AI Medical Compendium Topic:
Radiotherapy Planning, Computer-Assisted

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Deep Learning model for markerless tracking in spinal SBRT.

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)
Stereotactic Body Radiation Therapy (SBRT), alternatively termed Stereotactic ABlative Radiotherapy (SABR) or Stereotactic RadioSurgery (SRS), delivers high dose with a sub-millimeter accuracy. It requires meticulous precautions on positioning, as sh...

RapidBrachyDL: Rapid Radiation Dose Calculations in Brachytherapy Via Deep Learning.

International journal of radiation oncology, biology, physics
PURPOSE: Detailed and accurate absorbed dose calculations from radiation interactions with the human body can be obtained with the Monte Carlo (MC) method. However, the MC method can be slow for use in the time-sensitive clinical workflow. The aim of...

Clinical implementation of MRI-based organs-at-risk auto-segmentation with convolutional networks for prostate radiotherapy.

Radiation oncology (London, England)
BACKGROUND: Structure delineation is a necessary, yet time-consuming manual procedure in radiotherapy. Recently, convolutional neural networks have been proposed to speed-up and automatise this procedure, obtaining promising results. With the advent ...

Radiomics and deep learning in lung cancer.

Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]
Lung malignancies have been extensively characterized through radiomics and deep learning. By providing a three-dimensional characterization of the lesion, models based on radiomic features from computed tomography (CT) and positron-emission tomograp...

Comparison of CBCT based synthetic CT methods suitable for proton dose calculations in adaptive proton therapy.

Physics in medicine and biology
In-room imaging is a prerequisite for adaptive proton therapy. The use of onboard cone-beam computed tomography (CBCT) imaging, which is routinely acquired for patient position verification, can enable daily dose reconstructions and plan adaptation d...

Artificial Intelligence in radiotherapy: state of the art and future directions.

Medical oncology (Northwood, London, England)
Recent advances in computing capability allowed the development of sophisticated predictive models to assess complex relationships within observational data, described as Artificial Intelligence. Medicine is one of the several fields of application a...

Error detection using a convolutional neural network with dose difference maps in patient-specific quality assurance for volumetric modulated arc therapy.

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)
The aim of this study was to evaluate the use of dose difference maps with a convolutional neural network (CNN) to detect multi-leaf collimator (MLC) positional errors in patient-specific quality assurance for volumetric modulated radiation therapy (...

Deep convolutional neural networks for automated segmentation of brain metastases trained on clinical data.

Radiation oncology (London, England)
INTRODUCTION: Deep learning-based algorithms have demonstrated enormous performance in segmentation of medical images. We collected a dataset of multiparametric MRI and contour data acquired for use in radiosurgery, to evaluate the performance of dee...

4D-CT deformable image registration using multiscale unsupervised deep learning.

Physics in medicine and biology
Deformable image registration (DIR) of 4D-CT images is important in multiple radiation therapy applications including motion tracking of soft tissue or fiducial markers, target definition, image fusion, dose accumulation and treatment response evalua...