A voxel-based, forward projection algorithm for rendering surface and volumetric data

2003 ◽  
Author(s):  
J.R. Wright ◽  
J.C.L. Hsieh
Keyword(s):  
Projection Algorithm ◽  
Volumetric Data ◽  
Forward Projection

scholarly journals Optimizing Discount and Reputation Trade-Offs in E-Commerce Systems: Characterization and Online Learning

2019 ◽  
Vol 33 ◽  
pp. 7992-7999 ◽  
Author(s):  
Hong Xie ◽  
Yongkun Li ◽  
John C. S. Lui
Keyword(s):  
Learning Algorithm ◽  
Profit Maximization ◽  
Projection Algorithm ◽  
Reputation Systems ◽  
Maximization Problem ◽  
Transaction Data ◽  
Q Learning ◽  
Price Discounts ◽  
Trade Offs ◽  
Forward Projection

Feedback-based reputation systems are widely deployed in E-commerce systems. Evidences showed that earning a reputable label (for sellers of such systems) may take a substantial amount of time and this implies a reduction of profit. We propose to enhance sellers’ reputation via price discounts. However, the challenges are: (1) The demands from buyers depend on both the discount and reputation; (2) The demands are unknown to the seller. To address these challenges, we first formulate a profit maximization problem via a semiMarkov decision process (SMDP) to explore the optimal trade-offs in selecting price discounts. We prove the monotonicity of the optimal profit and optimal discount. Based on the monotonicity, we design a QLFP (Q-learning with forward projection) algorithm, which infers the optimal discount from historical transaction data. We conduct experiments on a dataset from to show that our QLFP algorithm improves the profit by as high as 50% over both the classical Q-learning and speedy Q-learning algorithm. Our QLFP algorithm also improves the profit by as high as four times over the case of not providing any price discount.

scholarly journals Physical Density Estimations of Single- and Dual-energy CT Using Material-based Forward Projection Algorithm

2020 ◽  
Author(s):  
Kai-wen Li ◽  
Daiyu FUjiwara ◽  
Akihiro Haga ◽  
Huisheng Liu ◽  
Li-Sheng Geng
Keyword(s):  
Biological Tissues ◽  
Ct Images ◽  
Dual Energy ◽  
Projection Algorithm ◽  
Dual Energy Ct ◽  
Density Prediction ◽  
Physical Density ◽  
Simulation Based ◽  
Forward Projection ◽  
Mean Square Errors

Abstract Purpose: This study aims to evaluate the accuracy of physical density prediction in single-energy CT (SECT) and dual-energy CT (DECT) by adapting a fully simulation-based method using a material-based forward projection algorithm (MBFPA). Methods: We used biological tissues referenced in ICRU Report 44 and tissue substitutes to prepare three different types of phantoms for calibrating the HU-to-density curves. Sinograms were first virtually generated by the MBFPA with four representative energy spectra (i.e. 80 kV, 100 kV, 120 kV, and 6 MV) and then reconstructed to form realistic CT images by adding statistical noise. The HU-to-density curves in each spectrum and their pairwise combinations were derived from the CT images. The accuracy of these curves was validated using the ICRP110 human phantoms.Results: The relative mean square errors (RMSEs) of the physical density by the HU-to-density curves calibrated with kV SECT nearly presented no phantom size dependence. The kV-kV DECT calibrated curves were also comparable with those from the kV SECT. The phantom size effect became notable when the MV X-ray beams were employed for both SECT and DECT due to beam hardening effects. The RMSEs were decreased using the biological tissue phantom.Conclusions: Simulation-based density prediction can be useful in the theoretical analysis of SECT and DECT calibrations. The results of this study indicated that the accuracy of SECT calibration is comparable with that of DECT using biological tissues. The size and shape of the calibration phantom could affect the accuracy, especially for MV CT calibrations.

Fast forward projection and backward projection algorithm using SIMD

2006 ◽  
Author(s):  
I. K. Hong ◽  
S. T. Chung ◽  
H. K. Kim ◽  
Y. B. Kim ◽  
Y. D. Son ◽  
...  
Keyword(s):  
Projection Algorithm ◽  
Forward Projection

Physical density estimations of single- and dual-energy CT using material-based forward projection algorithm: a simulation study

2021 ◽  
Author(s):  
Kai-Wen Li ◽  
Daiyu Fujiwara ◽  
Akihiro Haga ◽  
Huisheng Liu ◽  
Li-Sheng Geng
Keyword(s):  
Biological Tissues ◽  
Ct Images ◽  
Dual Energy ◽  
Projection Algorithm ◽  
Dual Energy Ct ◽  
X Ray ◽  
Density Prediction ◽  
Physical Density ◽  
Simulation Based ◽  
Forward Projection

