Onat
  • Bio
  • Projects
  • Projects
    • Pandas
    • PyTorch
    • scikit-learn
  • Experience
  • Publications
    • Semi-Supervised Learning of MRI Synthesis without Fully-Sampled Ground Truths
    • COVID-19 Detection from Respiratory Sounds with Hierarchical Spectrogram Transformers
    • Unsupervised Medical Image Translation with Adversarial Diffusion Models
    • One Model to Unite Them All: Personalized Federated Learning of Multi-Contrast MRI Synthesis
    • BolT: Fused Window Transformers for fMRI Time Series Analysis
    • Learning Fourier-Constrained Diffusion Bridges for MRI Reconstruction
    • ResViT: Residual Vision Transformers for Multimodal Medical Image Synthesis
  • Blog
    • MRI Clinical Updates and Practical Physics 2024
    • ISMRM 2024
    • M.Sc. Graduation
    • STANFORD
    • 🎉 Publication Alert
    • SPIE 2022
  • Publications
    • An example preprint / working paper
    • An example journal article
    • An example conference paper
  • Recent & Upcoming Talks
    • Example Talk
  • Teaching
    • Learn JavaScript
    • Learn Python

ISMRM 2024

May 8, 2024·
Onat Dalmaz
Onat Dalmaz
· 1 min read

Check out our work “Noise-induced Variability Quantification in Deep Learning-Based MRI Reconstructions” aiming to characterize noise in deep MRI reconstructions, which I presented at Singapore for ISMRM 2024.

Last updated on Nov 9, 2024
Onat Dalmaz
Authors
Onat Dalmaz
Ph.D. Student in Electrical Engineering
← MRI Clinical Updates and Practical Physics 2024 Jul 10, 2024
M.Sc. Graduation Aug 9, 2023 →

© 2024 Me. This work is licensed under CC BY NC ND 4.0

Published with Hugo Blox Builder — the free, open source website builder that empowers creators.