A new MRI and PET image fusion algorithm based on BEMD and IHS methods

Dilmaghani, Mehdi Sefidgar; Daneshvar, Sabalan; Dousty, Mehdy

doi:10.1109/iraniancee.2017.7985242

Cited by 10 publications

(3 citation statements)

References 8 publications

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“…Haddadpour et al [8] proposed a new fusion method which combining the IHS method with the two-dimensional Hilbert transform. The method [9] introduces the concept of BEMD when merging high-and low-frequency subbands. BEMD is called bidirectional empirical mode decomposition and is extended by empirical mode decomposition.…”

Section: Fusion Methodsmentioning

confidence: 99%

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A Review of Multimodal Medical Image Fusion Techniques

Huang

Yang

Yin

et al. 2020

Computational and Mathematical Methods in Medicine

108

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The medical image fusion is the process of coalescing multiple images from multiple imaging modalities to obtain a fused image with a large amount of information for increasing the clinical applicability of medical images. In this paper, we attempt to give an overview of multimodal medical image fusion methods, putting emphasis on the most recent advances in the domain based on (1) the current fusion methods, including based on deep learning, (2) imaging modalities of medical image fusion, and (3) performance analysis of medical image fusion on mainly data set. Finally, the conclusion of this paper is that the current multimodal medical image fusion research results are more significant and the development trend is on the rise but with many challenges in the research field.

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Section: Fusion Methodsmentioning

confidence: 99%

“…MRI/CT fusion research trend chart. MRI/SPECT fusion study trend chart 9. Computational and Mathematical Methods in Medicine…”

mentioning

confidence: 99%

A Review of Multimodal Medical Image Fusion Techniques

Huang

Yang

Yin

et al. 2020

Computational and Mathematical Methods in Medicine

108

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“…This technique helps to retain data from both source color images. In [24], an image fusion technique is introduced based on bidimensional empirical mode decomposition (BEMD) and IHS methods to fuse MRI and PET images. In this technique, HIS method is utilized to decompose PET image and BEMD method is utilized to examine the PET image intensity.…”

Section: Literature Surveymentioning

confidence: 99%

An Efficient Medical Image Fusion Technique based on IT2FLDS

Ramya¹

2019

IJCA

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Multiple modal medical image fusion is an essential method for medical imaging technologies. In these Multi-modal medical image fusion usually are Positron Emission Tomography(PET)) and Single-photon Emission Computer Tomography(SPECT), Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) images are utilized. However, the conventional state-of-art-fusion-techniques consists of less redundant and less comprehensive information. Therefore, here, we present an image fusion technique to control non-linear uncertainties and provide stability based on IT2FLDS for multi-modal medical color images. The core idea is to perform fusion on color source images of either functional or structural type by extracting both large and small structural information which is rarely done in any other conventional state-of-art-techniques. This can be achieved with the help of IT2FLDS. The fuzzy membership functions based image fusion technique helps to combining low and high frequency components of multimodel medical color images. Experimental results proves the superiority of our proposed image fusion model in terms of visual and quantitative analysis like mutual information, standard deviation and Feature Point Similarity Measure.

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