Objectives: This study aims to evaluate the accuracy of physical density prediction in single-energy CT (SECT) and dual-energy CT (DECT) by adapting a fully simulation-based method using a material-based forward projection algorithm (MBFPA). Methods: We used biological tissues referenced in ICRU Report 44 and tissue substitutes to prepare three different types of phantoms for calibrating the Hounsfield unit (HU)-to-density curves. Sinograms were first virtually generated by the MBFPA with four representative energy spectra (i.e. 80 kVp, 100 kVp, 120 kVp, and 6 MVp) and then reconstructed to form realistic CT images by adding statistical noise. The HU-to-density curves in each spectrum and their pairwise combinations were derived from the CT images. The accuracy of these curves was validated using the ICRP110 human phantoms. Results: The relative mean square errors (RMSEs) of the physical density by the HU-to-density curves calibrated with kV SECT nearly presented no phantom size dependence. The kV–kV DECT calibrated curves were also comparable with those from the kV SECT. The phantom size effect became notable when the MV X-ray beams were employed for both SECT and DECT due to beam-hardening effects. The RMSEs were decreased using the biological tissue phantom. Conclusion: Simulation-based density prediction can be useful in the theoretical analysis of SECT and DECT calibrations. The results of this study indicated that the accuracy of SECT calibration is comparable with that of DECT using biological tissues. The size and shape of the calibration phantom could affect the accuracy, especially for MV CT calibrations. Advances in knowledge: The present study is based on a full simulation environment, which accommodates various situations such as SECT, kV–kV DECT, and even kV–MV DECT. In this paper, we presented the advances pertaining to the accuracy of the physical density prediction when applied to SECT and DECT in the MV X-ray energy range. To the best of our knowledge, this study is the first to validate the physical density estimation both in SECT and DECT using human-type phantoms.

Electron Microscopy and image reconstruction reveal the structural basis for spectrin's elastic properties

1992 ◽  
Vol 50 (1) ◽  
pp. 510-511
Author(s):  
Amy M. McGough ◽  
Robert Josephs
Keyword(s):  
Electron Microscopy ◽  
Elastic Properties ◽  
Conformational Changes ◽  
Quaternary Structure ◽  
Three Dimensional ◽  
Membrane Skeleton ◽  
Projection Algorithm ◽  
Structural Basis ◽  
Iterative Approximation ◽  
Membrane Skeletons

The remarkable deformability of the erythrocyte derives in large part from the elastic properties of spectrin, the major component of the membrane skeleton. It is generally accepted that spectrin's elasticity arises from marked conformational changes which include variations in its overall length (1). In this work the structure of spectrin in partially expanded membrane skeletons was studied by electron microscopy to determine the molecular basis for spectrin's elastic properties. Spectrin molecules were analysed with respect to three features: length, conformation, and quaternary structure. The results of these studies lead to a model of how spectrin mediates the elastic deformation of the erythrocyte.Membrane skeletons were isolated from erythrocyte membrane ghosts, negatively stained, and examined by transmission electron microscopy (2). Particle lengths and end-to-end distances were measured from enlarged prints using the computer program MACMEASURE. Spectrin conformation (straightness) was assessed by calculating the particles’ correlation length by iterative approximation (3). Digitised spectrin images were correlation averaged or Fourier filtered to improve their signal-to-noise ratios. Three-dimensional reconstructions were performed using a suite of programs which were based on the filtered back-projection algorithm and executed on a cluster of Microvax 3200 workstations (4).

Custom Designed Orthodontic Attachment Manufactured Using a Biocompatible 3D Printing Material

2017 ◽  
Vol 54 (4) ◽  
pp. 757-758
Author(s):  
Riham Nagib ◽  
Camelia Szuhanek ◽  
Bogdan Moldoveanu ◽  
Meda Lavinia Negrutiu ◽  
Cosmin Sinescu ◽  
...  
Keyword(s):  
3D Printing ◽  
Treatment Planning ◽  
Computer Tomography ◽  
Volumetric Data ◽  
Impacted Teeth ◽  
3D Printing Technology ◽  
Custom Design ◽  
Custom Made ◽  
Materials Used ◽  
Orthodontic Forces

Treatment of impacted teeth often implies placing a bonded attachment and using orthodontic forces to move the tooth into occlusion. The aim of the paper is to describe a novel methodology of manufacturing orthodontic attachments for impacted teeth using the latest CAD software and 3D printing technology. A biocompatible acrylic based resin was used to print a custom made attachment designed based on the volumetric data aquired through cone bean computer tomography. Custom design of the attachment simplified clinical insertion and treatment planning and 3D printing made its manufacturing easier. Being a first trial, more reasearch is needed to improve the methodology and materials used.

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