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Related papers: Generating Synthetic Computed Tomography for Radio…

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Radiation therapy (RT) requires precise dose delivery over multiple fractions, with CT fundamental for treatment planning due to its electron density information. Repeated CT acquisitions impose radiation exposure and logistical burdens,…

Image synthesis is used to generate synthetic CTs (sCTs) from on-treatment cone-beam CTs (CBCTs) with a view to improving image quality and enabling accurate dose computation to facilitate a CBCT-based adaptive radiotherapy workflow. As…

Image and Video Processing · Electrical Eng. & Systems 2023-12-05 Chelsea A. H. Sargeant , Edward G. A. Henderson , Dónal M. McSweeney , Aaron G. Rankin , Denis Page

Purpose: Medical imaging has become increasingly important in diagnosing and treating oncological patients, particularly in radiotherapy. Recent advances in synthetic computed tomography (sCT) generation have increased interest in public…

Medical imaging is essential in modern radiotherapy, supporting diagnosis, treatment planning, and monitoring. Synthetic imaging, particularly synthetic computed tomography (sCT), is gaining traction in radiotherapy. The SynthRAD2025…

The generation of synthetic CT (sCT) images from cone-beam CT (CBCT) data using deep learning methodologies represents a significant advancement in radiation oncology. This systematic review, following PRISMA guidelines and using the PICO…

Image and Video Processing · Electrical Eng. & Systems 2025-01-27 Alzahra Altalib , Scott McGregor , Chunhui Li , Alessandro Perelli

AI requires extensive datasets, while medical data is subject to high data protection. Anonymization is essential, but poses a challenge for some regions, such as the head, as identifying structures overlap with regions of clinical…

Introduction: This study uses KV CBCT based Synthetic CT (sCT) generated through Velocity workstation and compare the target and normal tissue doses with Adaptive plan CT doses. Methods: Thirty head and neck cancer patients undergoing…

Purpose: CBCT-based adaptive radiotherapy requires daily images for accurate dose calculations. This study investigates the feasibility of applying a single convolutional network to facilitate CBCT-to-CT synthesis for head-and-neck, lung,…

Purpose: Organ-at-risk (OAR) delineation is a key step for cone-beam CT (CBCT) based adaptive radiotherapy planning that can be a time-consuming, labor-intensive, and subject-to-variability process. We aim to develop a fully automated…

Cone beam computed tomography (CBCT) images can be used for dose calculation in adaptive radiation therapy (ART). The main challenges are the large artefacts and inaccurate Hounsfield unit (HU) values. Currently, deformed planning CT images…

Medical Physics · Physics 2019-09-04 Xiao Liang , Liyuan Chen , Dan Nguyen , Zhiguo Zhou , Xuejun Gu , Ming Yang , Jing Wang , Steve Jiang

Generating synthetic CT (sCT) from MRI or CBCT plays a crucial role in enabling MRI-only and CBCT-based adaptive radiotherapy, improving treatment precision while reducing patient radiation exposure. To address this task, we adopt a fully…

Computer Vision and Pattern Recognition · Computer Science 2026-04-24 Arnela Hadzic , Simon Johannes Joham , Martin Urschler

In the field of radiotherapy, accurate imaging and image registration are of utmost importance for precise treatment planning. Magnetic Resonance Imaging (MRI) offers detailed imaging without being invasive and excels in soft-tissue…

Image and Video Processing · Electrical Eng. & Systems 2023-11-29 Saba Nikbakhsh , Lachin Naghashyar , Morteza Valizadeh , Mehdi Chehel Amirani

Cone-Beam Computed Tomography (CBCT) is widely used for real-time intraoperative imaging due to its low radiation dose and high acquisition speed. However, despite its high resolution, CBCT suffers from significant artifacts and thereby…

Image and Video Processing · Electrical Eng. & Systems 2025-06-11 Maximilian Tschuchnig , Lukas Lamminger , Philipp Steininger , Michael Gadermayr

Synthetic CT image generation from MRI scan is necessary to create radiotherapy plans without the need of co-registered MRI and CT scans. The chosen baseline adversarial model with cycle consistency permits unpaired image-to-image…

Image and Video Processing · Electrical Eng. & Systems 2023-08-16 Denis Prokopenko , Joël Valentin Stadelmann , Heinrich Schulz , Steffen Renisch , Dmitry V. Dylov

Purpose: Accurate dose calculation is essential in radiotherapy for precise tumor irradiation while sparing healthy tissue. With the growing adoption of MRI-guided and real-time adaptive radiotherapy, fast and accurate dose calculation on…

MR imaging will play a very important role in radiotherapy treatment planning for segmentation of tumor volumes and organs. However, the use of MR-based radiotherapy is limited because of the high cost and the increased use of metal…

Computer Vision and Pattern Recognition · Computer Science 2018-09-05 Cheng-Bin Jin , Hakil Kim , Wonmo Jung , Seongsu Joo , Ensik Park , Ahn Young Saem , In Ho Han , Jae Il Lee , Xuenan Cui

Cone-Beam Computed Tomography (CBCT) is widely used for intraoperative imaging due to its rapid acquisition and low radiation dose. However, CBCT images typically suffer from artifacts and lower visual quality compared to conventional…

Image and Video Processing · Electrical Eng. & Systems 2025-07-09 Maximilian Tschuchnig , Lukas Lamminger , Philipp Steininger , Michael Gadermayr

To enable magnetic resonance (MR)-only radiotherapy and facilitate modelling of radiation attenuation in humans, synthetic-CT (sCT) images need to be generated. Considering the application of MR-guided radiotherapy and online adaptive…

Accurate dose calculations in proton therapy rely on high-quality CT images. While planning CTs (pCTs) serve as a reference for dosimetric planning, Cone Beam CT (CBCT) is used throughout Adaptive Radiotherapy (ART) to generate sCTs for…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 David Vallmanya Poch , Yorick Estievenart , Elnura Zhalieva , Sukanya Patra , Mohammad Yaqub , Souhaib Ben Taieb

Purpose: This study assesses the effectiveness of Deep Learning (DL) for creating synthetic CT (sCT) images in MR-guided adaptive radiation therapy (MRgART). Methods: A Cycle-GAN model was trained with MRI and CT scan slices from MR-LINAC…

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