Depth Images are viable representations that can be computed from the real world using cameras and/or other scanning devices. The depth map provides 2-1 2 D structure of the scene. A set of Depth Images can provide hole-free rendering of the scene. Multiple views need to blended to provide smooth hole-free rendering, however. Such a representation of the scene is bulky and needs good algorithms for real-time rendering and efficient representation. In this paper, we present a discussion on the Depth Image representation and provide a GPU-based algorithm that can render large models represented using DIs in real time. We then present a proxy-based compression scheme for Depth Images and provide results for the same. Results are shown on synthetic scenes under different conditions and on some scenes generated from images. Lastly, we initiate discussion on varying quality levels in IBR and show a way to create representations using DIs with different trade-offs between model size and rendering quality. This enables the use of this representation for a variety of rendering situations.
The present study aimed to dosimetrically evaluate the small-fields of a 6 MV flattening filter-free (FFF) photon beam using different detectors.The 6 MV FFF photon beam was used for measurement of output factor, depth dose, and beam profile of small-fields of sizes 0.6 cm × 0.6 cm to 6.0 cm × 6.0 cm. The five detectors used were SNC125c, PinPoint, EDGE, EBT3, and TLD-100. All measurements were performed as per the International Atomic Energy Agency TRS 483 protocol. Output factors measured using different detectors as direct reading ratios showed significant variation for the smallest fields, whereas after correcting them according to TRS 483, all sets of output factors were nearly compatible with each other when measurement uncertainty was also considered. The beam profile measured using SNC125c showed the largest penumbra for all field sizes, whereas the smallest was recorded with EDGE. Compared with that of EBT3, the surface dose was found to be much higher for all the other detectors. PinPoint, EBT3, TLD-100, and EDGE were found to be the detector of choice for small-field output factor measurements; however, PinPoint needs special attention when used for the smallest field size (0.6 cm × 0.6 cm). EDGE and EBT3 are optimal for measuring beam profiles. EBT3, PinPoint, and EDGE can be selected for depth dose measurements, and EBT3 is suitable for surface dose estimation.
This study aimed to dosimetrically compare and evaluate the flattening filter-free (FFF) photon beambased three-dimensional conformal radiotherapy (3DCRT), intensity-modulated radiation therapy (IMRT), and volumetric modulated arc therapy (VMAT) for lung stereotactic body radiotherapy (SBRT). RANDO phantom computed tomography (CT) images were used for treatment planning. Gross tumor volumes (GTVs) were delineated in the central and peripheral lung locations. Planning target volumes (PTVs) was determined by adding a 5 mm margin to the GTV. 3DCRT, IMRT, and VMAT plans were generated using a 6-MV FFF photon beam. Dose calculations for all plans were performed using the anisotropic analytical algorithm (AAA) and Acuros XB algorithms. The accuracy of the algorithms was validated using the dose measured in a CIRS thorax phantom. The conformity index (CI), high dose volume (HDV), low dose location (D 2cm ), and homogeneity index (HI) improved with FFF-VMAT compared to FFF-IMRT and FFF-3DCRT, while low dose volume (R 50% ) and gradient index (GI) showed improvement with FFF-3DCRT. Compared with FFF-3DCRT, a drastic decrease in the mean treatment time (TT) value was observed with FFF-VMAT for different lung sites between 57.09% and 60.39%, while with FFF-IMRT it increased between 10.78% and 17.49%. The dose calculation with Acuros XB was found to be superior to that of AAA. Based on the comparison of dosimetric indices in this study, FFF-VMAT provides a superior treatment plan to FFF-IMRT and FFF-3DCRT in the treatment of peripheral and central lung PTVs. This study suggests that Acuros XB is a more accurate algorithm than AAA in the lung region.
We present a method for design and use of a digital mouse phantom for small animal optical imaging. We map the boundary of a mouse model from magnetic resonance imaging (MRI) data through image processing algorithms and discretize the geometry by a finite element (FE) descriptor. We use a validated FE implementation of the three-dimensional (3-D) diffusion equation to model transport of near infrared (NIR) light in the phantom with a mesh resolution optimized for representative tissue optical properties on a computing system with 8-GB RAM. Our simulations demonstrate that a section of the mouse near the light source is adequate for optical system design and that the variation of intensity of light on the boundary is well within typical noise levels for up to 20% variation in optical properties and nodes used to model the boundary of the phantom. We illustrate the use of the phantom in setting goals for specific binding of targeted exogenous fluorescent contrasts based on anatomical location by simulating a nearly tenfold change in the detectability of a 2-mm-deep target depending on its placement. The methodology described is sufficiently general and may be extended to generate digital phantoms for designing clinical optical imaging systems.
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