Zobrazeno 1 - 10
of 33
pro vyhledávání: '"Kuritcyn P"'
Autor:
Heinlein Lukas, Benz Michaela, Kuritcyn Petr, Bruns Volker, Hartmann Arndt, Keil Felix, Geppert Carol, Evert Katja, Wittenberg Thomas
Publikováno v:
Current Directions in Biomedical Engineering, Vol 9, Iss 1, Pp 166-169 (2023)
Background: The examination of lymph nodes (LNs) regarding metastases is vital for the staging of cancer patients, which is necessary for diagnosis and adequate treatment selection. Advancements in digital pathology, utilizing Whole-Slide Images (WSI
Externí odkaz:
https://doaj.org/article/5e3f07f60dad4f0cbd9b9ead58a31877
Autor:
Kletzander Rosalie, Kuritcyn Petr, Bruns Volker, Eckstein Markus, Geppert Carol, Hartmann Arndt, Benz Michaela
Publikováno v:
Current Directions in Biomedical Engineering, Vol 9, Iss 1, Pp 491-494 (2023)
Few-shot learning addresses the problem of classification when little data or few labels are available. This is especially relevant in histopathology, where labeling must be carried out by highly trained medical experts. Prototypical Networks promise
Externí odkaz:
https://doaj.org/article/ab3d9771c5d447de8354813a19560576
Autor:
Mohammed Aliya, Geppert Carol, Hartmann Arnd, Kuritcyn Petr, Bruns Volker, Schmid Ute, Wittenberg Thomas, Benz Michaela, Finzel Bettina
Publikováno v:
Current Directions in Biomedical Engineering, Vol 8, Iss 2, Pp 229-232 (2022)
Deep Learning-based tissue classification may support pathologists in analyzing digitized whole slide images. However, in such critical tasks, only approaches that can be validated by medical experts in advance to deployment, are suitable. We present
Externí odkaz:
https://doaj.org/article/74eb23bf620942ceb0023d7608d7c4cb
Autor:
Dexl Jakob, Benz Michaela, Kuritcyn Petr, Wittenberg Thomas, Bruns Volker, Geppert Carol, Hartmann Arndt, Bischl Bernd, Goschenhofer Jann
Publikováno v:
Current Directions in Biomedical Engineering, Vol 8, Iss 2, Pp 344-347 (2022)
We explore the task of tissue classification for colon cancer histology in a low label regime comparing a semi-supervised and a supervised learning strategy in a series of experiments. Further, we investigate the model robustness w.r.t. distribution
Externí odkaz:
https://doaj.org/article/3a436ac07def4f1294c9db3081cb1688
Autor:
Bruns Volker, Franz Daniela, Kuritcyn Petr, Wiesmann Veit, Rathke Magnus, Wittenberg Thomas, Wießner Alexandra, Kursawe Laura, Moter Annette, Kikhney Judith, Münzenmayer Christian
Publikováno v:
Current Directions in Biomedical Engineering, Vol 7, Iss 2, Pp 468-471 (2021)
Infective endocarditis (IE) is an infection of the endocardium, and the heart valves associated with high morbidity and mortality. Fluorescence in situ Hybridization (FISH) is a molecular imaging technique used for diagnosis of IE based on histologic
Externí odkaz:
https://doaj.org/article/abe05c92a6af45369499bf233736f0f2
Autor:
Petr Kuritcyn, Rosalie Kletzander, Sophia Eisenberg, Thomas Wittenberg, Volker Bruns, Katja Evert, Felix Keil, Paul K. Ziegler, Katrin Bankov, Peter Wild, Markus Eckstein, Arndt Hartmann, Carol I. Geppert, Michaela Benz
Publikováno v:
Journal of Pathology Informatics, Vol 15, Iss , Pp 100388- (2024)
A vast multitude of tasks in histopathology could potentially benefit from the support of artificial intelligence (AI). Many examples have been shown in the literature and first commercial products with FDA or CE-IVDR clearance are available. However
Externí odkaz:
https://doaj.org/article/5c6c7078dd8a43fa8158d82137e55b90
Mitotic figure detection is a challenging task in digital pathology that has a direct impact on therapeutic decisions. While automated methods often achieve acceptable results under laboratory conditions, they frequently fail in the clinical deployme
Externí odkaz:
http://arxiv.org/abs/2109.01485
Autor:
Wilm, Frauke, Benz, Michaela, Bruns, Volker, Baghdadlian, Serop, Dexl, Jakob, Hartmann, David, Kuritcyn, Petr, Weidenfeller, Martin, Wittenberg, Thomas, Merkel, Susanne, Hartmann, Arndt, Eckstein, Markus, Geppert, Carol I.
Publikováno v:
J. Med. Imag. 9(2), 027501 (2022)
Automatic outlining of different tissue types in digitized histological specimen provides a basis for follow-up analyses and can potentially guide subsequent medical decisions. The immense size of whole-slide-images (WSI), however, poses a challenge
Externí odkaz:
http://arxiv.org/abs/2106.15893
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Akademický článek
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