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Results for "sparse view": 10 found

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 ...

Deep Learning-Based Fast CBCT Imaging with Orthogonal X-Ray Projections for Gynecological Cancer Radiotherapy

Authors: Beth Bradshaw Ghavidel, Chih-Wei Chang, Yuan Gao, Priyanka Kapoor, Shaoyan Pan, Junbo Peng, Richard L.J. Qiu, Jill Remick, Justin R. Roper, Zhen Tian, Xiaofeng Yang

Affiliation: Whinship Cancer Institute, Emory University, Emory University, University of Chicago, Department of Radiation Oncology and Winship Cancer Institute, Emory University

Abstract Preview: Purpose: Current cone-beam computed tomography (CBCT) typically requires no less than 200 degrees of angular projections, which prolongs scanning time and increases radiation exposure. To address thes...

Development of an Orthogonal X-Ray Projections-Guided Cascading Volumetric Reconstruction and Tumor-Tracking Model for Adaptive Radiotherapy

Authors: Penghao Gao, Zejun Jiang, Huazhong Shu, Linlin Wang, Gongsen Zhang, Jian Zhu

Affiliation: Laboratory of Image Science and Technology, Key Laboratory of Computer Network and Information Integration, Southeast University, Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Artificial Intelligence Laboratory, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences

Abstract Preview: Purpose: We propose a cascading framework for time-varying anatomical volumetric reconstruction and tumor-tracking, guided by onboard orthogonal-view X-ray projections.
Methods: We employe multiple...

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 ...

Emulating Human Perception of Low-Dose CT Image Quality Via Deep Generative Models

Authors: Jongduk Baek, Jooho Lee, Adam S. Wang

Affiliation: Stanford University, Yonsei University

Abstract Preview: Purpose: Optimizing the balance between radiation dose and image quality in computed tomography (CT) is important for minimizing patient X-ray exposure while maintaining diagnostic accuracy. While rad...

Enhance Four-Dimension Cone-Beam Computed Tomography (4D-CBCT) from Sparse Views Using a Novel Deep Learning Model

Authors: Lei Ren, Jie Zhang

Affiliation: University of Maryland School of Medicine

Abstract Preview: Purpose: 4D-CBCT is valuable for imaging anatomy affected by respiratory motions to guide radiotherapy delivery. However, 4D-CBCT often has undersampled projections acquired in each respiratory phase ...

Rapid CBCT Imaging with Ultra-Sparse X-Ray Projections for Head & Neck Cancer Radiotherapy

Authors: Hania A. Al-Hallaq, Chih-Wei Chang, Anees H. Dhabaan, Yuan Gao, Shaoyan Pan, Junbo Peng, Richard L.J. Qiu, Keyur Shah, Sibo Tian, Zhen Tian, Xiaofeng Yang, David Yu, Jun Zhou

Affiliation: Emory University, Whinship Cancer Institute, Emory University, University of Chicago, Department of Radiation Oncology and Winship Cancer Institute, Emory University

Abstract Preview: Purpose: Traditional cone-beam computed tomography (CBCT) often requires multiple angular projections, increasing radiation exposure and extending scanning times, which may lead to heightened patient ...

Three-Dimensional Reconstruction of Triggered Images with Dehazing Algorithm for Precise Intrafraction Motion Detection in Spine SBRT

Authors: Hyosung Cho, Dae Yup Han, Duhee Jeon, Jiwon Park, Hyesun Yang

Affiliation: Department of Therapeutic Radiology, Yale University School of Medicine, Yonsei University

Abstract Preview: Purpose: To precisely detect intrafraction patient motion during spine stereotactic body radiotherapy (SBRT) treatment delivery, we propose an optimized technique for three-dimensional reconstruction ...

Ultra-Sparse-View Cone-Beam CT Reconstruction Based Strictly-Structure-Preserved Deep Neural Network in Image-Guided Radiation Therapy

Authors: Guangjun Li, Ying Song, Huanan Tang, Tianxiong Wu, Qiuyi Ye, Wei Zhang

Affiliation: West China Second Hospital of Sichuan University, United Imaging Healthcare, West China Hospital of Sichuan University

Abstract Preview: Purpose:
To propose a general low-dose reconstruction model for ultra-sparse-view cone-beam CT (CBCT) and evaluate its clinical application in improving image quality and reducing radiation dose fo...

Weakly Supervised Spatial Implicit Neural Representation Learning for 3D MRI-Ultrasound Deformable Image Registration in HDR Prostate Brachytherapy

Authors: Michael Baine, Yang Lei, Yu Lei, Ruirui Liu, Tian Liu, Jing Wang

Affiliation: Icahn School of Medicine at Mount Sinai, University of Nebraska Medical Center

Abstract Preview: Purpose: Accurate 3D deformable registration of MRI and ultrasound (US) is essential for real-time image guidance during high-dose-rate (HDR) prostate brachytherapy. However, MRI-US registration of th...