Automated defect analysis in electron microscopic images

Li, Wei; Field, Kevin G.; Morgan, Dane

doi:10.1038/s41524-018-0093-8

Title: Automated defect analysis in electron microscopic images

Abstract

Electron microscopy and defect analysis are a cornerstone of materials science, as they offer detailed insights on the microstructure and performance of a wide range of materials and material systems. Building a robust and flexible platform for automated defect recognition and classification in electron microscopy will result in the completion of analysis orders of magnitude faster after images are recorded, or even online during image acquisition. Automated analysis has the potential to be significantly more efficient, accurate, and repeatable than human analysis, and it can scale with the increasingly important methods of automated data generation. Herein, an automated recognition tool is developed based on a computer vison–based approach; it sequentially applies a cascade object detector, convolutional neural network, and local image analysis methods. We demonstrate that the automated tool performs as well as or better than manual human detection in terms of recall and precision and achieves quantitative image/defect analysis metrics close to the human average. The proposed approach works for images of varying contrast, brightness, and magnification. Furthermore, these promising results suggest that this and similar approaches are worth exploring for detecting multiple defect types and have the potential to locate, classify, and measure quantitative features for a rangemore »« less

Authors:

^[1];

^[2];

^[1]

Univ. of Wisconsin, Madison, WI (United States)
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

Publication Date:: 2018-07-18

Research Org.:: Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

Sponsoring Org.:: USDOE

OSTI Identifier:: 1462882

Grant/Contract Number:: AC05-00OR22725

Resource Type:: Accepted Manuscript

Journal Name:: npj Computational Materials

Additional Journal Information:: Journal Volume: 4; Journal Issue: 1; Journal ID: ISSN 2057-3960

Publisher:: Nature Publishing Group

Country of Publication:: United States

Language:: English

Subject:: 47 OTHER INSTRUMENTATION

Citation Formats


                    Li, Wei, Field, Kevin G., and Morgan, Dane. Automated defect analysis in electron microscopic images.  United States: N. p., 2018. 
Web.  doi:10.1038/s41524-018-0093-8.

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                    Li, Wei, Field, Kevin G., & Morgan, Dane. Automated defect analysis in electron microscopic images.  United States.  https://doi.org/10.1038/s41524-018-0093-8

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                    Li, Wei, Field, Kevin G., and Morgan, Dane. Wed .  
"Automated defect analysis in electron microscopic images".  United States.  https://doi.org/10.1038/s41524-018-0093-8.  https://www.osti.gov/servlets/purl/1462882.

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@article{osti_1462882,

  title        = {Automated defect analysis in electron microscopic images},

  author       = {Li, Wei and Field, Kevin G. and Morgan, Dane},

  abstractNote = {Electron microscopy and defect analysis are a cornerstone of materials science, as they offer detailed insights on the microstructure and performance of a wide range of materials and material systems. Building a robust and flexible platform for automated defect recognition and classification in electron microscopy will result in the completion of analysis orders of magnitude faster after images are recorded, or even online during image acquisition. Automated analysis has the potential to be significantly more efficient, accurate, and repeatable than human analysis, and it can scale with the increasingly important methods of automated data generation. Herein, an automated recognition tool is developed based on a computer vison–based approach; it sequentially applies a cascade object detector, convolutional neural network, and local image analysis methods. We demonstrate that the automated tool performs as well as or better than manual human detection in terms of recall and precision and achieves quantitative image/defect analysis metrics close to the human average. The proposed approach works for images of varying contrast, brightness, and magnification. Furthermore, these promising results suggest that this and similar approaches are worth exploring for detecting multiple defect types and have the potential to locate, classify, and measure quantitative features for a range of defect types, materials, and electron microscopic techniques.},

  doi          = {10.1038/s41524-018-0093-8},

  journal      = {npj Computational Materials},

  number       = 1,

  volume       = 4,

  place        = {United States},

  year         = {2018},

  month        = {7}

}

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Title: Automated defect analysis in electron microscopic images

