WO2013076506A2

WO2013076506A2 - Portable detector apparatus

Info

Publication number: WO2013076506A2
Application number: PCT/GB2012/052910
Authority: WO
Inventors: Stephen Whitaker SNOW; Ian Radley
Original assignee: Kromek Limited
Priority date: 2011-11-23
Filing date: 2012-11-23
Publication date: 2013-05-30
Also published as: GB2510290B; WO2013076506A3; GB201407748D0; GB2510290A; GB201120168D0

Abstract

A portable detector system for the processing of data derived from incident radiation is described comprising: a plurality of separately addressable radiation detectors having at least two different known response properties;a processing device comprising: a collection module to collect data from radiation incident at each detector and produce a spectral histogram for the collected data from each detector;a deconvolution module to deconvolve the histograms from each detector to derive a single spectral histogram that representatively combines information from the plurality of detectors;the plurality of separately addressable radiation detectors and the processing device being associated together in compact and portable manner, for example within a common casing.

Description

PORTABLE DETECTOR APPARATUS

The invention relates to a portable detector apparatus for combining spectral data from a plurality of radiation detectors. The invention is in particular a portable hybrid detector apparatus for combining spectral data from a plurality of radiation detectors of at least two different types/ having at least two different response properties, and in particular from a plurality of radiation detectors having at least two different energy resolutions and/ or of different efficiency.

The invention in particular relates to an apparatus making use spectral data from high energy ionizing radiation such as x-rays or gamma-rays emergent from an object where it is desirable to gain information about the particular radioactive isotopes that may be present.

The invention in particular relates to an apparatus employing a method for combining spectral data from at least one first detector with a relatively higher energy resolution but a relatively lower absolute efficiency and at least one second detector with a relatively lower energy resolution but a relatively higher absolute efficiency.

The use of radiation detectors of various types for the detection of ionizing radiation is well known. The value of resolving data spectrally is also known. For example, it is known that it is possible to identify particular radioactive isotopes from their characteristic spectra. There are many circumstances where identification of the presence of a particular isotope from a radioactive source or from a material contaminated by a radioactive source might be of value. It is also known that when a target object is scanned by high energy ionizing radiation the spectroscopic information from emergent radiation could be used to give information about the material content of the target object. It is known for example that the x-ray absorption properties of any material can vary spectroscopically. This has led to development of detectors which are capable of spectrally resolving emergent radiation whether from a radioactive source or from a contaminated object or from an object subject to external irradiation.

For spectroscopic ionizing radiation detection and measurement, performance is limited by various traits of the detector. In particular a given detector has as fundamental properties a detection efficiency and an energy resolution. The detector's efficiency is limited by its size and by the intrinsic efficiency of the detector material used. The detector material also dictates its energy resolution. For practical applications material cost and size are determining factors in detector material choice. Size is limited by mechanical and manufacturing constraints and may be further limited by application (for example if portability is desired). Practical detector devices may represent a trade off between cost and size, and between efficiency and energy resolution.

It is recognised that the efficiency of a system could be improved by adding more detectors to the system. Conventionally, this has been done using detectors of the same type. The measured spectra of such like detectors can be combined by simple summation subject to common calibration.

Hybrid detector systems for example including detector elements with a relatively higher energy resolution but a relatively lower absolute efficiency and detector elements with a relatively lower energy resolution but a relatively higher absolute efficiency might in principle represent an effective solution that allows the weaknesses of each detector element to be offset by their complementary strengths. However the simple summation approach is not appropriate when combining different types of detectors with very different peak response functions.

International Patent Publication WO2009/082587 considers a hybrid detector system in which one or more high efficiency/ low resolution detectors are combined with one or more low efficiency/ high resolution detectors and in which a particular method is applied to combine spectral data from the detectors of these two different types.

As described in WO2009/082587 a baseline estimation is performed on each acquired spectrum to separate the measured peak response from the underlying continuum. The resulting peak spectra are all rebinned to a common energy calibration. Then the peak spectra are multiplied by channel number to yield a convolution spectrum. Counts in each peak spectrum channel are then redistributed to match the local convolution spectrum distribution with a window width set according to the respective detector local characteristic peak width. The final spectrum is the summation of all the redistributed peak spectra.

The method gives some co-operably produced aspect to the data, but the information that is derived is limited. Fundamentally, plural spectra are generated as accumulating histograms in an essentially conventional manner, and peaks are then identified in the plural spectra separately by separating out the underlying continuum. The multiplication step as a result yields a relatively crude convolution that in particular des not fully exploit the complementary strengths/ mitigate the weaknesses of the plural detector types.

