Imaging, Sensing and Applications in Digital Holographic Microscopy
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensing and Imaging".
Deadline for manuscript submissions: closed (31 July 2023) | Viewed by 270
Special Issue Editors
Interests: biomedical systems; optical imaging systems for microscopy; multidimensional imaging techniques; computational imaging for microscopy
Special Issues, Collections and Topics in MDPI journals
Interests: optical systems; deep learning techniques; computational imaging strategies
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The advancement of DHM technology, including simultaneous hardware and software development, has enabled the unique observation of biological cells, organisms, and systems with high sensitivity, accuracy, and spatial and temporal resolutions, keeping low phototoxicity and photodamaging of the cells. Such achievements have unraveled novel dynamics and mechanisms of biological systems, encouraging the scientific community to advance DHM imaging and sensing technology. An advantage of DHM systems is also their applicability to material science applications, such as vibration analysis and surface topography. This Special Feature calls for innovative and original contributions in developing imaging, sensing, reconstruction approaches, and applications that show the applicability of DHM technology in biomedical and material science research.
Topics of interest include, but are not limited to, the following:
- Development and performance of new DHM imaging systems.
- Development and performance of novel three-dimensional DHM imaging sensing systems.
- Investigation of DHM systems applied to biological and material science research.
- Development of polarization-sensitive DHM systems.
- Development of miniaturized DHM devices for point-of-care diagnosis.
- Development and performance of new computational imaging approaches, for instance, compressive sensing and machine learning techniques, including different and adapted versions of deep neural network (DNN) strategies.
Dr. Ana Doblas
Dr. Carlos Trujillo
Guest Editors
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