• Laser & Optoelectronics Progress
  • Vol. 56, Issue 15, 151004 (2019)
Jian Wang and Xisheng Wu*
Author Affiliations
  • School of Internet of Things Engineering, Jiangnan University, Wuxi, Jiangsu 214122, China
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    DOI: 10.3788/LOP56.151004 Cite this Article Set citation alerts
    Jian Wang, Xisheng Wu. Medical Image Fusion Based on Improved Guided Filtering and Dual-Channel Pulse Coupled Neural Networks[J]. Laser & Optoelectronics Progress, 2019, 56(15): 151004 Copy Citation Text show less
    Diagram of NSST decomposition process
    Fig. 1. Diagram of NSST decomposition process
    Model of dual-channel PCNN
    Fig. 2. Model of dual-channel PCNN
    Flow chart of fusion based on dual-channel PCNN and improved guided filtering
    Fig. 3. Flow chart of fusion based on dual-channel PCNN and improved guided filtering
    CT and MR-T1 images and fusion images of each algorithm. (a) MR-Gad; (b) SPECT-T1; (c) algorithm in Ref. [3]; (d) algorithm in Ref. [4]; (e) algorithm in Ref. [10]; (f) proposed algorithm
    Fig. 4. CT and MR-T1 images and fusion images of each algorithm. (a) MR-Gad; (b) SPECT-T1; (c) algorithm in Ref. [3]; (d) algorithm in Ref. [4]; (e) algorithm in Ref. [10]; (f) proposed algorithm
    MR-Gad and SPECT-T1 images and fusion images of each algorithm. (a) MR-Gad; (b) SPECT-T1; (c) algorithm in Ref. [3]; (d) algorithm in Ref. [4]; (e) algorithm in Ref. [10]; (f) proposed algorithm
    Fig. 5. MR-Gad and SPECT-T1 images and fusion images of each algorithm. (a) MR-Gad; (b) SPECT-T1; (c) algorithm in Ref. [3]; (d) algorithm in Ref. [4]; (e) algorithm in Ref. [10]; (f) proposed algorithm
    MR-T1 and PET images and fusion images of each algorithm. (a) MR-Gad; (b) SPECT-T1; (c) algorithm in Ref. [3]; (d) algorithm in Ref. [4]; (e) algorithm in Ref. [10]; (f) proposed algorithm
    Fig. 6. MR-T1 and PET images and fusion images of each algorithm. (a) MR-Gad; (b) SPECT-T1; (c) algorithm in Ref. [3]; (d) algorithm in Ref. [4]; (e) algorithm in Ref. [10]; (f) proposed algorithm
    Source imageEvaluationindexAlgorithmin Ref. [3]Algorithmin Ref. [4]Algorithmin Ref. [10]Proposedalgorithm
    CTMR-T1iM2.44513.21352.15433.6669
    NE3.42564.68242.91955.0323
    MSSI0.80750.83920.83160.8507
    Ga7.05616.85357.21627.1859
    Table 1. Evaluation index of each algorithm for CT and MR-T1 image fusion
    Source imageEvaluationindexAlgorithmin Ref. [3]Algorithmin Ref. [4]Algorithmin Ref. [10]Proposedalgorithm
    MR-GadSPECT-T1iM1.48510.957391.34041.7719
    NE4.09494.06464.33584.152
    MSSI0.63730.75970.73110.7734
    Ga4.62065.06376.00856.2403
    Table 2. Evaluation index of each algorithm for MR-Gad and SPECT-T1 image fusion
    Source imageEvaluationindexAlgorithmin Ref. [3]Algorithmin Ref. [4]Algorithmin Ref. [10]Proposedalgorithm
    MR-T1PETiM1.25331.56431.23821.6606
    NE2.85832.84822.93184.0349
    MSSI0.74330.73570.76040.7670
    Ga4.49154.85465.06655.4657
    Table 3. Evaluation index of each algorithm for MR-T1 and PET image fusion
    Jian Wang, Xisheng Wu. Medical Image Fusion Based on Improved Guided Filtering and Dual-Channel Pulse Coupled Neural Networks[J]. Laser & Optoelectronics Progress, 2019, 56(15): 151004
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