It is desirable to develop a portable detector apparatus based on an alternative method for the convolved processing of spectral data from a plurality of radiation detectors that is able to accommodate differences in response properties between the detectors.

It is in particular desirable to develop a portable detector apparatus based on an alternative method for the convolved processing of spectral data from a plurality of radiation detectors with at least two different known response properties, and in particular from a plurality of radiation detectors having at least two different energy resolutions and/ or of different efficiency, that mitigates at least some of the disadvantages of prior art methods and/ or that more effectively exploits the complementary spectral data content provided by the at least two different detector responses.

It is in particular desirable to develop a portable detector apparatus that is better able to make use of spectral data from high energy ionizing radiation such as x-rays or gamma-rays emergent from an object where it is desirable to gain information about the particular radioactive isotopes that may be present

Thus, in accordance with the invention in a first most general aspect, a portable detector system for the processing of data derived from incident radiation comprises:

a plurality of separately addressable radiation detectors having at least two different known response properties;

a processing device comprising:

a collection module to collect data from radiation incident at each detector and produce a spectral histogram for the collected data from each detector;

a deconvolution module to deconvolve the histograms from each detector to derive a single spectral histogram that representatively combines information from the plurality of detectors;

the plurality of separately addressable radiation detectors and the processing device being associated together in compact and portable manner, for example within a common casing.

Thus, the portable system of the invention is a hybrid detector system comprising, for example within the common casing, a plurality of radiation detectors having at least two different response properties. The system of the invention effects this by means of a deconvolution module that is adapted to apply a numerical deconvolution to derive a single spectral histogram that representatively combines information from the plurality of detectors. Preferably the detector system comprises a plurality of radiation detectors having at least two different energy resolutions and/ or of at least two different efficiencies.

Optionally the detector system comprises a spectrum storage register to store the derived spectral histogram and/ or a display to display the derived spectral histogram and/ or further data processing means to process the derived spectral histogram, for example to determine peaks therein.

Optionally the detector system is a system for the testing of an object under test that is emitting radiation and where a spectral analysis of the emitted radiation is desirable. In a particularly convenient case the object is radioactive source and the system is a system for collecting and analysing of emitted radiation data from the radioactive source. For example a detector system may comprise a peak discriminator to compare the peaks in the derived single histogram with levels that define the statistical significance of their height relative to the continuum background. For example a detector system may comprise a peak integrator adapted to integrate the area of peaks in the derived single histogram and use this as input to a calculation of source activity. Optionally the detector system comprises a sample holder to retain a sample object for testing in appropriate juxtaposition relative to the plurality of radiation detectors.

Preferably the detector system is adapted to identify the presence of or characterise a contribution of one or more particular radioactive isotopes present in the collected data from their characteristic spectra, and comprises an identification module to isolate and identify the presence or absence of one or more predetermined characteristic spectral features of at least one particular radioactive isotope and so identify a contribution from the at least one particular radioactive isotope in the collected data. In this manner the detector system is adapted to identify the presence of or characterise one or more particular radioactive isotopes present in the source. To perform the identification the detector system may make reference to a suitable data register of stored predetermined characteristic spectral features of particular radioactive isotopes. The detector system may include such a data register and or may include a data communication means to communicate remotely with such a data register.

In a possible embodiment, the detector system comprises a compact and self contained system adapted for portable use for example in situ in the field.

The invention in particular preferably relates to the detection of high-energy radiation such as ionising radiation, for example high-energy electromagnetic radiation such as x-rays and/or gamma rays, or subatomic particle radiation. Each of the plurality of detectors making up a detector system operated in accordance with the principles of the invention is preferably adapted correspondingly to detect such radiation. In particular preferably separate detectors are provided to detect soft x-rays and/or hard x-rays and/ or gamma rays.

The invention relates to the combining of spectral data from a plurality of different radiation detectors having different response functions.

The invention in particular preferably relates to the combining of spectral data from a detector with a relatively higher energy resolution and/ or a relatively lower absolute efficiency and a detector with a relatively lower energy resolution and/ or a relatively higher absolute efficiency. Hereinafter for convenience a detector of the former type is referred to as a detector of a first class and a detector of the latter type is referred to as a detector of a second class, but this reference is purely for ease of distinction of the two classes and no further meaning or limitation should be inferred. It would be equally valid to use the terms interchangeably. Hybrid detectors may include one or more detectors from first, second and further classes however defined having different energy resolutions and/ or of different efficiency. The invention in particular preferably relates to the combining of spectral data from a hybrid detector system, for example comprising at least one detector of a first class having a relatively higher energy resolution and/ or a relatively lower absolute efficiency and at least one detector of a second class having a relatively lower energy resolution and/ or a relatively higher absolute efficiency.

