[HTML][HTML] Digital in-line holographic microscopy for label-free identification and tracking of biological cells
J Kim, SJ Lee - Military Medical Research, 2024 - Springer
Digital in-line holographic microscopy (DIHM) is a non-invasive, real-time, label-free
technique that captures three-dimensional (3D) positional, orientational, and morphological …
technique that captures three-dimensional (3D) positional, orientational, and morphological …
Object detection, auto-focusing and transfer learning for digital holography of solid composite propellant using efficient neural network
G Xu, Y Huang, J Lyu, P Liu, W Ao - Optics and Lasers in Engineering, 2024 - Elsevier
Digital holography has emerged as a powerful tool for various applications. However,
applications such as target detection and depth prediction in complex scenarios like …
applications such as target detection and depth prediction in complex scenarios like …
End-to-end infrared radiation sensing technique based on holography-guided visual attention network
Infrared radiation imaging is extensively utilized due to its unique advantages in terms of
wavelengths. This paper presents an end-to-end short-wave infrared digital holography …
wavelengths. This paper presents an end-to-end short-wave infrared digital holography …
Lensfree auto-focusing imaging with coarse-to-fine tuning method
Sample-to-sensor distance is a crucial predefined parameter for lensfree on-chip
microscopes. Inaccurate estimation of the distance could lead to a failure of high-frequency …
microscopes. Inaccurate estimation of the distance could lead to a failure of high-frequency …
[HTML][HTML] Illumination system contributing zooming function to lensless digital holographic microscope by using lightguide incorporated with volume holographic optical …
Illumination systems play a crucial role in determining the image quality of lens-less images.
In this paper, we propose an illumination system that uses a light guide with a volume …
In this paper, we propose an illumination system that uses a light guide with a volume …
[HTML][HTML] OptiGUI DataCollector: A graphical user interface for automating the data collecting process in optical and photonics labs
J Soto-Perdomo, J Morales-Guerra, JD Arango… - SoftwareX, 2023 - Elsevier
Abstract OptiGUI DataCollector is a Python 3.8-based graphical user interface that facilitates
automated data collection in optics and photonics research and development equipment. It …
automated data collection in optics and photonics research and development equipment. It …
Open-access database for digital lensless holographic microscopy and its application on the improvement of deep-learning-based autofocusing models
C Buitrago-Duque, H Tobón-Maya… - Applied Optics, 2024 - opg.optica.org
Among modern optical microscopy techniques, digital lensless holographic microscopy
(DLHM) is one of the simplest label-free coherent imaging approaches. However, the …
(DLHM) is one of the simplest label-free coherent imaging approaches. However, the …
Auto focusing of in-Line Holography based on Stacked Auto Encoder with Sparse Bayesian Regression and Compressive Sensing
C Vimala, A Ajeena - Multimedia Tools and Applications, 2024 - Springer
In recent years, Digital holography has emerged as an exceptional imaging technology for
tracking high-contrast object particles and, interestingly, analyzing 3D object data in real …
tracking high-contrast object particles and, interestingly, analyzing 3D object data in real …
A Miniaturized and Intelligent Lensless Holographic Imaging System With Auto-Focusing and Deep Learning-Based Object Detection for Label-Free Cell …
J Chen, W Han, L Fu, Z Lv, H Chen… - IEEE Photonics …, 2024 - ieeexplore.ieee.org
Cell detection and classification is a key technique for disease diagnosis, but conventional
methods such as optical microscopy and flow cytometry have limitations in terms of field-of …
methods such as optical microscopy and flow cytometry have limitations in terms of field-of …
Enhancing digital hologram reconstruction using reverse-attention loss for untrained physics-driven deep learning models with uncertain distance
Untrained Physics-based Deep Learning (DL) methods for digital holography have gained
significant attention due to their benefits, such as not requiring an annotated training dataset …
significant attention due to their benefits, such as not requiring an annotated training dataset …