发明公开
- 专利标题: Neural network prediction for radiographic x-ray exposures
- 专利标题(中): 预测通过用于X射线的神经网络
-
申请号: EP99306158.9申请日: 1999-08-03
-
公开(公告)号: EP0979027A3公开(公告)日: 2001-08-29
- 发明人: Aufrichtig, Richard , Gordon, Clarence L., III , Relihan, Gary Francis , Ma, Baoming
- 申请人: GENERAL ELECTRIC COMPANY
- 申请人地址: 1 River Road Schenectady, NY 12345 US
- 专利权人: GENERAL ELECTRIC COMPANY
- 当前专利权人: GENERAL ELECTRIC COMPANY
- 当前专利权人地址: 1 River Road Schenectady, NY 12345 US
- 代理机构: Goode, Ian Roy
- 优先权: US130779 19980807
- 主分类号: H05G1/28
- IPC分类号: H05G1/28 ; G01T1/00
摘要:
A neural network prediction has been provided for predicting radiation exposure and/or Air-Kerma at a predefined arbitrary distance during an x-ray exposure; and for predicting radiation exposure and/or Air-Kerma area product for a radiographic x-ray exposure. The Air-Kerma levels are predicted directly from the x-ray exposure parameters. The method or model is provided to predict the radiation exposure or Air-Kerma for an arbitrary radiographic x-ray exposure by providing input variables (36,38,40) to identify the spectral characteristics of the x-ray beam, providing a neural net (32) which has been trained to calculate the exposure or Air-Kerma value, and by scaling (34) the neural net output by the calibrated tube efficiency (52), and the actual current through the x-ray tube and the duration of the exposure. The prediction for exposure/Air-Kerma further applies (50) the actual source-toobject distance, and the prediction for exposure/AirKerma area product further applies (54) the actual imaged field area at a source-to-image distance.
公开/授权文献
- EP0979027A2 Neural network prediction for radiographic x-ray exposures 公开/授权日:2000-02-09
信息查询