Purpose: The first aim of this study is to investigate the feasibility of online autocontouring of
tumor in low field MR images (0.2 and 0.5 T) by means of a phantom and simulation study …

Purpose: To develop a neural‐network based autocontouring algorithm for intrafractional
lung‐tumor tracking using Linac‐MR and evaluate its performance with phantom and in‐vivo …

To add an intelligent parameter optimization capability to our autocontouring algorithm, and
evaluate its performance using in-vivo data. Methods An autocontouring algorithm for …

Purpose Real‐time tracking of lung tumors using magnetic resonance imaging (MRI) has
been proposed as a potential strategy to mitigate the ill‐effects of breathing motion in …

Purpose: This study introduces a novel autocontouring algorithm based on particle filter for
lung tumors. It is validated on dynamic magnetic resonance (MR) images and is developed …

Background and purpose Radiotherapy guidance based on magnetic resonance imaging
(MRI) is currently becoming a clinical reality. Fast 2d cine MRI sequences are expected to …

This work introduces a 2D motion prediction algorithm for lung tumors applied to dynamic
MR images that combines intrafractional tumor deformations. It is developed in the context of …

Purpose: To address practical issues of implementing artificial neural networks (ANN) for
lung‐tumor motion prediction in MRI‐based intrafractional lung‐tumor tracking. Methods: A …

Abstract 2D cine MR imaging may be utilized to monitor rapidly moving tumors and organs-
at-risk for real-time adaptive radiotherapy. This study systematically investigates the impact …

Purpose: Intrafraction deformation limits targeting accuracy in radiotherapy. Studies show
tumor deformation of over 10 mm for both single tumor deformation and system deformation …