AIMC Topic: Radiotherapy, Image-Guided
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An Upgraded Siamese Neural Network for Motion Tracking in Ultrasound Image Sequences.
IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Nov 23, 2021
Deep learning is heavily being borrowed to solve problems in medical imaging applications, and Siamese neural networks are the front runners of motion tracking. In this article, we propose to upgrade one such Siamese architecture-based neural network...
Deep learning-based motion tracking using ultrasound images.
Medical physics
Nov 13, 2021
PURPOSE: Ultrasound (US) imaging is an established imaging modality capable of offering video-rate volumetric images without ionizing radiation. It has the potential for intra-fraction motion tracking in radiation therapy. In this study, a deep learn...
Deep learning-based thoracic CBCT correction with histogram matching.
Biomedical physics & engineering express
Oct 29, 2021
Kilovoltage cone-beam computed tomography (CBCT)-based image-guided radiation therapy (IGRT) is used for daily delivery of radiation therapy, especially for stereotactic body radiation therapy (SBRT), which imposes particularly high demands for setup...
Few-shot learning for deformable image registration in 4DCT images.
The British journal of radiology
Oct 18, 2021
OBJECTIVES: To develop a rapid and accurate 4D deformable image registration (DIR) approach for online adaptive radiotherapy.
Clinical implementation of deep-learning based auto-contouring tools-Experience of three French radiotherapy centers.
Cancer radiotherapie : journal de la Societe francaise de radiotherapie oncologique
Aug 11, 2021
Deep-learning (DL)-based auto-contouring solutions have recently been proposed as a convincing alternative to decrease workload of target volumes and organs-at-risk (OAR) delineation in radiotherapy planning and improve inter-observer consistency. Ho...
Predictive online 3D target tracking with population-based generative networks for image-guided radiotherapy.
International journal of computer assisted radiology and surgery
Jun 10, 2021
PURPOSE: Respiratory motion of thoracic organs poses a severe challenge for the administration of image-guided radiotherapy treatments. Providing online and up-to-date volumetric information during free breathing can improve target tracking, ultimate...
Artificial Intelligence in magnetic Resonance guided Radiotherapy: Medical and physical considerations on state of art and future perspectives.
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
May 19, 2021
Over the last years, technological innovation in Radiotherapy (RT) led to the introduction of Magnetic Resonance-guided RT (MRgRT) systems. Due to the higher soft tissue contrast compared to on-board CT-based systems, MRgRT is expected to significant...
DeepMC: a deep learning method for efficient Monte Carlo beamlet dose calculation by predictive denoising in magnetic resonance-guided radiotherapy.
Physics in medicine and biology
Jan 29, 2021
Emerging magnetic resonance (MR) guided radiotherapy affords significantly improved anatomy visualization and, subsequently, more effective personalized treatment. The new therapy paradigm imposes significant demands on radiation dose calculation qua...
Enhancing digital tomosynthesis (DTS) for lung radiotherapy guidance using patient-specific deep learning model.
Physics in medicine and biology
Jan 26, 2021
Digital tomosynthesis (DTS) has been proposed as a fast low-dose imaging technique for image-guided radiation therapy (IGRT). However, due to the limited scanning angle, DTS reconstructed by the conventional FDK method suffers from significant distor...
Real-time liver tracking algorithm based on LSTM and SVR networks for use in surface-guided radiation therapy.
Radiation oncology (London, England)
Jan 14, 2021
BACKGROUND: Surface-guided radiation therapy can be used to continuously monitor a patient's surface motions during radiotherapy by a non-irradiating, noninvasive optical surface imaging technique. In this study, machine learning methods were applied...
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