Dr. Yu Gan Profile

Dr. Yu Gan

Assistant Professor at Stevens Institute of Technology

SPIE Involvement:

Conference Program Committee | Author | Student Chapter Advisor

Websites:

Personal Website

Publications (26)

Proceedings Article | 2 April 2024 Presentation + Paper

Label refinement for noisy annotation in weakly supervised segmentation

Ziyi Huang, Hongshan Liu, Haofeng Zhang, Fuyong Xing, Andrew Laine, Elsa Angelini, Christine Hendon, Yu Gan

Proceedings Volume 12926, 129260W (2024) https://doi.org/10.1117/12.3006817

KEYWORDS: Image segmentation, Neural networks, Optical coherence tomography, Medical imaging, Deep learning

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SPIE Journal Paper | 25 March 2024 Open Access

Structurally constrained and pathology-aware convolutional transformer generative adversarial network for virtual histology staining of human coronary optical coherence tomography images

Xueshen Li, Hongshan Liu, Xiaoyu Song, Charles Marboe, Brigitta Brott, Silvio Litovsky, Yu Gan

JBO, Vol. 29, Issue 03, 036004, (March 2024) https://doi.org/10.1117/12.10.1117/1.JBO.29.3.036004

KEYWORDS: Optical coherence tomography, Transformers, Pathology, Education and training, Design, Histopathology, Arteries, Visualization, Image quality, Gallium nitride

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SignificanceThere is a significant need for the generation of virtual histological information from coronary optical coherence tomography (OCT) images to better guide the treatment of coronary artery disease (CAD). However, existing methods either require a large pixel-wise paired training dataset or have limited capability to map pathological regions.AimThe aim of this work is to generate virtual histological information from coronary OCT images, without a pixel-wise paired training dataset while capable of providing pathological patterns.ApproachWe design a structurally constrained, pathology-aware, transformer generative adversarial network, namely structurally constrained pathology-aware convolutional transformer generative adversarial network (SCPAT-GAN), to generate virtual stained H&E histology from OCT images. We quantitatively evaluate the quality of virtual stained histology images by measuring the Fréchet inception distance (FID) and perceptual hash value (PHV). Moreover, we invite experienced pathologists to evaluate the virtual stained images. Furthermore, we visually inspect the virtual stained image generated by SCPAT-GAN. Also, we perform an ablation study to validate the design of the proposed SCPAT-GAN. Finally, we demonstrate 3D virtual stained histology images.ResultsCompared to previous research, the proposed SCPAT-GAN achieves better FID and PHV scores. The visual inspection suggests that the virtual histology images generated by SCPAT-GAN resemble both normal and pathological features without artifacts. As confirmed by the pathologists, the virtual stained images have good quality compared to real histology images. The ablation study confirms the effectiveness of the combination of proposed pathological awareness and structural constraining modules.ConclusionsThe proposed SCPAT-GAN is the first to demonstrate the feasibility of generating both normal and pathological patterns without pixel-wisely supervised training. We expect the SCPAT-GAN to assist in the clinical evaluation of treating the CAD by providing 2D and 3D histopathological visualizations.

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Proceedings Article | 13 March 2024 Presentation

Generating virtual histology staining of human coronary OCT images using transformer-based neural network

Xueshen Li, Hongshan Liu, Xiaoyu Song, Brigitta Brott, Silvio Litovsky, Yu Gan

Proceedings Volume 12819, 1281903 (2024) https://doi.org/10.1117/12.3003138

KEYWORDS: Optical coherence tomography, Neural networks, Histopathology, Databases, Cardiovascular disorders, Visualization, Transformers, Statistical analysis, Spectral resolution, Real time imaging

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Proceedings Article | 13 March 2024 Paper

Simulation of manual and automatic navigation of magnetically controlled wireless capsule endoscopy examination of human gastric