Thus, an apparatus in accordance with the principles of the invention preferably comprises at least one detector of a first class having a relatively higher energy resolution and/ or a relatively lower absolute efficiency and at least one detector of a second class having a relatively lower energy resolution and/ or a relatively higher absolute efficiency.

In particular, the invention applies to an apparatus for combining spectral data from at least one detector from a first class having a relatively higher energy resolution and a relatively lower absolute efficiency and at least one detector from a second class having a detector with a relatively lower energy resolution and a relatively higher absolute efficiency.

In such an apparatus, it may be possible for the perceived weaknesses of each class of detector, for example as regards any compromise between cost and size, between efficiency and energy resolution, etc, to be offset by their complementary strengths.

Plural detectors may be provided from each class, whether having the same or different energy resolution and/ or efficiency. Nor is the invention limited to cases where there are only two classes of detector. Multiple classes of detector each having different energy resolution and/ or efficiency may be employed in a method and apparatus of the invention.

Examples of detectors in the first class might include direct-conversion semiconductor detector devices (that is, detector devices that convert high-energy radiation such as high-energy photons into an electric charge directly within a detector element with no use of intermediate materials). Examples of such direct-conversion semiconductor detector devices might include semiconductor detector devices with detector elements comprising a large direct band gap semiconductor material, for example a group II-VI semiconductor material such as cadmium telluride (CdTe), cadmium zinc telluride (CZT), cadmium manganese telluride (CMT) or the like, for example formed as a bulk single crystal (where bulk crystal in this context indicates a crystal thickness of at least 500 μηι, and preferably of at least 1 mm). Particularly preferably such semiconductor detector devices might have detector elements selected from cadmium telluride, cadmium zinc telluride (CZT), cadmium manganese telluride (CMT) and alloys thereof, and for example comprise crystalline Cdi-(a₊b)Mn_aZnbTe where a and/ or b may be zero. Combination of these and any other such materials may be considered which give spectroscopic detection rather than merely detecting amplitude of incident radiation monochromatically.

Examples of detectors in the second class might include indirect-conversion semiconductor detector devices such as scintillator detector devices (that is, detector devices that have a scintillator detector element that first converts high- energy radiation such as high-energy photons into lower energy photons and for example visible light which is then converted into an electric charge by means of secondary photodetector).

Examples of such indirect-conversion semiconductor detector devices might include devices with scintillator detector elements comprising organic or inorganic crystal scintillator detector elements. The invention is not limited to particular scintillator detector element compositions, but by way of example inorganic crystal scintillator detector elements selected from alkali metal halides such as optionally doped sodium iodide, cesium iodide, cesium fluoride, potassium iodide, lithium iodide and like materials, and for example will be familiar Nal(Tl), CsI(Tl) will be familiar. Other examples in the second class might include semiconductor detector devices of similar material to the first class but of different thickness. If a similar material is used with substantially greater thickness the detector in the second class may have higher efficiency but lower resolution as a consequence of that greater thickness.

These are examples of classes of detector element which might meet the underlying condition that data is combined from at least two different types of detector. However the invention is not limited to an apparatus with both direct and indirect detector devices. It merely requires a combination of spectral data from at least one detector having a relatively higher energy resolution and/ or a relatively lower absolute efficiency and at least one detector having a relatively lower energy resolution and/ or a relatively higher absolute efficiency. The principle could be applied for example to any combination of suitable direct-conversion solid state detectors and/ or indirect-conversion scintillator detectors in solid or liquid state and/ or gas-based detectors provided only that this condition is met. In particular therefore the principle could equally be applied to a combination of spectral data from plural different direct-conversion detectors alone or plural different indirect- conversion detectors alone or any combination of the same provided only that this condition is met.

The plurality of detectors may together cover and provide a detection capability for a broad spectrum of incident radiation over a range of energies, for example a broad spectrum of x-rays. At least some detectors may be adapted to exhibit a spectroscopically variable response across at least a part of such a broad spectrum allowing spectroscopic information to be retrieved and allowing intensity information to be detected at a plurality of differentiated energy bands across the spectrum of the source.

The system is adapted to perform a suitable analysis of the data. A preferred method of analysis is described below. The system is adapted to implement the method, whether integrally or via data communication to a suitable separate processor.

In particular the system includes a processing device having a deconvolution module adapted at least to deconvolve the histograms from each detector to derive a single spectral histogram that representatively combines information from the plurality of detectors. Additionally in this regard, the processing device may comprise additional modules adapted to perform any of the steps of the processing method described below and/ or may comprise a data communication link to communicate with remote processing means configured and/ or programmed to perform any of the steps of the processing method described below.

