Soft tissue microscopy with X-ray grating interferometry
(2025) FYSM64 20251Department of Physics
- Abstract
- Grating-based X-ray interferometry is a promising imaging technique for visualizing soft biological tissues such as muscles or lungs, which are often difficult to distinguish using conventional absorption-based X-ray imaging. It enables the retrieval of absorption, 2 directional differential phase and dark field signal from a single shot measurement. In this work a single grating imaging experiment was performed at the ForMAX beamline at the MAX IV synchrotron. A simulation tool was developed in Python to simulate the
interference patterns of an arbitrary phase grating under the coherence conditions of the synchrotron. The simulation was tested for three different phase gratings and proved to have a qualitative agreement between... (More) - Grating-based X-ray interferometry is a promising imaging technique for visualizing soft biological tissues such as muscles or lungs, which are often difficult to distinguish using conventional absorption-based X-ray imaging. It enables the retrieval of absorption, 2 directional differential phase and dark field signal from a single shot measurement. In this work a single grating imaging experiment was performed at the ForMAX beamline at the MAX IV synchrotron. A simulation tool was developed in Python to simulate the
interference patterns of an arbitrary phase grating under the coherence conditions of the synchrotron. The simulation was tested for three different phase gratings and proved to have a qualitative agreement between simulation and experiment. The simulation can thus be used in future experiments to assess whether grating-based imaging is feasible under specific beamline conditions for a given grating.
Additionally, a continuity equation based reconstruction algorithm with similar assumptions as propagation based imaging was implemented in python and tested on full field X-ray microscopy data. The algorithm enabled a quick and efficient multi-contrast retrieval of the data. Though the images had a low signal to noise ratio and the method is sensitive to experimental instabilities it is still a valuable tool for quick sample characterization. (Less) - Popular Abstract
- Everyone has seen classic X-ray images: bones glowing white, surrounded by shadowy outlines of softer tissue. While these images are excellent for spotting fractures, they do not reveal much about the organs, muscles, or tissues that make up most of the human body. To truly understand soft biological structures, we need more advanced imaging tools that can reveal subtle differences without the need for invasive procedures.
Traditional X-ray imaging relies on obtaining contrast through absorption. Denser materials like bones block more X-rays while soft tissues allow more X-rays to pass through. However , the difference in absorption between different types of soft tissues is small, creating a challenge to differentiate among them. For... (More) - Everyone has seen classic X-ray images: bones glowing white, surrounded by shadowy outlines of softer tissue. While these images are excellent for spotting fractures, they do not reveal much about the organs, muscles, or tissues that make up most of the human body. To truly understand soft biological structures, we need more advanced imaging tools that can reveal subtle differences without the need for invasive procedures.
Traditional X-ray imaging relies on obtaining contrast through absorption. Denser materials like bones block more X-rays while soft tissues allow more X-rays to pass through. However , the difference in absorption between different types of soft tissues is small, creating a challenge to differentiate among them. For this reason, our research explores different ways to obtain image contrast. An experimental method which can capture multiple contrast mechanisms at once is grating interferometry. For this technique a grating is placed between the X-ray source and the sample. The grating will create an interference pattern, much like overlapping ripples in a pond. When a sample is placed on the path of this interference pattern, it distorts them in a unique way. These distortions can then be analyzed to extract not just one but three types of image contrast: absorption, differential phase contrast (how X-rays are refracted) and dark-field contrast (how they scatter in small angles). The properties and shape of the interference pattern is of vital importance for the image quality.
To this end, a simulation tool was developed using Python. It models how the interference patterns change under different experimental conditions such as varying grating to detector distance or the size of the X-ray source. This tool was tested by comparing it to an experiment at the MAX IV synchrotron, a facility where very bright X-rays are generated. The simulations qualitatively matched the measured data from the experiment, validating the tool can be used for grating characterization for future experiments.
In addition, a fast image reconstruction algorithm based on previous works was coded in Python. This method processes grating based X-ray microscopy data to produce images with all three contrast types using only a single exposure. The algorithm was tested on biological samples, like a tree branch to test its quality. Though the results showed to have a lower resolution compared to other algorithms it can still be used to visulualize the sample quickly and efficiently.
This is especially useful in fast-paced experimental settings where time is limited for a quick characterization of the sample.
In conclusion, advanced X-ray techniques like grating interferometry offer a powerful way to visualize soft biological tissues by providing multiple types of contrast in a single image. The development of a Python-based simulation tool and a fast reconstruction algorithm enables more efficient experiment planning and rapid image generation for future experiments. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/9201309
- author
- van Dijk, Benjamin LU
- supervisor
-
- Martin Bech LU
- Jesper Wallentin LU
- organization
- course
- FYSM64 20251
- year
- 2025
- type
- H2 - Master's Degree (Two Years)
- subject
- keywords
- X-ray, Grating interferometry, synchrotron, radiation, imaging, contrast, dark field, small angle scattering, phase contrast
- language
- English
- id
- 9201309
- date added to LUP
- 2025-06-30 11:46:27
- date last changed
- 2025-06-30 11:46:27
@misc{9201309,
abstract = {{Grating-based X-ray interferometry is a promising imaging technique for visualizing soft biological tissues such as muscles or lungs, which are often difficult to distinguish using conventional absorption-based X-ray imaging. It enables the retrieval of absorption, 2 directional differential phase and dark field signal from a single shot measurement. In this work a single grating imaging experiment was performed at the ForMAX beamline at the MAX IV synchrotron. A simulation tool was developed in Python to simulate the
interference patterns of an arbitrary phase grating under the coherence conditions of the synchrotron. The simulation was tested for three different phase gratings and proved to have a qualitative agreement between simulation and experiment. The simulation can thus be used in future experiments to assess whether grating-based imaging is feasible under specific beamline conditions for a given grating.
Additionally, a continuity equation based reconstruction algorithm with similar assumptions as propagation based imaging was implemented in python and tested on full field X-ray microscopy data. The algorithm enabled a quick and efficient multi-contrast retrieval of the data. Though the images had a low signal to noise ratio and the method is sensitive to experimental instabilities it is still a valuable tool for quick sample characterization.}},
author = {{van Dijk, Benjamin}},
language = {{eng}},
note = {{Student Paper}},
title = {{Soft tissue microscopy with X-ray grating interferometry}},
year = {{2025}},
}