Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved?
2018 · IEEE Transactions on Medical Imaging · 2,134 citations
https://doi.org/10.1109/tmi.2018.2837502
I
Ivana Išgum
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Ivana Išgum is an academic researcher from Radboud University Nijmegen. The author has contributed to research in topics: Cardiac Imaging and Diagnostics & Advanced X-ray and CT Imaging & Medical Imaging Techniques and Applications. The author has an h-index of 64, co-authored 291 publications.
ORCID: 0000-0003-1869-5034Papers by this author
worksDeep MR to CT Synthesis Using Unpaired Data
2017 · Lecture notes in computer science · 569 citations
https://doi.org/10.1007/978-3-319-68127-6_2
Deep Learning for Automatic Calcium Scoring in CT: Validation Using Multiple Cardiac CT and Chest CT Protocols
2020 · Radiology · 226 citations
https://doi.org/10.1148/radiol.2020191621
Comparing coronary artery calcium and thoracic aorta calcium for prediction of all-cause mortality and cardiovascular events on low-dose non-gated computed tomography in a high-risk population of heavy smokers
2009 · Atherosclerosis · 134 citations
https://doi.org/10.1016/j.atherosclerosis.2009.09.031
Brain Volumes at Term-Equivalent Age in Preterm Infants: Imaging Biomarkers for Neurodevelopmental Outcome through Early School Age
2016 · The Journal of Pediatrics · 131 citations
https://doi.org/10.1016/j.jpeds.2015.12.023
Automated Coronary Artery Calcification Scoring in Non-Gated Chest CT: Agreement and Reliability
2014 · PLoS ONE · 128 citations
https://doi.org/10.1371/journal.pone.0091239
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