Fabrication of a Normoxic Polymer Gel Dosimeter and its Dose Distribution Characteristics

Cho, Yu Ra; Park, Hyung Wook; Kim, Ae Ran; Park, Chae Hee; Bong, Ji Hye; Lee, Jae Choon; Kwon, Soo Il; Cho, Kwang Hwan; Lee, Sang Hoon; Cho, Sam Ju; Ko, In Ok; Park, Ji Ae; Kim, Kyong Min; Kim, Kum Bae; Shin, Sang Hun; Jung, Haijo; Ji, Young Hoon

doi:10.3938/jkps.59.169

Cited by 11 publications

(4 citation statements)

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“…Mathieu et al ( 2019) also use their hyperbolic VAE to learn representations of MNIST and find that using both the Riemannian normal and the gyroplane layer improve test loglikelihoods, especially at low latent dimensions. Cho et al (2022) extend the previous two works by proposing a new version of the hyperbolic wrapped normal distribution (HWN) in Lorentz model. Their primary observation is that for the wrapped normal distribution, the principal axes of the distributions are not aligned with the local standard axes, see Fig.…”

Section: Hyperbolic Vaesmentioning

confidence: 79%

Hyperbolic Deep Learning in Computer Vision: A Survey

Mettes,

Ghadimi Atigh,

Keller-Ressel

et al. 2024

Int J Comput Vis

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Deep representation learning is a ubiquitous part of modern computer vision. While Euclidean space has been the de facto standard manifold for learning visual representations, hyperbolic space has recently gained rapid traction for learning in computer vision. Specifically, hyperbolic learning has shown a strong potential to embed hierarchical structures, learn from limited samples, quantify uncertainty, add robustness, limit error severity, and more. In this paper, we provide a categorization and in-depth overview of current literature on hyperbolic learning for computer vision. We research both supervised and unsupervised literature and identify three main research themes in each direction. We outline how hyperbolic learning is performed in all themes and discuss the main research problems that benefit from current advances in hyperbolic learning for computer vision. Moreover, we provide a high-level intuition behind hyperbolic geometry and outline open research questions to further advance research in this direction.

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Section: Hyperbolic Vaesmentioning

confidence: 79%

Hyperbolic Deep Learning in Computer Vision: A Survey

Mettes,

Ghadimi Atigh,

Keller-Ressel

et al. 2024

Int J Comput Vis

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“…Since it is evident that no additional mass is added to polymer gels through irradiation, observed mass density changes may result from the mass redistribution within the polymer system, or from gels volume change due to irradiation, which is linked with the potential loss of spatial integrity in polymer gels [ 19 ]. Density changes of the irradiated dose gels may occur due to the presence of two parallel processes running in irradiated gels: gelation and post-irradiation polymerization During the gelation process, there is a transition from a liquid to a semi-liquid phase due to the formation of macromolecular structures from a branched polymer structure [ 43 ]. It is important to note that this process is extremely fast when the solution is cooled down below 35 °C, but the evolution is much slower in later phases.…”

Section: Resultsmentioning

confidence: 99%

“…It is important to note that this process is extremely fast when the solution is cooled down below 35 °C, but the evolution is much slower in later phases. This process can take up to 30 daysor longer and may cause shrinkage of the gel by losing water, which leads to the density changes in irradiated gels contributing to the evolution/instability in the dose responses [ 10 , 39 , 43 , 44 , 45 ]. Post-irradiation polymerization reactions progress up to 10 h after the irradiation [ 19 , 42 ], however, they do not fully stop due to the presence of remaining long-term radicals.…”

Section: Resultsmentioning

confidence: 99%

The Impact of Temporal Changes in Irradiated nMAG Polymer Gels on Their Applicability in Small Field Dosimetry in Radiotherapy

