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Low-dose sparse-view HAADF-STEM-EDX
tomography of nanocrystals using
unsupervised deep learning
Eunju Cha*, Hyungjin Chung*, Jaeduck Jang, Junho Lee, Eunha Lee, Jong Chul Ye
*: Equal contribution
Hyungjin Chung
Introduction
HAADF-STEM-EDX tomography
• High-angle annular dark-field (HAADF)
• Energy dispersive X-ray (EDX)
• Both signals acquired through scanning
transmission electron microscopy (STEM)
• Signals are…
• Sparse view: 2~13 views
• Low dose: very low SNR
Method
Unsupervised method for 3D tomographic reconstruction
CycleGAN-based kernel regression
• Physics informed
cycleGAN for
unsupervised kernel
regression network
• Exploit the correlation btw.
EDX / z-contrast images
• Dramatically increase SNR
Unsupervised method for 3D tomographic reconstruction
ProjectionGAN for 3D recon.
• CycleGAN boosts quality of unmeasured-view projections - ProjectionGAN
Results
Kernel regression results
proposed
Phantom 3D reconstruction
Quantom dot (QD) 3D reconstruction (3-view)

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Low-dose sparse-view HAADF-STEM-EDX tomography of nanocrystals using unsupervised deep learning.pptx