CBCT-DRRs superior to CT-DRRs for target-tracking applications for pancreatic SBRT.

In current radiograph-based intra-fraction markerless target-tracking, digitally reconstructed radiographs (DRRs) from planning CTs (CT-DRRs) are often used to train deep learning models that extract information from the intra-fraction radiographs acquired during treatment. Traditional DRR algorithms were designed for patient alignment (bone matching) and may not replicate the radiographic image quality of intra-fraction radiographs at treatment. Hypothetically, generating DRRs from pre-treatment Cone-Beam CTs (CBCT-DRRs) with DRR algorithms incorporating physical modelling of on-board-imagers (OBIs) could improve the similarity between intra-fraction radiographs and DRRs by eliminating inter-fraction variation and reducing image-quality mismatches between radiographs and DRRs.

Evaluation of deep learning based implanted fiducial markers tracking in pancreatic cancer patients.

Real-time target position verification during pancreas stereotactic body radiation therapy (SBRT) is important for the detection of unplanned tumour motions. Fast and accurate fiducial marker segmentation is a Requirement of real-time marker-based verification. Deep learning (DL) segmentation techniques are ideal because they don't require additional learning imaging or prior marker information (e.

In-line MRI-LINAC depth dose measurements using an in-house plastic scintillation dosimeter.

Plastic scintillation dosimeters (PSDs) have many properties that make them desirable for relative dosimetry with MRI-LINACs. An in-house PSD, Farmer ionisation chamber and Gafchromic EBT3 film were used to measure central axis percentage depth dose distributions (PDDs) at the Australian MRI-LINAC Mean errors were calculated between each detector's responses, where the in-house PSD was on average within 0.7% of the Farmer chamber and 1.

Temporal modelling of beryllium oxide ceramics' real-time OSL for dosimetry with a superficial 140 kVp X-ray beam.

A new analysis method for the rtOSL of BeO ceramics is presented, using temporal curve fitting of an expected rtOSL signal to measured rtOSL signals. The presented technique does not require heavy signal averaging to determine the OSL bleaching correction associated with the ΔrtOSL method, reducing uncertainties in the post-correction rtOSL. The corrected rtOSL signal was demonstrated to be linear with dose, and dose-rate independent.

MRI-LINAC beam profile measurements using a plastic scintillation dosimeter.

Plastic scintillation dosimeters (PSDs) possess many desirable qualities for dosimetry with LINACs. These qualities are expected to make PSDs effective for MRI-LINAC dosimetry, however little research has been conducted investigating their dosimetric performance with MRI-LINACs. In this work, an in-house PSD was used to measure 8 beam profiles with an in-line MRI-LINAC, compared with film measurements.

First measurements with a plastic scintillation dosimeter at the Australian MRI-LINAC.

MRI-LINACs combine MRI and LINAC technologies with the potential for image guided radiation therapy with optimal soft-tissue contrast. In this work, we present the advantages and limitations of plastic scintillation dosimeters (PSDs) for relative dosimetry with MRI-LINACs. PSDs possess many desirable qualities, including magnetic field insensitivity and irradiation angle independence, which are expected to make them suitable for dosimetry with MRI-LINACs.

An algorithmic approach to single-probe Cherenkov removal in pulsed x-ray beams.

Purpose: The removal of Cherenkov light in an optical dosimetry system is an important process to ensure accurate dosimetry without compromising spatial resolution. Many solutions have been presented in the literature, each with advantages and disadvantages. We present a methodology to remove Cherenkov light from a scintillator fiber optic dosimeter in a pulsed megavoltage x-ray beam using the temporal waveform across the pulse.

Temporal separation of Cerenkov radiation and scintillation using a clinical LINAC and artificial intelligence.

Convolutional neural network (CNN) type artificial intelligences were trained to estimate the Cerenkov radiation present in the temporal response of a LINAC irradiated scintillator-fiber optic dosimeter. The CNN estimate of Cerenkov radiation is subtracted from the combined scintillation and Cerenkov radiation temporal response of the irradiated scintillator-fiber optic dosimeter, giving the sole scintillation signal, which is proportional to the scintillator dose. The CNN measured scintillator dose was compared to the background subtraction measured scintillator dose and ionisation chamber measured dose.

Temporal separation of Cerenkov radiation and scintillation using artificial neural networks in Clinical LINACs.

The irradiation of scintillator-fiber optic dosimeters by clinical LINACs results in the measurement of scintillation and Cerenkov radiation. In scintillator-fiber optic dosimetry, the scintillation and Cerenkov radiation responses are separated to determine the dose deposited in the scintillator volume. Artificial neural networks (ANNs) were trained and applied in a novel single probe method for the temporal separation of scintillation and Cerenkov radiation.

A comparison of temporal Cherenkov separation techniques in pulsed signal scintillator dosimetry.

Cherenkov radiation is the primary source of unwanted light in a scintillator dosimetry system. In this work we compare two techniques for temporally separating Cherenkov radiation from a slow scintillator signal. These techniques are applicable to a pulsed radiation beam.

Temporally separating Cherenkov radiation in a scintillator probe exposed to a pulsed X-ray beam.

Cherenkov radiation is generated in optical systems exposed to ionising radiation. In water or plastic devices, if the incident radiation has components with high enough energy (for example, electrons or positrons with energy greater than 175keV), Cherenkov radiation will be generated. A scintillator dosimeter that collects optical light, guided by optical fibre, will have Cherenkov radiation generated throughout the length of fibre exposed to the radiation field and compromise the signal.