Krauleidis

Adlienė

Rutkūnienė

2022

Gels

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As advanced radiotherapy techniques progress to deliver a high absorbed dose to the target volume while minimizing the dose to normal tissues using intensity-modulated beams, arcs or stereotactic radiosurgery, new challenges occur to assure that the high treatment dose is delivered homogeneously to the tumor. Small irradiation field sizes (≤1 cm2) that tightly conform to precise target regions and allow for the deliverance of doses with a high therapeutic ratio, are of particular interest. However, the small field dosimetry using conventional dosimeters is limited by the relative large size of the detector. Radiation-sensitive polymer gels have the potential to meet this dosimetry challenge due to their almost unlimited ability in resolving three-dimensional dose distributions of any shape and makes them unique and suitable for the evaluation of dose profiles and the verification of complex doses. In this work, dose distributions in nMAG gels that have been irradiated to different doses by applying a 6 MV FFF photon beam collimated to 1 cm2, were analyzed and the dose profiles were evaluated by applying a gamma passing rate criteria of 3%/3 mm and considering different post-irradiation time intervals between the irradiation and the gels read out process. X-ray CT and NMR imaging procedures were used for the dose evaluation. It was found that the shape and uniformity of the dose profiles were changing due to post-irradiation polymerization and gelation processes, indicating time dependent growing uniformity which was better expressed for the higher delivered doses. It was estimated that in order to obtain acceptably symmetric small field dose profiles, a longer post-irradiation time is needed for getting the full scope of the polymerization as compared with the recently recommended 24 h period between irradiation and the read out processes of the dose gels. An estimated overall uncertainty (double standard deviation, 95% confidence level) of 3.66% was achieved by applying R2 measurements (NMR read out), and a 3.81–applying X-ray CT read out for 12 Gy irradiated gels 56 h post-irradiation. An increasing tendency for the uncertainty was observed with a decreasing post-irradiation time. A gamma passing rate of 90.3% was estimated for the 12 Gy irradiated gels and, 56 h post-irradiation, the X-ray CT evaluated gels as well as a gamma passing rate of 92.7% was obtained for the NMR evaluated gels applying a 3%/3mm passing criteria.

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“…Therefore, the dose distribution can be obtained by measuring the changes of growing polymer chains. Several modalities have been used, including X-ray computed tomography [ 4 ], optical computed tomography [ 5 , 6 ], ultrasound [ 7 ], and magnetic resonance imaging (MRI) [ 8 , 9 ]. In MRI, the spin–spin relaxation rate (R2) depends on the mobility of water molecules.…”

Section: Introductionmentioning

confidence: 99%

A Comprehensive Evaluation of NIPAM Polymer Gel Dosimeters on Three Orthogonal Planes and Temporal Stability Analysis

2016

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Polymer gel dosimeters have been proven useful for dose evaluation in radiotherapy treatments. Previous studies have demonstrated that using a polymer gel dosimeter requires a 24 h reaction time to stabilize and further evaluate the measured dose distribution in two-dimensional dosimetry. In this study, the short-term stability within 24 h and feasibility of N-isopropylacrylamide (NIPAM) polymer gel dosimeters for use in three-dimensional dosimetry were evaluated using magnetic resonance imaging (MRI). NIPAM gels were used to measure the dose volume in a clinical case of intensity-modulated radiation therapy (IMRT). For dose readouts, MR images of irradiated NIPAM gel phantoms were acquired at 2, 5, 12, and 24 h after dose delivery. The mean standard errors of dose conversion from using dose calibration curves (DRC) were calculated. The measured dose volumes at the four time points were compared with those calculated using a treatment planning system (TPS). The mean standard errors of the dose conversion from using the DRCs were lower than 1 Gy. Mean pass rates of 2, 5, 12, and 24 h axial dose maps calculated using gamma evaluation with 3% dose difference and 3 mm distance-to-agreement criteria were 83.5% ± 0.9%, 85.9% ± 0.6%, 98.7% ± 0.3%, and 98.5% ± 0.9%, respectively. Compared with the dose volume histogram of the TPS, the absolute mean relative volume differences of the 2, 5, 12, and 24 h measured dose volumes were lower than 1% for the irradiated region with an absorbed dose higher than 2.8 Gy. It was concluded that a 12 h reaction time was sufficient to acquire accurate dose volume using the NIPAM gels with MR readouts.

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Fabrication of a Normoxic Polymer Gel Dosimeter and its Dose Distribution Characteristics

Cited by 11 publications

References 0 publications

Hyperbolic Deep Learning in Computer Vision: A Survey

Hyperbolic Deep Learning in Computer Vision: A Survey

The Impact of Temporal Changes in Irradiated nMAG Polymer Gels on Their Applicability in Small Field Dosimetry in Radiotherapy

A Comprehensive Evaluation of NIPAM Polymer Gel Dosimeters on Three Orthogonal Planes and Temporal Stability Analysis

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