Dr. Shuwen Wei Profile

Dr. Shuwen Wei

at Johns Hopkins Univ.

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Author

Publications (13)

Proceedings Article | 2 April 2024 Poster + Paper

Deep-learning-based segmentation of hydrocephalus brain ventricle from ultrasound

Yuli Wang, Yihao Liu, Shuwen Wei, Yuan Xue, Lianrui Zuo, Samuel Remedios, Zhangxing Bian, Michael Meggyesy, Jheesoo Ahn, Ryan Lee, Mark Luciano, Jerry Prince, Aaron Carass

Proceedings Volume 12926, 1292639 (2024) https://doi.org/10.1117/12.3007668

KEYWORDS: Ultrasonography, Image segmentation, Brain, Neuroimaging, Deep learning, Video, Magnetic resonance imaging, Education and training, Computed tomography, Convolution

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Proceedings Article | 2 April 2024 Presentation + Paper

Is registering raw tagged-MR enough for strain estimation in the era of deep learning? (Image Processing Best Student Paper Award)

Zhangxing Bian, Ahmed Alshareef, Shuwen Wei, Junyu Chen, Yuli Wang, Jonghye Woo, Dzung Pham, Jiachen Zhuo, Aaron Carass, Jerry Prince

Proceedings Volume 12926, 129260A (2024) https://doi.org/10.1117/12.3006906

KEYWORDS: Deformation, Anatomy, Magnetic resonance imaging, Deep learning, Motion estimation, Motion measurement, Image registration

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Proceedings Article | 2 April 2024 Presentation + Paper

Pushing the limits of zero-shot self-supervised super-resolution of anisotropic MR images

Samuel Remedios, Shuwen Wei, Blake Dewey, Aaron Carass, Dzung Pham, Jerry Prince

Proceedings Volume 12926, 1292606 (2024) https://doi.org/10.1117/12.3007304

KEYWORDS: Magnetic resonance imaging, Super resolution, Machine learning, Interpolation, Wavelets, Image resolution, Deep learning

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Proceedings Article | 13 March 2024 Presentation + Paper

Deep learning-based single-shot fringe projection profilometry

Ruizhi Zuo, Shuwen Wei, Yaning Wang, Michael Kam, Justin Opfermann, Michael Hsieh, Axel Krieger, Jin Kang

Proceedings Volume 12831, 1283106 (2024) https://doi.org/10.1117/12.3001837

KEYWORDS: Depth maps, Point clouds, Biological samples, Fringe analysis, Cameras, Transformers, Reconstruction algorithms, Biological imaging, Tissues

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SPIE Journal Paper | 24 August 2023 Open Access

Depth-dependent attenuation and backscattering characterization of optical coherence tomography by stationary iterative method

Yaning Wang, Shuwen Wei, Jin U. Kang

JBO, Vol. 28, Issue 08, 085002, (August 2023) https://doi.org/10.1117/12.10.1117/1.JBO.28.8.085002

KEYWORDS: Signal attenuation, Optical coherence tomography, Backscatter, Tissues, Signal intensity, Monte Carlo methods, Biological samples, Scattering, Optical properties, Attenuation

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SignificanceExtracting optical properties of tissue [e.g., the attenuation coefficient (μ) and the backscattering fraction] from the optical coherence tomography (OCT) images is a valuable tool for parametric imaging and related diagnostic applications. Previous attenuation estimation models depend on the assumption of the uniformity of the backscattering fraction (R) within layers or whole samples, which does not accurately represent real-world conditions.AimOur aim is to develop a robust and accurate model that calculates depth-wise values of attenuation and backscattering fractions simultaneously from OCT signals. Furthermore, we aim to develop an attenuation compensation model for OCT images that utilizes the optical properties we obtained to improve the visual representation of tissues.ApproachUsing the stationary iteration method under suitable constraint conditions, we derived the approximated solutions of μ and R on a single scattering model. During the iteration, the estimated value of μ can be rectified by introducing the large variations of R, whereas the small ones were automatically ignored. Based on the calculation of the structure information, the OCT intensity with attenuation compensation was deduced and compared with the original OCT profiles.ResultsThe preliminary validation was performed in the OCT A-line simulation and Monte Carlo modeling, and the subsequent experiment was conducted on multi-layer silicone-dye-TiO2 phantoms and ex vivo cow eyes. Our method achieved robust and precise estimation of μ and R for both simulated and experimental data. Moreover, corresponding OCT images with attenuation compensation provided an improved resolution over the entire imaging range.ConclusionsOur proposed method was able to correct the estimation bias induced by the variations of R and provided accurate depth-resolved measurements of both μ and R simultaneously. The method does not require prior knowledge of the morphological information of tissue and represents more real-life tissues. Thus, it has the potential to help OCT imaging based disease diagnosis of complex and multi-layer biological tissue.

