Direct reconstruction for simultaneous dual-tracer PET imaging based on multi-task learning

EJNMMI Research

Table 2 Quantitative results of the simulation experiments

EXP	Dataset	Method	Tracer I			Tracer II
			MSE	MS-SSIM	PSNR	MSE	MS-SSIM	PSNR
1-1	Individual difference I	FBP-CNN	2.3561	0.8783	23.92	6.1724	0.9248	30.32
		Proposed	1.2661	0.9534	27.61	1.8536	0.9927	35.85
1-2	Individual difference II	FBP-CNN	4.1080	0.8586	22.21	11.4220	0.9139	26.67
		Proposed	1.4566	0.9592	27.47	4.5473	0.9889	33.57
2	Tracer combination I	FBP-CNN	1.5350	0.8222	23.86	7.5759	0.9231	30.00
		Proposed	0.3599	0.9705	30.02	2.7090	0.9897	34.41
	Tracer combination II	FBP-CNN	4.8387	0.8956	24.32	2.9304	0.4762	17.13
		Proposed	0.6687	0.9872	32.77	0.2906	0.9561	28.52
3	Scanning protocol I	FBP-CNN	2.9040	0.8555	24.63	1.2512	0.8592	23.81
		Proposed	0.4325	0.9787	31.94	0.2508	0.9789	30.51
	Scanning protocol II	FBP-CNN	2.8501	0.8560	24.75	1.1370	0.8691	24.40
		Proposed	0.4504	0.9778	31.78	0.2753	0.9759	29.75
	Scanning protocol III	FBP-CNN	3.1287	0.8539	24.71	1.2879	0.8116	21.16
		Proposed	0.4722	0.9799	32.28	0.2476	0.9676	28.58

The lower MSE, higher MS-SSIM and higher PSNR are noted in bold font in the comparison of the proposed method and FBP-CNN