Cell Detection and Segmentation in Quantitative Digital Holographic Phase Contrast Images Utilizing a Mask Region-based Convolutional Neural Network

Tobias Kutscher; Kai Eder; Anne Marzi; Álvaro Barroso; Jürgen Schnekenburger; Björn Kemper

doi:10.1364/AIS.2021.JTu5A.23

OSA Optical Sensors and Sensing Congress 2021 (AIS, FTS, HISE, SENSORS, ES)
OSA Technical Digest (Optica Publishing Group, 2021),
paper JTu5A.23
•https://doi.org/10.1364/AIS.2021.JTu5A.23

Cell Detection and Segmentation in Quantitative Digital Holographic Phase Contrast Images Utilizing a Mask Region-based Convolutional Neural Network

Tobias Kutscher, Kai Eder, Anne Marzi, Álvaro Barroso, Jürgen Schnekenburger, and Björn Kemper

Fourier Transform Spectroscopy 2021

Washington, DC United States
19–23 July 2021
ISBN: 978-1-943580-90-3

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Joint Poster Session I (JTu5A)

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T. Kutscher, K. Eder, A. Marzi, Á. Barroso, J. Schnekenburger, and B. Kemper, "Cell Detection and Segmentation in Quantitative Digital Holographic Phase Contrast Images Utilizing a Mask Region-based Convolutional Neural Network," in OSA Optical Sensors and Sensing Congress 2021 (AIS, FTS, HISE, SENSORS, ES), S. Buckley, F. Vanier, S. Shi, K. Walker, I. Coddington, S. Paine, K. Lok Chan, W. Moses, S. Qian, P. Pellegrino, F. Vollmer, G. , J. Jágerská, R. Menzies, L. Emmenegger, and J. Westberg, eds., OSA Technical Digest (Optica Publishing Group, 2021), paper JTu5A.23.

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Abstract

We analyzed the capabilities of a Mask Region-based Convolutional Neural Network to detect and segment macrophages in quantitative digital holographic phase images and demonstrate that both tasks can be performed in a single process.

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