Artificial intelligence-enabled quantitative phase imaging methods for life sciences
Quantitative phase imaging, integrated with artificial intelligence, allows for the rapid and
label-free investigation of the physiology and pathology of biological systems. This review …
label-free investigation of the physiology and pathology of biological systems. This review …
On the use of deep learning for phase recovery
Phase recovery (PR) refers to calculating the phase of the light field from its intensity
measurements. As exemplified from quantitative phase imaging and coherent diffraction …
measurements. As exemplified from quantitative phase imaging and coherent diffraction …
Label-free multiplexed microtomography of endogenous subcellular dynamics using generalizable deep learning
Simultaneous imaging of various facets of intact biological systems across multiple
spatiotemporal scales is a long-standing goal in biology and medicine, for which progress is …
spatiotemporal scales is a long-standing goal in biology and medicine, for which progress is …
Roadmap on Label‐Free Super‐Resolution Imaging
VN Astratov, YB Sahel, YC Eldar… - Laser & Photonics …, 2023 - Wiley Online Library
Label‐free super‐resolution (LFSR) imaging relies on light‐scattering processes in
nanoscale objects without a need for fluorescent (FL) staining required in super‐resolved FL …
nanoscale objects without a need for fluorescent (FL) staining required in super‐resolved FL …
Live-dead assay on unlabeled cells using phase imaging with computational specificity
Existing approaches to evaluate cell viability involve cell staining with chemical reagents.
However, the step of exogenous staining makes these methods undesirable for rapid …
However, the step of exogenous staining makes these methods undesirable for rapid …
[HTML][HTML] Artificial intelligence in andrology: from semen analysis to image diagnostics
R Abou Ghayda, R Cannarella… - The World Journal of …, 2024 - ncbi.nlm.nih.gov
Artificial intelligence (AI) in medicine has gained a lot of momentum in the last decades and
has been applied to various fields of medicine. Advances in computer science, medical …
has been applied to various fields of medicine. Advances in computer science, medical …
Spatial light interference microscopy: principle and applications to biomedicine
In this paper, we review spatial light interference microscopy (SLIM), a common-path, phase-
shifting interferometer, built onto a phase-contrast microscope, with white-light illumination …
shifting interferometer, built onto a phase-contrast microscope, with white-light illumination …
Deep learning based evaluation of spermatozoid motility for artificial insemination
V Valiuškaitė, V Raudonis, R Maskeliūnas… - Sensors, 2020 - mdpi.com
We propose a deep learning method based on the Region Based Convolutional Neural
Networks (R-CNN) architecture for the evaluation of sperm head motility in human semen …
Networks (R-CNN) architecture for the evaluation of sperm head motility in human semen …
Deep learning in biomedical optics
This article reviews deep learning applications in biomedical optics with a particular
emphasis on image formation. The review is organized by imaging domains within …
emphasis on image formation. The review is organized by imaging domains within …
Does artificial intelligence have a role in the IVF clinic?
DJX Chow, P Wijesinghe, K Dholakia… - Reproduction and …, 2021 - raf.bioscientifica.com
Lay summary The success of IVF has remained stagnant for a decade. The focus of a great
deal of research is to improve on the current~ 30% success rate of IVF. Artificial intelligence …
deal of research is to improve on the current~ 30% success rate of IVF. Artificial intelligence …