AIMC Topic: Radiotherapy Dosage

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A comparative study of auto-contouring softwares in delineation of organs at risk in lung cancer and rectal cancer.

Scientific reports
Radiotherapy requires the target area and the organs at risk to be contoured on the CT image of the patient. During the process of organs-at-Risk (OAR) of the chest and abdomen, the doctor needs to contour at each CT image. The delineations of large ...

Clinical suitability of deep learning based synthetic CTs for adaptive proton therapy of lung cancer.

Medical physics
PURPOSE: Adaptive proton therapy (APT) of lung cancer patients requires frequent volumetric imaging of diagnostic quality. Cone-beam CT (CBCT) can provide these daily images, but x-ray scattering limits CBCT-image quality and hampers dose calculation...

Evaluation of deep learning-based autosegmentation in breast cancer radiotherapy.

Radiation oncology (London, England)
PURPOSE: To study the performance of a proposed deep learning-based autocontouring system in delineating organs at risk (OARs) in breast radiotherapy with a group of experts.

Deep learning-augmented radioluminescence imaging for radiotherapy dose verification.

Medical physics
PURPOSE: We developed a novel dose verification method using a camera-based radioluminescence imaging system (CRIS) combined with a deep learning-based signal processing technique.

Outcome-based multiobjective optimization of lymphoma radiation therapy plans.

The British journal of radiology
At its core, radiation therapy (RT) requires balancing therapeutic effects against risk of adverse events in cancer survivors. The radiation oncologist weighs numerous disease and patient-level factors when considering the expected risk-benefit ratio...

Deep learning-enabled EPID-based 3D dosimetry for dose verification of step-and-shoot radiotherapy.

Medical physics
PURPOSE: The study aims at a novel dosimetry methodology to reconstruct a 3D dose distribution as imparted to a virtual cylindrical phantom using an electronic portal imaging device (EPID).

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 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...

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-...