Multimodal Image Fusion Based on Non-subsampled Shearlet Transform and Neuro-Fuzzy

Hermessi, Haithem; Mourali, Olfa; Zagrouba, Ezzeddine

doi:10.1007/978-3-319-60654-5_14

Cited by 2 publications

(1 citation statement)

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“…This approach utilizes an artificial neural network to train the parameters of the membership function, and has been used in the fusion of MRI/CT images [121,122]. Similar to fuzzy logic fusion, neuro-fuzzy logic can be combined with WT, Contourlet transform [123], NSST [124] and NSCT [125] to optimize fusion performance.…”

Section: Fuzzy Logic Based Methodsmentioning

confidence: 99%

Application of Image Fusion in Diagnosis and Treatment of Liver Cancer

Zhu

2020

Applied Sciences

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With the accelerated development of medical imaging equipment and techniques, image fusion technology has been effectively applied for diagnosis, biopsy and radiofrequency ablation, especially for liver tumor. Tumor treatment relying on a single medical imaging modality might face challenges, due to the deep positioning of the lesions, operation history and the specific background conditions of the liver disease. Image fusion technology has been employed to address these challenges. Using the image fusion technology, one could obtain real-time anatomical imaging superimposed by functional images showing the same plane to facilitate the diagnosis and treatments of liver tumors. This paper presents a review of the key principles of image fusion technology, its application in tumor treatments, particularly in liver tumors, and concludes with a discussion of the limitations and prospects of the image fusion technology.

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