Dr. Adrian Krenzer
University of Würzburg
Department for Artificial Intelligence
and Knowledge Systems
Am Hubland
D-97074 Würzburg
Room: B015
Phone: +49 931 / 31-84971
adrian.krenzer@uni-wuerzburg.de
Publications
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Development and evaluation of a deep learning model to improve the usability of polyp detection systems during interventions. . In United European Gastroenterology Journal, 10(5), bll 477–484. Wiley Online Library, 2022.
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Pilotphase einer Studie zum Einsatz einer neuen, frei verfügbaren Polypendetektionssoftware im klinischen Alltag. . In Zeitschrift für Gastroenterologie, 60(08), bl KA438. Georg Thieme Verlag, 2022.
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A video based benchmark data set (ENDOTEST) to evaluate computer-aided polyp detection systems. . In Scandinavian Journal of Gastroenterology, 57(11), bll 1397–1403. Taylor \& Francis, 2022.
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Pilot study of a new freely available computer-aided polyp detection system in clinical practice. . In International Journal of Colorectal Disease, 37(6), bll 1349–1354. Springer, 2022.
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Frame-by-frame analysis of a commercially available artificial intelligence polyp detection system in full-length colonoscopies. . In Digestion, 103(5), bll 378–385. Karger Publishers, 2022.
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Deep Learning using temporal information for automatic polyp detection in videos. . 2022.
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New concept for colonoscopy including side optics and artificial intelligence. . In Gastrointestinal Endoscopy, 95(4), bll 794–798. Elsevier, 2022.
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A User Interface for Automatic Polyp Detection Based on Deep Learning with Extended Vision. . In Medical Image Understanding and Analysis: 26th Annual Conference, MIUA 2022, Cambridge, UK, July 27--29, 2022, Proceedings, bll 851–868. Springer, 2022.
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Automated classification of polyps using deep learning architectures and few-shot learning. . 2022.
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Biomedical image analysis competitions: The state of current participation practice. . In arXiv preprint arXiv:2212.08568. 2022.
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Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy. . In Medical image analysis, 70, bl 102002. Elsevier, 2021.
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Semi-Automated Machine Learning Video Annotation for Gastroenterologists. . In Studies in health technology and informatics, 281, bll 484–485. 2021.
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Entwicklung des Polypendetektionssystems ENDOMIND und Vergleich mit einem kommerziell erhältlichen CADe System. . In Zeitschrift für Gastroenterologie, 59(08), bl A-325. Georg Thieme Verlag KG, 2021.
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Fast Machine Learning Annotation in the Medical Domain: A Semi-Automated Video Annotation Tool for Gastroenterologists. . In BioMedical Engineering OnLine. 2021.
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Künstliche Intelligenz zur Detektion von Kolonpolypen-Detaillierte Aufarbeitung relevanter Faktoren mittels Einzelbildanalyse. . In Zeitschrift für Gastroenterologie, 59(08), bl A-327. Georg Thieme Verlag KG, 2021.
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Endoscopic Detection and Segmentation of Gastroenterological Diseases with Deep Convolutional Neural Networks. . Vol. 2595, S. Ali; C. Daul; J. Rittscher; D. Stoyanov; E. Grisan (reds.). CEUR-WS, 2020.
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Bigger Networks are not Always Better: Deep Convolutional Neural Networks for Automated Polyp Segmentation. . 2020.
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Künstliche Intelligenz zur Detektion von Kolonpolypen - eine systematische Aufarbeitung relevanter Faktoren. . In Zeitschrift für Gastroenterologie, 58(08), bl PKV-33. {\copyright} Georg Thieme Verlag KG, 2020.
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Augmented Intelligence for Quality Control of Manual Assembly Processes using Industrial Wearable Systems. . 2019.
Teaching
Term | Course |
Summer 2023 | Programmieren mit Neuronalen Netzen |
Winter 2022/2023 | Künstliche Intelligenz II |
Summer 2022 | Programmieren mit Neuronalen Netzen |
Winter 2021/2022 | Künstliche Intelligenz II |
Summer 2021 | Softwaretechnik |
Winter 2020/2021 | Künstliche Intelligenz II |
Summer 2020 | Softwaretechnik |