Conveniently the processing device of the portable system comprises, for example within the common casing, some or all of: a collection module; a deconvolution module; a spectrum storage register; a display; data processing means to process the derived spectral histogram, for example to determine peaks therein; an identification module; a data register; thereby to perform any of the steps of the processing method described below. A possible method for the combined processing of spectral data from a plurality of radiation detectors comprises:

collecting data from radiation incident at each detector;

producing a spectral histogram for the collected data from each detector;

deconvoluting the histograms from each detector by applying a numerical deconvolution to derive a single spectral histogram that representatively combines information from the plurality of detectors.

In a preferred case the method comprises applying a numerical deconvolution that makes use of a response matrix for each detector. In a particular preferred implementation of the method, the method comprises in an initial step obtaining a response matrix for each detector, and in a deconvolution step deconvoluting the histograms from each detector by applying a numerical deconvolution which makes use of respective detector response matrices for the detectors. The invention is applied to data from a plurality of radiation detectors in such manner as to be able to accommodate differences in response properties between the detectors. The invention is in particular preferably applied to data from at least two detectors having at least two different known response properties, for example in that their response functions are known, previously measured, or determined in a calibration step. The invention in particular may comprise a step of collecting data from radiation incident on at least one first detector and at least one second detector, the first and second detectors having different response properties and subsequent steps of producing a spectral histogram for the collected data from each detector and deconvoluting the histograms from each detector by applying a suitable numerical deconvolution to derive a single spectral histogram that representatively combines information from the plurality of detectors and in the preferred case that makes use of the response matrix for each detector in the deconvolution.

The method is thus a method for combining spectral data from a plurality of radiation detectors and in particular is a method that can be applied to data from a plurality of radiation detectors having at least two different known response properties. In a particular case, the method combines spectral data from a plurality of radiation detectors having at least two different energy resolutions and/ or of different efficiency. In a preferred case thus the first and second detectors have different energy resolutions and/ or different efficiency. In the preferred case, the method is thus a method for the processing of spectral data from a hybrid detector system having at least two different response properties.

The method is distinctly characterized by the use of a numerical deconvolution to combine data from the plural radiation detectors in a manner which enables spectral data content provided by the plural detectors exhibiting at least two different detector responses to be combined in a simple but effective complementary manner and in particular in the preferred case by the use of the response matrix for each detector within the deconvolution step. Each detector is separately addressable and data regarding incident radiation is collected separately therefrom to produce a spectral histogram for the detector, with the data then being combined via the suitable deconvolution method. As such the method can be contrasted with the method described in WO2009/082587 for the co-processing of data from the radiation detectors of a hybrid system having at least two different response properties. For example, it can be seen in the method of WO2009/082587 that the first step after obtaining accumulation histograms is to separate the peaks from the underlying continuum. The step is performed for each individual detector used and is performed prior to combination of the information. In order to perform this step it is necessary already to have enough statistics to see the peaks in the responses of all the individual detectors and this makes the combining of information of less value. The strength of the combined deconvolution method of the present invention when contrasted with this prior art approach is that it first combines information from all the detectors without requiring anyassumptions to be made about peaks in the individual spectra, leaving the decision about what peaks (if any) are present to be made using the combined information.

A suitable numerical deconvolution method is for example an iterative and/ or convergent deconvolution method, and is in a particular embodiment a Bayesian deconvolution method. It is distinctively characterised by the use of the respective detector response matrices within the numerical method and for example used as or to derive an initial condition for the iteration and for example used as or to derive a Bayesian prior.

In a possible implementation of the method, the method thus comprises in an initial step obtaining a response matrix for each detector, and in a deconvolution step deconvoluting the histograms from each detector by applying a Bayesian deconvolution which makes use of the respective detector response matrices. In a particular case the respective detector response matrices are used to derive the prior for the Bayesian deconvolution. They may be used to derive the prior directly for example by being applied directly for example as a weighting factor, or they may be used to derive the prior otherwise indirectly. Where used herein, a response matrix for a detector is defined as a matrix which transforms detector system input to detector system output across a range of possible interactions, and for example across a substantial part of the possible breadth of the range of possible interactions. Measured response matrices may be used. However in the preferred case a response matrix is simulated and for example is generated by a Monte Carlo simulation or like method. In a possible case a GEANT4 simulation is used.

A previously obtained response matrix may for example be stored for subsequent use in a deconvolution step of the method applied to subsequently collected data, and/ or may be obtained and for example generated as an initial step of an implementation of the method.

