DarkFocus: numerical autofocusing in digital in-line holographic microscopy using variance of computational dark-field gradient

Trusiak, Maciej; Picazo-Bueno, José Ángel; Zdańkowski, Piotr; Micó, Vicente

doi:10.1016/j.optlaseng.2020.106195

Cited by 42 publications

(14 citation statements)

References 84 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Additionally, we show the full 3D trajectories followed by the two sperm cells during the recording time in two different perspectives (see Figure 10b), where we include both the 3D movement and the projection on the XY plane of the sperm cells in movies Videos S3 and S4. For obtaining the trajectories, we apply a local focusing criteria based on the recently published DarkFocus numerical autofocusing method [45], but other methods can be also employed instead [46,47].…”

Section: Application To Dynamic Biosamplesmentioning

confidence: 99%

Design, Calibration, and Application of a Robust, Cost-Effective, and High-Resolution Lensless Holographic Microscope

Picazo-Bueno

Trindade

Sanz

et al. 2022

Sensors

Self Cite

View full text Add to dashboard Cite

Lensless holographic microscope (LHM) is an emerging very promising technology that provides high-quality imaging and analysis of biological samples without utilizing any lens for imaging. Due to its small size and reduced price, LHM can be a very useful tool for the point-of-care diagnosis of diseases, sperm assessment, or microfluidics, among others, not only employed in advanced laboratories but also in poor and/or remote areas. Recently, several LHMs have been reported in the literature. However, complete characterization of their optical parameters remains not much presented yet. Hence, we present a complete analysis of the performance of a compact, reduced cost, and high-resolution LHM. In particular, optical parameters such as lateral and axial resolutions, lateral magnification, and field of view are discussed into detail, comparing the experimental results with the expected theoretical values for different layout configurations. We use high-resolution amplitude and phase test targets and several microbeads to characterize the proposed microscope. This characterization is used to define a balanced and matched setup showing a good compromise between the involved parameters. Finally, such a microscope is utilized for visualization of static, as well as dynamic biosamples.

show abstract

Section: Application To Dynamic Biosamplesmentioning

confidence: 99%

Design, Calibration, and Application of a Robust, Cost-Effective, and High-Resolution Lensless Holographic Microscope

Picazo-Bueno

Trindade

Sanz

et al. 2022

Sensors

Self Cite

View full text Add to dashboard Cite

show abstract

“…There are many autofocus algorithms for numerical refocusing including those that use amplitude, 182 sparsity, 183,184 a correlation coefficient, 185 and other properties 186 to determine optimal focus in DHM. One example of a DHM numerical refocusing metric that achieves the desired properties of a focal position algorithm is the DarkFocus (DF) metric, 181 which optimizes for the sharpness of images as…”

Section: Solving the Fundamental Problem Of Quantitative Phasementioning

confidence: 99%

Quantitative Phase Imaging: Recent Advances and Expanding Potential in Biomedicine

et al. 2022

View full text Add to dashboard Cite

Quantitative phase imaging (QPI) is a label-free, wide-field microscopy approach with significant opportunities for biomedical applications. QPI uses the natural phase shift of light as it passes through a transparent object, such as a mammalian cell, to quantify biomass distribution and spatial and temporal changes in biomass. Reported in cell studies more than 60 years ago, ongoing advances in QPI hardware and software are leading to numerous applications in biology, with a dramatic expansion in utility over the past two decades. Today, investigations of cell size, morphology, behavior, cellular viscoelasticity, drug efficacy, biomass accumulation and turnover, and transport mechanics are supporting studies of development, physiology, neural activity, cancer, and additional physiological processes and diseases. Here, we review the field of QPI in biology starting with underlying principles, followed by a discussion of technical approaches currently available or being developed, and end with an examination of the breadth of applications in use or under development. We comment on strengths and shortcomings for the deployment of QPI in key biomedical contexts and conclude with emerging challenges and opportunities based on combining QPI with other methodologies that expand the scope and utility of QPI even further.

show abstract

“…In the study, 50 transfer functions were created with a 10 µm step size, multiplied with a hologram, and the sample images were obtained. Tenenbaum gradient, Brenner gradient, and Tamura gradient of all images were calculated to find the optimum distance through the images [56,57].…”

Section: Microscopy Setup and Imaging Evaluationmentioning

confidence: 99%

DWT‐SVD Based Watermarking for High‐Resolution Medical Holographic Images

et al. 2022

View full text Add to dashboard Cite

Watermarking is one of the most common techniques used to protect data’s authenticity, integrity, and security. The obfuscation in the frequency domain used in the watermarking method makes the watermarking stronger than the obfuscation in the spatial domain. It occupies an important place in watermarking works in imperceptibility, capacity, and robustness. Finding the optimal location to hide the watermarking is one of the most challenging tasks in these methods and affects the method’s performance. In this article, sample identification information is processed with the method of watermaking on the hiding environment created by using a chaos-based random number generator on biomedical data to provide solutions to problems such as visual attack, identity theft, and information confusion. In order to obtain biomedical data, a lensless digital in-line holographic microscopy (DIHM) setup was designed, and holographic data of human blood and cancer cell lines, which are widely used in the laboratory environment, were obtained. The standard USAF 1951 target was used to evaluate the resolution of our imaging setup. Various QR codes were generated for medical sample identification, and the captured medical data were processed by watermarking it with chaos-based random number generators. A new method using chaos-based discrete wavelet transform (DWT) and singular value decomposition (SVD) has been developed and applied to high-resolution data to eliminate the problem of encrypted data being directly targeted by third-party attacks. The performance of the proposed new watermarking method has been demonstrated by various robustness and invisibility tests. Experimental results showed that the proposed scheme reached an average PSNR value of 564588 dB and SSIM value of 0.9972 against several geometric and destructive attacks, which means that the proposed method does not affect the image quality and also ensures the security of the watermarking information. The results of the proposed method have shown that it can be used efficiently in various fields.

show abstract

DarkFocus: numerical autofocusing in digital in-line holographic microscopy using variance of computational dark-field gradient

Cited by 42 publications

References 84 publications

Design, Calibration, and Application of a Robust, Cost-Effective, and High-Resolution Lensless Holographic Microscope

Design, Calibration, and Application of a Robust, Cost-Effective, and High-Resolution Lensless Holographic Microscope

Quantitative Phase Imaging: Recent Advances and Expanding Potential in Biomedicine

DWT‐SVD Based Watermarking for High‐Resolution Medical Holographic Images

Contact Info

Product

Resources

About