Fast four‐dimensional cone‐beam computed tomography reconstruction using deformable convolutional networks-Reference-Cited by-同舟云学术

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Fast four‐dimensional cone‐beam computed tomography reconstruction using deformable convolutional networks

Published:2022-06-22 Issue:10 Volume:49 Page:6461-6476
ISSN:0094-2405
Container-title:Medical Physics
language:en
Short-container-title:Medical Physics

Author:

Jiang Zhuoran¹,Chang Yushi²,Zhang Zeyu¹,Yin Fang‐Fang¹³⁴,Ren Lei⁵

Affiliation:

1. Medical Physics Graduate Program Duke University Durham North Carolina USA

2. Department of Radiation Oncology Hospital of the University of Pennsylvania Philadelphia Pennsylvania USA

3. Department of Radiation Oncology Duke University Medical Center Durham North Carolina USA

4. Medical Physics Graduate Program Duke Kunshan University Kunshan Jiangsu China

5. Department of Radiation Oncology University of Maryland, Baltimore Baltimore Maryland USA

Funder

National Institutes of Health

Publisher

Wiley

Subject

General Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/mp.15806

Reference39 articles.

1. Respiratory correlated cone beam CT

2. Frameless Stereotactic Body Radiotherapy for Lung Cancer Using Four-Dimensional Cone Beam CT Guidance

3. SPARE: Sparse‐view reconstruction challenge for 4D cone‐beam CT from a 1‐min scan

4. A novel digital tomosynthesis (DTS) reconstruction method using a deformation field map

5. A technique for estimating 4D-CBCT using prior knowledge and limited-angle projections

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2. Motion compensated cone-beam CT reconstruction using an a priori motion model from CT simulation: a pilot study;Physics in Medicine & Biology;2024-03-26

3. Artifact Reduction in 3D and 4D Cone-Beam Computed Tomography Images With Deep Learning: A Review;IEEE Access;2024

4. Electrical Impedance Tomography Deep Imaging With Dual-Branch U-Net Based on Deformable Convolution and Hyper-Convolution;IEEE Transactions on Instrumentation and Measurement;2024

5. Radiation-induced acoustic signal denoising using a supervised deep learning framework for imaging and therapy monitoring;Physics in Medicine & Biology;2023-11-29

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