Mr. Wei Yu Profile

Wei Yu

at Shanghai Jiao Tong Univ.

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Proceedings Article | 3 April 2023 Poster + Paper

Cardiac dynamics compensation for intravascular ultrasound sequences

Runing Xiao, Wei Yu, Shengxian Tu

Proceedings Volume 12464, 124643Q (2023) https://doi.org/10.1117/12.2653405

KEYWORDS: Intravascular ultrasound, Tunable filters, Linear filtering, Solids, Image segmentation, Heart, Tissues, Image registration, Biomedical optics, Visualization

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Intravascular ultrasound (IVUS) is a well-established imaging technique for the assessment of coronary atherosclerotic plaque. IVUS has the ability to identify the arterial wall morphology, fibrous plaque locations and thicknesses, and internal lumen area. However, the motion of the imaging catheter with respect to the coronary wall caused by cardiac contraction during image acquisition impairs the subsequent visualization and quantification of IVUS image pullbacks. In this study, we propose a method to compensate for cardiac dynamics in IVUS. Keeping the original sensor field center origin unchanged, the vessel geometric centers are first extracted based on lumen segmentation. Subsequently, the periodic fluctuations of the geometric center sequence are used to formulate a heartbeat motion filtering algorithm based on the comb filter. Cardiac dynamics are then compensated by effectively filtering heartbeat deflection from both translational and rotational motion components. We evaluated 35 in vivo IVUS pullbacks and the experimental results showed an average percentage of artifact suppression of 77.82(± 7.55) %, demonstrating the reliability of the presented method in clinical cases. The method eliminates the need for image center correction and helps to maintain the original geometry of the vessel axes. Compared with existing methods, the presented method can more simply extract the heartbeat frequency and effectively filter out the higher order harmonic components of the heartbeat, resulting in more accurate cardiac dynamics compensation.

Proceedings Article | 15 February 2021 Poster + Presentation + Paper

Segmentation of side branch regions in intravascular images using multi-modal information

Biao Huang, Su Zhang, Peng Wu, Xuebo Liu, Wei Yu, Yingguang Li, Shengxian Tu

Proceedings Volume 11602, 1160214 (2021) https://doi.org/10.1117/12.2580473

KEYWORDS: Image segmentation, Intravascular ultrasound, Optical coherence tomography

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Fractional flow reserve (FFR) is the reference standard to identify flow-limiting coronary stenosis that requires revascularization. Accurate computation of FFR from coronary intravascular images is based on the precise reconstruction of the side branches. In this paper, a novel approach for segmentation of side branches in intravascular images is presented. The framework consists of an image-to-image translation module and two side branch region segmentation modules. By using the image-to-image translation module, information from intravascular optical coherence tomography (IVOCT) and intravascular ultrasound (IVUS) images is combined to improve the segmentation performance. The framework is trained on a total of 62475 IVOCT and 186110 IVUS images, and evaluated on an independent dataset which contains 9344 IVOCT images with 91 side branches and 39450 IVUS images with 128 side branches. The Dice coefficients of IVOCT and IVUS side branches segmentation are 0.935±0.039 and 0.856±0.038, respectively. The validation results of side branches detection are: Precision = 0.934, Recall = 0.923, F₁Score = 0.929 in IVOCT, and 0.925, 0.868, 0.895 in IVUS, accordingly. Ablation studies demonstrate excellent efficiency in incorporating multi-modal information with our proposed image-to-image translation module.

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