Next-generation detection system Smart Lab

Senior Assistant Professor UEDA Ryosuke

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Themes

Development of X-ray CT reconstruction algorithm

Development of X-ray phase imaging method

Application of machine learning to X-ray phase imaging

Keywords

X-ray optics, X-ray imaging, X-ray phase imaging, tomography, machine learning, simulation

Research Activities

Exploration of X-ray phase imaging using experiments, mathematical physics, and data science.

X-rays can visualize the inside of a sample. In particular, computed tomography (CT), which is also used in the medical field, is an excellent observation technique for obtaining three-dimensional structures and cross-sectional images. In addition, X-rays have the property of waves. High-contrast images can be obtained by capturing the phase shift of the waves caused by the specimen. To utilize these techniques for medical diagnostics and material science, we are working on the following activities.

・Development of CT reconstruction algorithms and phase imaging methods We are developing methods to obtain CT and phase images under conditions that are difficult to measure with conventional methods by combining state-of-the-art mathematical information technology and machine learning methods with X-ray imaging methods.

・Exploration of the scientific principles of X-ray imaging We are exploring the scientific theories of X-ray imaging by examining experimentally observed phenomena using mathematical models based on the X-ray optics and verifying them through simulations.

ABS resins during laser engraving are visualized by high-speed X-ray phase imaging (differential phase images from the side view).