Xueshen Li, Yu Gan, David Duan, Xiao Yang

Proceedings Volume 12820, 1282006 (2024) https://doi.org/10.1117/12.3003356

KEYWORDS: Head, Magnetism, Endoscopy, Education and training, Design, Angular velocity, Stomach, Diseases and disorders, 3D modeling, Point clouds

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Proceedings Article | 3 April 2023 Poster + Paper

Detecting human gastric peristalsis using magnetically controlled capsule endoscope via deep learning

Xueshen Li, Yu Gan, David Duan, Xiao Yang

Proceedings Volume 12464, 124641F (2023) https://doi.org/10.1117/12.2646723

KEYWORDS: Electronic filtering, Video, Education and training, Cameras, Diseases and disorders, Deep learning, Tunable filters, Optical filters, Endoscopes, Algorithm development

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Proceedings Article | 3 April 2023 Presentation + Paper

Peripapillary atrophy segmentation in fundus images via multi-task learning

Xiao Wei, Bo Jiang, Yuye Ling, Peiyao Jin, Yifan Wang, Xinbing Wang, Chenghu Zhou, Yu Gan

Proceedings Volume 12464, 124641C (2023) https://doi.org/10.1117/12.2652897

KEYWORDS: Image segmentation, Feature extraction, Data modeling, Image classification, Statistical modeling, Statistical analysis

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SPIE Journal Paper | 27 March 2023 Open Access

Toward reliable calcification detection: calibration of uncertainty in object detection from coronary optical coherence tomography images

Hongshan Liu, Xueshen Li, Abdul Latif Bamba, Xiaoyu Song, Brigitta C. Brott, Silvio H. Litovsky, Yu Gan

JBO, Vol. 28, Issue 03, 036008, (March 2023) https://doi.org/10.1117/12.10.1117/1.JBO.28.3.036008

KEYWORDS: Object detection, Calibration, Optical coherence tomography, Deep learning, Image segmentation, Arteries, Data modeling, Electrochemical etching, Computer aided detection, Image processing

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Proceedings Article | 8 March 2023 Poster + Paper

Uncertainty measurement and confidence calibration for calcium detection in optical coherence images

Hongshan Liu, Abdul Latif Bamba, Yu Gan

Proceedings Volume 12367, 1236715 (2023) https://doi.org/10.1117/12.2652944

KEYWORDS: Object detection, Calibration, Optical coherence tomography, Measurement uncertainty, Calcium, Deep learning, Electrochemical etching, Education and training, Arteries, Cardiovascular disorders

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Proceedings Article | 4 April 2022 Presentation + Paper

Multi-scale sparse representation-based shadow inpainting for retinal OCT images

Yaoqi Tang, Yufan Li, Hongshan Liu, Jiaxuan Li, Peiyao Jin, Yu Gan, Yuye Ling, Yikai Su

Proceedings Volume 12032, 1203204 (2022) https://doi.org/10.1117/12.2611281

KEYWORDS: Optical coherence tomography, Image segmentation, Image processing, Super resolution, Medical imaging

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Proceedings Article | 7 March 2022 Presentation

Automated object detection within coronary optical coherence tomography images

Hongshan Liu, Xuesheng Li, Yu Gan

Proceedings Volume PC11936, PC119360E (2022) https://doi.org/10.1117/12.2610257

KEYWORDS: Optical coherence tomography, Tissues, Image processing, Spectral resolution, Image resolution, Convolutional neural networks

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Proceedings Article | 5 March 2021 Presentation

Automated adipose segmentation within cardiac optical coherence tomography images

Ziyi Huang, Yu Gan, Theresa Lye, Yanchen Liu, Andrew Laine, Elsa Angelini, Christine Hendon

Proceedings Volume 11621, 1162107 (2021) https://doi.org/10.1117/12.2578814

KEYWORDS: Image segmentation, Optical coherence tomography, Heart, Tissues, Spectral resolution, Radiofrequency ablation, Machine learning, Image resolution, Image processing algorithms and systems, Binary data

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Proceedings Article | 5 March 2021 Poster + Presentation

