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Radiotherapy, Image-Guided

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Evaluation of Deep Learning to Augment Image-Guided Radiotherapy for Head and Neck and Prostate Cancers.

JAMA network open
IMPORTANCE: Personalized radiotherapy planning depends on high-quality delineation of target tumors and surrounding organs at risk (OARs). This process puts additional time burdens on oncologists and introduces variability among both experts and inst...

Development and evaluation of a deep learning based artificial intelligence for automatic identification of gold fiducial markers in an MRI-only prostate radiotherapy workflow.

Physics in medicine and biology
Identification of prostate gold fiducial markers in magnetic resonance imaging (MRI) images is challenging when CT images are not available, due to misclassifications from intra-prostatic calcifications. It is also a time consuming task and automated...

Real-time liver tracking algorithm based on LSTM and SVR networks for use in surface-guided radiation therapy.

Radiation oncology (London, England)
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...

Performance of deep learning synthetic CTs for MR-only brain radiation therapy.

Journal of applied clinical medical physics
PURPOSE: To evaluate the dosimetric and image-guided radiation therapy (IGRT) performance of a novel generative adversarial network (GAN) generated synthetic CT (synCT) in the brain and compare its performance for clinical use including conventional ...

Enhancing digital tomosynthesis (DTS) for lung radiotherapy guidance using patient-specific deep learning model.

Physics in medicine and biology
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...

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
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...

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)
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...

Predictive online 3D target tracking with population-based generative networks for image-guided radiotherapy.

International journal of computer assisted radiology and surgery
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...

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
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...

An Upgraded Siamese Neural Network for Motion Tracking in Ultrasound Image Sequences.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
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...