Dr. Yupei Zhang Profile

Dr. Yupei Zhang

at Emory Univ

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Author

Publications (7)

Proceedings Article | 4 April 2022 Presentation + Paper

Liver motion tracking in ultrasound images using attention guided mask R-CNN with long-short-term-memory network

Yupei Zhang, Xianjin Dai, Zhen Tian, Yang Lei, Yue Chen, Pretesh Patel, Jeffrey Bradley, Tian Liu, Xiaofeng Yang

Proceedings Volume 12038, 120380O (2022) https://doi.org/10.1117/12.2613013

KEYWORDS: Liver, Ultrasonography, Radiotherapy, Video, Temporal resolution, Network architectures, Cancer, Real time imaging, Radiation oncology, Liver cancer

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Proceedings Article | 15 February 2021 Presentation + Paper

Region of interest discovery using discriminative concrete autoencoder for COVID-19 lung CT images

Yupei Zhang, Yang Lei, Mingquan Lin, Walter Curran, Tian Liu, Xiaofeng Yang

Proceedings Volume 11597, 115970U (2021) https://doi.org/10.1117/12.2581143

KEYWORDS: Lung, Computed tomography, Image classification, Head, Feature selection, Quantitative analysis, Neural networks, Feature extraction, Chest

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Proceedings Article | 15 February 2021 Poster + Paper

Deep learning-based multi-catheter reconstruction for MRI-guided HDR prostate brachytherapy

Xianjin Dai, Yang Lei, Yupei Zhang, Tonghe Wang, Walter Curran, Pretesh Patel, Tian Liu, Xiaofeng Yang

Proceedings Volume 11598, 115981S (2021) https://doi.org/10.1117/12.2581123

KEYWORDS: Prostate, High dynamic range imaging, Magnetic resonance imaging, Prostate cancer, Visualization, Tissues, Rectum, Medical imaging, Convolutional neural networks, Blood vessels

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Reconstructing catheters on medical images is a crucial step in high-dose-rate (HDR) brachytherapy for treating prostate cancer. However, manually identify the catheters is labor intensive. With its superior soft-tissue contrast, magnetic resonance imaging (MRI) can provide superior anatomic visualization of prostate gland and its surrounding tissues such as the rectum and the bladder. There is a considerable increase of using MRI-guided HDR prostate brachytherapy over the past decades. By incorporating MRI into prostate brachytherapy procedure, the therapeutic ratio could be improved attribute to MRI's capability of differentiating dominant prostatic lesions. However, it has been realized that challenge remains in recognition of multiple catheters in MRI because catheters used in routine HDR prostate brachytherapy appear dark, thus can be easily confused with blood vessels. In this study, we developed a deep learningbased catheter reconstruction method to tackle the challenge. Particularly, a 3D mask scoring regional convolutional neural network has been implemented to automatically identify all the catheters in MRI that are acquired after catheters insertion during HDR prostate brachytherapy. The network was trained using the paired MR images and binary catheter annotation images offered by experienced medical physicists as ground truth. After the network was trained, the locations, sizes and shapes of all the catheters can be predicted given MR images of a new prostate cancer patient receiving HDR brachytherapy. Quantities including catheter tip and shaft errors were computed to assess our proposed method. Our method detected 164 catheters from 11 patients receiving HDR prostate brachytherapy with a catheter tip error of 0.62±1.83 mm and a catheter shaft error of 0.94±0.52 mm. The proposed multi-catheter reconstruction method has the capability of precisely localizing the tips and shafts of catheters in 3D MRI images of HDR prostate brachytherapy. It paves the way for elevating the quality and treatment outcome of MRI-guided HDR prostate brachytherapy.

Proceedings Article | 15 February 2021 Poster + Paper

Multi-needle detection in ultrasound image using max-margin mask R-CNN

Yupei Zhang, Zhen Tian, Yang Lei, Tonghe Wang, Pretesh Patel, Ashesh Jani, Walter Curran, Tian Liu, Xiaofeng Yang

Proceedings Volume 11602, 1160216 (2021) https://doi.org/10.1117/12.2580803

KEYWORDS: Ultrasonography, Prostate, High dynamic range imaging, Process modeling, Neural networks, Detection and tracking algorithms

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Proceedings Article | 15 February 2021 Poster + Paper

Ultrasound multi-needle detection using deep attention U-Net with TV regularizations

Yupei Zhang, Yang Lei, Xiuxiu He, Zhen Tian, Jiwoong Jeong, Tonghe Wang, Qiulan Zeng, Ashesh Jani, Walter Curran, Pretesh Patel, Tian Liu, Xiaofeng Yang

Proceedings Volume 11598, 1159829 (2021) https://doi.org/10.1117/12.2580802

KEYWORDS: Ultrasonography, High dynamic range imaging, Prostate cancer, Prostate, Image segmentation, 3D modeling, 3D image processing, Silver, Binary data

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Proceedings Article | 16 March 2020 Presentation + Paper

Multi-needle detection in 3D ultrasound images with sparse dictionary learning

Yupei Zhang, Xiuxiu He, Zhen Tian, Jiwoong Jeong, Yang Lei, Tonghe Wang, Qiulan Zeng, Ashesh Jani, Walter Curran, Pretesh Patel, Tian Liu, Xiaofeng Yang

Proceedings Volume 11319, 113190I (2020) https://doi.org/10.1117/12.2549005

KEYWORDS: Associative arrays, 3D image processing, Prostate, Ultrasonography, Cancer, Visualization, 3D acquisition, Detection and tracking algorithms, Reconstruction algorithms, Prostate cancer

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Proceedings Article | 16 March 2020 Paper

Weakly supervised multi-needle detection in 3D ultrasound images with bidirectional convolutional sparse coding

Yupei Zhang, Joseph Harms, Yang Lei, Tonghe Wang, Tian Liu, Ashesh Jani, Walter Curran, Pretesh Patel, Xiaofeng Yang

Proceedings Volume 11319, 1131914 (2020) https://doi.org/10.1117/12.2549283

KEYWORDS: Computed tomography, Associative arrays, 3D image processing, Prostate, 3D modeling, Process modeling, Reconstruction algorithms, Ultrasonography, High dynamic range imaging, Visualization

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Showing 5 of 7 publications

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