Išgum, Ivana

Deep learning techniques for automatic MRI cardiac multi-structures segmentation and diagnosis: is the problem solved?

Bernard, O., Lalande, A., Zotti, C., Cervenansky, F., Yang, X., Heng, P.-A., Cetin, I., Lekadir, K., Camara, O., Gonzalez Ballester, M. A., et al. (2018) · IEEE Transactions on Medical Imaging

Medical Image Segmentation TechniquesCardiac Imaging and Diagnostics

Cited by 2,431

A deep learning framework for unsupervised affine and deformable image registration

de Vos, B. D., Berendsen, F. F., Viergever, M. A., Sokooti, H., Staring, M., & Išgum, I. (2019) · Medical Image Analysis

Medical Image Segmentation TechniquesDomain Adaptation and Few-Shot Learning

Cited by 818

Nonrigid Image Registration Using Multi-scale 3D Convolutional Neural Networks

Sokooti, H., de Vos, B., Berendsen, F., Lelieveldt, B. P. F., Išgum, I., & Staring, M. (2017) · Lecture Notes in Computer Science

Medical Image Segmentation TechniquesAdvanced Radiotherapy Techniques

Cited by 340

Automatic coronary artery calcium scoring in cardiac CT angiography using paired convolutional neural networks

Wolterink, J. M., Leiner, T., de Vos, B. D., van Hamersvelt, R. W., Viergever, M. A., & Išgum, I. (2016) · Medical Image Analysis

Cardiac Imaging and DiagnosticsMedical Image Segmentation Techniques

Cited by 321

Deep Learning for Automatic Calcium Scoring in CT: Validation Using Multiple Cardiac CT and Chest CT Protocols

van Velzen, S. G. M., Lessmann, N., Velthuis, B. K., Bank, I. E. M., van den Bongard, D. H. J. G., Leiner, T., de Jong, P. A., Veldhuis, W. B., Correa, A., Terry, J. G., et al. (2020) · Radiology

Cardiac Imaging and DiagnosticsArtificial Intelligence in Healthcare and Education

Cited by 244

Brain Volumes at Term-Equivalent Age in Preterm Infants: Imaging Biomarkers for Neurodevelopmental Outcome through Early School Age

Keunen, K., Išgum, I., van Kooij, B. J. M., Anbeek, P., van Haastert, I. C., Koopman-Esseboom, C., Fieret-van Stam, P. C., Nievelstein, R. A. J., Viergever, M. A., de Vries, L. S., et al. (2016) · The Journal of Pediatrics

Infant Development and Preterm CareNeonatal and fetal brain pathology

Cited by 132

Quantification of coronary artery calcium in nongated CT to predict cardiovascular events in male lung cancer screening participants: Results of the NELSON study

Takx, R. A. P., Išgum, I., Willemink, M. J., van der Graaf, Y., de Koning, H. J., Vliegenthart, R., Oudkerk, M., Leiner, T., & de Jong, P. A. (2015) · Journal of Cardiovascular Computed Tomography

Cardiac Imaging and DiagnosticsLung Cancer Diagnosis and Treatment

Cited by 75

Delayed cortical gray matter development in neonates with severe congenital heart disease

; on behalf of the Research Group Heart and Brain, Claessens, N. H. P., Moeskops, P., Buchmann, A., Latal, B., Knirsch, W., Scheer, I., Išgum, I., de Vries, L. S., Benders, M. J. N. L., et al. (2016) · Pediatric Research

Congenital Heart Disease StudiesFetal and Pediatric Neurological Disorders

Cited by 66

Multiethnic Exome-Wide Association Study of Subclinical Atherosclerosis

Natarajan, P., Bis, J. C., Bielak, L. F., Cox, A. J., Dörr, M., Feitosa, M. F., Franceschini, N., Guo, X., Hwang, S.-J., Isaacs, A., et al. (2016) · Circulation: Cardiovascular Genetics

Genetic Associations and EpidemiologyAtherosclerosis and Cardiovascular Diseases

Cited by 66

Sex Differences in Coronary Artery and Thoracic Aorta Calcification and Their Association With Cardiovascular Mortality in Heavy Smokers

Lessmann, N., de Jong, P. A., Celeng, C., Takx, R. A. P., Viergever, M. A., van Ginneken, B., & Išgum, I. (2019) · JACC: Cardiovascular Imaging

Cardiac Imaging and DiagnosticsMedical Imaging and Pathology Studies

Cited by 49

Multimodal explainable artificial intelligence identifies patients with non-ischaemic cardiomyopathy at risk of lethal ventricular arrhythmias

Kolk, M. Z. H., Ruipérez-Campillo, S., Allaart, C. P., Wilde, A. A. M., Knops, R. E., Narayan, S. M., Tjong, F. V. Y., DEEP RISK investigators, Raijmakers, F. D., Van Der Lingen, A.-L. C. J., et al. (2024) · Scientific Reports

Cardiac electrophysiology and arrhythmiasECG Monitoring and Analysis

Cited by 49

Automated calcium scores collected during myocardial perfusion imaging improve identification of obstructive coronary artery disease

Dekker, M., Waissi, F., Bank, I. E. M., Lessmann, N., Išgum, I., Velthuis, B. K., Scholtens, A. M., Leenders, G. E., Pasterkamp, G., de Kleijn, D. P. V., et al. (2020) · IJC Heart & Vasculature

Cardiac Imaging and DiagnosticsCoronary Interventions and Diagnostics

Cited by 20