Modelling the shift-variance in Fourier-domain optical coherence tomography

Yuye Ling, Mengyuan Wang, Yu Gan, Xinwen Yao, Leopold Schmetterer, Chuanqing Zhou, Yikai Su

Proceedings Volume 11630, 1163025 (2021) https://doi.org/10.1117/12.2580633

KEYWORDS: Optical coherence tomography, Modeling, Image acquisition, Reconstruction algorithms, Numerical simulations, Imaging systems, Image restoration, Clinical research, Algorithm development

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Proceedings Article | 5 March 2021 Presentation + Paper

A GCN-assisted deep learning method for peripapillary retinal layer segmentation in OCT images

Jiaxuan Li, Yuye Ling, Jiangnan He, Peiyao Jin, Jianfeng Zhu, Haidong Zou, Xun Xu, Shuo Shao, Yu Gan, Yikai Su

Proceedings Volume 11630, 1163010 (2021) https://doi.org/10.1117/12.2582905

KEYWORDS: Image segmentation, Optical coherence tomography, Neural networks, Retina, Nerve, Computer programming

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Proceedings Article | 17 February 2021 Poster + Presentation + Paper

HydraNet: a multi-branch convolutional neural network architecture for MRI denoising

Stephen Gregory, Hu Cheng, Sharlene Newman, Yu Gan

Proceedings Volume 11596, 1159638 (2021) https://doi.org/10.1117/12.2582286

KEYWORDS: Magnetic resonance imaging, Denoising, Convolutional neural networks, Network architectures, Signal to noise ratio, Image resolution

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Proceedings Article | 24 May 2019 Presentation + Paper

Convolutional neural network (CNN) classification of breast cancer in optical coherence tomography (OCT) images

Diana Mojahed, Peter Chang, Yu Gan, Xinwen Yao, Brigid Angelini, Hanina Hibshoosh, Richard Ha, Christine Hendon

Proceedings Volume 10867, 108671N (2019) https://doi.org/10.1117/12.2504966

KEYWORDS: Optical coherence tomography, Tissues, Breast, Image classification, Breast cancer, Convolutional neural networks, Cancer, Algorithm development, Tumors, Surgery

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Proceedings Article | 14 March 2018 Presentation

Functional endomyocardial imaging by single-channel high resolution cross-polarization OCT (Conference Presentation)

Xinwen Yao, Yu Gan, Yuye Ling, Charles Marboe, Christine Hendon

Proceedings Volume 10471, 104710K (2018) https://doi.org/10.1117/12.2287525

KEYWORDS: Optical coherence tomography, Tissues, Imaging systems, Polarization, Range imaging, Signal detection, Image resolution, Tissue optics, Biomedical optics, Biotechnology

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Proceedings Article | 24 August 2017 Paper

A sparsity-based simplification method for segmentation of spectral-domain optical coherence tomography images

William Meiniel, Yu Gan, Jean-Christophe Olivo-Marin, Elsa Angelini

Proceedings Volume 10394, 1039406 (2017) https://doi.org/10.1117/12.2274126

KEYWORDS: Image segmentation, Optical coherence tomography, Image denoising, Compressed sensing

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Proceedings Article | 19 April 2017 Presentation

Visualization and tissue classification of human breast cancer images using ultrahigh-resolution OCT (Conference Presentation)

Xinwen Yao, Yu Gan, Ernest Chang, Hanina Hibshoosh, Sheldon Feldman, Christine Hendon

Proceedings Volume 10053, 100532A (2017) https://doi.org/10.1117/12.2254842

KEYWORDS: Visualization, Optical coherence tomography, Tissues, Breast cancer, Image classification, Machine learning, Image resolution, Breast, Imaging systems, Tumor growth modeling

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Proceedings Article | 19 April 2017 Presentation

Longitudinal analysis on human cervical tissue using optical coherence tomography (Conference Presentation)

