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Results for "Deshan Yang": 15 found

4D CBCT Dynamic Images Recovery Using a 4D Neural Network

Authors: Ziheng Deng, Yao Hao, Runping Hou, Deshan Yang, Jun Zhao, Yufu Zhou

Affiliation: Department of Radiation Oncology, Duke University, School of Biomedical Engineering, Shanghai Jiao Tong University, Washington University School of Medicine, Department of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine

Abstract Preview: Purpose: 4D CBCT has been developed to provide dynamic images for image-guided radiation therapy. However, as projection data are sorted into sparse and clustered phase-specific bins, 4D CBCT images a...

A Motion Analysis of Cardiac Substructures for Guiding Stereotactic Arrhythmia Radiotherapy Motion Management

Authors: Hongyu An, Phillip Cuculich, H Michael Gach, Yao Hao, Trevor McKeown, Clifford Robinson, Yuhao Wang, Deshan Yang

Affiliation: Washington University School of Medicine in St. Louis, Washington University School of Medicine, Duke University, Department of Radiation Oncology, Duke University, Washington University in St. Louis, Department of Radiation Oncology, Washington University School of Medicine in St. Louis

Abstract Preview: Purpose: This study investigated cardiac motion characteristics of ventricular tachycardia patients to support patient-specific motion management for stereotactic arrhythmia radiotherapy (STAR) treatm...

A Novel Group-Wise Non-Rigid Iterative Closest Point Shape Registration Algorithm with Temporal Smoothness Regularizations for Computing the Respiratory Motion of the Heart in Respiratory 4DCTs and Avoiding Random Cardiac Motion Artifacts

Authors: Hongyu An, Phillip Cuculich, H Michael Gach, Yao Hao, Trevor McKeown, Clifford Robinson, Yuhao Wang, Deshan Yang

Affiliation: Washington University School of Medicine in St. Louis, Washington University School of Medicine, Duke University, Department of Radiation Oncology, Duke University, Washington University in St. Louis, Department of Radiation Oncology, Washington University School of Medicine in St. Louis

Abstract Preview: Purpose: Cardiorespiratory motion management is crucial in stereotactic arrhythmia radiotherapy to define target margins and minimize cardiac toxicity. While respiratory 4DCT (r4DCT) images can infer ...

A Novel Groupwise Shape Deformable Registration Algorithm to Quantify the Respiratory Motion of the Heart in Respiratory 4DCTs While Accounting for Random Cardiac Motion Artifacts in the Respiratory 4DCTs

Authors: Anna E. Rodrigues, Yuhao Wang, Deshan Yang

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

Abstract Preview: Purpose: Accurate motion margin definition in StereoTactic Arrhythmia Radiotherapy (STAR) requires accurate cardiorespiratory motion assessment. However, respiratory 4DCT (r4DCT) images are affected b...

A Semi-Automated Landmark Identification Framework for Liver MR-CT Image Pairs: Towards a Multi-Modality DIR Benchmark Dataset

Authors: Deshan Yang, Zhendong Zhang

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

Abstract Preview: Purpose:
The evaluation of deformable image registration (DIR) algorithms is crucial for improving accuracy and clinical adoption. However, reliable benchmarks, especially for inter-modality regist...

A Single-View-Based Electroacoustic Tomography Imaging Using Deep Learning for Electroporation Monitoring

Authors: Yankun Lang, Lei Ren, Leshan Sun, Liangzhong Xiang, Yifei Xu, Jie Zhang

Affiliation: University of Maryland School of Medicine, University of California, Irvine

Abstract Preview: Purpose: To achieve the full-view image from a single-view sinogram using a two-stage deep learning model for electroacoustic-tomography (EAT), which is an emerging imaging technique with significant ...

Brain Vessel Segmentation and Tracking in Longitudinal Glioblastoma MRI Scans

Authors: Evan Calabrese, Edward Robert Criscuolo, Deshan Yang

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

Abstract Preview: Purpose: Glioblastoma (GBM) is the most common and aggressive form of brain cancer. Deformable image registration (DIR) is a powerful tool to compute anatomical changes in longitudinal MRI scans, whic...

Dynamic X-Ray Acoustic Computed Tomography (XACT)

Authors: Leshan Sun, Liangzhong Xiang, Yifei Xu, Yuchen Yan

Affiliation: University of California, Irvine

Abstract Preview: Purpose: X-ray Acoustic Computed Tomography (XACT) is a transformative innovation in medical imaging, overcoming the limitations of conventional X-ray techniques. It introduces new possibilities in cl...

Enhanced 3D Volumetric Denoising for Low-Dose CT Images Using Hformer

Authors: Edward Robert Criscuolo, Chenlu Qin, Deshan Yang, Zhendong Zhang

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

Abstract Preview: Purpose:
Low-dose CT (LDCT) imaging minimizes radiation exposure but introduces significant noise, compromising image quality. While deep learning-based denoising models such as HFormer achieve sta...

Enhancing Image Quality in Acoustic Imaging Using the Segment Anything Model (SAM)

Authors: Jadon Buller, Zhuoran Jiang, Yankun Lang, Lei Ren, Leshan Sun, Liangzhong Xiang, Yifei Xu

Affiliation: University of Maryland School of Medicine, University of California, Irvine, University of California, Stanford University

Abstract Preview: Purpose: Electroacoustic tomography (EAT) and Protoacoustic (PA) imaging are novel modalities for treatment verification of electroporation and proton therapy. However, the limited acquisition angle i...

Image Similarity Measurement Based on Handcrafted and Deep Learning Radiomics

Authors: John Ginn, Chenlu Qin, Deshan Yang

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

Abstract Preview: Purpose: Clinical implementation of auto-segmentation tools has been hindered by poor interpretability and generalizability of AI models, necessitating the development of automated contour quality ass...

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...

Parameterized 4D Deformable Registration (p4Dreg) in Abdominal 4DCT Scans

Authors: Edward Robert Criscuolo, Deshan Yang

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

Abstract Preview: Purpose:
Deformable registration of 4DCT images has many clinical applications, but current methods are unreliable and can produce dangerous errors. Iterative, parametrized image registration does ...

Physics-Informed Neural Network for In Vivo Dosimetry during Proton Therapy Using Protoacoustic Tomography

Authors: Kristina Bjegovic, Yong Chen, Gilberto Gonzalez, Yankun Lang, Lei Ren, Leshan Sun, Liangzhong Xiang, Yifei Xu

Affiliation: University of Maryland School of Medicine, University of California, Irvine, University of Oklahoma Health Sciences Center, University of Oklahoma Health Science Center

Abstract Preview: Purpose: Proton therapy is becoming an increasingly popular choice for cancer treatment due to its precision, reduced side effects, and effectiveness. While dosimetry is fundamental to the success of ...

Synthesizing High-Quality Hepatic Vascular Tree Segmentation Datasets to Improve Segmentation Model Performance

Authors: Trevor McKeown, Deshan Yang, Zhendong Zhang

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

Abstract Preview: Purpose: Accurate delineation of liver blood vascular structures is crucial for planning and executing therapeutic interventions in liver-related medical procedures. However, current auto-segmentation...