Segmentation and visualization of digital in-line holographic microscopy of three-dimensional scenes using reconstructed intensity images

Abstract

This paper demonstrates a technique that could prove useful for extracting three-dimensional (3D) models from a single two-dimensional (2D) digital in-line holographic microscopy (DIHM) recording. Multiple intensity images are reconstructed at a range of depths through a transmissive or partially transmissive scene recorded by DIHM. A two step segmentation of each of these reconstructed intensity images facilitates the construction of a data set of surfaces in 3D. First an adaptive thresholding step and then a border following step are implemented. The surfaces of segmented features are rendered in 3D by applying the marching cubes algorithm to polygonize the data set. Experimental results for a real world DIHM capture of a transmissive glass sample are presented to demonstrate this segmentation and visualization process.

Lensless multispectral digital in-line holographic microscope

“…8) falls below (outside) the threshold cutoff value, thus producing a small underestimate of the percentage confluence. A nonuniform or adaptive thresholding technique 21 could be applied to minimize the error in selecting areas that contain cells, and such techniques can be readily implemented numerically. In this paper, our aim is to provide automated estimating of the percentage confluence values.…”

“…Using multiple computer-based amplitude reconstructions at differing depths (i.e., by simulating the backpropagation of the field through space), a volume or tomographic image surface of imaged features is rendered. 21 As with standard imaging systems, greater lateral and longitudinal resolution is achievable by increasing the systems numerical aperture (NA). 22 However, in the case of digital holographic reconstruction, the resolution depends on the location of the plane examined.…”

Multispectral lensless digital holographic microscope: imaging MCF-7 and MDA-MB-231 cancer cell cultures

“…An adaptive threshold algorithm [15] was used to remove unwanted out of focus features. These included background noise and out of focus features, as well contributions from speckle noise and the twin image.…”

“…From this two-dimensional intensity image, the object wavefront is numerically reconstructed to give a full hologram as a complex image with both amplitude and phase information. Using multiple computer-based amplitude reconstructions at differing depths, a three-dimensional (3D) surface of imaged features is rendered [15]. Greater lateral and longitudinal resolution is achievable by increasing the systems numerical aperture (NA) [16].…”