Presentation + Paper
12 March 2024 Urine sediment analysis utilizing quantitative phase imaging with digital holographic microscopy
Marlene Kallaß, Álvaro Barroso, Yussef Hanna, Steffi Ketelhut, Eva Döpker, Jürgen Schnekenburger, Björn Kemper
Author Affiliations +
Abstract
We explored the capabilities of quantitative phase imaging (QPI) with digital holographic microscopy (DHM) for the characterization and classification of urine sediments. Bright-field images and off-axis holograms from a liquid control for urine analysis and human urine samples were acquired with a modular DHM system. From the retrieved images, particle morphology parameters were extracted by threshold and convolution neural network (CNN)-based segmentation procedures. Moreover, the ability of supervised machine learning algorithms to classify and identify urine sediment components based on biophysical parameters was evaluated. Our results demonstrate DHM as a reliable urine sediment analysis tool.
Conference Presentation
© (2024) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Marlene Kallaß, Álvaro Barroso, Yussef Hanna, Steffi Ketelhut, Eva Döpker, Jürgen Schnekenburger, and Björn Kemper "Urine sediment analysis utilizing quantitative phase imaging with digital holographic microscopy", Proc. SPIE 12854, Label-free Biomedical Imaging and Sensing (LBIS) 2024, 128540G (12 March 2024); https://doi.org/10.1117/12.3002360
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KEYWORDS
Image segmentation

Digital holography

Particles

Machine learning

Phase contrast

Holography

Microscopy

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