Exposure management and control system and method

• US 6,233,310 B1
• Filed: 07/12/1999
• Issued: 05/15/2001
• Est. Priority Date: 07/12/1999
• Status: Expired due to Term

• Current Assignee: General Electric Company
• Original Assignee: General Electric Company
• Inventors: Ma, Baoming, Goodman, George C., Gordon, Clarence L. III, Relihan, Gary F.
• Primary Examiner(s): BRUCE, DAVID VERNON
• Application Number:
  US09/351,755
• Time in Patent Office: 673 Days
• Field of Search: 378/101, 378/108-112
• US Class Current: 378/108
• CPC Class Codes: A61B 6/545 involving automatic set-up of acquisition parameters
• CPC Class Codes: H05G 1/46 Combined control of different quantities, e.g. exposure time as well as voltage or current
• CPC Class Codes: H05G 1/58 Switching arrangements for changing-over from one mode of operation to another, e.g. from radioscopy to radiography, from radioscopy to irradiation or from one tube voltage to another

Abstract

An exposure management and control system and method for x-ray technique selection is provided. Optimal x-ray technique, which affects image quality, can be accurately predetermined to use for any application. A patient model is combined with a closed loop brightness control, using a parameter that does not affect image quality. This is used to create a control system that operates as a knowledge based control system. The x-ray system brightness control system comprises a first and second regulator. The first regulator is an image quality, or brightness, regulator. The brightness regulator can have multiple functions, such as peak mA control, power limiter, skin dose limiter, and an override function. The second regulator is a dose error regulator. The second regulator is independent of the first regulator, and cooperates with the first regulator to provide x-ray technique optimization independent of brightness control.

Claims

1. An x-ray system technique control system comprising:

an image quality regulator; and

a dose error regulator, independent of the image quality regulator, for cooperating with the image quality regulator to provide x-ray technique optimization.

2. A control system as claimed in claim 1 wherein the image quality regulator comprises;

a means for determining x-ray techniques;

a means for determining receptor dose per image;

a means for calculating patient absorption using the x-ray techniques and receptor dose per image determinations;

a means for using the patient absorption calculation and predetermined clinical imaging requirements to determine an optimal technique; and

a means for adjusting the optimal technique up or down when the dose error regulator is in limit.

3. A control system as claimed in claim 2 wherein the patient size is calculated through a neural net trained with real or modeled technique and entrance dose data.

4. A control system as claimed in claim 2 wherein the optimal technique is determined through a look up table containing optimal techniques determined a-priori and loaded into the image quality regulator based on system selections.

5. A control system as claimed in claim 2 wherein the optimal technique is determined through real time technique optimization using a model based optimization engine.

6. A control system as claimed in claim 2 wherein the optimal technique is determined by creating a real time look up table containing optimized techniques at selection time utilizing a model based optimization engine.

7. A control system as claimed in claim 1 wherein the dose error regulator comprises:

a means for determining entrance dose error from a comparison of measured entrance dose and a reference dose;

a means for limiting power output to protect limitations of the x-ray system;

a means for preventing exposure to a patient from exceeding regulatory limits or any desired level; and

a means for indicating a non-optimal control setting resulting from limit conditions.

8. A control system as claimed in claim 7 wherein the reference dose comprises an optimized reference dose.

9. A control system as claimed in claim 7 further comprising a means for correcting the entrance dose.

10. A control system as claimed in claim 9 wherein the means for correcting the entrance dose comprises means for controlling x-ray tube emission current.

11. A control system as claimed in claim 9 wherein the means for correcting the entrance dose comprises means for controlling x-ray tube potential.

12. A method of x-ray system image quality control selection comprising the steps of:

providing an image quality regulator;

providing a dose error regulator; and

inducing the image quality regulator to cooperate with the dose error regulator to optimize image quality control selection.

13. A method as claimed in claim 12 wherein the step of inducing cooperation comprises the steps of:

defining a clinical application;

defining key image quality attributes for the clinical application;

determining optimal control parameters as a function of patient absorption, to generate an optimization;

providing a computer model to numerically perform the optimization with a computer model of the x-ray system;

calculating attenuation factors based on previous x-ray exposures; and

optimizing image quality control selection using the computer model and the attenuation factors.

14. A method as claimed in claim 13 wherein the image quality regulator utilizes x-ray tube emission as an independent brightness control while allowing automatic setting of x-ray tube peak voltage, exposure time and video gain to independently set contrast, signal-to-noise ratio and motion stopping requirements for the clinical application.

15. A method as claimed in claim 13 further comprising the step of using a first exposure sequence to determine a proper technique for subsequent exposure sequences, regardless of changes initiated by an operator with respect to field of view, mode selections and accompanying entrance dose change or frame rate changes.

16. A method as claimed in claim 13 further comprising the steps of:

calculating skin dose delivered to a patient; and

controlling the skin dose needed for optimal visualization by adaptive control based on clinical application requirements.

17. A method as claimed in claim 13 further comprising the step of using a real time model to predict both cross-sectional absorption and skin dose of a patient for all x-ray acquisition modes.

18. A method as claimed in claim 13 further comprising the step of using a neural network trained to model complex x-ray spectra input/output relationships.