Zobrazeno 1 - 5
of 5
pro vyhledávání: '"David L. Holscher"'
Autor:
Mehdi Joodaki, Mina Shaigan, Victor Parra, Roman D. Buelow, Christoph Kuppe, David L. Holscher, Mingbo Cheng, James S. Nagai, Nassim Bouteldja, Vladimir Tesar, Jonathan Barratt, Ian S. D. Roberts, Rosanna Coppo, Rafael Kramann, Peter Boor, Ivan G. Costa
Publikováno v:
Cold Spring Harbor : Cold Spring Harbor Laboratory, bioRxiv : the preprint server for biology [1]-24 (2022). doi:10.1101/2022.12.16.520739
Although clinical applications represent the next challenge in single-cell genomics and digital pathology, we still lack computational methods to analyze single-cell and pathomics data to find sample level trajectories or clusters associated with dis
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::72b38dcefde29a560a55153f98a14383
https://publications.rwth-aachen.de/record/862383
https://publications.rwth-aachen.de/record/862383
Autor:
David L. Hölscher, Michael Goedertier, Barbara M. Klinkhammer, Patrick Droste, Ivan G. Costa, Peter Boor, Roman D. Bülow
Publikováno v:
BMC Bioinformatics, Vol 25, Iss 1, Pp 1-11 (2024)
Abstract Background Pathomics facilitates automated, reproducible and precise histopathology analysis and morphological phenotyping. Similar to molecular omics, pathomics datasets are high-dimensional, but also face large outlier variability and inhe
Externí odkaz:
https://doaj.org/article/b0d0aa69d8504016b2e20a8120906e4d
Publikováno v:
npj Systems Biology and Applications, Vol 9, Iss 1, Pp 1-3 (2023)
Externí odkaz:
https://doaj.org/article/73bbfbcb523746e588c6a20fdef6a5b4
Autor:
David L. Hölscher, Nassim Bouteldja, Mehdi Joodaki, Maria L. Russo, Yu-Chia Lan, Alireza Vafaei Sadr, Mingbo Cheng, Vladimir Tesar, Saskia V. Stillfried, Barbara M. Klinkhammer, Jonathan Barratt, Jürgen Floege, Ian S. D. Roberts, Rosanna Coppo, Ivan G. Costa, Roman D. Bülow, Peter Boor
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-14 (2023)
Pathology diagnostics still rely on tissue morphology assessment by trained experts. Here, the authors perform deep-learning-based segmentation followed by large-scale feature extraction of histological images, i.e., next-generation morphometry, to e
Externí odkaz:
https://doaj.org/article/23a6ad923ea34d429c8664558993fafc
Autor:
Nassim Bouteldja, David L. Hölscher, Roman D. Bülow, Ian S.D. Roberts, Rosanna Coppo, Peter Boor
Publikováno v:
Journal of Pathology Informatics, Vol 13, Iss , Pp 100140- (2022)
Background: Considerable inter- and intra-laboratory stain variability exists in pathology, representing a challenge in development and application of deep learning (DL) approaches. Since tackling all sources of stain variability with manual annotati
Externí odkaz:
https://doaj.org/article/d241d70955614405ab441fd9e1530ec1