Dual-Energy Computed Tomography Material Decomposition Network Based on Mamba and Channel Attention

Tianhao Ge; Fanning Kong; Zaifeng Shi; Yichao Jin; Qingjie Cao

doi:10.3788/LOP241085

Laser & Optoelectronics Progress, Volume. 62, Issue 2, 0237003(2025)

Dual-Energy Computed Tomography Material Decomposition Network Based on Mamba and Channel Attention

Tianhao Ge^1、*, Fanning Kong¹, Zaifeng Shi^1,3, Yichao Jin¹, and Qingjie Cao²

Author Affiliations

¹School of Microelectronics, Tianjin University, Tianjin 300072, China

²School of Mathematical Sciences, Tianjin Normal University, Tianjin 300387, China

³Tianjin Key Laboratory of Imaging and Sensing Microelectronic Technology, Tianjin 300072, China

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Figures & Tables(9)

Fig. 1. Structure of DM-Unet model

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Fig. 2. Structure of SSM-2D module

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Fig. 3. Treatment results of different substance decomposition methods

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Fig. 4. Comparison of ROI effects by different material decomposition methods

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Fig. 5. Comparison of SSIM and RMSE for results by different material decomposition methods

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Fig. 6. Comparison of PSNR for results by different material decomposition methods

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Fig. 7. Test results by different methods on mouse dataset

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Table 1. Quantitative indicators for base substances obtained by different material decomposition methods

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Table 1. Quantitative indicators for base substances obtained by different material decomposition methods

Method	PSNR /dB				SSIM				RMSE /（g∙cm^-3）
Method	Head （bone）	Head （tissue）	Chest （bone）	Chest （tissue）	Head （bone）	Head （tissue）	Chest （bone）	Chest （tissue）	Head （bone）	Head （tissue）	Chest （bone）	Chest （tissue）
DMID	26.15	25.59	26.82	25.06	0.9877	0.9855	0.9927	0.9833	0.092	0.097	0.088	0.091
ID^［27］	30.20	28.84	29.33	28.12	0.9894	0.9887	0.9936	0.9879	0.068	0.072	0.061	0.068
Butterfly-Net^［28］	33.11	31.90	34.27	32.33	0.9962	0.9975	0.9967	0.9958	0.057	0.054	0.052	0.050
Incept-Net^［29］	34.72	32.27	35.92	33.87	0.9971	0.9971	0.9964	0.9962	0.051	0.059	0.049	0.052
DM-Unet	35.67	33.09	36.54	36.15	0.9981	0.9978	0.9972	0.9969	0.044	0.051	0.041	0.043

Table 2. Results of ablation experiments

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Table 2. Results of ablation experiments

Section	ECA	RC	APRC	MS-SSIM	Edge	Bone			Tissue
Section	ECA	RC	APRC	MS-SSIM	Edge	PSNR /dB	SSIM	RMSE /（g∙cm^-3）	PSNR /dB	SSIM	RMSE /（g∙cm^-3）
Head		√				34.34	0.9945	0.071	32.39	0.9953	0.068
	√	√				34.67	0.9951	0.067	32.42	0.9957	0.064
	√		√			35.17	0.9954	0.052	32.74	0.9964	0.059
	√		√	√		35.53	0.9973	0.047	32.97	0.9977	0.055
	√		√	√	√	35.67	0.9981	0.044	33.09	0.9978	0.051
Chest		√				35.74	0.9935	0.069	35.30	0.9923	0.074
	√	√				35.88	0.9939	0.062	35.32	0.9927	0.064
	√		√			36.41	0.9964	0.049	35.74	0.9959	0.053
	√		√	√		36.52	0.9970	0.045	36.03	0.9964	0.049
	√		√	√	√	36.54	0.9972	0.041	36.15	0.9969	0.043

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Tianhao Ge, Fanning Kong, Zaifeng Shi, Yichao Jin, Qingjie Cao. Dual-Energy Computed Tomography Material Decomposition Network Based on Mamba and Channel Attention[J]. Laser & Optoelectronics Progress, 2025, 62(2): 0237003

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Paper Information

Category: Digital Image Processing

Received: Apr. 11, 2024

Accepted: May. 7, 2024

Published Online: Dec. 17, 2024

The Author Email:

DOI:10.3788/LOP241085

CSTR:32186.14.LOP241085

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology