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Results for "Zhenyu Yang": 19 found

A Radiomic Quantification Framework for Hyperparameter Optimization in Texture Characterization

Authors: Yuli Lu, Chendong Ni, Cheng Qian, Kun Qian, Weiwei Sang, Chunhao Wang, Fan Xia, Zhenyu Yang, Fang-Fang Yin, Rihui Zhang, Haiming Zhu

Affiliation: Jiahui International Hospital, Radiation Oncology, Duke University, Medical Physics Graduate Program, Duke Kunshan University, Duke Kunshan University, The First People's Hospital of Kunshan

Abstract Preview: Purpose: To develop a radiomic quantification framework to evaluate the effects of radiomic image preprocessing hyperparameters (i.e., image resampling and discretization) on texture characterization ...

An Assessment of the Potential Impact of the Elekta Unityโ€™s 1.5T Magnetic Field upon the Performance of a Conventional Linac Installed in an Adjacent Vault: A Case Study

Authors: Matthew Stephen Andriotty, Taoran Cui, Josh Kilian-Meneghin, Ke Nie, Xiao Wang, Zhenyu Xiong, Ning J. Yue, Yin Zhang

Affiliation: Rutgers Cancer Institute of New Jersey, RWJBarnabas Health

Abstract Preview: Purpose: To investigate the potential impact of the Elekta Unityโ€™s 1.5T magnetic field upon the performance of a conventional linac installed in an adjacent vault.
Methods: The linac vaults for thi...

Assessing the Risks of Synthetic MRI Data in Deep Learning: A Study on U-Net Segmentation Accuracy

Authors: Chuangxin Chu, Haotian Huang, Tianhao Li, Jingyu Lu, Zhenyu Yang, Fang-Fang Yin, Tianyu Zeng, Chulong Zhang, Yujia Zheng

Affiliation: The Hong Kong Polytechnic University, Nanyang Technological University, Australian National University, Medical Physics Graduate Program, Duke Kunshan University, North China University of Technology, Duke Kunshan University

Abstract Preview: Purpose: Deep learning segmentation models, such as U-Net, rely on high-quality image-segmentation pairs for accurate predictions. However, the recent increasing use of generative networks for creatin...

Biologically Guided Deep Learning for MRI-Based Brain Metastasis Outcome Prediction after Stereotactic Radiosurgery

Authors: Evan Calabrese, Hangjie Ji, Kyle J. Lafata, Casey Y. Lee, Eugene Vaios, Chunhao Wang, Lana Wang, Zhenyu Yang, Jingtong Zhao

Affiliation: Duke University, Department of Radiation Oncology, Duke University, Duke Kunshan University, North Carolina State University

Abstract Preview: Purpose: To develop a biologically guided deep learning (DL) model for predicting brain metastasis(BM) local control outcomes following stereotactic radiosurgery (SRS). By integrating pre-SRS MR image...

Biomechanically Guided Deep Learning for Deformable Multimodality Liver Registration Framework

Authors: Yunfei Dong, Dongyang Guo, Zhenyu Yang, Fang-Fang Yin, Zeyu Zhang

Affiliation: Duke University, Duke Kunshan University, Medical Physics Graduate Program, Duke Kunshan University

Abstract Preview: Purpose:
To develop a Biomechanically Guided Deep Learning Registration Network (BG-DRNet) that improves both accuracy and physiological plausibility in liver image registration. While cone-beam CT...

Combining Patch-Based CNN Models with Hierarchical Shapley Explanations for Breast Cancer Diagnosis

Authors: Xuelian Chen, John Ginn, Zhuhong Li, Kaizhong Shi, Chunhao Wang, Jianliang Wang, Chuan Wu, Zhenyu Yang, Fang-Fang Yin, Jingtong Zhao

Affiliation: The First People's Hospital of Kunshan, Duke University, Medical Physics Graduate Program, Duke Kunshan University, Duke Kunshan University, Department of Radiation Oncology, Duke Kunshan University

Abstract Preview: Purpose: Developing deep learning-based models for accurate automated breast cancer diagnosis from mammography presents significant challenges due to the small size and subtle nature of breast lesions...

Deep Learning Based Filter with Back-Projection Operator for CT Reconstruction

Authors: Justus Adamson, Mu Chen, Ke Lu, Zhenyu Yang, Fang-Fang Yin, Rihui Zhang, Yaogong Zhang, Haipeng Zhao, Haiming Zhu, Yuchun Zhu

Affiliation: Shanghai Dacheng Medical Technology, Duke University, Medical Physics Graduate Program, Duke Kunshan University, Duke Kunshan University, The First People's Hospital of Kunshan

Abstract Preview: Purpose: In filtered back-projection (FBP) reconstruction, conventional filters often reduce noise at the expense of high-frequency details, leading to structural details loss. To address this limitat...

Dual-Branch Attention-Driven Network for Enhanced Sparse-View CBCT Reconstruction Using Planning CT As Prior Knowledge

Authors: Xiaoyi Dai, Manju Liu, Weiwei Sang, Pulin Sun, Fan Xia, Zhenyu Yang, Fang-Fang Yin, Chulong Zhang, Rihui Zhang

Affiliation: Jiahui International Hospital, Radiation Oncology, Duke Kunshan University, Medical Physics Graduate Program, Duke Kunshan University

Abstract Preview: Purpose:
Current deep learning-based sparse-view CBCT reconstruction methods are prone to hallucinatory artifacts, as they rely on inferred image details that may not correspond to true anatomical ...

Enhancing CNN-Based Brain Metastasis Detection in MRI By Integrating Locoregional 3D Deformation Technique

Authors: Minbin Chen, Ke Lu, Kaizhong Shi, Chunhao Wang, Chuan Wu, Zhenyu Yang, Fang-Fang Yin, Jingtong Zhao

Affiliation: The First People's Hospital of Kunshan, Duke University, Medical Physics Graduate Program, Duke Kunshan University, Duke Kunshan University, Department of Radiation Oncology, Duke Kunshan University

Abstract Preview: Purpose: MRI-based automatic detection of brain metastases is often challenged by the small size and subtle nature of metastases. This study aimed to develop a novel deep learning-based brain metastas...

Graph Neural Network with Long Short-Term Memory for CT-Based Macrotrabecular-Massive Hepatocellular Carcinoma Diagnosis

Authors: Enhui Chang, Yunfei Dong, Yifei Hao, Chengliang Jin, Shengsheng Lai, Yi Long, Mengni Wu, Yulu Wu, Ruimeng Yang, Zhenyu Yang, Yue Yuan, Lei Zhang, Wanli Zhang, Yaogong Zhang

Affiliation: Duke Kunshan University, Department of Radiology, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Medical Physics Graduate Program, Duke Kunshan University

Abstract Preview: Purpose: Macrotrabecular-Massive Hepatocellular Carcinoma (MTM-HCC) is one type of liver cancer showed minimum image signature for accurate non-invasive diagnosis. This study aims to develop and evalu...

High-Fidelity Synthetic CT Generation from CBCT for Dibh Breast Cancer Patients Using Shortest Path Regularization

Authors: Manju Liu, Weiwei Sang, Yanyan Shi, Zhenyu Yang, Fang-Fang Yin, Chulong Zhang, Lihua Zhang, Rihui Zhang

Affiliation: Jiahui International Hospital, Jiahui International Hospital, Radiation Oncology, Duke Kunshan University, Medical Physics Graduate Program, Duke Kunshan University

Abstract Preview: Purpose: This study aims to transform cone-beam computed tomography (CBCT) images acquired from deep inspiration breath-hold (DIBH) breast cancer patients into high-fidelity synthetic CT (sCT) images....

Improving Mammography Diagnosis Accuracy through Global Context and Local Lesion Integration

Authors: Minbin Chen, Xiaoyi Dai, Xiaoyu Duan, Chunhao Wang, Fan Xia, Zhenyu Yang, Fang-Fang Yin, Chulong Zhang, Rihui Zhang

Affiliation: Duke University, Duke Kunshan University, Medical Physics Graduate Program, Duke Kunshan University, The First People's Hospital of Kunshan

Abstract Preview: Purpose: Deep learning (DL)-based mammography diagnosis presents unique challenges, as accurate interpretation requires both global breast condition analysis and local lesion structural information. E...

Improving Post-SRS Brain Metastasis Radionecrosis Diagnosis Accuracy Via Deep Feature Space Analysis

Authors: Evan Calabrese, Scott R. Floyd, Kyle J. Lafata, Zachary J. Reitman, Eugene Vaios, Chunhao Wang, Lana Wang, Deshan Yang, Zhenyu Yang, Jingtong Zhao

Affiliation: Duke University, Department of Radiation Oncology, Duke University, Duke Kunshan University

Abstract Preview: Purpose:
This study proposes a novel neural ordinary differential equation (NODE) framework to distinguish post-SRS radionecrosis from recurrence in brain metastases (BMs). By integrating imaging f...

Knowledge-Based Deep Residual U-Net for Synthetic CT Generation Using a Single MR Volume for Frameless Radiosurgery

Authors: Justus Adamson, John Ginn, Yongbok Kim, Ke Lu, Trey Mullikin, Xiwen Shu, Chunhao Wang, Zhenyu Yang, Jingtong Zhao

Affiliation: Duke University, Duke Kunshan University

Abstract Preview: Purpose:
To develop a knowledge-based deep model for synthetic CT (sCT) generation from a single MR volume in frameless radiosurgery (SRS), eliminating the need for CT simulation prior to the SRS d...

Mitigating Discrepancies in Radiology Reports: A Robust LLM Approach for Generating Consistent Impressions

Authors: Junwen Liu, Mengzhen Wang, Ning Wen, Jifeng Xiao, Fuhua Yan, Yanzhao Yang, Xuekun Zhang, Zheyu Zhang

Affiliation: Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Department of Radiology, Ruijin Hospital Shanghai Jiaotong University School of Medicine, Shanghai Jiaotong University, The SJTU-Ruijin-UIH Institute for Medical Imaging Technology, Shanghai Jiaotong University Schoo of Medicine

Abstract Preview: Purpose:This study aims to develop and evaluate a large language model (LLM) fine-tuned to generate consistent and accurate impressions from imaging findings. Additionally, the study investigates the ...

Multi-Mechanism CNN and Long Short-Term Memory Fusion Model for Improved CT-Based Thyroid Cancer Diagnosis

Authors: Yunfei Dong, Dongyang Guo, Jiongli Pan, Tao Peng, Caiyin Tang, Zhenyu Yang, Fang-Fang Yin, Lei Zhang, Tianyi Zhang, Yaogong Zhang

Affiliation: Duke Kunshan University, Department of Radiology, Taizhou Peopleโ€™s Hospital Affiliated to Nanjing Medical University, School of Future Science and Engineering, Soochow University, Medical Physics Graduate Program, Duke Kunshan University

Abstract Preview: Purpose: This study aims to improve the accuracy of CT-based diagnosis of thyroid cancer by developing a hybrid model that integrates Convolutional Neural Networks (CNNs) with Long Short-Term Memory (...

Pancrea-Seg-Net: A Semi-Supervised Deep Learning Framework for Pancreatic Tumor and Vessel Segmentation

Authors: Manju Liu, Ning Wen, Fuhua Yan, Yanzhao Yang, Zhenyu Yang, Haoran Zhang, Lei Zhang, Yajiao Zhang

Affiliation: Department of Radiology, Ruijin Hospital Shanghai Jiaotong University School of Medicine, Duke Kunshan University, Medical Physics Graduate Program, Duke Kunshan University

Abstract Preview: Purpose: Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy where precise segmentation of tumors and adjacent vessels is crucial for effective treatment planning. This study dev...

Predicting Brain V60% in Linac-Based Single-Isocenter-Multiple-Targets (SIMT) Stereotactic Radiosurgery Using Machine Learning

Authors: John Ginn, Zhuoyun Huang, Yongbok Kim, Ke Lu, Chunhao Wang, Yibo Xie, Zhenyu Yang, Jingtong Zhao

Affiliation: Duke University, Duke Kunshan University

Abstract Preview: Purpose: This study aims to develop and validate a machine learning model for predicting V60%, a critical dosimetric metric in LINAC-based Single-Isocenter-Multiple-Targets (SIMT) stereotactic radiosu...

Spherical Slicing and Convolutions for Accurate Glioma Tumor Segmentation Using Multi-Parametric MRI

Authors: Ke Lu, Chunhao Wang, Ruoxu Xia, Zhenyu Yang, Fang-Fang Yin, Chulong Zhang, Lei Zhang, Rihui Zhang, Jingtong Zhao, Haiming Zhu

Affiliation: Duke University, Duke Kunshan University, Medical Physics Graduate Program, Duke Kunshan University, The First People's Hospital of Kunshan

Abstract Preview: Purpose: The human brainโ€™s spherical geometry offers unique opportunities for improving the segmentation of tiny and irregular anatomical structures. We hypothesize that representing the brain in sphe...