Strictly controlling the cleanness of transport mirror surface in high power laser system has an important significance. Removal efficiencies of dust in different sizes and on different positions of the transport mirror surface are studied, by using the air knife blowing method with different inlet pressures and installation positions. Full experiments and range analysis show that the air knife blowing method is an effective way to control the cleanness of the transport mirror surface. The removal efficiency of dust particles in different sizes and positions of the transport mirror surface is better when inlet pressure is 0.9 MPa and the air knife installation position is 3 mm. Besides that, some simulations on flow fields are conducted. The simulation results and the experimental results have a good consistency.
MR imaging has been used to perform imaging guided high-intensity focused ultrasound (HIFU) and meanwhile can also be used precisely to measure tissue temperature in theory. But in practice, the temperature environment and target are complex. Therefore, it is difficult to measure targeted temperature just by simply using the theory of numerical calculation based on MR image information. In this presentation, we presented new MR temperature measurement, based on imaging informatics, to measure the targeted tissue temperature in MR imaging guided HIFU therapeutic procedure. By heating up the water phantom experiments under HIFU, the new algorithm gives a satisfactory result compared with existing algorithm. Based on experimental data, we can see the accuracy increase 37.5% from 0.4048℃ up to 0.2530℃ when we choose new algorithms.
To have comprehensive and completed understanding healthcare status of a patient, doctors need to search patient
medical records from different healthcare information systems, such as PACS, RIS, HIS, USIS, as a reference of
diagnosis and treatment decisions for the patient. However, it is time-consuming and tedious to do these procedures. In
order to solve this kind of problems, we developed a patient-oriented visual index system (VIS) to use the visual
technology to show health status and to retrieve the patients' examination information stored in each system with a 3D
human model. In this presentation, we present a new approach about how to extract the semantic and characteristic
information from the medical record systems such as RIS/USIS to create the 3D Visual Index. This approach includes
following steps: (1) Building a medical characteristic semantic knowledge base; (2) Developing natural language
processing (NLP) engine to perform semantic analysis and logical judgment on text-based medical records; (3) Applying
the knowledge base and NLP engine on medical records to extract medical characteristics (e.g., the positive focus
information), and then mapping extracted information to related organ/parts of 3D human model to create the visual
index. We performed the testing procedures on 559 samples of radiological reports which include 853 focuses, and
achieved 828 focuses' information. The successful rate of focus extraction is about 97.1%.