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ORCIDIñaki Soto Rey
Person information
- affiliation: University of Augsburg, Faculty of Medicine, Germany
- affiliation (PhD 2016): University of Münster, Institute of Medical Informatics, Germany
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2020 – today
- 2025
[j2]Samiksha Pachade
, Prasanna Porwal, Manesh Kokare, Girish Deshmukh, Vivek Sahasrabuddhe, Zhengbo Luo, Feng Han, Zitang Sun, Li Qihan, Sei-ichiro Kamata, Edward Ho, Edward Wang, Asaanth Sivajohan, Saerom Youn, Kevin Lane, Jin Chun, Xinliang Wang, Yunchao Gu, Sixu Lu, Young-tack Oh, Hyunjin Park, Chia-Yen Lee, Hung Yeh, Kai-Wen Cheng, Haoyu Wang, Jin Ye, Junjun He, Lixu Gu, Dominik Müller, Iñaki Soto Rey, Frank Kramer, Hidehisa Arai, Yuma Ochi, Takami Okada, Luca Giancardo, Gwenolé Quellec, Fabrice Mériaudeau:
RFMiD: Retinal Image Analysis for multi-Disease Detection challenge. Medical Image Anal. 99: 103365 (2025)- 2024
- [c18]Dominik Müller, Philip Meyer, Lukas Rentschler, Robin Manz, Daniel Hieber, Jonas Bäcker, Samantha Cramer, Christoph Wengenmayr, Bruno Märkl, Ralf Huss, Frank Kramer, Iñaki Soto Rey, Johannes Raffler:
Assessing the Performance of Deep Learning for Automated Gleason Grading in Prostate Cancer. MIE 2024: 1110-1114 - [i9]Dominik Müller, Philip Meyer, Lukas Rentschler, Robin Manz, Jonas Bäcker, Samantha Cramer, Christoph Wengenmayr, Bruno Märkl, Ralf Huss, Iñaki Soto Rey, Johannes Raffler:
DeepGleason: a System for Automated Gleason Grading of Prostate Cancer using Deep Neural Networks. CoRR abs/2403.16678 (2024) - [i8]Dominik Müller, Philip Meyer, Lukas Rentschler, Robin Manz, Daniel Hieber, Jonas Bäcker, Samantha Cramer, Christoph Wengenmayr, Bruno Märkl, Ralf Huss, Frank Kramer, Iñaki Soto Rey, Johannes Raffler:
Assessing the Performance of Deep Learning for Automated Gleason Grading in Prostate Cancer. CoRR abs/2403.16695 (2024) - 2023
- [c17]Dominik Müller, Dennis Hartmann, Iñaki Soto Rey, Frank Kramer:
Abstract: AUCMEDI - Von der Insellösung zur einheitlichen und automatischen Klassifizierung von Medizinischen Bildern. Bildverarbeitung für die Medizin 2023: 253 - 2022
- [j1]Dominik Müller, Iñaki Soto Rey, Frank Kramer:
An Analysis on Ensemble Learning Optimized Medical Image Classification With Deep Convolutional Neural Networks. IEEE Access 10: 66467-66480 (2022) - [c16]Dominik Müller, Dennis Hartmann, Philip Meyer, Florian Auer, Iñaki Soto Rey, Frank Kramer:
MISeval: A Metric Library for Medical Image Segmentation Evaluation. MIE 2022: 33-37 - [i7]Dominik Müller, Dennis Hartmann, Philip Meyer, Florian Auer, Iñaki Soto Rey, Frank Kramer:
MISeval: a Metric Library for Medical Image Segmentation Evaluation. CoRR abs/2201.09395 (2022) - [i6]Dominik Müller, Iñaki Soto Rey, Frank Kramer:
An Analysis on Ensemble Learning optimized Medical Image Classification with Deep Convolutional Neural Networks. CoRR abs/2201.11440 (2022) - [i5]Dominik Müller, Iñaki Soto Rey, Frank Kramer:
Towards a Guideline for Evaluation Metrics in Medical Image Segmentation. CoRR abs/2202.05273 (2022) - [i4]Dennis Hartmann, Verena Schmid, Philip Meyer, Iñaki Soto Rey, Dominik Müller, Frank Kramer:
MISm: A Medical Image Segmentation Metric for Evaluation of weak labeled Data. CoRR abs/2210.13642 (2022) - 2021
- [c15]Dominik Müller, Iñaki Soto Rey, Frank Kramer:
Multi-Disease Detection in Retinal Imaging Based on Ensembling Heterogeneous Deep Learning Models. GMDS 2021: 23-31 - [c14]Philip Meyer, Dominik Müller, Iñaki Soto Rey, Frank Kramer:
COVID-19 Image Segmentation Based on Deep Learning and Ensemble Learning. MIE 2021: 518-519 - [i3]Dominik Müller, Iñaki Soto Rey, Frank Kramer:
Multi-Disease Detection in Retinal Imaging based on Ensembling Heterogeneous Deep Learning Models. CoRR abs/2103.14660 (2021) - [i2]Dennis Hartmann, Dominik Müller, Iñaki Soto Rey, Frank Kramer:
Assessing the Role of Random Forests in Medical Image Segmentation. CoRR abs/2103.16492 (2021) - 2020
- [i1]Dominik Müller, Iñaki Soto Rey, Frank Kramer:
Automated Chest CT Image Segmentation of COVID-19 Lung Infection based on 3D U-Net. CoRR abs/2007.04774 (2020)
2010 – 2019
- 2019
- [c13]Tobias Johannes Brix, Philipp Neuhaus, Michael Storck, Iñaki Soto Rey, Martin Dugas:
Reviving 30 Year Old Technology: Lessons Learned from Transferring Patient Data Using Data Matrix Codes. EFMI-STC 2019: 90-94 - [c12]Michael Storck, Luca Hollenberg, Martin Dugas, Iñaki Soto Rey:
Interoperability Improvement of Mobile Patient Survey (MoPat) Implementing Fast Health Interoperability Resources (FHIR). EFMI-STC 2019: 141-145 - [c11]Iñaki Soto Rey, Tobias Hardt, Luca Hollenberg, Philipp Bruland, Sonja Ständer, Martin Dugas, Michael Storck:
Electronic Image Documentation of Patient Reported Outcomes Using Mobile Technologies. MedInfo 2019: 1779-1780 - 2018
- [c10]Michael Storck, Gundula Christians, Birgit Möller, Martin Dugas, Iñaki Soto Rey:
Conducting a Multilingual Study Researching Traumatised Refugees Utilizing a Patient-Reported Outcome System. GMDS 2018: 109-113 - [c9]Iñaki Soto Rey, Philipp Neuhaus, Philipp Bruland, Sophia Geßner, Julian Varghese, Stefan Hegselmann, Tobias J. Brix, Martin Dugas, Michael Storck:
Standardising the Development of ODM Converters: The ODMToolBox. MIE 2018: 231-235 - 2017
- [c8]Sophia Gessner, Michael Storck, Stefan Hegselmann, Martin Dugas, Iñaki Soto Rey:
Automated Transformation of CDISC ODM to OpenClinica. GMDS 2017: 95-99 - [c7]Iñaki Soto Rey, Sophia Geßner, Martin Dugas:
Operational Data Model Conversion to ResearchKit. MedInfo 2017: 225-229 - [c6]Sophia Geßner, Philipp Neuhaus, Julian Varghese, Philipp Bruland, Alexandra Meidt, Iñaki Soto Rey, Michael Storck, Justin Doods, Martin Dugas:
The Portal of Medical Data Models: Where Have We Been and Where Are We Going? MedInfo 2017: 858-862 - 2016
- [b1]Iñaki Soto Rey:
Efficiency and effectiveness evaluation of an automated multi-country patient count cohort system. University of Münster, Germany, 2016 - [c5]Iñaki Soto Rey, Martin Dugas, Michael Storck:
Implementation of an ODM and HL7 Compliant Electronic Patient-Reported Outcome System. MIE 2016: 421-425 - 2015
- [c4]Iñaki Soto Rey, Benjamin Trinczek, Jose Ignacio Amo, Jesús Bauselas, Martin Dugas, Fleur Fritz:
Web-Based Multi-Site Feasibility Questionnaire Tool. eHealth 2015: 88-93 - [c3]Iñaki Soto Rey, Martin Dugas, Fleur Fritz:
Clinical Trial Feasibility Study Questionnaire Analysis. MedInfo 2015: 1029 - 2014
- [c2]Iñaki Soto Rey, Benjamin Trinczek, Töresin Karakoyun, Martin Dugas, Fleur Fritz:
Protocol Feasibility Workflow Using an Automated Multi-country Patient Cohort System. MIE 2014: 985-989 - 2013
- [c1]Iñaki Soto Rey, Richard Bache, Martin Dugas, Fleur Fritz:
Query Engine Optimization for the EHR4CR Protocol Feasibility Scenario. MedInfo 2013: 1080
Coauthor Index
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