Yu Gan, Wang Yao, Kristin Myers, Joy-Sarah Vink, Ronald Wapner, Christine Hendon

Proceedings Volume 10053, 1005318 (2017) https://doi.org/10.1117/12.2254156

KEYWORDS: Optical coherence tomography, Cervix, Collagen, Tissue optics, Structured optical fibers, Uterus, Vagina, Tissues, Natural surfaces, Statistical analysis

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Proceedings Article | 19 April 2017 Presentation

Automated adipose study for assessing cancerous human breast tissue using optical coherence tomography (Conference Presentation)

Yu Gan, Xinwen Yao, Ernest Chang, Syed Bin Amir, Hanina Hibshoosh, Sheldon Feldman, Christine Hendon

Proceedings Volume 10043, 100430G (2017) https://doi.org/10.1117/12.2253263

KEYWORDS: Tumors, Tissues, Breast, Optical coherence tomography, Signal to noise ratio, Tissue optics, Breast cancer, Cancer, Interference (communication), Feature extraction

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Proceedings Article | 8 February 2017 Paper

Mapping the human atria with optical coherence tomography

Theresa Lye, Yu Gan, Christine Hendon

Proceedings Volume 10042, 1004203 (2017) https://doi.org/10.1117/12.2251048

KEYWORDS: Optical coherence tomography, Imaging systems, Algorithm development, Tissues, Veins, Collagen, Heart, Tissue optics, Natural surfaces, Image visualization

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Proceedings Article | 8 February 2017 Presentation + Paper

Characterization of ventricular endomyocardial tissue using optical coherence tomography

Yu Gan, Xinwen Yao, David Tsay, Charles Marboe, Christine Hendon

Proceedings Volume 10042, 1004207 (2017) https://doi.org/10.1117/12.2253200

KEYWORDS: Image classification, Optical coherence tomography, Biopsy, Image processing, Heart, Image segmentation, Feature extraction, In vivo imaging, Collagen

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Proceedings Article | 27 April 2016 Presentation

Dispersion analysis of collagen fiber networks in cervical tissue using optical coherence tomography (Conference Presentation)

Yu Gan, Wang Yao, Kristin Myers, Joy Vink, Ronald Wapner, Christine Hendon

Proceedings Volume 9689, 96893X (2016) https://doi.org/10.1117/12.2212747

KEYWORDS: Collagen, Dispersion, Tissue optics, Optical coherence tomography, Tissues, Signal to noise ratio, Physiology, Cervix, Natural surfaces, Interference (communication)

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Proceedings Article | 26 April 2016 Presentation

Automated tissue classification of intracardiac optical coherence tomography images (Conference Presentation)

Yu Gan, David Tsay, Syed Amir, Charles Marboe, Christine Hendon

Proceedings Volume 9697, 96970C (2016) https://doi.org/10.1117/12.2212796

KEYWORDS: Tissues, Optical coherence tomography, Tissue optics, Image segmentation, Image classification, Heart, Collagen, Machine vision, Statistical analysis, Radiofrequency ablation

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SPIE Journal Paper | 22 March 2016 Open Access

Myocardial imaging using ultrahigh-resolution spectral domain optical coherence tomography

Xinwen Yao, Yu Gan, Charles Marboe, Christine Hendon

JBO, Vol. 21, Issue 06, 061006, (March 2016) https://doi.org/10.1117/12.10.1117/1.JBO.21.6.061006

KEYWORDS: Optical coherence tomography, Heart, Optical fibers, Tissues, Spectroscopy, Image resolution, Imaging systems, Point spread functions, Birefringence, Collagen

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SPIE Journal Paper | 29 February 2016 Open Access

Automated classification of optical coherence tomography images of human atrial tissue

Yu Gan, David Tsay, Syed Amir, Charles Marboe, Christine Hendon

JBO, Vol. 21, Issue 10, 101407, (February 2016) https://doi.org/10.1117/12.10.1117/1.JBO.21.10.101407

KEYWORDS: Tissues, Optical coherence tomography, Image segmentation, Tissue optics, Image classification, Collagen, Heart, Feature extraction, Statistical analysis, Signal attenuation

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