Abstract

Digital holographic microscopy allows capture of the full wavefront from microscopic objects without marking and scanning. Multi-label segmentation of digital holograms of three-dimensional Madin-Darby canine kidney cell clusters is realized using a fully convolutional neural network.

© 2019 The Author(s)

PDF Article
More Like This
Detection of an object in the field of view of a digital hologram with an heuristic algorithm parameterized using a convolutional neural network

Tomi Pitkäaho, Aki Manninen, and Thomas J. Naughton
Th3A.3 Digital Holography and Three-Dimensional Imaging (DH) 2019

Temporal deep learning classification of digital hologram reconstructions of multicellular samples

Tomi Pitkäaho, Aki Manninen, and Thomas J. Naughton
JW3A.14 Clinical and Translational Biophotonics (Translational) 2018

Focus classification in digital holographic microscopy using deep convolutional neural networks

Tomi Pitkäaho, Aki Manninen, and Thomas J. Naughton
104140K European Conference on Biomedical Optics (ECBO) 2017

References

You do not have subscription access to this journal. Citation lists with outbound citation links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription