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Magnetic Resonance Spectroscopy

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Non-destructive classification of unlabeled cells: Combining an automated benchtop magnetic resonance scanner and artificial intelligence.

PLoS computational biology
In order to treat degenerative diseases, the importance of advanced therapy medicinal products has increased in recent years. The newly developed treatment strategies require a rethinking of the appropriate analytical methods. Current standards are m...

Deep learning-based accurate delineation of primary gross tumor volume of nasopharyngeal carcinoma on heterogeneous magnetic resonance imaging: A large-scale and multi-center study.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: The problem of obtaining accurate primary gross tumor volume (GTVp) segmentation for nasopharyngeal carcinoma (NPC) on heterogeneous magnetic resonance imaging (MRI) images with deep learning remains unsolved. Herein, we repor...

Application of fuzzy algorithms in conjunction with H-NMR spectroscopy to differentiate alcoholic beverages.

Journal of the science of food and agriculture
BACKGROUND: Recent statistics from the European Commission indicate that wine is one of the commodities most commonly subject to food fraud. In this context, the development of reliable classification models to differentiate alcoholic beverages requi...

Deep-Learning-Based Contrast Synthesis From MRF Parameter Maps in the Knee Joint.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Magnetic resonance fingerprinting (MRF) is a method to speed up acquisition of quantitative MRI data. However, MRF does not usually produce contrast-weighted images that are required by radiologists, limiting reachable total scan time imp...

An accurate and time-efficient deep learning-based system for automated segmentation and reporting of cardiac magnetic resonance-detected ischemic scar.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Myocardial infarction scar (MIS) assessment by cardiac magnetic resonance provides prognostic information and guides patients' clinical management. However, MIS segmentation is time-consuming and not performed routinely. Th...

A Bibliometric Review: Brain Tumor Magnetic Resonance Imagings Using Different Convolutional Neural Network Architectures.

World neurosurgery
BACKGROUND: Numerous scientists and researchers have been developing advanced procedures and methods for diagnosing the kind and phase of a human tumor. Brain tumors, which are neoplastic and abnormal developments of brain cells, are one of the most ...

NMR spectrum reconstruction as a pattern recognition problem.

Journal of magnetic resonance (San Diego, Calif. : 1997)
A new deep neural network based on the WaveNet architecture (WNN) is presented, which is designed to grasp specific patterns in the NMR spectra. When trained at a fixed non-uniform sampling (NUS) schedule, the WNN benefits from pattern recognition of...

Scalable graph neural network for NMR chemical shift prediction.

Physical chemistry chemical physics : PCCP
Graph neural networks (GNNs) have been proven effective in the fast and accurate prediction of nuclear magnetic resonance (NMR) chemical shifts of a molecule. Existing methods, despite their effectiveness, suffer from high space complexity and are th...

Natural language processing for identification of hypertrophic cardiomyopathy patients from cardiac magnetic resonance reports.

BMC medical informatics and decision making
BACKGROUND: Cardiac magnetic resonance (CMR) imaging is important for diagnosis and risk stratification of hypertrophic cardiomyopathy (HCM) patients. However, collection of information from large numbers of CMR reports by manual review is time-consu...

Rapid protein assignments and structures from raw NMR spectra with the deep learning technique ARTINA.

Nature communications
Nuclear Magnetic Resonance (NMR) spectroscopy is a major technique in structural biology with over 11,800 protein structures deposited in the Protein Data Bank. NMR can elucidate structures and dynamics of small and medium size proteins in solution, ...