<title>Fluorescence microtomography: multiangle image acquisition and 3D digital reconstruction</title>

Abstract

We have developed a prototype fluorescence microscope which, using tomographic image acquisition and reconstruction techniques, can automatically combine conventional and/or confocal image stacks taken at a number of orientations into a single, very-high-resolution 3D image. We use the term "microtomography" in a broad sense to denote digital image reconstruction from multiple imaging operations which are not necessarily projections. Our system holds a biological specimen inside a thin capillary tube which is rotatable over a 360 degree range beneath an immersion objective. 3D fluorescence image data volumes are acquired by frame-grabbing a through-focus series of 2D images at each angle of rotation. Digital reconstruction of the multiangle data volumes produces a single very-high-resolution 3D image and involves algorithms which perform rotation, interpolation, alignment and normalization operations in frequency (Fourier) space.

4D retrospective lineage tracing using SPIM for zebrafish organogenesis studies

“…Therefore microscope systems that employ a horizontal rotation axis typically have the sample either inside a rigid glass capillary, e.g. [25], which will introduce aberrations in living samples that require an aqueous environment, or on the surface of such capillaries, which limits the viewing angle to a fraction of the full 360 [26]. Since in SPIM the rotation axis is parallel to the force of gravity, deformations of the agarose are minimized and accurate rotation and positioning of the sample are possible.…”

A Bayesian reconstruction method for micro‐rotation imaging in light microscopy

“…Through-stacking protocols compound this problem such that any resulting 3D reconstruction is distorted by this x, y, z resolution asymmetry, and the objects surface and volume are convolved in a complex and mostly irrecuperable manner. To overcome these problems, axial tomography (tilted-view) has been proposed by Shaw et al (1989), Cogswell et al (1996), Bradl et al (1996), Heintzmann and Cremer (2002) and Renaud et al (2007). In axial tomography, several z-stack data sets are collected from different orientations by rotating the specimen, by known angles and then all the views are fused into a single reconstruction volume (see Fig.…”

Intensity-based point-spread-function-aware registration for multi-view applications in optical microscopy

“…This anisotropy translates to an axial resolution that is worse than the lateral resolution in the acquired data. Multi-view microscopy attempts to circumvent this problem by merging acquisitions from multiple tilted directions [1][2][3][4][5][6][7]. However, operations therein, such as multi-view fusion and deconvolution, require the volumes to be precisely registered before they can be used.…”

“…In lieu of external markers, Keller et al [10] followed a data-specific strategy to automatically detect cell nuclei and treat them as landmarks for multi-view registration. Others have used techniques such as cross-correlation [1,2,4,5] based on the pixel-wise similarity between datasets for registration. However, such approaches can lead to inaccuracies because they ignore the anisotropy inherent in the image formation process.…”