AIMC Topic: Magnetic Resonance Imaging

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20-fold Accelerated 7T fMRI Using Referenceless Self-Supervised Deep Learning Reconstruction.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
High spatial and temporal resolution across the whole brain is essential to accurately resolve neural activities in fMRI. Therefore, accelerated imaging techniques target improved coverage with high spatio-temporal resolution. Simultaneous multi-slic...

DeepQSMSeg: A Deep Learning-based Sub-cortical Nucleus Segmentation Tool for Quantitative Susceptibility Mapping.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Deep brain nuclei are closely related to the pathogenesis of neurodegenerative diseases. Automatic segmentation for brain nuclei plays a significant role in aging and disease-related assessment. Quantitative susceptibility mapping (QSM), as a novel M...

A CNN and LSTM Network for Eye-Blink Classification from MRI Scanner Monitoring Videos.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Eye closure changes brain activity, so eye-blink tracking of subjects undergoing resting-state functional magnetic resonance imaging (fMRI) is relevant for identifying when a subject blinks, falls asleep, or keeps their eyes closed. Existing MRI eye-...

Learning to Generate Missing Pulse Sequence in MRI using Deep Convolution Neural Network Trained with Visual Turing Test.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Magnetic resonance imaging (MRI) is widely used in clinical applications due to its ability to acquire a wide variety of soft tissues using multiple pulse sequences. Each sequence provides information that generally complements the other. However, fa...

Deep learning model for automatic prostate segmentation on bicentric T2w images with and without endorectal coil.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Automatic segmentation of the prostate on Magnetic Resonance Imaging (MRI) is one of the topics on which research has focused in recent years as it is a fundamental first step in the building process of a Computer aided diagnosis (CAD) system for can...

XCloud-pFISTA: A Medical Intelligence Cloud for Accelerated MRI.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Machine learning and artificial intelligence have shown remarkable performance in accelerated magnetic resonance imaging (MRI). Cloud computing technologies have great advantages in building an easily accessible platform to deploy advanced algorithms...

Nonlinear registration as an effective preprocessing technique for Deep learning based classification of disease.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
A number of machine learning (ML), and particularly in recent years, deep learning (DL) approaches have been proposed for automatic classification of Alzheimer's disease (AD) using brain structural magnetic resonance imaging (MRI) data. However, the ...

Brain Tumors Classification for MR images based on Attention Guided Deep Learning Model.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Magnetic Resonance Imaging (MRI) technology has been widely applied to generate high-resolution images for brain tumor diagnosis. However, manual image reading is very time and labor consuming. Instead, automatic tumor detection based on deep learnin...

Input Agnostic Deep Learning for Alzheimer's Disease Classification Using Multimodal MRI Images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Alzheimer's disease (AD) is a progressive brain disorder that causes memory and functional impairments. The advances in machine learning and publicly available medical datasets initiated multiple studies in AD diagnosis. In this work, we utilize a mu...

Data-Limited Deep Learning Methods for Mild Cognitive Impairment Classification in Alzheimer's Disease Patients.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Mild Cognitive Impairment (MCI) is the stage between the declining of normal brain function and the more serious decline of dementia. Alzheimer's disease (AD) is one of the leading forms of dementia. Although MCI does not always lead to AD, an early ...