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

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