Zobrazeno 1 - 10
of 307
pro vyhledávání: '"Afacan, Onur"'
Diffusion-weighted magnetic resonance imaging (DW-MRI) is a powerful, non-invasive tool for detecting and characterizing abdominal lesions to facilitate early diagnosis, but respiratory motion during a scan reduces image quality and accuracy of quant
Externí odkaz:
http://arxiv.org/abs/2409.00798
HAITCH: A Framework for Distortion and Motion Correction in Fetal Multi-Shell Diffusion-Weighted MRI
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 with magnetic field inhomogeneities result in artifacts and data scatt
Externí odkaz:
http://arxiv.org/abs/2406.20042
Quantitative analysis of fetal lung Diffusion-Weighted MRI (DWI) data shows potential in providing quantitative imaging biomarkers that indirectly reflect fetal lung maturation. However, fetal motion during the acquisition hampered quantitative analy
Externí odkaz:
http://arxiv.org/abs/2208.09836
Autor:
Korngut, Noam, Rotman, Elad, Afacan, Onur, Kurugol, Sila, Zaffrani-Reznikov, Yael, Nemirovsky-Rotman, Shira, Warfield, Simon, Freiman, Moti
Intra-voxel incoherent motion (IVIM) analysis of fetal lungs Diffusion-Weighted MRI (DWI) data shows potential in providing quantitative imaging bio-markers that reflect, indirectly, diffusion and pseudo-diffusion for non-invasive fetal lung maturati
Externí odkaz:
http://arxiv.org/abs/2206.03820
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 error-prone manual delineation procedures are aimed to be alleviated by
Externí odkaz:
http://arxiv.org/abs/2205.09601
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 estimation of TK model parameters requires an accurate measurement of
Externí odkaz:
http://arxiv.org/abs/2109.07548
Publikováno v:
In Medical Image Analysis January 2024 91
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 based on deep neural networks have resulted in promising improvements, com
Externí odkaz:
http://arxiv.org/abs/1912.12325
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 reconstruction methods for fast MRI acquisition mostly relied on different regula
Externí odkaz:
http://arxiv.org/abs/1909.00089
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-based MRI reconstruction techniques were suggested to accelerate MR im
Externí odkaz:
http://arxiv.org/abs/1808.02122