AI Medical Compendium Topic:
Radiotherapy Planning, Computer-Assisted

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Catheter position prediction using deep-learning-based multi-atlas registration for high-dose rate prostate brachytherapy.

Medical physics
PURPOSE: High-dose-rate (HDR) prostate brachytherapy involves treatment catheter placement, which is currently empirical and physician dependent. The lack of proper catheter placement guidance during the procedure has left the physicians to rely on a...

Deep learning based synthetic-CT generation in radiotherapy and PET: A review.

Medical physics
Recently,deep learning (DL)-based methods for the generation of synthetic computed tomography (sCT) have received significant research attention as an alternative to classical ones. We present here a systematic review of these methods by grouping the...

Deep learning methods to generate synthetic CT from MRI in radiotherapy: A literature review.

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)
PURPOSE: In radiotherapy, MRI is used for target volume and organs-at-risk delineation for its superior soft-tissue contrast as compared to CT imaging. However, MRI does not provide the electron density of tissue necessary for dose calculation. Sever...

Saliency-guided deep learning network for automatic tumor bed volume delineation in post-operative breast irradiation.

Physics in medicine and biology
Efficient, reliable and reproducible target volume delineation is a key step in the effective planning of breast radiotherapy. However, post-operative breast target delineation is challenging as the contrast between the tumor bed volume (TBV) and nor...

Deep learning method for prediction of patient-specific dose distribution in breast cancer.

Radiation oncology (London, England)
BACKGROUND: Patient-specific dose prediction improves the efficiency and quality of radiation treatment planning and reduces the time required to find the optimal plan. In this study, a patient-specific dose prediction model was developed for a left-...

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...

Managing tumor changes during radiotherapy using a deep learning model.

Medical physics
PURPOSE: We propose a treatment planning framework that accounts for weekly lung tumor shrinkage using cone beam computed tomography (CBCT) images with a deep learning-based model.

A deep learning-based radiomic nomogram for prognosis and treatment decision in advanced nasopharyngeal carcinoma: A multicentre study.

EBioMedicine
BACKGROUND: Induction chemotherapy (ICT) plus concurrent chemoradiotherapy (CCRT) and CCRT alone were the optional treatment regimens in locoregionally advanced nasopharyngeal carcinoma (NPC) patients. Currently, the choice of them remains equivocal ...

Personalized brachytherapy dose reconstruction using deep learning.

Computers in biology and medicine
BACKGROUND AND PURPOSE: Accurate calculation of the absorbed dose delivered to the tumor and normal tissues improves treatment gain factor, which is the major advantage of brachytherapy over external radiation therapy. To address the simplifications ...

Applications of machine and deep learning to patient-specific IMRT/VMAT quality assurance.

Journal of applied clinical medical physics
In order to deliver accurate and safe treatment to cancer patients in radiation therapy using advanced techniques such as intensity modulated radiation therapy (IMRT) and volumetric-arc radiation therapy (VMAT), patient specific quality assurance (QA...