Model-free classification of X-ray scattering signals applied to image segmentation

Autor: Marco Stampanoni, Martin J. Blunt, Zsuzsanna Varga, Andreas Menzel, Leon Leu, Ana Diaz, Viviane Lutz-Bueno, Manuel Guizar-Sicairos, Maxime Lebugle, Pablo Villanueva-Perez, P. Bertier, Zhentian Wang, Christian David, Andreas Busch, Carolina Arboleda, A. Georgiadis, Joyce Schmatz
Přispěvatelé: University of Zurich, Guizar-Sicairos, M
Jazyk: angličtina
Rok vydání: 2018
Předmět:
Chemistry
Multidisciplinary
02 engineering and technology
DIFFRACTION
OPALINUS CLAY
01 natural sciences
09 Engineering
GAS-TRANSPORT
SCANNING SAXS
Crystallography
02 Physical Sciences
polarized resonant soft X-ray scattering
Small-angle X-ray scattering
021001 nanoscience & nanotechnology
Sample (graphics)
Research Papers
Chemistry
Physical Sciences
ddc:540
Inorganic & Nuclear Chemistry
0210 nano-technology
BONE
anisotropic nanostructures
Similarity (geometry)
Astrophysics::High Energy Astrophysical Phenomena
BENIGN
610 Medicine & health
Genetics and Molecular Biology
010403 inorganic & nuclear chemistry
General Biochemistry
Genetics and Molecular Biology
1300 General Biochemistry
Genetics and Molecular Biology
electromagnetic modeling
10049 Institute of Pathology and Molecular Pathology
BREAST-CANCER
Cluster analysis
01 Mathematical Sciences
Science & Technology
Pixel
Scattering
business.industry
Dimensionality reduction
WAXS MICROSCOPY
Pattern recognition
Image segmentation
ANGLE
0104 chemical sciences
TENSOR TOMOGRAPHY
General Biochemistry
Artificial intelligence
business
Zdroj: Journal of applied crystallography 51(5), 1378-1386 (2018). doi:10.1107/S1600576718011032
Journal of Applied Crystallography
Journal of Applied Crystallography, 51
ISSN: 0021-8898
1600-5767
DOI: 10.5167/uzh-158041
Popis: In most cases, the analysis of small-angle and wide-angle X-ray scattering (SAXS and WAXS, respectively) requires a theoretical model to describe the sample's scattering, complicating the interpretation of the scattering resulting from complex heterogeneous samples. This is the reason why, in general, the analysis of a large number of scattering patterns, such as are generated by time-resolved and scanning methods, remains challenging. Here, a model-free classification method to separate SAXS/WAXS signals on the basis of their inflection points is introduced and demonstrated. This article focuses on the segmentation of scanning SAXS/WAXS maps for which each pixel corresponds to an azimuthally integrated scattering curve. In such a way, the sample composition distribution can be segmented through signal classification without applying a model or previous sample knowledge. Dimensionality reduction and clustering algorithms are employed to classify SAXS/WAXS signals according to their similarity. The number of clusters, i.e. the main sample regions detected by SAXS/WAXS signal similarity, is automatically estimated. From each cluster, a main representative SAXS/WAXS signal is extracted to uncover the spatial distribution of the mixtures of phases that form the sample. As examples of applications, a mudrock sample and two breast tissue lesions are segmented.
Journal of Applied Crystallography, 51
ISSN:0021-8898
ISSN:1600-5767
Databáze: OpenAIRE
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