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Proceedings Article | 9 March 2022 Presentation

Numerical landmark detection algorithm for fringe projection profilometry during autonomous robotic suturing

Shuwen Wei, Michael Kam, Yaning Wang, Justin Opfermann, Hamed Saeidi, Michael Hsieh, Axel Krieger, Jin Kang

Proceedings Volume PC11949, PC119490A (2022) https://doi.org/10.1117/12.2609134

KEYWORDS: Robotics, Detection and tracking algorithms, Clouds, Tissues, Reliability, Luminescence, Safety, Robotic surgery, Robot vision, Light sources

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Proceedings Article | 7 March 2022 Poster

Robust phase stabilization algorithm for swept source optical coherence tomography based on a wrapped Gaussian mixture model

Shuwen Wei, Jin Kang

Proceedings Volume PC11948, PC119481J (2022) https://doi.org/10.1117/12.2612688

KEYWORDS: Optical coherence tomography, Expectation maximization algorithms, Numerical analysis, Systems modeling, System integration, Structural imaging, Particles, In vivo imaging, Graphics processing units, Doppler tomography

Proceedings Article | 2 March 2022 Presentation + Paper

Depth-resolved backscattering signal reconstruction based OCT attenuation compensation

Yaning Wang, Shuwen Wei, Jin Kang

Proceedings Volume 11953, 119530D (2022) https://doi.org/10.1117/12.2609114

KEYWORDS: Signal attenuation, Backscatter, Optical coherence tomography, Biological research, Signal detection, Optical properties, Error analysis, Computer simulations, Tissue optics

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Proceedings Article | 2 March 2022 Presentation + Paper

Automated OCT A-line abdominal tissue classification using a hybrid MLP-CNN classifier during ventral hernia repair

Yaning Wang, Shuwen Wei, Justin Opfermann, Michael Kam, Hamed Saeidi, Michael Hsieh, Axel Krieger, Jin Kang

Proceedings Volume 11953, 1195307 (2022) https://doi.org/10.1117/12.2609103

KEYWORDS: Tissues, Optical coherence tomography, Signal attenuation, Surgery, Laparoscopy, Backscatter, Scattering, Sensors, Network architectures, Intestine

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Proceedings Article | 5 March 2021 Presentation + Paper

Optimized OCT-based depth-resolved model for attenuation compensation using point-spread-function calibration

Yaning Wang, Shuwen Wei, Shoujing Guo, Jin Kang

Proceedings Volume 11635, 116350E (2021) https://doi.org/10.1117/12.2577847

KEYWORDS: Signal attenuation, Optical coherence tomography, Tissues, Calibration, Monte Carlo methods, Image segmentation, Visualization, Speckle, Signal to noise ratio, Point spread functions

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Proceedings Article | 5 March 2021 Presentation

Optical flow optical coherence tomography for determining accurate velocity fields

Shuwen Wei, Jin Kang

Proceedings Volume 11630, 1163018 (2021) https://doi.org/10.1117/12.2577786

KEYWORDS: Optical coherence tomography, Optical flow, Speckle, Scattering, Microfluidics, Medical research, Graphics processing units, Fluid dynamics, Doppler tomography, Associative arrays

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Proceedings Article | 9 March 2020 Presentation

Convolutional neural network (CNN) based needle-tracking for OCT-guided cornea “Big Bubble” procedure (Conference Presentation)

Ruizhi Zuo, Jin Kang, Soohyun Lee, Shoujing Guo, Shuwen Wei

Proceedings Volume 11243, 112431L (2020) https://doi.org/10.1117/12.2546547

KEYWORDS: Cornea, Convolutional neural networks, Surgery, Optical coherence tomography, Image segmentation, Image processing, Image filtering, Spatial filters, Hough transforms

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SPIE Journal Paper | 14 February 2020 Open Access

Selective retina therapy monitoring by speckle variance optical coherence tomography for dosimetry control

Soohyun Lee, Shuwen Wei, Shoujing Guo, Jongmin Kim, Bongkyun Kim, Gihoon Kim, Jin Kang

JBO, Vol. 25, Issue 02, 026001, (February 2020) https://doi.org/10.1117/12.10.1117/1.JBO.25.2.026001

KEYWORDS: Retina, Optical coherence tomography, Pulsed laser operation, Laser energy, Speckle, Laser irradiation, Imaging systems, Optical simulations, Thermal effects, Eye

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