Realistic IVUS Image Generation in Different Intraluminal Pressures

Cardoso, Fernando; Moraes, Matheus Cardoso; Furuie, S.S.

doi:10.1016/j.ultrasmedbio.2012.08.005

Cited by 11 publications

(20 citation statements)

References 43 publications

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“…Due to computational models advancements (Hoskins, 2008), numerical phantoms were used. The phantoms, deformation outcomes and gold standard strain maps were obtained by the framework described by Cardoso et al (2012). The complete method is embedded in the Toolbox called IVUSSim.…”

Section: Methodsmentioning

confidence: 99%

“…It is a citationware software, available online at http://www. leb.usp.br/IVUSSim, free of charge for research and educational purposes (Cardoso et al, 2012). A brief explanation of the framework is given below.…”

Section: Methodsmentioning

confidence: 99%

“…In addition, some related results, such as the corresponding non-deformed and deformed gray level images (Figure 2c), strain maps ( Figure 2d) are also generated to serve as gold standard to many investigations (Cardoso et al, 2012). In summary, the framework works as follows: First the user selects an available, or designs a new coronary cross section model, representing a coronary cross section in a diastole cardiac phase (Figure 2a).…”

Section: Realistic Ivus Image Generation In Differentmentioning

confidence: 99%

“…Therefore, the gray level images, and strain map (Figures 2c and d) can be used as gold standards for investigation of structural deformations and shifting of small particles, such as speckle or pixel. For more information about the phantom creation framework, please refer to Cardoso et al (2012).…”

Section: Realistic Ivus Image Generation In Differentmentioning

confidence: 99%

“…After, the Plaque Area Computation (Figures 1c and d), the plaque areas under inspection in the IVUS images are segmented and the area of a suspecting plaque quantified in different pressures. Next, Ratio of the Plaque Area Variation, the overall percentage of plaque deformation is calculated (Cardoso et al, 2012). As a result, the type of the predominant tissue of the suspecting area is estimated based on the regional deformation values.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Atherosclerotic plaque characterization using plaque area variation in IVUS images during compression: a computational investigation

Moraes

Cardoso

Furuie

2014

Rev. Bras. Eng. Bioméd.

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Introduction: The rupture of atherosclerotic plaques causes millions of death yearly. It is known that the kind of predominant tissue is associated with its dangerousness. In addition, the mechanical properties of plaques have been proved to be a good parameter to characterize the type of tissue, important information for therapeutic decisions. Methods: Therefore, we present an alternative and simple way to discriminate tissues. The procedure relies on computing an index, the ratio of the plaque area variation of a suspecting plaque, using images acquired with vessel and plaques, pre and post-deformation, under different intraluminal pressure. Numerical phantoms of coronary cross-sections with different morphological aspects, and simulated with a range of properties, were used for evaluation. Results: The outcomes provided by this index and a widely used one were compared, so as to measure their correspondence. As a result, correlations up to 99%, a strong agreement with Bland-Altman and very similar histograms between the two indices, have shown a good level of equivalence between the methods. Conclusion: The results demonstrated that the proposed index discriminates highly lipidic from fibro-lipidic and calcified tissues in many situations, as good as the widely used index, yet the proposed method is much simpler to be computed.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Realistic Ivus Image Generation In Differentmentioning

confidence: 99%

Section: Realistic Ivus Image Generation In Differentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Atherosclerotic plaque characterization using plaque area variation in IVUS images during compression: a computational investigation

Moraes

Cardoso

Furuie

2014

Rev. Bras. Eng. Bioméd.

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Radial‐Biased Tracking Method to Assess Tissue Displacement in Intravascular Ultrasound Sequences: A Phantom Framework Evaluation

Grinet

Moraes

2019

J of Ultrasound Medicine

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Objectives We created and evaluated a pixel‐tracking method capable of accurately identify the displacement of tissue in intravascular ultrasound (IVUS) images. Methods Our proposed pixel‐tracking method assessed the horizontal and vertical displacement of tissue from a numerical phantom of IVUS sequences. The proposed tracking method is based on a block‐matching framework, comparing 2 distinct frames within a selected region by normalized cross‐correlation. Our method, specialized for IVUS applications, reduced the tracking area by implementing a limiting radius and a radial bias during the search. Results The method was evaluated by using 54 numerical phantom image sequences from 9 distinct arterial models, resulting in different arteries with atherosclerotic plaques under a range of pressures. The ground truth reference coordinates of the tracked tissue were extracted from each numerical phantom sequence. Our results were compared to 8 other methods present in the literature. The mean absolute tracking errors ± SD for our method were 15.56 ± 19.46 and 13.04 ± 13.82 μm for the horizontal and vertical directions, respectively, between 2 subsequent frames, and 162.58 ± 305.93 and 102.22 ± 130.61 μm from lower to higher pressures in the range of 6 frames (n = 42,036). Conclusions Our application‐specific pixel‐tracking method showed promising results and no statistically significant tracking error (P = .954), comparable to state‐of‐the‐art methods present in the literature. Application‐specific tracking methods have advantages over general methods by turning tissue‐specific behavior into a directional bias in the tracking algorithm.

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Full-Wave Intravascular Ultrasound Simulation from Histology

Kraft

Conjeti

Noël

et al. 2014

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014

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In this paper, we introduce a framework for simulating intravascular ultrasound (IVUS) images and radiofrequency (RF) signals from histology image counterparts. We modeled the wave propagation through the Westervelt equation, which is solved explicitly with a finite differences scheme in polar coordinates by taking into account attenuation and non-linear effects. Our results demonstrate good correlation for textural and spectral information driven from simulated IVUS data in contrast to real data, acquired with single-element mechanically rotating 40 MHz transducer, as ground truth.

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Realistic IVUS Image Generation in Different Intraluminal Pressures

Cited by 11 publications

References 43 publications

Atherosclerotic plaque characterization using plaque area variation in IVUS images during compression: a computational investigation

Atherosclerotic plaque characterization using plaque area variation in IVUS images during compression: a computational investigation

Radial‐Biased Tracking Method to Assess Tissue Displacement in Intravascular Ultrasound Sequences: A Phantom Framework Evaluation

Full-Wave Intravascular Ultrasound Simulation from Histology

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