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Magnetic microbubble-mediated ultrasound-MRI registration based on robust optical flow model.

Hou M, Chen C, Tang D, Luo S, Yang F, Gu N - Biomed Eng Online (2015)

Bottom Line: In order to reduce the influence of the speckle noise to registration, semi-automatic segmentations of US image and MRI were carried out by using active contour model.After that, a robust optical flow model between US image segmentation (floating image) and MRI segmentation (reference image) was built, and the vector flow field was estimated by using the Coarse-to-fine Gaussian pyramid and graduated non-convexity (GNC) schemes.The proposed algorithm combined with MMBs contends with larger deformation and performs well not only for local deformation but also for global deformation.

View Article: PubMed Central - HTML - PubMed

ABSTRACT

Background: As a dual-modality contrast agent, magnetic microbubbles (MMBs) can not only improve contrast of ultrasound (US) image, but can also serve as a contrast agent of magnetic resonance image (MRI). With the help of MMBs, a new registration method between US image and MRI is presented.

Methods: In this method, MMBs were used in both ultrasound and magnetic resonance imaging process to enhance the most important information of interest. In order to reduce the influence of the speckle noise to registration, semi-automatic segmentations of US image and MRI were carried out by using active contour model. After that, a robust optical flow model between US image segmentation (floating image) and MRI segmentation (reference image) was built, and the vector flow field was estimated by using the Coarse-to-fine Gaussian pyramid and graduated non-convexity (GNC) schemes.

Results: Qualitative and quantitative analyses of multiple group comparison experiments showed that registration results using all methods tested in this paper without MMBs were unsatisfactory. On the contrary, the proposed method combined with MMBs led to the best registration results.

Conclusion: The proposed algorithm combined with MMBs contends with larger deformation and performs well not only for local deformation but also for global deformation. The comparison experiments also demonstrated that ultrasound-MRI registration using the above-mentioned method might be a promising method for obtaining more accurate image information.

Show MeSH
Enhancement imaging based on MMBs. (a) US image without MMBs. (b) US image with MMBs. (c) MRI without MMBs. (d) MRI with MMBs.
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Figure 3: Enhancement imaging based on MMBs. (a) US image without MMBs. (b) US image with MMBs. (c) MRI without MMBs. (d) MRI with MMBs.

Mentions: Figure 3 includes US and MRI images showing the effectiveness of MMBs. I, II and III in Figures 3(a)~(d) represent the above-mentioned three objects imaging. Without MMBs the tube boundary can't be seen, while with MMBs, the tube upper boundary and three targets can be seen from the B-mode image. Under ultrasonic conditions, gas imaging shows strong echo whereas liquid imaging has no echo, and MMBs almost float upward to the three targets and upper boundary of the tube, therefore the echo of the tube upper boundary and three targets is strong. The phantom surface is hard, and not easily deformed, and moreover the convex array probe is used, which lead to the poor contact between the probe and the phantom surface, and further bring lateral wall echo drop-out.


Magnetic microbubble-mediated ultrasound-MRI registration based on robust optical flow model.

Hou M, Chen C, Tang D, Luo S, Yang F, Gu N - Biomed Eng Online (2015)

Enhancement imaging based on MMBs. (a) US image without MMBs. (b) US image with MMBs. (c) MRI without MMBs. (d) MRI with MMBs.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4306103&req=5

Figure 3: Enhancement imaging based on MMBs. (a) US image without MMBs. (b) US image with MMBs. (c) MRI without MMBs. (d) MRI with MMBs.
Mentions: Figure 3 includes US and MRI images showing the effectiveness of MMBs. I, II and III in Figures 3(a)~(d) represent the above-mentioned three objects imaging. Without MMBs the tube boundary can't be seen, while with MMBs, the tube upper boundary and three targets can be seen from the B-mode image. Under ultrasonic conditions, gas imaging shows strong echo whereas liquid imaging has no echo, and MMBs almost float upward to the three targets and upper boundary of the tube, therefore the echo of the tube upper boundary and three targets is strong. The phantom surface is hard, and not easily deformed, and moreover the convex array probe is used, which lead to the poor contact between the probe and the phantom surface, and further bring lateral wall echo drop-out.

Bottom Line: In order to reduce the influence of the speckle noise to registration, semi-automatic segmentations of US image and MRI were carried out by using active contour model.After that, a robust optical flow model between US image segmentation (floating image) and MRI segmentation (reference image) was built, and the vector flow field was estimated by using the Coarse-to-fine Gaussian pyramid and graduated non-convexity (GNC) schemes.The proposed algorithm combined with MMBs contends with larger deformation and performs well not only for local deformation but also for global deformation.

View Article: PubMed Central - HTML - PubMed

ABSTRACT

Background: As a dual-modality contrast agent, magnetic microbubbles (MMBs) can not only improve contrast of ultrasound (US) image, but can also serve as a contrast agent of magnetic resonance image (MRI). With the help of MMBs, a new registration method between US image and MRI is presented.

Methods: In this method, MMBs were used in both ultrasound and magnetic resonance imaging process to enhance the most important information of interest. In order to reduce the influence of the speckle noise to registration, semi-automatic segmentations of US image and MRI were carried out by using active contour model. After that, a robust optical flow model between US image segmentation (floating image) and MRI segmentation (reference image) was built, and the vector flow field was estimated by using the Coarse-to-fine Gaussian pyramid and graduated non-convexity (GNC) schemes.

Results: Qualitative and quantitative analyses of multiple group comparison experiments showed that registration results using all methods tested in this paper without MMBs were unsatisfactory. On the contrary, the proposed method combined with MMBs led to the best registration results.

Conclusion: The proposed algorithm combined with MMBs contends with larger deformation and performs well not only for local deformation but also for global deformation. The comparison experiments also demonstrated that ultrasound-MRI registration using the above-mentioned method might be a promising method for obtaining more accurate image information.

Show MeSH