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- Title
Rapid Image Segmentation Pipeline to Support Multimodal STEM Acquisition.
- Authors
Day, Alexandra L; Wahl, Carolin B; Reis, Roberto dos; Liao, Wei-keng; Li, Youjia; Kilic, Muhammed Nur Talha; Mirkin, Chad A; Dravid, Vinayak P; Choudhary, Alok; Agrawal, Ankit
- Abstract
This article discusses a fully automated pipeline for processing and segmenting grayscale images in order to support the acquisition of analytical data in Scanning Transmission Electron Microscopy (STEM). The pipeline utilizes computer vision and unsupervised segmentation tools to identify and size regions within high-quality images for further data acquisition. The authors designed and validated their method using grayscale images collected on a scanning transmission electron microscope, and they report significant improvements in speed and storage space compared to current methods. The article concludes by highlighting the potential of computer vision and unsupervised clustering techniques to accelerate automated materials characterization.
- Subjects
SCANNING transmission electron microscopy; IMAGE segmentation; MATERIALS science; TRANSMISSION electron microscopes; SCANNING electron microscopes; DEEP learning
- Publication
Microscopy & Microanalysis, 2024, Vol 30, p1
- ISSN
1431-9276
- Publication type
Article
- DOI
10.1093/mam/ozae044.204