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ORCIDEce Ozkan
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2020 – today
- 2024
[j3]Hanna Ragnarsdóttir, Ece Ozkan
, Holger Michel, Kieran Chin-Cheong, Laura Manduchi, Sven Wellmann, Julia E. Vogt:
Deep Learning Based Prediction of Pulmonary Hypertension in Newborns Using Echocardiograms. Int. J. Comput. Vis. 132(7): 2567-2584 (2024)- [j2]Ricards Marcinkevics, Patricia Reis Wolfertstetter, Ugne Klimiene, Kieran Chin-Cheong, Alyssia Paschke, Julia Zerres, Markus Denzinger, David Niederberger, Sven Wellmann, Ece Ozkan, Christian Knorr, Julia E. Vogt:
Interpretable and intervenable ultrasonography-based machine learning models for pediatric appendicitis. Medical Image Anal. 91: 103042 (2024) - 2023
- [c6]Ece Ozkan, Thomas M. Sutter, Yurong Hu, Sebastian Balzer, Julia E. Vogt:
M(otion)-Mode Based Prediction of Ejection Fraction Using Echocardiograms. DAGM 2023: 307-320 - [i8]Ricards Marcinkevics, Patricia Reis Wolfertstetter, Ugne Klimiene, Ece Ozkan, Kieran Chin-Cheong, Alyssia Paschke, Julia Zerres, Markus Denzinger, David Niederberger, Sven Wellmann, Christian Knorr, Julia E. Vogt:
Interpretable and Intervenable Ultrasonography-based Machine Learning Models for Pediatric Appendicitis. CoRR abs/2302.14460 (2023) - [i7]Ece Ozkan, Thomas M. Sutter, Yurong Hu, Sebastian Balzer, Julia E. Vogt:
M(otion)-mode Based Prediction of Ejection Fraction using Echocardiograms. CoRR abs/2309.03759 (2023) - [i6]Ece Ozkan, Xavier Boix:
Multi-domain improves out-of-distribution and data-limited scenarios for medical image analysis. CoRR abs/2310.06737 (2023) - 2022
- [c5]Hanna Ragnarsdóttir, Laura Manduchi, Holger Michel, Fabian Laumer, Sven Wellmann, Ece Ozkan, Julia E. Vogt:
Interpretable Prediction of Pulmonary Hypertension in Newborns Using Echocardiograms. GCPR 2022: 529-542 - [c4]Ricards Marcinkevics, Ece Ozkan, Julia E. Vogt:
Debiasing Deep Chest X-Ray Classifiers using Intra- and Post-processing Methods. MLHC 2022: 504-536 - [i5]Hanna Ragnarsdóttir, Laura Manduchi, Holger Michel, Fabian Laumer, Sven Wellmann, Ece Ozkan, Julia E. Vogt:
Interpretable Prediction of Pulmonary Hypertension in Newborns using Echocardiograms. CoRR abs/2203.13038 (2022) - [i4]Ricards Marcinkevics, Ece Ozkan, Julia E. Vogt:
Debiasing Deep Chest X-Ray Classifiers using Intra- and Post-processing Methods. CoRR abs/2208.00781 (2022) - [i3]Ricards Marcinkevics, Ece Ozkan, Julia E. Vogt:
Introduction to Machine Learning for Physicians: A Survival Guide for Data Deluge. CoRR abs/2212.12303 (2022)
2010 – 2019
- 2019
- [c3]Alvaro Gomariz, Weiye Li, Ece Ozkan, Christine Tanner, Orcun Goksel:
Siamese Networks With Location Prior for Landmark Tracking in Liver Ultrasound Sequences. ISBI 2019: 1757-1760 - [i2]Alvaro Gomariz, Weiye Li, Ece Ozkan, Christine Tanner, Orçun Göksel:
Siamese Networks with Location Prior for Landmark Tracking in Liver Ultrasound Sequences. CoRR abs/1901.08109 (2019) - 2017
- [j1]Ece Ozkan, Christine Tanner, Matej Kastelic, Oliver Mattausch, Maxim Makhinya, Orcun Goksel:
Robust motion tracking in liver from 2D ultrasound images using supporters. Int. J. Comput. Assist. Radiol. Surg. 12(6): 941-950 (2017) - 2016
- [c2]Firat Özdemir, Ece Ozkan, Orcun Goksel:
Graphical Modeling of Ultrasound Propagation in Tissue for Automatic Bone Segmentation. MICCAI (2) 2016: 256-264 - [i1]Ece Ozkan, Gemma Roig, Orcun Goksel, Xavier Boix:
Herding Generalizes Diverse M -Best Solutions. CoRR abs/1611.04353 (2016) - 2015
- [c1]Ece Ozkan, Orcun Goksel:
Compliance boundary conditions for simulating deformations in a limited target region. EMBC 2015: 929-932
Coauthor Index
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