An object-oriented framework for medical image registration, fusion, and visualization

Zhu, Yang‐Ming; Cochoff, Steven M.

doi:10.1016/j.cmpb.2006.04.007

Cited by 36 publications

(19 citation statements)

References 14 publications

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“…In this case, only one kind of image may not be sufficient to provide accurate clinical requirements for the physicians. Therefore, the fusion of the multimodal medical images is necessary and it has become a promising and very challenging research area in recent years [2,3].…”

Section: Introductionmentioning

confidence: 99%

Medical Image Fusion via an Effective Wavelet-Based Approach

Yang

Park

Huang

et al. 2010

EURASIP J. Adv. Signal Process.

155

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A novel wavelet-based approach for medical image fusion is presented, which is developed by taking into not only account the characteristics of human visual system (HVS) but also the physical meaning of the wavelet coefficients. After the medical images to be fused are decomposed by the wavelet transform, different-fusion schemes for combining the coefficients are proposed: coefficients in low-frequency band are selected with a visibility-based scheme, and coefficients in high-frequency bands are selected with a variance based method. To overcome the presence of noise and guarantee the homogeneity of the fused image, all the coefficients are subsequently performed by a window-based consistency verification process. The fused image is finally constructed by the inverse wavelet transform with all composite coefficients. To quantitatively evaluate and prove the performance of the proposed method, series of experiments and comparisons with some existing fusion methods are carried out in the paper. Experimental results on simulated and real medical images indicate that the proposed method is effective and can get satisfactory fusion results.

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Section: Introductionmentioning

confidence: 99%

Medical Image Fusion via an Effective Wavelet-Based Approach

Yang

Park

Huang

et al. 2010

EURASIP J. Adv. Signal Process.

155

View full text Add to dashboard Cite

show abstract

“…Li and Wang employed the non-subsampled contourlet transform (NSCT) for thecombination ofMRI and SPECT in [5]. Compared with other multiscale decomposition, NSCT proposed by da Cunha et al [6] is a more prominent tool and it has been successfully used in image denoising [7] and image enhancement [8]. Because of its properties of multiscale, multi-direction, DOI: 10.9790/0661-1902010714 www.iosrjournals.org 10 | Page and the full shift-invariance, when it is used for image decomposition, it can capture the higher dimensional singularities such as edges and contours that cannot be effectively represented by the wavelets and avoid pseudo-Gibbs phenomena that presents in the contourlet transform.…”

Section: G Non-subsampled Contourlet Transform Based Methodsmentioning

confidence: 99%

A Survey on Multimodal Medical Image Fusion

Devanna¹,

Kumar²

2017

IOSR JCE

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“…The model contains some important properties of human visual perception, such as local orientation analysis and a Gaussian derivative model of early vision. Zhu and Cochoff [11] developed an object-oriented framework for image registration, fusion and visualization, which employed many design patterns to facilitate legacy code re-use, manage software complexity, and enhance the maintainability and portability of the framework.…”

Section: Introductionmentioning

confidence: 99%

Three-dimensional multimodal image non-rigid registration and fusion in a High Intensity Focused Ultrasound system

Suo

Liu

et al. 2011

Computer Aided Surgery

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High Intensity Focused Ultrasound (HIFU) has been successfully applied in tumor therapy. For a successful HIFU therapy, it is crucial to localize the tumor region accurately. In this paper, we present a semi-automatic non-rigid registration method for implementing image guided surgery navigation and localization by matching pre-operative CT/MR images and intra-operative ultrasound images. The global motion of the target is modeled by an affine transformation, while the local deformation of the target is described by Free-Form Deformation (FFD) based on B-splines. The results of our experiments on simulated and real data show that the non-rigid registration method based on HPV interpolation (partial volume based on the Hanning windowed sinc function) is effective at restraining local extrema and improves the accuracy of registration results. A preliminary clinical validation of the use of the non-rigid registration method in image guided localization of a HIFU system is also reported.

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An object-oriented framework for medical image registration, fusion, and visualization

Cited by 36 publications

References 14 publications

Medical Image Fusion via an Effective Wavelet-Based Approach

Medical Image Fusion via an Effective Wavelet-Based Approach

A Survey on Multimodal Medical Image Fusion

Three-dimensional multimodal image non-rigid registration and fusion in a High Intensity Focused Ultrasound system

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