Thus, in the preferred case, the method comprises the processing of data from a plurality of detector responses to derive a spectrum more representative of a notional true spectrum, and in particular to identify spectral peaks therein, than that which would be derived from a single detector response, and in particular by separately identifying the spectral peaks therein. Peaks in a spectrum from a single detector response need not be separately identified. The method may produce a useable spectrum and in particular identified spectral peaks therein which could not so effectively be identified by an analysis that required determination of peaks in a spectrum from each single detector response separately.

The data from the plural radiation detectors, for example having at least two different known response properties, is preferably processed simultaneously/ closely successively to derive a spectrum more representative of a notional true spectrum than that which would be derived from a single detector response.

In a possible implementation of the method as above, the method comprises in an initial step obtaining a response matrix for each detector, and in a deconvolution step deconvoluting the histograms from each detector by applying a deconvolution such as a Bayesian deconvolution which makes use of the respective detector response matrices.

In such a case in a possible implementation of the method of collecting and analysing emitted radiation data from an object under test, the method is applied to a radiation detector system for which a response matrix for each detector has been previously obtained for use in the deconvolution step and/ or the method comprises the step of obtaining a response matrix for each detector for use in the deconvolution step prior to implementing the foregoing steps on one or more objects under test.

A previously obtained response matrix may for example be stored by the apparatus for use in a deconvolution step of the method applied to subsequently collected radiation emergent from on one or more objects under test. Alternatively a response matrix may be obtained in an initial step prior to implementation of the foregoing steps on an object under test.

The deconvolution module may be adapted to perform and/ or the processing device may comprise additional modules adapted to perform any of the steps of the processing method described above.

For example, the deconvolution module may be adapted to apply a deconvolution algorithm comprising for example an iterative and/ or convergent deconvolution method, and in a particular embodiment a Bayesian deconvolution method. Preferably, the deconvolution module is adapted to apply a deconvolution algorithm that makes use of the respective detector response matrices and for example uses the respective detector response matrices as or to derive an initial condition for the iteration and for example uses the respective detector response matrices as or to derive a Bayesian prior.

The deconvolution module may include and/ or the processing device may comprise data storage modules to store the results of any of the steps of the processing method for subsequent output or used in subsequent steps. For example the deconvolution module may include and/ or the detector may comprise means to derive and/ or store a response matrix for each detector, and as required a data link to enable the deconvolution module to apply the derived and/ or stored response matrix to be applied in the deconvolution step to derive a single spectral histogram that representatively combines information from the plurality of detectors.

In a particular preferred case the Bayesian or other numerical deconvolution method step is performed repeatedly and successively in iterative manner with respect to data from the radiation detectors having at least two different response properties to approach in iterative manner a derived spectrum more representative of a nominal true spectrum than that which would be derived from a single detector response. The method thus comprises the use of a Bayesian or other numerical deconvolution to produce a single spectral histogram that representatively combines information from the plurality of detectors, in particular to be more representative of a nominal true spectrum than that which would be derived from a single detector response. An example method for performance of a Bayesian analysis of the collected data from each detector, by deconvoluting the histograms from each detector to derive a single spectral histogram, is discussed in more detail below.

It is a particular advantage of the method that the derived single spectral histogram may be made available for a range of conventional further processing and analysis steps.

For example, one or more of the following steps may be performed:

optionally, displaying the single histogram;

optionally, comparing the peaks in the single histogram with levels that define the statistical significance of their height relative to the continuum background; optionally, integrating the area of peaks in the single histogram and using this as input to a calculation of source activity.

The portable system may be adapted to perform these steps integrally or remotely.

For example a possible further processing and analysis step may comprises determining from the single derived histogram the presence of one or more spectral features such as peaks characteristic of the spectrum of one or more particular radioactive isotopes and thereby identifying the presence of a contribution from one or more particular radioactive isotopes in the derived histogram. The method thus allows inferences to be drawn about the particular radioactive isotopes producing a collected signal, from which may be drawn inferences about the particular radioactive isotopes present in a test object. The method may thus comprise an initial step of collecting emitted radiation data from an object under test.

In a possible more complete aspect of the invention, it follows that the method is a method of collecting and analysing emitted radiation data from an object under test, and comprises the steps of:

providing a radiation detector system comprising a plurality of detectors;

disposing an object relative to the radiation detector system in such arrangement that radiation emergent from the object is caused to be incident upon the plurality of detectors;

collecting data from radiation so incident at each detector and performing the analysis hereinbefore described.

An object under test may be any object from that is emitting radiation and where a spectral analysis of the emitted radiation is desirable. In a particularly convenient case the object is radioactive source, whether being an intended radioactive source or an object secondarily contaminated by a source of radiation, and the method is a method of collecting and analysing emitted radiation data from the radioactive source.