Abstract

Citation Formats

Deep learning journal, May 2015

Face Description with Local Binary Patterns: Application to Face Recognition journal, December 2006

Deep Learning of Atomically Resolved Scanning Transmission Electron Microscopy Images: Chemical Identification and Tracking Local Transformations journal, October 2016

A practical implementation of face detection by using Matlab cascade object detector conference, October 2015

Image driven machine learning methods for microstructure recognition journal, October 2016

Robust Real-Time Face Detection journal, May 2004

Histograms of Oriented Gradients for Human Detection conference, January 2005

Exploring the microstructure manifold: Image texture representations applied to ultrahigh carbon steel microstructures journal, July 2017

A general review of human face detection including a study of neural networks and Haar feature-based cascade classifier in face detection conference, August 2014

Object recognition from local scale-invariant features conference, January 1999

Rethinking the Inception Architecture for Computer Vision conference, June 2016

Characterization of irradiation defect structures and densities by transmission electron microscopy journal, February 2015

Fully convolutional networks for semantic segmentation conference, June 2015

Dislocation loop formation in model FeCrAl alloys after neutron irradiation below 1 dpa journal, November 2017

Big Data Analytics for Scanning Transmission Electron Microscopy Ptychography journal, May 2016

Inferring low-dimensional microstructure representations using convolutional neural networks journal, November 2017

Watersheds in digital spaces: an efficient algorithm based on immersion simulations journal, June 1991

Structural materials for fission & fusion energy journal, November 2009

A Method for Detection and Classification of Glass Defects in Low Resolution Images conference, August 2011

Shape matching and object recognition using shape contexts journal, April 2002

TEM characterization of dislocation loops in irradiated bcc Fe-based steels journal, March 2013

Automated Detection and Segmentation of Synaptic Contacts in Nearly Isotropic Serial Electron Microscopy Images journal, October 2011

Diffraction contrast STEM of dislocations: Imaging and simulations journal, August 2011

Face Detection with the Faster R-CNN conference, May 2017

Object Detection with Discriminatively Trained Part-Based Models journal, September 2010

Rapid object detection using a boosted cascade of simple features conference, January 2001

Heterogeneous dislocation loop formation near grain boundaries in a neutron-irradiated commercial FeCrAl alloy journal, January 2017

Application of STEM characterization for investigating radiation effects in BCC Fe-based alloys journal, April 2015

Radiation tolerance of neutron-irradiated model Fe–Cr–Al alloys journal, October 2015

Mask R-CNN conference, October 2017

Big data and deep data in scanning and electron microscopies: deriving functionality from multidimensional data sets journal, May 2015

A deep convolutional neural network to analyze position averaged convergent beam electron diffraction patterns journal, May 2018

Better matching with fewer features: The selection of useful features in large database recognition problems conference, September 2009

Mask R-CNN journal, February 2020

Fully Convolutional Networks for Semantic Segmentation journal, April 2017

Deep Learning text, January 2018

Robust real-time face detection conference, January 2001

Rethinking the Inception Architecture for Computer Vision preprint, January 2015

Fully Convolutional Networks for Semantic Segmentation preprint, January 2016

A Deep Convolutional Neural Network to Analyze Position Averaged Convergent Beam Electron Diffraction Patterns text, January 2017

Deep Learning of Atomically Resolved Scanning Transmission Electron Microscopy Images: Chemical Identification and Tracking Local Transformations text, January 2018

Detection of Open Loop Defects in STEM Images of Irradiation-Damaged Alloys – Source Code for Detection and Image Dataset dataset, January 2018

Interplay Between Grain Boundaries and Radiation Damage journal, March 2019

Deep Learning for Semantic Segmentation of Defects in Advanced STEM Images of Steels journal, September 2019

Machine-learning-assisted screening of pure-silica zeolites for effective removal of linear siloxanes and derivatives journal, January 2020

Data-driven approach for synchrotron X-ray Laue microdiffraction scan analysis journal, October 2019

