Dose optimization approach to fast X-ray microtomography of the lung alveoli

Abstract

A basic prerequisite for in vivo X-ray imaging of the lung is the exact determination of radiation dose. Achieving resolutions of the order of micrometres may become particularly challenging owing to increased dose, which in the worst case can be lethal for the imaged animal model. A framework for linking image quality to radiation dose in order to optimize experimental parameters with respect to dose reduction is presented. The approach may find application for current and future in vivo studies to facilitate proper experiment planning and radiation risk assessment on the one hand and exploit imaging capabilities on the other.

Four-Dimensional Morphological Evolution of an Aluminum Silicon Alloy Using Propagation-Based Phase Contrast X-ray Tomographic Microscopy

“…This approach utilizes information from the reconstructions of both absorption-based and phase retrieved images at a single object-detector distance, in a manner similar to the so-called fusion algorithm. 15,16) For reconstructions each 2D section of the 3D data set was segmented individually rather than directly in 3D. These binarized 2D sections were then combined to reveal the 3D microstructure.…”

Integrated approach to the data processing of four-dimensional datasets from phase-contrast x-ray tomography

“…In other words, whereas Ref. [14] tuned the propagation distance for optimal image quality, we optimize the relative contributions of PAG and FBP images in μ + (x, y), at a single sample-to-detector distance. In this way, varying the scalar allows for robust segmentation of our PCT images.…”

“…To circumvent the problems in segmenting PCT images, Ref. [14] proposed combining FBP and PAG images in Fourier space in their study of lung aveoli. Two-dimensional composite images were produced that were then easily thresholded [14].…”

“…[14] proposed combining FBP and PAG images in Fourier space in their study of lung aveoli. Two-dimensional composite images were produced that were then easily thresholded [14]. We propose an integrated image processing methodology that utilizes both phase and absorption contrast, derived from applying PAG and FBP algorithms separately to the raw PCT data, along with a suite of data processing methods to allow the automated segmentation of large datasets acquired through 4D tomography.…”

“…Unlike the work of Ref. [14], the images are combined in real space, and due to the complexity of the microstructure and the sensitivity of our measurements, a more robust image processing procedure is necessary. The hybrid images feature improved contrast-to-noise ratio and spatial resolution, thereby enabling the automated segmentation of such images by non-linear diffusion filtering and fuzzy logic.…”