scholarly journals Size characterization of core-corona spherical particles using model-free inverse Fourier transform method

Polymer ◽  
2020 ◽  
Vol 202 ◽  
pp. 122623
Author(s):  
Liwen Chen ◽  
Sangwoo Lee
Keyword(s):  
Fourier Transform ◽  
Inverse Fourier Transform ◽  
Spherical Particles ◽  
Transform Method ◽  
Fourier Transform Method ◽  
Model Free ◽  
Size Characterization

Characterization of static and dynamic microstructures by microscopic interferometry based on a Fourier transform method

2006 ◽  
Vol 17 (6) ◽  
pp. 1312-1318 ◽  
Author(s):  
Xiaodong Hu ◽  
Gang Liu ◽  
Chunguang Hu ◽  
Tong Guo ◽  
Xiaotang Hu
Keyword(s):  
Fourier Transform ◽  
Transform Method ◽  
Fourier Transform Method

scholarly journals Deep Learning Based Instance Segmentation of Titanium Dioxide Particles in the Form of Agglomerates in Scanning Electron Microscopy

Nanomaterials ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 968
Author(s):  
Paul Monchot ◽  
Loïc Coquelin ◽  
Khaled Guerroudj ◽  
Nicolas Feltin ◽  
Alexandra Delvallée ◽  
...  
Keyword(s):  
Electron Microscopy ◽  
Scanning Electron Microscopy ◽  
Titanium Dioxide ◽  
Learning Community ◽  
Spherical Particles ◽  
Average Value ◽  
Size Characterization ◽  
Scanning Electron

The size characterization of particles present in the form of agglomerates in images measured by scanning electron microscopy (SEM) requires a powerful image segmentation tool in order to properly define the boundaries of each particle. In this work, we propose to use an algorithm from the deep statistical learning community, the Mask-RCNN, coupled with transfer learning to overcome the problem of generalization of the commonly used image processing methods such as watershed or active contour. Indeed, the adjustment of the parameters of these algorithms is almost systematically necessary and slows down the automation of the processing chain. The Mask-RCNN is adapted here to the case study and we present results obtained on titanium dioxide samples (non-spherical particles) with a level of performance evaluated by different metrics such as the DICE coefficient, which reaches an average value of 0.95 on the test images.

Sign in / Sign up

Export Citation Format

Share Document