Deep learning
journal, May 2015

Face Description with Local Binary Patterns: Application to Face Recognition
journal, December 2006

Deep Learning of Atomically Resolved Scanning Transmission Electron Microscopy Images: Chemical Identification and Tracking Local Transformations
journal, October 2016

A practical implementation of face detection by using Matlab cascade object detector
conference, October 2015

Image driven machine learning methods for microstructure recognition
journal, October 2016

Robust Real-Time Face Detection
journal, May 2004

Histograms of Oriented Gradients for Human Detection
conference, January 2005

Exploring the microstructure manifold: Image texture representations applied to ultrahigh carbon steel microstructures
journal, July 2017

A general review of human face detection including a study of neural networks and Haar feature-based cascade classifier in face detection
conference, August 2014

Object recognition from local scale-invariant features
conference, January 1999

Rethinking the Inception Architecture for Computer Vision
conference, June 2016

Characterization of irradiation defect structures and densities by transmission electron microscopy
journal, February 2015

Fully convolutional networks for semantic segmentation
conference, June 2015

Dislocation loop formation in model FeCrAl alloys after neutron irradiation below 1 dpa
journal, November 2017

Big Data Analytics for Scanning Transmission Electron Microscopy Ptychography
journal, May 2016

Inferring low-dimensional microstructure representations using convolutional neural networks
journal, November 2017

Watersheds in digital spaces: an efficient algorithm based on immersion simulations
journal, June 1991

Structural materials for fission & fusion energy
journal, November 2009

A Method for Detection and Classification of Glass Defects in Low Resolution Images
conference, August 2011

Shape matching and object recognition using shape contexts
journal, April 2002

TEM characterization of dislocation loops in irradiated bcc Fe-based steels
journal, March 2013

Automated Detection and Segmentation of Synaptic Contacts in Nearly Isotropic Serial Electron Microscopy Images
journal, October 2011

Diffraction contrast STEM of dislocations: Imaging and simulations
journal, August 2011

Face Detection with the Faster R-CNN
conference, May 2017

Object Detection with Discriminatively Trained Part-Based Models
journal, September 2010

Rapid object detection using a boosted cascade of simple features
conference, January 2001

Heterogeneous dislocation loop formation near grain boundaries in a neutron-irradiated commercial FeCrAl alloy
journal, January 2017

Application of STEM characterization for investigating radiation effects in BCC Fe-based alloys
journal, April 2015

Radiation tolerance of neutron-irradiated model Fe–Cr–Al alloys
journal, October 2015

Mask R-CNN
conference, October 2017

Big data and deep data in scanning and electron microscopies: deriving functionality from multidimensional data sets
journal, May 2015

A deep convolutional neural network to analyze position averaged convergent beam electron diffraction patterns
journal, May 2018

Better matching with fewer features: The selection of useful features in large database recognition problems
conference, September 2009

Mask R-CNN
journal, February 2020

Fully Convolutional Networks for Semantic Segmentation
journal, April 2017

Deep Learning
text, January 2018

Robust real-time face detection
conference, January 2001

Rethinking the Inception Architecture for Computer Vision
preprint, January 2015

Fully Convolutional Networks for Semantic Segmentation
preprint, January 2016

A Deep Convolutional Neural Network to Analyze Position Averaged Convergent Beam Electron Diffraction Patterns
text, January 2017

Deep Learning of Atomically Resolved Scanning Transmission Electron Microscopy Images: Chemical Identification and Tracking Local Transformations
text, January 2018

Detection of Open Loop Defects in STEM Images of Irradiation-Damaged Alloys – Source Code for Detection and Image Dataset
dataset, January 2018

Interplay Between Grain Boundaries and Radiation Damage
journal, March 2019

Deep Learning for Semantic Segmentation of Defects in Advanced STEM Images of Steels
journal, September 2019

Machine-learning-assisted screening of pure-silica zeolites for effective removal of linear siloxanes and derivatives
journal, January 2020

Data-driven approach for synchrotron X-ray Laue microdiffraction scan analysis
journal, October 2019