Demkowicz MJ, Liu M, McCue ID, Seita M, Stuckner J, Xie K. Quantitative multi-image analysis in metals research.
MRS Commun 2022;
12:1030-1036. [PMID:
36474648 PMCID:
PMC9718709 DOI:
10.1557/s43579-022-00265-7]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Accepted: 09/02/2022] [Indexed: 06/17/2023]
Abstract
UNLABELLED
Quantitative multi-image analysis (QMA) is the systematic extraction of new information and insight through the simultaneous analysis of multiple, related images. We present examples illustrating the potential for QMA to advance materials research in multi-image characterization, automatic feature identification, and discovery of novel processing-structure-property relationships. We conclude by discussing opportunities and challenges for continued advancement of QMA, including instrumentation development, uncertainty quantification, and automatic parsing of literature data.
SUPPLEMENTARY INFORMATION
The online version contains supplementary material available at 10.1557/s43579-022-00265-7.
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