Machine Learning Based Prediction of Squamous Cell Carcinoma in Ex Vivo Confocal Laser Scanning Microscopy
Image classification with convolutional neural networks (CNN) offers an unprecedented opportunity to medical imaging. Regulatory agencies in the USA and Europe have already cleared numerous deep learning/machine learning based medical devices and algorithms. While the field of radiology is on the fo...
Guardado en:
Autores principales: | Cristel Ruini, Sophia Schlingmann, Žan Jonke, Pinar Avci, Víctor Padrón-Laso, Florian Neumeier, Istvan Koveshazi, Ikenna U. Ikeliani, Kathrin Patzer, Elena Kunrad, Benjamin Kendziora, Elke Sattler, Lars E. French, Daniela Hartmann |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
MDPI AG
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/f55b4b793c9c407f97c8de4c2c434cba |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Deep Learning on Oral Squamous Cell Carcinoma Ex Vivo Fluorescent Confocal Microscopy Data: A Feasibility Study
por: Veronika Shavlokhova, et al.
Publicado: (2021) -
Ex vivo confocal microscopy: an emerging technique in dermatology
por: Elisa Cinotti, et al.
Publicado: (2018) -
The use of reflectance confocal microscopy for monitoring response to therapy of skin malignancies
por: Marina Ulrich, et al.
Publicado: (2012) -
Recognizing the benefits and pitfalls of reflectance confocal microscopy in melanoma diagnosis
por: Alon Scope, et al.
Publicado: (2014) -
Reflectance confocal microscopy of mammary Paget disease
por: Fezal Ozdemir, et al.
Publicado: (2017)