Digital holographic microscopy and focusing methods based on image sharpness

İlhan, Hazar Aytekin; Doğar, Mert; Özcan, Meriç

doi:10.1111/jmi.12144

Cited by 31 publications

(18 citation statements)

References 22 publications

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“…First, the CCV Pipeline saves slices of the hologram (i.e., focal planes) from Octopus in user‐specified μ m increments across the 22 mm path between the point source and the camera. Next, a sharpness score is computed for each pixel in all image planes and the maximum value is stored, a technique alike ones previously developed (Guildenbecher et al 2012; İlhan et al 2014). As neighboring in‐focus pixels are likely to belong to the same object, pixels are grouped to segments in the second step of the processing (Suzuki and Be 1985).…”

Section: Methodsmentioning

confidence: 99%

Assessment of holographic microscopy for quantifying marine particle size and concentration

Walcutt

Knörlein

Cetinić

et al. 2020

Limnology & Ocean Methods

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Holographic microscopy has emerged as a tool for in situ imaging of microscopic organisms and other particles in the marine environment: appealing because of the relatively larger sampling volume and simpler optical configuration compared to other imaging systems. However, its quantitative capabilities have so far remained uncertain, in part because hologram reconstruction and image recognition have required manual operation. Here, we assess the quantitative skill of our automated hologram processing pipeline (CCV Pipeline), to evaluate the size and concentration measurements of environmental and cultured assemblages of marine plankton particles, and microspheres. Over 1 million particles, ranging from 10 to 200 μm in equivalent spherical diameter, imaged by the 4‐Deep HoloSea digital inline holographic microscope (DIHM) are analyzed. These measurements were collected in parallel with a FlowCam (FC), Imaging FlowCytobot (IFCB), and manual microscope identification. Once corrections for particle location and nonuniform illumination were developed and applied, the DIHM showed an underestimate in ESD of about 3% to 10%, but successfully reproduced the size spectral slope from environmental samples, and the size distribution of cultures (Dunaliella tertiolecta, Heterosigma akashiwo, and Prorocentrum micans) and microspheres. DIHM concentrations (order 1 to 1000 particles ml−1) showed a linear agreement (r2 = 0.73) with the other instruments, but individual comparisons at times had large uncertainty. Overall, we found the DIHM and the CCV Pipeline required extensive manual correction, but once corrected, provided concentration and size estimates comparable to the other imaging systems assessed in this study. Holographic cameras are mechanically simple, autonomous, can operate at very high pressures, and provide a larger sampling volume than comparable lens‐based tools. Thus, we anticipate that these characterization efforts will be rewarded with novel discovery in new oceanic environments.

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Section: Methodsmentioning

confidence: 99%

Assessment of holographic microscopy for quantifying marine particle size and concentration

Walcutt

Knörlein

Cetinić

et al. 2020

Limnology & Ocean Methods

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show abstract

“…We therefore developed a custom hologram processing pipeline which first computes a sharpness score for each pixel across all image planes in the whole volume and stores for each pixel the maximum value (Guildenbecher et al, 2012;Ihan et al, 2014). As neighboring pixels in focus are likely to belong to the same object, pixels are grouped to segments in a second step.…”

Section: Data Visualization-holographic Microscopymentioning

confidence: 99%

Virtual Reality and Oceanography: Overview, Applications, and Perspective

et al. 2019

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With the ongoing, exponential increase in ocean data from autonomous platforms, satellites, models, and in particular, the growing field of quantitative imaging, there arises a need for scalable and cost-efficient visualization tools to interpret these large volumes of data. With the recent proliferation of consumer grade head-mounted displays, the emerging field of virtual reality (VR) has demonstrated its benefit in numerous disciplines, ranging from medicine to archeology. However, these benefits have not received as much attention in the ocean sciences. Here, we summarize some of the ways that virtual reality has been applied to this field. We highlight a few examples in which we (the authors) demonstrate the utility of VR as a tool for ocean scientists. For oceanic datasets that are well-suited for three-dimensional visualization, virtual reality has the potential to enhance the practice of ocean science.

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“…However, the gradient-based index is advantageous for the SPR patterns [29]. The sharpness for focusing was used for light control in previous studies [15][16][17]30], the gradient-based index was considered for lighting, and the Tenenbaum gradient was finally chosen [31].…”

Section: Image Correction and Indexmentioning

confidence: 99%

Optimal Color Lighting for Scanning Images of Flat Panel Display using Simplex Search

Kim

Jin

et al. 2018

J. Imaging

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A system for inspecting flat panel displays (FPDs) acquires scanning images using multiline charge-coupled device (CCD) cameras and industrial machine vision. Optical filters are currently installed in front of these inspection systems to obtain high-quality images. However, the combination of optical filters required is determined manually and by using empirical methods; this is referred to as passive color control. In this study, active color control is proposed for inspecting FPDs. This inspection scheme requires the scanning of images, which is achieved using a mixed color light source and a mixing algorithm. The light source utilizes high-power light emitting diodes (LEDs) of multiple colors and a communication port to dim their level. Mixed light illuminates an active-matrix organic light-emitting diode (AMOLED) panel after passing through a beam expander and after being shaped into a line beam. The image quality is then evaluated using the Tenenbaum gradient after intensity calibration of the scanning images. The dimming levels are determined using the simplex search method which maximizes the image quality. The color of the light was varied after every scan of an AMOLED panel, and the variation was iterated until the image quality approached a local maximization. The number of scans performed was less than 225, while the number of dimming level combinations was 2048 4 . The proposed method can reduce manual tasks in setting-up inspection machines, and hence is useful for the inspection machines in FPD processes.

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Digital holographic microscopy and focusing methods based on image sharpness

Cited by 31 publications

References 22 publications

Assessment of holographic microscopy for quantifying marine particle size and concentration

Assessment of holographic microscopy for quantifying marine particle size and concentration

Virtual Reality and Oceanography: Overview, Applications, and Perspective

Optimal Color Lighting for Scanning Images of Flat Panel Display using Simplex Search

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