In a convenient case the method is applied to identify the presence of or characterise a contribution in the collected data of one or more particular radioactive isotopes from their characteristic spectra, and thus draw inferences about the composition of the source. The method comprises the steps above described performed so as to isolate and identify the presence or absence of one or more predetermined characteristic spectral features such as predetermined characteristic peaks of at least one particular radioactive isotope and so identify the presence of the at least one particular radioactive isotope in the radioactive source. Reference may for example be made to a suitable data register of stored predetermined characteristic spectral features of particular radioactive isotopes, whether stored on or in association with a detector device or in a separately and for example remotely addressable database.

However the invention does not exclude application in a system which involves the irradiation of a target object from an external source. In such a possible more complete embodiment, the method is a method of collecting and analysing radiation interaction data from a target object, for example to obtain information about its composition and/ or contents, and comprises the steps of: providing a radiation source and a radiation detector system comprising a plurality of detectors;

disposing an object relative to the radiation source and the radiation detector system in such arrangement that radiation from the source is caused to be incident upon the plurality of detectors after a radiation interaction with the object;

Again, in each case the invention is applied to data from a plurality of radiation detectors in such manner as to be able to accommodate differences in response properties between the detectors and is in particular preferably applied to data from at least two detectors having at least two different known response properties, for example having at least two different energy resolutions and/ or of different efficiency.

It will be understood generally that any numerical or other data processing step in the method described can be implemented by a suitable set of machine readable instructions or code. These machine readable instructions may be loaded onto a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a means for implementing the step specified.

These machine readable instructions may be stored in a computer readable medium that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in a computer readable medium produce an article of manufacture including instruction means to implement some or all of the numerical steps in the method described. Computer program instructions may also be loaded onto a computer or other programmable apparatus to produce a machine capable of implementing a computer executed process such that the instructions are executed on the computer or other programmable apparatus providing steps for implementing some or all of the data processing steps in the method.

It will be understood that a step can be implemented by, and a means of the apparatus for performing such a step composed in, any suitable combinations of special purpose hardware and/ or computer instructions. A step can be implemented in either software or hardware. Firmware implementations can be constructed with the algorithms embedded in processors such as Field Programmable Gate Arrays (FPGA), Application Specific Integrated Circuits (ASIC) and System on a Chip (SoC) embodiments. The invention will now be described by way of example only by way of the foregoing example of a Bayesian deconvolution model and with reference to figures 1 to 5 of the accompanying drawings in which:

Figure 1 is a schematic diagram representing an embodiment of the system of the invention featuring multiple detectors of different type and having different response functions;

Figure 2 shows simulated responses for a hybrid CZT/ Csl detector system;

Figure 3 shows the effect of carrying out a Bayesian deconvolution (on the spectra in Figure 2;

Figure 4 shows a plot of efficiency versus data collection time when the acceptance ratio of the two detectors is 1:5;

Figure 5 shows for comparison a plot of efficiency versus data collection time when the acceptance ratio of the two detectors is 1:50. A simple schematic of an apparatus for performing the invention is illustrated in figure 1.

This embodiment depicts a source which is under observation (2) being detected by a hybrid system having multiple ionizing radiation detector elements of two respective types (4, 6).

The multiple detectors have known performance function. Some of the multiple detectors have high efficiency with low resolution (4) and some of the detectors have low efficiency with high resolution (6). Example high efficiency/ low resolution detectors might be Nal(Tl), CsI(Tl) scintillators. Example low efficiency/ high resolution detectors might be CdTe, CZT.

Each detector element (4, 6) collects incident radiation events in familiar manner and a spectral histogram for the collected data from each detector is produced. In the schematic of a typical arrangement shown for analogue pulse processing, each detector element sends its pulse output to suitable signal output processing electronics (8), for example including preamplifier/ amplifier. The processed signal feeds into an analogue to digital converter (ADC) (10) which in turn feeds a multichannel analyser (MCA) (12). The MCA outputs from each detector are subsequently fed to a central processor (14). The processor (14) performs the novel processing steps to process a spectral histogram for the collected data from each detector by applying a Bayesian deconvolution to derive a single spectral histogram that representatively combines information from the plurality of detectors thereby to combine the multiple source data into a single final spectrum. The processor for example includes a module to collect data from radiation incident at each detector and produce a spectral histogram for the collected data from each detector and a module to deconvolve the histograms from each detector by applying a Bayesian deconvolution to derive a single spectral histogram that representatively combines information from the plurality of detectors. The process may be so constituted by any suitable combination of software/ firmware/ hardware.

The system is embodied in a portable format with at least the detector element (4, 6) and the processor (14) being associated together in compact and portable manner, for example within a common casing. A possible casing is represented schematically by the broken line (20) around the various components.

