Classifications

• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
  • G06T5/00—Image enhancement or restoration
  • G06T5/90—Dynamic range modification of images or parts thereof
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
  • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
  • H04N23/30—Cameras or camera modules comprising electronic image sensors; Control thereof for generating image signals from X-rays
• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
  • G06T2207/00—Indexing scheme for image analysis or image enhancement
  • G06T2207/10—Image acquisition modality
  • G06T2207/10116—X-ray image
• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
  • G06T2207/00—Indexing scheme for image analysis or image enhancement
  • G06T2207/10—Image acquisition modality
  • G06T2207/10141—Special mode during image acquisition
  • G06T2207/10144—Varying exposure

Definitions

• the present invention relates to an optimizing method based on multi-sensor technique for automatic exposure control in X-ray equipment, said method involving the use of a control- unit equipped apparatus for measuring the radiation intensities of at least two detectors passing through an imaging target during exposure.
• An object of the present invention is to provide an optimizing method, capable of providing the automatic exposure control of an X-ray apparatus with high reproducibility and reliability.
• a method of the invention is characterized in that, in a first stage of the method during an imaging procedure, the control unit is in the process of applying the intensity levels of the detectors to pre-established identification rules and each rule is provided with calculated weight values correlating with the fitness thereof for identifying on the basis thereof the most probable shape and/or location of a target, that in a subsequent stage the measuring intensity of each detector can be calculably corrected/weighted as a function of the above- discovered shape/location quantity in such a way that the control basis for automatic exposure calculated as an end result will become as optimal as possible in terms of the measuring range.
• fig. 1 shows one example of a method of the invention in a block diagram
• figs. 2-5 show in more detail the contents of various blocks included in the block diagram of fig. 1.
• the illustrated embodiment of a method of the invention is carried out by first defining various membership functions in a block 2 of fig. 1 and by feeding the various membership functions to blocks 3, 4 and 5.
• Block 3 applying rules to references
• Block 4 modelling rules
• block 5 optical reference
• the actual optimizing method is implemented by using a plurality of detectors, the number of which in the illustrated embodiment is five A, B, C, D and E, and the radiation intensities (inputs) coming from the detectors are received by a reference grabber (block 1 in fig. 1) .
• the references obtained from the reference grabber are applied in block 3 to pre-established identification rules and the resulting weight values of various identification rules are modelled in block 4 by means of pre-established modelling rules.
• the weighted model output from block 4 is optimized in block 5 by using a pre-established coefficient matrix.
• block 5 is supplied with references for optimization.
• the resulting optimized reference is then delivered to automatic exposure control, block 6, for defining the required exposure factors.
• One benefit of the invention is an improvement m the accuracy and reproducibility of the identification/focusmg of a measuring range calculable on stepless application bases, which also improves the results of automatic exposure control and the reproducibility thereof as a result of a control quantity optimized for automatic exposure control.
• Fig. 2 illustrates the definition of membership functions by way of an example associated with mammography imaging.
• the bottom left-hand corner of fig. 2 shows the arrangement of detectors A-E as a model example m connection with five different breast figures.
• the breast figures include left small L-S, left large L-L, medium large M-L, right large R-L, and right small R-S.
• the top left-hand corner of fig. 2 shows reference membership functions as a graphic representation, wherein the vertical axis is constituted by the fitness of a reference on a scale of 0-1 and the horizontal axis is constituted by detector responses (the intensity of radiation received by the detectors) , m the present embodiment the responses are presented as kHz.
• the top right-hand corner of fig. 2 illustrates model membership functions as a graphic representation, wherein the vertical xis is constituted by the fitness of a model on a scale of 0-1 and the horizontal axis is constituted by models (various breast figures) 1-5, whereby 1 represents the model left small L-S, 2 represents the model left large L-L, 3 represents the model medium large M-L, 4 represents the model right large R-L, and 5 represents the model right small R-S.
• the bottom right-hand corner of fig. 2 shows by way of an example the criteria for various models.
• criteria can be determined e.g. beforehand experimentally manually by taking a lot of pictures of certain imaging targets, by establishing the criteria, and by testing clinically the fitness thereof.
• the criteria are fixed, not resettable.
• Another alternative is to apply a calibration mode used for measuring responses for each model and these are used for establishing rules or criteria, which are subsequently applied as bases for control and which can also be changed by means of the same protocol.
• the criteria are re- calibrable .
• Fig. 3 illustrates by way of an example the application of criteria to references.
• the left-hand graphic representation of fig. 3 illustrates the fitness of input B, according to which it is "on edge" up to 60 % .
• the right-hand graphic represtantion of fig. 3 illustrates respectively the fitness of input D, according to which it is "full” up to 95 % .
• the middle of fig. 3 is shown the fitness of model L-L (left large) in an exemplary case.
• Fig. 4 illustrates the modelling of rules included in block 4 of fig. 1 in the case of the above example.
• reference inputs A-E are applied to each identification rule 1-5 for determining the weight of each identification rule for the fitnesses of various models.
• the resulting weight for rule 1 is 25 %, for rule 2, as shown in fig. 3, 60 %, and for the rest of the rules 0 %.
• the graphic representation of fig. 4 indicates the fitness of each model (model L-S 25 %, model L- L 60 , and other models 0 %) on a horizontal line and there is defined a so-called centre of area, the resulting weighted model assuming the value 1.70, i.e. the model is between models L-S and L-L closer to model L-L.
• This weighted model is used in block 5 (fig. 5) for optimizing references.
• the weighting criterion is constituted by a matrix, wherein references A-E are given certain coefficients corresponding to each model L-S - R-S.
• the weighted model 1.70 By applying the weighted model 1.70 to the matrix shown in fig. 5 it is possible to define the coefficients for reference values of various detectors.
• These coefficients can be used for determining a weighted reference value by multiplying the originally obtained reference values by coefficients obtained from the matrix and by dividing the sum of thus obtained reference values by the sum of the coefficients.
• the resulting weighted reference value will be 35 kHz, which is then delivered to automatic exposure control (block 6) for defining the exposure factors.

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• Engineering & Computer Science (AREA)
• Physics & Mathematics (AREA)
• General Physics & Mathematics (AREA)
• Theoretical Computer Science (AREA)
• Multimedia (AREA)
• Signal Processing (AREA)
• Apparatus For Radiation Diagnosis (AREA)

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Cited By (1)

Citations (4)

• 1996
  • 1996-11-14 FI FI964557A patent/FI102140B/fi not_active IP Right Cessation
• 1997
  • 1997-10-27 DE DE19782123T patent/DE19782123T1/de not_active Withdrawn
  • 1997-10-27 JP JP52220898A patent/JP2001503563A/ja active Pending
  • 1997-10-27 WO PCT/FI1997/000653 patent/WO1998021884A1/en active Application Filing

Patent Citations (4)

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