activity
20232025
most citedDenoising Simulated Low-Field MRI (70mT) using Denoising Autoencoders (DAE) and Cycle-Consistent Generative Adversarial Networks (Cycle-GAN)

4 citations · 4 across the 9 of their papers we have counts for

collaborators

9 papers

q-bio.GN2025

Genetic Influences on Brain Aging: Analyzing Sex Differences in the UK Biobank using Structural MRI

Karen Ardila, Aashka Mohite, Abdoljalil Addeh +4

Brain aging trajectories differ between males and females, yet the genetic factors underlying these differences remain underexplored. Using structural MRI and genotyping data from…

eess.IV2025

Direct Estimation of Pediatric Heart Rate Variability from BOLD-fMRI: A Machine Learning Approach Using Dynamic Connectivity

Abdoljalil Addeh, Karen Ardila, Rebecca J Williams +2

In many pediatric fMRI studies, cardiac signals are often missing or of poor quality. A tool to extract Heart Rate Variation (HRV) waveforms directly from fMRI data, without the ne…

eess.IV2024

The Useful Side of Motion: Using Head Motion Parameters to Correct for Respiratory Confounds in BOLD fMRI

Abdoljalil Addeh, G. Bruce Pike, M. Ethan MacDonald

Acquiring accurate external respiratory data during functional Magnetic Resonance Imaging (fMRI) is challenging, prompting the exploration of machine learning methods to estimate r…

cs.LG2024

AI Learning Algorithms: Deep Learning, Hybrid Models, and Large-Scale Model Integration

Noorbakhsh Amiri Golilarz, Elias Hossain, Abdoljalil Addeh +1

In this paper, we discuss learning algorithms and their importance in different types of applications which includes training to identify important patterns and features in a strai…

eess.IV2024

Three-Dimensional Amyloid-Beta PET Synthesis from Structural MRI with Conditional Generative Adversarial Networks

Fernando Vega, Abdoljalil Addeh, M. Ethan MacDonald

Motivation: Alzheimer's Disease hallmarks include amyloid-beta deposits and brain atrophy, detectable via PET and MRI scans, respectively. PET is expensive, invasive and exposes pa…

cs.LG2024

Machine Learning-based Estimation of Respiratory Fluctuations in a Healthy Adult Population using BOLD fMRI and Head Motion Parameters

Abdoljalil Addeh, Fernando Vega, Rebecca J. Williams +2

Motivation: In many fMRI studies, respiratory signals are often missing or of poor quality. Therefore, it could be highly beneficial to have a tool to extract respiratory variation…

eess.IV2023

Amyloid-Beta Axial Plane PET Synthesis from Structural MRI: An Image Translation Approach for Screening Alzheimer's Disease

Fernando Vega, Abdoljalil Addeh, M. Ethan MacDonald

In this work, an image translation model is implemented to produce synthetic amyloid-beta PET images from structural MRI that are quantitatively accurate. Image pairs of amyloid-be…

eess.IV2023★ 4 cited

Denoising Simulated Low-Field MRI (70mT) using Denoising Autoencoders (DAE) and Cycle-Consistent Generative Adversarial Networks (Cycle-GAN)

Fernando Vega, Abdoljalil Addeh, M. Ethan MacDonald

In this work, a denoising Cycle-GAN (Cycle Consistent Generative Adversarial Network) is implemented to yield high-field, high resolution, high signal-to-noise ratio (SNR) Magnetic…

eess.SP2023

Using BOLD-fMRI to Compute the Respiration Volume per Time (RTV) and Respiration Variation (RV) with Convolutional Neural Networks (CNN) in the Human Connectome Development Cohort

Abdoljalil Addeh, Fernando Vega, Rebecca J Williams +3

In many fMRI studies, respiratory signals are unavailable or do not have acceptable quality. Consequently, the direct removal of low-frequency respiratory variations from BOLD sign…