A particular advantage of the invention is that the derived single spectral histogram can then be passed for standard spectral analysis or display. It will be appreciated that although separate signal processing/ ADC/ MCA modules are shown in the schematic this is to illustrate the separate collection of spectra and does not require or imply discrete components. Likewise exemplification by analogue signal processing does not imply that a digital signal processing alternative could not be used.

An example of a process for combining spectra from multiple radiation detectors is now described. This uses a CZT/ Csl hybrid model such as could be employed as the embedment of figure 1, and considers an example method for the numerical processing of the collected data and a presentation of some example results.

An example method expressed generally might be:

a) Use two or more spectroscopic detectors whose response functions are

known and have for example previously been measured.

b) Collect spectral histograms from these detectors.

c) De-convolute these histograms using the algorithm described below to

produce a single histogram that combines the information from all detectors. d) Optionally display the single histogram.

e) Optionally compare the peaks in the single histogram with levels that define the statistical significance of their height relative to the continuum

background.

f) Optionally integrate the area of peaks in the single histogram and use this as input to a calculation of source activity.

SIMULATION

An example simulation is shown in Figures 2 and 3, made with an ideal simulation of two detectors labelled 'CZT' and 'Nal' that have very different resolutions (1% and 3.5% ). The Nal detector has ten times greater efficiency than the CZT. The simulated spectrum is a flat continuum with two lines of equal intensity at 580 and 600 keV.

Figure 2 shows the simulated responses of the two detectors. It shows that only one peak is seen by the Nal because of its poor resolution, whereas the two peaks are partly resolved by the CZT.

Figure 3 shows the effect of carrying out a Bayesian deconvolution (200 iterations) on the spectra in Figure 2. The separate deconvolution of the individual CZT and Nal spectra is known from Kennett et al. and these curves are just shown for comparison. The point to note is that with a reasonable number of iterations the Nal response alone can not be deconvoluted into separate peaks.

The invention is the deconvolution using both spectra together, for example using the algorithm described in further detail below. The point to note is that the joint deconvolution can distinguish the two separate lines (as can the CZT alone) but it also contains the statistical information about the source activity from the Nal spectrum.

DISCUSSION OF DECONVOLUTION MODEL Model description

The model describes two detectors representing CZT and Csl labelled with subscripts 1,2 respectively. Each detector has a Gaussian resolution with width that is a percentage of the energy; oi = 2% and σ₂ = 7%. Each detector has an acceptance value which is the probability that a gamma from the source will be contained in that detector. Initially these acceptances were set to;

= 0.02 and ε₂ = 0.1.

Parameters common to both detectors are:

• A background rate Br is set at 10 gamma ray photons per second per keV interval.

• A line from the source which has energy 550 keV and rate Sr 100 /s.

• The simulated data capture time t; usually varied in a range up to 200

seconds.

• The energy range simulated is from 400 to 1000 keV but only the range from 460 to 940 keV is used in the analysis.

The background level is assumed to scale with its efficiency for seeing the source, so the number of background counts per keV interval in the CZT detector is txBrxei, while the total number of counts from the source in the same detector is txSrxei where these counts will be spread over several energy bins by the resolution. Bavesian Deconvolution

Bayesian deconvolution is a method to iteratively approach a good estimate of a true spectrum, based on a measurement that is influenced by known systematic distortions and unknown random noise. In general the measurement process can be described by

M E )

R(E_k' , E, ).T(E_l ) + N(E_k' ) ₍₁₎ i

where M is the measured spectrum, T is the true spectrum, R is the response matrix that describes the known systematic distortions of the measurement, and N is the noise. In the model below the assumption is made that the only noise is Poisson statistical fluctuations.

If there was no noise and the number of measurement bins was chosen to be equal to the number of bins in the true spectrum then this equation could be exactly solved for T by finding the inverse of the response matrix, R ¹ and applying it to the measured spectrum. However, if there is even a moderate amount of noise in the measurement then this solution falls down; the noise is amplified and the resulting 'true' spectrum has very large bin-to-bin fluctuations and some bins can even be negative.

A better solution is to use an approach based on Bayes' theorem which has the desirable properties that it is less sensitive to noise and the 'true' spectrum that it yields is guaranteed to be positive in all bins. The method involves choosing a first estimate of the true spectrum and using it as the prior function in Bayes' theorem to yield an improved estimate of the true spectrum, which is then fed back as the new prior in the next iteration. The resulting equation is;

Where the terms have the same meanings as equation 1 and the superscript on T refers to the iteration number. The reasonableness of this equation can be seen if one notes that the denominator is equal to the expected number of events, Ek", that would are predicted in measurement bin k given the truth spectrum of iteration n and no noise;

j

Furthermore, %,/ε, is a set of weights summing to 1 that link measurement bin k with truth bin /. So, on each iteration T, is multiplied by the factor Ff;

This factor F," will be greater than one if the measurements in bins linked to / are generally above expectation and it will be less than one if measurements in the linked bins are generally less than expectation.

