Patents
Literature
Hiro is an intelligent assistant for R&D personnel, combined with Patent DNA, to facilitate innovative research.
Hiro

47 results about "Dual Scan" patented technology

Dual Scan, also known as dual-scan supertwist nematic or DSTN, is an LCD technology in which a screen is divided into two sections which are simultaneously refreshed giving faster refresh rate than traditional passive matrix screens. It is an improved form of supertwist nematic display that offers low power consumption but inferior sharpness and brightness compared to TFT screens. For several years (late '90s to early 2000s), TFT screens were only found in high-end laptops due to them being more expensive and lower-end laptops offering DSTN screens only. This was at a time when the screen was often the most expensive component of laptops. The price difference between a laptop with DSTN and one with TFT could easily be $400 or more. However, TFT gradually became cheaper and has essentially captured the entire market.

Dual-energy dual-90-degree CT scanning image reconstruction method and device based on generative adversarial network

The invention discloses a dual-energy dual-90-degree CT scanning image reconstruction method based on a generative adversarial network. The method comprises the following steps: firstly, designing a generative adversarial network model to describe a coupling relationship between missing projection data and 180-degree projection data distribution probability; the method comprises the following steps: constructing a training set and training to obtain a trained generative adversarial network model, complementing dual-energy 90-degree projection data into dual-energy 180-degree projection data byusing the model, and finally reconstructing the dual-energy 180-degree projection data by using a SART-TV algorithm to obtain a reconstructed low-energy image and a reconstructed high-energy image. The invention further discloses a dual-energy dual-90-degree CT scanning image reconstruction device based on the generative adversarial network. According to the method, the generative adversarial network is adopted, the dual-energy dual-90-degree projection data input by the network is made to generate the dual-energy dual-180-degree projection data, a good performance effect is achieved on the aspects of reducing hardware cost and improving image quality, and the accuracy of object-based material decomposition is improved.
Owner:PLA STRATEGIC SUPPORT FORCE INFORMATION ENG UNIV PLA SSF IEU
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products