Nadieh Khalili

According to our database, Nadieh Khalili authored at least 11 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Uncertainty-guided annotation enhances segmentation with the human-in-the-loop.

Nadieh Khalili, Joey Spronck, Francesco Ciompi, Jeroen van der Laak, Geert Litjens

CoRR, 2024

2021

Structure-Preserving Multi-domain Stain Color Augmentation Using Style-Transfer with Disentangled Representations.

Sophia J. Wagner, Nadieh Khalili, Raghav Sharma, Melanie Boxberg, Carsten Marr, Walter de Back, Tingying Peng

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

2020

Machine learning for automatic segmentation of neonatal and fetal MR brain images.

Nadieh Khalili

PhD thesis, 2020

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, Jelmer M. Wolterink, Michiel Voskuil, Max A. Viergever, Tim Leiner, Ivana Isgum

IEEE Trans. Medical Imaging, 2020

2019

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, Robbert W. van Hamersvelt, Jelmer M. Wolterink, Michiel Voskuil, Max A. Viergever, Ivana Isgum

CoRR, 2019

Automatic brain tissue segmentation in fetal MRI using convolutional neural networks.

Nadieh Khalili, Nikolas Leßmann, Elise Turk, Nathalie H. P. Claessens, R. de Heus, T. Kolk, Max A. Viergever, Manon J. N. L. Benders, Ivana Isgum

CoRR, 2019

Deep learning analysis of cardiac CT angiography for detection of coronary arteries with functionally significant stenosis.

Majd Zreik, Robbert W. van Hamersvelt, Nadieh Khalili, Jelmer M. Wolterink, Michiel Voskuil, Max A. Viergever, Tim Leiner, Ivana Isgum

CoRR, 2019

Convolutional Neural Network-Based Regression for Quantification of Brain Characteristics Using MRI.

João Fernandes, Victor Alves, Nadieh Khalili, Manon J. N. L. Benders, Ivana Isgum, Josien P. W. Pluim, Pim Moeskops

Proceedings of the New Knowledge in Information Systems and Technologies, 2019

Generative Adversarial Network for Segmentation of Motion Affected Neonatal Brain MRI.

Nadieh Khalili, Elise Turk, Majd Zreik, Max A. Viergever, Manon J. N. L. Benders, Ivana Isgum

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

2017

Automatic segmentation of the intracranialvolume in fetal MR images.

Nadieh Khalili, Pim Moeskops, Nathalie H. P. Claessens, S. Scherpenzeel, Elise Turk, R. de Heus, Manon J. N. L. Benders, Max A. Viergever, Josien P. W. Pluim, Ivana Isgum

CoRR, 2017

Automatic Segmentation of the Intracranial Volume in Fetal MR Images.

Nadieh Khalili, Pim Moeskops, Nathalie H. P. Claessens, S. Scherpenzeel, Elise Turk, R. de Heus, Manon J. N. L. Benders, Max A. Viergever, Josien P. W. Pluim, Ivana Isgum

Proceedings of the Fetal, Infant and Ophthalmic Medical Image Analysis, 2017