nuclear magnetic resonance (NMR) chemical shifts. To build a prediction model, the existing methods require a training data set that comprises molecules whose NMR-active at...

MRI-guided lumbar spinal injections with body-mounted robotic system: cadaver studies.

Minimally invasive therapy & allied technologies : MITAT : official journal of the Society for Minimally Invasive Therapy
INTRODUCTION: This paper reports the system integration and cadaveric assessment of a body-mounted robotic system for MRI-guided lumbar spine injections. The system is developed to enable MR-guided interventions in closed bore magnet and avoid proble...

Deep learning using preoperative magnetic resonance imaging information to predict early recovery of urinary continence after robot-assisted radical prostatectomy.

International journal of urology : official journal of the Japanese Urological Association
OBJECTIVES: To investigate whether a deep learning model from magnetic resonance imaging information is an accurate method to predict the risk of urinary incontinence after robot-assisted radical prostatectomy.

Soft Tissue Sarcoma: Preoperative MRI-Based Radiomics and Machine Learning May Be Accurate Predictors of Histopathologic Grade.

AJR. American journal of roentgenology
The purpose of this study was to assess the value of radiomics features for differentiating soft tissue sarcomas (STSs) of different histopathologic grades. The T1-weighted and fat-suppressed T2-weighted MR images of 70 STSs of varying grades (35 l...

IKWI-net: A cross-domain convolutional neural network for undersampled magnetic resonance image reconstruction.

Magnetic resonance imaging
Magnetic resonance imaging (MRI) is widely used to get the information of anatomical structure and physiological function with the advantages of high resolution and non-invasive scanning. But the long acquisition time limits its application. To reduc...

Machine Learning for Brain Stroke: A Review.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Machine Learning (ML) delivers an accurate and quick prediction outcome and it has become a powerful tool in health settings, offering personalized clinical care for stroke patients. An application of ML and Deep Learning in health care is growing ho...

Experimentally revealed stochastic preferences for multicomponent choice options.

Journal of experimental psychology. Animal learning and cognition
Realistic, everyday rewards contain multiple components. An apple has taste and size. However, we choose in single dimensions, simply preferring some apples to others. How can such single-dimensional preference relationships refer to multicomponent c...