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Scanning electron microscopy image representativeness: morphological data on nanoparticles
Author(s) -
ODZIOMEK KATARZYNA,
USHIZIMA DANIELA,
OBERBEK PRZEMYSLAW,
KURZYDŁOWSKI KRZYSZTOF JAN,
PUZYN TOMASZ,
HARANCZYK MACIEJ
Publication year - 2017
Publication title -
journal of microscopy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.569
H-Index - 111
eISSN - 1365-2818
pISSN - 0022-2720
DOI - 10.1111/jmi.12461
Subject(s) - scanning electron microscope , representativeness heuristic , sample (material) , microscopy , scanning confocal electron microscopy , image (mathematics) , characterization (materials science) , computer science , materials science , artificial intelligence , biological system , optics , computer vision , nanotechnology , chemistry , mathematics , physics , statistics , biology , chromatography
Summary A sample of a nanomaterial contains a distribution of nanoparticles of various shapes and/or sizes. A scanning electron microscopy image of such a sample often captures only a fragment of the morphological variety present in the sample. In order to quantitatively analyse the sample using scanning electron microscope digital images, and, in particular, to derive numerical representations of the sample morphology, image content has to be assessed. In this work, we present a framework for extracting morphological information contained in scanning electron microscopy images using computer vision algorithms, and for converting them into numerical particle descriptors. We explore the concept of image representativeness and provide a set of protocols for selecting optimal scanning electron microscopy images as well as determining the smallest representative image set for each of the morphological features. We demonstrate the practical aspects of our methodology by investigating tricalcium phosphate, Ca 3 (PO 4 ) 2 , and calcium hydroxyphosphate, Ca 5 (PO 4 ) 3 (OH), both naturally occurring minerals with a wide range of biomedical applications.