Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Nov 1, 2021
Modeling the rich, dynamic spatiotemporal variations captured by human brain functional magnetic resonance imaging (fMRI) data is a complicated task. Analysis at the brain's regional and connection levels provides more straightforward biological inte...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Nov 1, 2021
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...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Nov 1, 2021
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-...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Nov 1, 2021
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...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Nov 1, 2021
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 ...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Nov 1, 2021
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...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Nov 1, 2021
Cell individualization has a vital role in digital pathology image analysis. Deep Learning is considered as an efficient tool for instance segmentation tasks, including cell individualization. However, the precision of the Deep Learning model relies ...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Nov 1, 2021
The earlier studies on brain vasculature semantic segmentation used classical image analysis methods to extract the vascular tree from images. Nowadays, deep learning methods are widely exploited for various image analysis tasks. One of the strong re...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Nov 1, 2021
Diffusion Tensor Imaging (DTI) is widely used to find brain biomarkers for various stages of brain structural and neuronal development. Processing DTI data requires a detailed Quality Assessment (QA) to detect artifactual volumes amongst a large pool...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Nov 1, 2021
Human big data decoding is of great potential to reveal the complex patterns of human dynamics like physiological and biomechanical signals. In this study, we take special interest in brain visual dynamics, e.g., eye movement signals, and investigate...