12 citations · 39 across the 14 of their papers we have counts for
15 papers
Primitive Representation Learning for Unsupervised Dynamic Contrast Enhanced MRI Reconstruction
Veronika Spieker, Wenqi Huang, Cemre Ariyurek +5
Reliable quantitative analysis of dynamic contrast-enhanced MRI requires high-quality spatiotemporal reconstructions at high undersampling rates. Scan-specific reconstructions usin…
Vendor-Agnostic Joint Relaxometry and Myelin Water Fraction Mapping with B1 and Motion Correction
Unay Dorken Gallastegi, Shohei Fujita, Yohan Jun +19
Obtaining consistent quantitative maps of myelin content and relaxation times across different sites and vendors is essential for advancing our understanding of brain development.…
MRI Super-Resolution with Deep Learning: A Comprehensive Survey
Mohammad Khateri, Serge Vasylechko, Morteza Ghahremani +9
High-resolution (HR) magnetic resonance imaging (MRI) is crucial for many clinical and research applications. However, achieving it remains costly and constrained by technical trad…
An MRI Atlas of the Human Fetal Brain: Reference and Segmentation Tools for Fetal Brain MRI Analysis
Mahdi Bagheri, Clemente Velasco-Annis, Jian Wang +10
Characterizing in-utero brain development is essential for understanding typical and atypical neurodevelopment. Building on prior spatiotemporal fetal brain MRI atlases, we present…
Rapid, High-resolution and Distortion-free Mapping of Fetal Brain using Multi-echo Radial FLASH and Model-based Reconstruction
Xiaoqing Wang, Hongli Fan, Zhengguo Tan +7
Purpose: To develop a rapid, high-resolution and distortion-free technique for simultaneous water-fat separation, and mapping of the fetal brain at 3T. Methods:…
An Optimized Binning and Probabilistic Slice Sharing Algorithm for Motion Correction in Abdominal DW-MRI
Michelle Su, Cemre Ariyurek, Serge Vasylechko +2
Diffusion-weighted magnetic resonance imaging (DW-MRI) is a powerful, non-invasive tool for detecting and characterizing abdominal lesions to facilitate early diagnosis, but respir…
HAITCH: A Framework for Distortion and Motion Correction in Fetal Multi-Shell Diffusion-Weighted MRI
Haykel Snoussi, Davood Karimi, Onur Afacan +2
Diffusion magnetic resonance imaging (dMRI) is pivotal for probing the microstructure of the rapidly-developing fetal brain. However, fetal motion during scans and its interaction…
IVIM-Morph: Motion-compensated quantitative Intra-voxel Incoherent Motion (IVIM) analysis for functional fetal lung maturity assessment from diffusion-weighted MRI data
Noga Kertes, Yael Zaffrani-Reznikov, Onur Afacan +3
Quantitative analysis of pseudo-diffusion in diffusion-weighted magnetic resonance imaging (DWI) data shows potential for assessing fetal lung maturation and generating valuable im…
qDWI-Morph: Motion-compensated quantitative Diffusion-Weighted MRI analysis for fetal lung maturity assessment
Yael Zaffrani-Reznikov, Onur Afacan, Sila Kurugol +2
Quantitative analysis of fetal lung Diffusion-Weighted MRI (DWI) data shows potential in providing quantitative imaging biomarkers that indirectly reflect fetal lung maturation. Ho…
SUPER-IVIM-DC: Intra-voxel incoherent motion based Fetal lung maturity assessment from limited DWI data using supervised learning coupled with data-consistency
Noam Korngut, Elad Rotman, Onur Afacan +5
Intra-voxel incoherent motion (IVIM) analysis of fetal lungs Diffusion-Weighted MRI (DWI) data shows potential in providing quantitative imaging bio-markers that reflect, indirectl…
CORPS: Cost-free Rigorous Pseudo-labeling based on Similarity-ranking for Brain MRI Segmentation
Can Taylan Sari, Sila Kurugol, Onur Afacan +1
Segmentation of brain magnetic resonance images (MRI) is crucial for the analysis of the human brain and diagnosis of various brain disorders. The drawbacks of time-consuming and e…
Learning the Regularization in DCE-MR Image Reconstruction for Functional Imaging of Kidneys
Aziz Koçanaoğulları, Cemre Ariyurek, Onur Afacan +1
Kidney DCE-MRI aims at both qualitative assessment of kidney anatomy and quantitative assessment of kidney function by estimating the tracer kinetic (TK) model parameters. Accurate…
ODE-based Deep Network for MRI Reconstruction
Ali Pour Yazdanpanah, Onur Afacan, Simon K. Warfield
Fast data acquisition in Magnetic Resonance Imaging (MRI) is vastly in demand and scan time directly depends on the number of acquired k-space samples. The data-driven methods base…
Deep Plug-and-Play Prior for Parallel MRI Reconstruction
Ali Pour Yazdanpanah, Onur Afacan, Simon K. Warfield
Fast data acquisition in Magnetic Resonance Imaging (MRI) is vastly in demand and scan time directly depends on the number of acquired k-space samples. Conventional MRI reconstruct…
Non-Learning based Deep Parallel MRI Reconstruction (NLDpMRI)
Ali Pour Yazdanpanah, Onur Afacan, Simon K. Warfield
Fast data acquisition in Magnetic Resonance Imaging (MRI) is vastly in demand and scan time directly depends on the number of acquired k-space samples. Recently, the deep learning-…