Comprehensive Modeling and Visualization of Cardiac Anatomy and Physiology from CT Imaging and Computer Simulations

Xiong, Guanglei; Sun, Peng; Zhou, Huajun; Ha, Seongmin; Hartaigh, Bríain ó; Truong, Quynh A.; Min, James K.

doi:10.1109/tvcg.2016.2520946

Cited by 17 publications

(8 citation statements)

References 65 publications

(76 reference statements)

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“…ECHO techniques might also be adopted but their applications are usually limited to diagnostic parameters assessment rather than computational domains definition. In comparison with other modes, CT is the technique with the best resolution available ( 1 , 2 ): its standard spatial resolution is usually around 0.5 mm, but it can reach smaller values ( 3 ) according to the last generation scanners. Given these features, literature studies report a significant contribution of CT-based techniques for aortic structures assessment ( 4 , 5 ).…”

Section: Introductionmentioning

confidence: 99%

On the Role and Effects of Uncertainties in Cardiovascular in silico Analyses

Celi

Vignali

Capellini

et al. 2021

Front. Med. Technol.

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The assessment of cardiovascular hemodynamics with computational techniques is establishing its fundamental contribution within the world of modern clinics. Great research interest was focused on the aortic vessel. The study of aortic flow, pressure, and stresses is at the basis of the understanding of complex pathologies such as aneurysms. Nevertheless, the computational approaches are still affected by sources of errors and uncertainties. These phenomena occur at different levels of the computational analysis, and they also strongly depend on the type of approach adopted. With the current study, the effect of error sources was characterized for an aortic case. In particular, the geometry of a patient-specific aorta structure was segmented at different phases of a cardiac cycle to be adopted in a computational analysis. Different levels of surface smoothing were imposed to define their influence on the numerical results. After this, three different simulation methods were imposed on the same geometry: a rigid wall computational fluid dynamics (CFD), a moving-wall CFD based on radial basis functions (RBF) CFD, and a fluid-structure interaction (FSI) simulation. The differences of the implemented methods were defined in terms of wall shear stress (WSS) analysis. In particular, for all the cases reported, the systolic WSS and the time-averaged WSS (TAWSS) were defined.

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Section: Introductionmentioning

confidence: 99%

On the Role and Effects of Uncertainties in Cardiovascular in silico Analyses

Celi

Vignali

Capellini

et al. 2021

Front. Med. Technol.

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show abstract

“…It possesses some advantages such as high calculating speed and positioning accuracy. But it is innately susceptible to noise, which can result in either under-segmentation or oversegmentation (Cai et al 2017;Farag et al 2017;Shahzad et al 2017;Tovia-Brodie et al 2017;Xiong et al 2017;Yan et al 2017). Therefore, the present work combined multiple methods to overcome this drawback; these methods and the processes are shown in Fig.1.…”

Section: -D Visualizationmentioning

confidence: 99%

Internal Structural Imaging of Cultural Wooden Relics Based on Three-Dimensional Computed Tomography

Zhao¹,

Qiu

Shen

et al. 2018

BioResources

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An efficient method for the internal structural imaging of cultural wooden relics was explored through experimental techniques of three-dimensional (3-D) tomography and reconstruction. The techniques of filtering and segmentation were applied to the 3-D scanned data of wooden cultural relics.To obtain high resolution 3D data model, it was necessary to preprocess the raw data after CT scanning. Preprocessing included denoising, filtering, and segmentation. After completing these three steps, three-dimensional reconstruction experiments were carried out (including surface rendering and volume rendering). After the 3-D reconstruction, the wood internal properties were visually analyzed and used to create internal structural imaging of wooden artifacts. On the basis of volume rendering, wooden artifacts could be graphically divided at any angle and any position. The textures of local wooden relics were clearly revealed in the segmentation of the reconstruction pictures, and these were compared with the presented internal structural image testing of the wooden artifacts. This study showed that the proposed technology can successfully create internal structural images of wooden artifacts, as well as provide important data and models to support the renovation and recovery of the cultural wooden relics. Keywords INTRODUCTIONCurrently, three-dimensional (3-D) tomography technology is mainly used in the medical field but not in the protection and identification of wooden artifacts. However, there are some studies utilizing structural imaging technology in wood. Kak and Slaney (1988) used computed temography (CT) to analyze and graph X-ray detection results. Schmoldt et al. (1999) visualized the internal structure of wood with X-rays; the initial approach only contained one signal detector, and the wood had to be constantly moved. Ekevad (2004) described a CT-directional method where the fiber directions of wood in 3-D space were calculated from the pixel information on a series of two-dimensional (2-D) computed tomography images. This CT-directional method is a nondestructive way to measure fiber directions locally and in the interior of a piece of wood. Sarigul et al. (2005) developed the IntelliPost model system to improve the CT detection ability of wood defects. This system contained a learning model and an operation model. The learning model included wood defects identified by the operating equipment and established a system imaging rules for defects. The operational model discriminated the defects

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“…Saquib et al [9] diagnosed heart disease by calculating the volume ratio. Xiong et al [10] combined CT images with clinical data for analysis. Wolterink et al [11] used dilated convolutional neural networks to segment MR images.…”

Section: Introductionmentioning

confidence: 99%

A Heart Segmentation Algorithm Based on Dynamic Ultrasound

Tian

Zheng

2022

BioMed Research International

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The heart is one of the most important organs of the human body. The role of the heart is to promote blood flow and provide sufficient blood flow to organs and tissues. The research on the heart has important theoretical and clinical significance. Because of the noninvasive and intuitive display of ultrasound image, it can dynamically obtain the heart state and has become the main means to detect the heart dynamics. We analyze the characteristics of cardiac ultrasound image from the medical point of view and signal processing. The heart movement is periodic and rhythmic. The image signal can be decomposed. Firstly, the image is decomposed into high- and low-frequency signals to highlight different dimensional information. Then, the attention model was introduced, focusing on the heart region. Finally, the multidimensional network carrying model was established to achieve cardiac segmentation. The experimental results show that the AOM of the algorithm proposed in this paper reaches 92%, which has a certain degree of advancement and can assist doctors to make accurate diagnosis.

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Comprehensive Modeling and Visualization of Cardiac Anatomy and Physiology from CT Imaging and Computer Simulations

Cited by 17 publications

References 65 publications

On the Role and Effects of Uncertainties in Cardiovascular in silico Analyses

On the Role and Effects of Uncertainties in Cardiovascular in silico Analyses

Internal Structural Imaging of Cultural Wooden Relics Based on Three-Dimensional Computed Tomography

A Heart Segmentation Algorithm Based on Dynamic Ultrasound

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