dr. I. (Ivana) Isgum
Associate Professor
- Image Sciences Institute
Contact
Biography
Ivana Išgum graduated in Mathematics at the University of Zagreb, Croatia in 1999. The same year she was employed as a scientific software engineer at Silicon Biomedical Instruments BV, The Netherlands. In 2001 she became a PhD student at the Image Sciences Institute. Her PhD degree was obtained in 2007 with a thesis entitled Computer-aided detection and quantification of arterial calcifications with CT. She then worked for a year as a PostDoc at the Laboratory for Clinical and Experimental Image Processing in Leiden University Medical Center on the detection of atherosclerotic carotid plaque from combined magnetic resonance angiography and vessel wall images. Ivana is currently an Associate Professor at UMC Utrecht where she is leading Quantitative Medical Image Analysis (QIA) group at the Image Sciences Institute. QIA group is focusing on the development of algorithms for quantitative analysis of medical images to enable automatic patient diagnosis and prognosis using techniques from the fields of machine learning and deep learning.
Research Output (149)
Automated calcium scores collected during myocardial perfusion imaging improve identification of obstructive coronary artery disease
Dekker Mirthe, Waissi Farahnaz, Bank Ingrid E.M., Lessmann Nikolas, Išgum Ivana, Velthuis Birgitta K., Scholtens Asbjørn M., Leenders Geert E., Pasterkamp Gerard, de Kleijn Dominique P.V., Timmers Leo, Mosterd Arend 1 feb 2020, In: IJC Heart and Vasculature. 26 6 p.
Automatic brain tissue segmentation in fetal MRI using convolutional neural networks
Khalili N., Lessmann N., Turk E., Claessens N., de Heus R., Kolk T., Viergever M. A., Benders M. J. N. L., Isgum I. dec 2019, In: Magnetic Resonance Imaging. 64 , p. 77-89 13 p.
Deep learning analysis of coronary arteries in cardiac CT angiography for detection of patients requiring invasive coronary angiography
Zreik Majd, van Hamersvelt Robbert W, Khalili Nadieh, Wolterink Jelmer M, Voskuil Michiel, Viergever Max A, Leiner Tim, Isgum Ivana 12 nov 2019, In: IEEE Transactions on Medical Imaging. 39 , p. 1545-1557 13 p.
Etidronate halts systemic arterial calcification in pseudoxanthoma elasticum
Bartstra Jonas W., de Jong Pim A., Kranenburg Guido, Wolterink Jelmer M., Isgum Ivana, Wijsman Alayna, Wolf Bas, den Harder Annemarie M., Mali Willem P.Th M., Spiering Wilko 11 okt 2019, In: Atherosclerosis. 292 , p. 37-41 5 p.
Machine learning in cardiovascular magnetic resonance:basic concepts and applications
Leiner Tim, Rueckert Daniel, Suinesiaputra Avan, Baeßler Bettina, Nezafat Reza, Išgum Ivana, Young Alistair A 7 okt 2019, In: Journal of Cardiovascular Magnetic Resonance. 21
Knowledge-based and deep learning-based automated chest wall segmentation in magnetic resonance images of extremely dense breasts
Verburg Erik, Wolterink Jelmer M., de Waard Stephanie N., Išgum Ivana, van Gils Carla H., Veldhuis Wouter B., Gilhuijs Kenneth G.A. 1 okt 2019, In: Medical Physics. 46 , p. 4405-4416 12 p.
Direct Automatic Coronary Calcium Scoring in Cardiac and Chest CT
de Vos Bob D., Wolterink Jelmer M., Leiner Tim, de Jong Pim A., Lessmann Nikolas, Isgum Ivana 1 sep 2019, In: IEEE transactions on medical imaging. 38 , p. 2127-2138 12 p.
Enhancing cardiovascular artificial intelligence (AI) research in the Netherlands:CVON-AI consortium
Benjamins J. W., van Leeuwen K., Hofstra L., Rienstra M., Appelman Y., Nijhof W., Verlaat B., Everts I., den Ruijter H. M., Isgum I., Leiner T., Vliegenthart R., Asselbergs F. W., Juarez-Orozco L. E., van der Harst P. 1 sep 2019, In: Netherlands Heart Journal. 27 , p. 414-425 12 p.
State-of-the-Art Deep Learning in Cardiovascular Image Analysis
Litjens G., Ciompi Francesco, Wolterink Jelmer M., de Vos B. D., Leiner Tim, Teuwen J., Išgum I. 1 aug 2019, In: JACC: Cardiovascular Imaging. 12 , p. 1549-1565 17 p.
Bragatston study protocol:a multicentre cohort study on automated quantification of cardiovascular calcifications on radiotherapy planning CT scans for cardiovascular risk prediction in patients with breast cancer
Emaus Marleen J, Išgum Ivana, van Velzen Sanne G M, van den Bongard H J G Desirée, Gernaat Sofie A M, Lessmann Nikolas, Sattler Margriet G A, Teske Arco J, Penninkhof Joan, Meijer Hanneke, Pignol Jean-Philippe, Verkooijen Helena M, 1 jul 2019, In: BMJ Open. 9