Performances of automated digital imaging of Gram-stained slides with on-screen reading against manual microscopy
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
-
1435-4373
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Anmerkungen
-
online resource.
- Erschienen in
-
Performances of automated digital imaging of Gram-stained slides with on-screen reading against manual microscopy ; day:8 ; month:5 ; year:2021 ; pages:1-6
European journal of clinical microbiology & infectious diseases ; (8.5.2021), 1-6
- Urheber
-
Fischer, Adrien
Azam, Nouria
Rasga, Lara
Barras, Valérie
Tangomo, Manuela
Renzi, Gesuele
Vuilleumier, Nicolas
Schrenzel, Jacques
Cherkaoui, Abdessalam
- Beteiligte Personen und Organisationen
-
SpringerLink (Online service)
- DOI
-
10.1007/s10096-021-04233-2
- URN
-
urn:nbn:de:101:1-2021091106210611039507
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
15.08.2025, 07:31 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Fischer, Adrien
- Azam, Nouria
- Rasga, Lara
- Barras, Valérie
- Tangomo, Manuela
- Renzi, Gesuele
- Vuilleumier, Nicolas
- Schrenzel, Jacques
- Cherkaoui, Abdessalam
- SpringerLink (Online service)
Ähnliche Objekte (12)
Weakly-supervised deep learning models enable HER2-low prediction from H &E stained slides
Efficient Deep Learning at Inference Time for Gram Stained Image Classification
Stained glass
Stained glass
Stained glass
Stained ground
Stained glass
Semi-Supervised Learning to Automate Tumor Bud Detection in Cytokeratin-Stained Whole-Slide Images of Colorectal Cancer
Multispectral in-line hologram reconstruction with aberration compensation applied to Gram-stained bacteria microscopy
Machine learning can aid in prediction of IDH mutation from H&E-stained histology slides in infiltrating gliomas
Detection of follicular regions in actin-stained whole slide images of the human lymph node by shock filter
2: Stained glass
Weakly-supervised deep learning models enable HER2-low prediction from H &E stained slides
Efficient Deep Learning at Inference Time for Gram Stained Image Classification
Stained glass
Stained glass
Stained glass
Stained ground
Stained glass
Semi-Supervised Learning to Automate Tumor Bud Detection in Cytokeratin-Stained Whole-Slide Images of Colorectal Cancer
Multispectral in-line hologram reconstruction with aberration compensation applied to Gram-stained bacteria microscopy
Machine learning can aid in prediction of IDH mutation from H&E-stained histology slides in infiltrating gliomas
Detection of follicular regions in actin-stained whole slide images of the human lymph node by shock filter
2: Stained glass
Weakly-supervised deep learning models enable HER2-low prediction from H &E stained slides
Efficient Deep Learning at Inference Time for Gram Stained Image Classification
Stained glass
Stained glass
Stained glass
Stained ground
Stained glass
Semi-Supervised Learning to Automate Tumor Bud Detection in Cytokeratin-Stained Whole-Slide Images of Colorectal Cancer
Multispectral in-line hologram reconstruction with aberration compensation applied to Gram-stained bacteria microscopy
Machine learning can aid in prediction of IDH mutation from H&E-stained histology slides in infiltrating gliomas
Detection of follicular regions in actin-stained whole slide images of the human lymph node by shock filter