AIMC Topic: Diffusion Magnetic Resonance Imaging
Clear Filters Showing 221 to 230 of 338 articles
Prediction of Microvascular Invasion of Hepatocellular Carcinoma Based on Preoperative Diffusion-Weighted MR Using Deep Learning.
Academic radiology
Dec 7, 2020
RATIONALE AND OBJECTIVES: To investigate the value of diffusion-weighted magnetic resonance imaging for the prediction of microvascular invasion (MVI) of Hepatocellular Carcinoma (HCC) using Convolutional Neural Networks (CNN).
Meningioma Consistency Can Be Defined by Combining the Radiomic Features of Magnetic Resonance Imaging and Ultrasound Elastography. A Pilot Study Using Machine Learning Classifiers.
World neurosurgery
Nov 28, 2020
BACKGROUND: The consistency of meningioma is a factor that may influence surgical planning and the extent of resection. The aim of our study is to develop a predictive model of tumor consistency using the radiomic features of preoperative magnetic re...
Humans
Neural Networks, Computer
Machine Learning
Elasticity Imaging Techniques
Meningeal Neoplasms
Diffusion Magnetic Resonance Imaging
Preoperative Care
Intraoperative Care
Meningioma
Supratentorial Neoplasms
Magnetic Resonance Imaging
Decision Trees
Retrospective Studies
Bayes Theorem
Computational Biology
Female
Male
Aged
Logistic Models
Middle Aged
Support Vector Machine
Pilot Projects
Super-Resolved q-Space deep learning with uncertainty quantification.
Medical image analysis
Oct 26, 2020
Diffusion magnetic resonance imaging (dMRI) provides a noninvasive method for measuring brain tissue microstructure. q-Space deep learning(q-DL) methods have been developed to accurately estimate tissue microstructure from dMRI scans acquired with a ...
Automatic intraprostatic lesion segmentation in multiparametric magnetic resonance images with proposed multiple branch UNet.
Medical physics
Oct 24, 2020
PURPOSE: Contouring intraprostatic lesions is a prerequisite for dose-escalating these lesions in radiotherapy to improve the local cancer control. In this study, a deep learning-based approach was developed for automatic intraprostatic lesion segmen...
Image segmentation of plexiform neurofibromas from a deep neural network using multiple b-value diffusion data.
Scientific reports
Oct 20, 2020
We assessed the accuracy of semi-automated tumor volume maps of plexiform neurofibroma (PN) generated by a deep neural network, compared to manual segmentation using diffusion weighted imaging (DWI) data. NF1 Patients were recruited from a phase II c...
Deep learning-based method for reducing residual motion effects in diffusion parameter estimation.
Magnetic resonance in medicine
Oct 15, 2020
PURPOSE: Conventional motion-correction techniques for diffusion MRI can introduce motion-level-dependent bias in derived metrics. To address this challenge, a deep learning-based technique was developed to minimize such residual motion effects.
Uncertainty modelling in deep learning for safer neuroimage enhancement: Demonstration in diffusion MRI.
NeuroImage
Oct 9, 2020
Deep learning (DL) has shown great potential in medical image enhancement problems, such as super-resolution or image synthesis. However, to date, most existing approaches are based on deterministic models, neglecting the presence of different source...
Machine learning based white matter models with permeability: An experimental study in cuprizone treated in-vivo mouse model of axonal demyelination.
NeuroImage
Oct 6, 2020
The intra-axonal water exchange time (τ), a parameter associated with axonal permeability, could be an important biomarker for understanding and treating demyelinating pathologies such as Multiple Sclerosis. Diffusion-Weighted MRI (DW-MRI) is sensiti...
Classifyber, a robust streamline-based linear classifier for white matter bundle segmentation.
NeuroImage
Sep 23, 2020
Virtual delineation of white matter bundles in the human brain is of paramount importance for multiple applications, such as pre-surgical planning and connectomics. A substantial body of literature is related to methods that automatically segment bun...
Classification of parotid gland tumors by using multimodal MRI and deep learning.
NMR in biomedicine
Sep 4, 2020
Various MRI sequences have shown their potential to discriminate parotid gland tumors, including but not limited to T -weighted, postcontrast T -weighted, and diffusion-weighted images. In this study, we present a fully automatic system for the diagn...
Stay Ahead of Medical AI
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 31032
- Neural Networks, Computer 29717
- Algorithms 26831
- Deep Learning 26345
- Artificial Intelligence 24290
- Robotics 13311
- Image Processing, Computer-Assisted 9521
- Retrospective Studies 9110
- Magnetic Resonance Imaging 6181
- Reproducibility of Results 5592
- Tomography, X-Ray Computed 4770
- Support Vector Machine 4686
- Computational Biology 4236
- Brain 4050
- Computer Simulation 3881
Recent Journals
- Scientific reports 5940
- Sensors (Basel, Switzerland) 4794
- PloS one 4015
- Neural networks : the official journal of the International Neural Network Society 2929
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1854
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1278
- IEEE journal of biomedical and health informatics 1130
- Journal of chemical information and modeling 998
- Nature communications 943
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 861
- Briefings in bioinformatics 853
- IEEE transactions on neural networks and learning systems 826