ORIGINAL RESEARCH article
Front. Phys.
Sec. Radiation Detectors and Imaging
Volume 13 - 2025 | doi: 10.3389/fphy.2025.1626220
This article is part of the Research TopicAdvanced Signal Processing Techniques in Radiation Detection and Imaging, Volume IIView all 3 articles
Mul-material Decomposition Method for Sandstone Spectral CT Images Based on I-MultiEncFusion-Net
Provisionally accepted
- 1North University of China, Taiyuan, Shanxi Province, China
- 2Institute of Geology and Geophysics, Chinese Academy of Sciences (CAS), Beijing, Beijing Municipality, China
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Material analysis in sandstone is essential for oil and gas extraction. Energy spectrum Computed Tomography (CT) can acquire various spectrally distinct datasets and reconstruct energy-selective images. Additionally, deep learning significantly label, while simultaneously incorporating correlations of base material images extracted by a High-Resolution Network (HRNet) as an auxiliary loss constraint for material decomposition. Validation experiments using spectral CT data of sandstone demonstrate the method's efficacy. Both simulated and practical results indicate that I-MultiEncFusion-Net exhibits superior generalization capability, preserves internal image details, and produces decomposed images with sharper edges.
Keywords: I-MultiEncFusion-Net, High-resolution network, multi-material decomposition, Layer Normalization and Feature Aggregation, Energy spectrum CT
Received: 10 May 2025; Accepted: 07 Jul 2025.
Copyright: © 2025 Wu, Zhang, Kong, Chen and ZOU. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Huihua Kong, North University of China, Taiyuan, 030051, Shanxi Province, China
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