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Unraveling the deep learning gearbox in optical coherence tomography image segmentation towards explainable artificial intelligence

Maloca et al. implement convolutional neural network (CNN) to automatically segment OCT images obtained from cynomolgus monkeys. The results are compared to annotations generated by human graders. The ambiguity in ground truth had noteworthy impact on machine learning results, which could be visuali...

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Detalles Bibliográficos
Principais autores: Peter M. Maloca, Philipp L. Müller, Aaron Y. Lee, Adnan Tufail, Konstantinos Balaskas, Stephanie Niklaus, Pascal Kaiser, Susanne Suter, Javier Zarranz-Ventura, Catherine Egan, Hendrik P. N. Scholl, Tobias K. Schnitzer, Thomas Singer, Pascal W. Hasler, Nora Denk
Formato: Artigo
Idioma:Inglês
Publicado: Nature Portfolio 2021-02-01
Series:Communications Biology
Acceso en liña:https://doi.org/10.1038/s42003-021-01697-y
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