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20172024
most citedAutomatic segmentation of the intracranialvolume in fetal MR images

3 citations · 9 across the 7 of their papers we have counts for

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Showing eess.IVShow all

5 papers · 1 filter

eess.IV2021★ 2 cited

Structure-Preserving Multi-Domain Stain Color Augmentation using Style-Transfer with Disentangled Representations

Sophia J. Wagner, Nadieh Khalili, Raghav Sharma +4

In digital pathology, different staining procedures and scanners cause substantial color variations in whole-slide images (WSIs), especially across different laboratories. These co…

eess.IV2019

Combined analysis of coronary arteries and the left ventricular myocardium in cardiac CT angiography for detection of patients with functionally significant stenosis

Majd Zreik, Tim Leiner, Nadieh Khalili +5

Treatment of patients with obstructive coronary artery disease is guided by the functional significance of a coronary artery stenosis. Fractional flow reserve (FFR), measured durin…

eess.IV2019

Automatic brain tissue segmentation in fetal MRI using convolutional neural networks

N. Khalili, N. Lessmann, E. Turk +6

MR images of fetuses allow clinicians to detect brain abnormalities in an early stage of development. The cornerstone of volumetric and morphologic analysis in fetal MRI is segment…

eess.IV2019★ 2 cited

Generative adversarial network for segmentation of motion affected neonatal brain MRI

N. Khalili, E. Turk, M. Zreik +3

Automatic neonatal brain tissue segmentation in preterm born infants is a prerequisite for evaluation of brain development. However, automatic segmentation is often hampered by mot…

eess.IV2019★ 1 cited

Deep learning analysis of coronary arteries in cardiac CT angiography for detection of patients requiring invasive coronary angiography

Majd Zreik, Robbert W. van Hamersvelt, Nadieh Khalili +5

In patients with obstructive coronary artery disease, the functional significance of a coronary artery stenosis needs to be determined to guide treatment. This is typically establi…