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Syed Murtaza Arshad, M.S.

Ph.D. Candidate, Electrical & Computer Engineering

I develop machine learning, deep learning and novel optimization techniques for advanced reconstruction and post-processing of medical images. My doctoral research, funded by NIH Grant R01HL151697, focuses on motion-robust, real-time whole-heart flow MRI. I am co-advised by Rizwan Ahmad and Lee Potter at The Ohio State University. In summer 2025, I completed a research internship with the MR Feature Development team at Canon Medical Research USA (CMRU). I was awarded the Presidential Fellowship 2025-26 and received the Graduate Associate Leadership Award (2024).

News & Updates

Interests & Skills

Research Interests

Image reconstruction Machine learning Deep learning Deep image priors Optimization algorithms Outlier rejection Medical Image Processing 4D flow imaging Real-time imaging

Skills

  • Programming:
    Python MATLAB Java
  • Libraries:
    PyTorch NumPy Optuna OpenCV TensorFlow scikit-learn

Research Projects

Motion-robust 5D MRI GIF

Motion-robust 5D MRI Reconstruction

Integrated expectation-maximization (EM) framework, an unsupervised technique, in 5D MRI reconstruction to correct motion binning errors and reject outliers.

4D Flow Image Reconstruction GIF

Motion-robust 4D Flow Image Reconstruction

Developed a novel optimization technique integrated with outlier rejection for motion-robust reconstruction of 4D flow cardiovascular magnetic resonance images.

4D Flow Image Reconstruction GIF

Motion-robust 3D cine Image Reconstruction

Proposed a novel optimization technique integrated with outlier rejection for motion-robust reconstruction of 3D cine cardiovascular magnetic resonance images.

In-magnet exercise CMR

In-magnet Exercise Cardiovascular MRI

Assessing and validating new CMR protocols and reconstruction frameworks to facilitate assessment of cardiac function during exercise stress using planar, volumetric and flow imaging.

In-magnet exercise CMR

Low-Field 4D flow Cardiac Magnetic Resonance Imaging

Developed new CMR protocols and reconstruction frameworks to facilitate volumetric flow imaging at a low-field scanner.

iSight

iSight: Smart Glasses & Cane for Visually Impaired

Developed a wearable prototype integrating computer vision-based smart glasses and sensor fusion-based smart cane, providing real-time audio guidance to visually impaired individuals for object identification, obstacle avoidance, and navigation.

Publications & Patents

Journal Articles

Preprints

Abstracts

Patents

Talks & Presentations