Equation (2) was derived by Kennett et al (NIM 151 (1978) 285-292). The normalisation factor, s_i = R_ki , was not included by Kennett et al because they k

defined ¾, in such a way that it summed to one. The convergence properties, noise properties and implementation of this algorithm on a computer were investigated by Kennett et al in the late 1970s and this method has been used by other workers since.

Extension to the case of two or more detectors The model applied in accordance with the example method extends this formalism to the case of two or more detectors, which may have very different response functions, by extending the meaning of index k in equation (2). Conventionally k is supposed to denote a set of energy measurement bins of a single detector. But we use one part of the range of k to denote measurements in one detector and another part of the k range to denote measurements in a different detector. For example suppose there are two detectors and the set of indices k is divided into two parts labelled a and b relating to the two detectors, then equation (4) can be re-written as;

The epsilon term can also be separated between the two detectors so that

^ =∑¾ , ^ =∑¾ and ε, = ε? ₊ ε? (6] where we have capitalised the A to indicate that it is no longer an index for summation. Finally, substituting equation (6) into (5) and rearranging gives

B F F

T n _ An " i . T Bn ° i

i ~ i „A . β ' . „B (7)

ε, + ^ε, ^ε, + ^ε,

Where F,^An is defined exactly as in equation (4) and the superscript A is reminding us that we are considering only detector A. Equation (7) tells us that when we wish to carry out a Bayesian deconvolution of the spectra from multiple detectors measuring the same source, we should do so by calculating the iteration factors F for each detector individually and then combining the F factors using weights built up from the epsilons of each individual detector to produce a joint F value that represents the hybrid system. Since equation (7) is derived rigorously from the much studied equation (2) a method based on equation (7) may exploit the known benefits of optimal information use, convergence, noise immunity and reasonableness that come with the Bayesian deconvolution method.

Fundamentally, the Bayesian method involves choosing a first estimate of the spectrum for each detector and using it as the prior function in Bayes' theorem to yield an improved estimate of the true spectrum. In a particular implementation, a response matrix is obtained for each detector, and the respective detector response matrices are used to derive the priors. They may be used to derive the prior directly for example by being applied directly for example as a weighting factor, or they may be used to derive the prior otherwise indirectly.

Simulation A single 'experiment' consists of generating a spectrum with Poisson fluctuations in both detectors. The spectra are then analysed with the Bayes deconvolution fit to extract lines. The analysis may use either detector alone or combine the information from the two. Success is defined as finding a line within ±15 keV of the position of the input line. A false positive is defined as when the input line intensity is set to zero but a line is found at the correct position anyway because of background fluctuations.

A series of 100 experiments with source switched off are used to find the threshold setting that will give a 1% false positive rate. The lines used to measure the false positive rate are in the fiducial range 460-940 keV and it is assumed that the false positive peaks are equally likely to be anywhere in this range. So this threshold setting procedure consists of choosing the 100 ^χ 1% ^χ (480 keV)/(30 keV) = 16^th highest peak from these 100 experiments and using it as the threshold level. Finally a series of 100 experiments using the chosen threshold and with lines switched on gives the efficiency.

Results

Figure 4 shows the efficiency versus data collection time when the acceptance ratio of the two detectors is 1:5. The CZT alone is somewhat more efficient than the Csl alone but the best efficiency comes from combing data from both detectors.

If we now increase the acceptance of the Csl to give an acceptance ratio of 1:50 we get the results shown in Figure 5. The Csl now has such high acceptance that it performs much better than the CZT but the combined analysis still benefits from the presence of the CZT. It is thus illustrated that application of this model after a number of iterations of the algorithm described above it is possible to obtain a more representative solution for the truth distribution Ti. It may be suggested that this truth distribution contains the optimum combination of information from the two detectors, assuming no prior knowledge about the truth spectrum.

In accordance with the model a method is offered for the convolved processing of spectral data from a plurality of radiation detectors with at least two different known response properties, and in particular from a plurality of radiation detectors having at least two different energy resolutions and/ or of different efficiency that extracts data more effectively than would be possible by analysis of the spectra separately and that more effectively exploits the complementary spectral data content provided by the at least two different detector responses.

Claims

A portable detector system for the processing of data derived from incident radiation comprising:

a processing device comprising:

the plurality of separately addressable radiation detectors and the processing device being associated together in compact and portable manner.

2. A detector system in accordance with claim 1 wherein the deconvolution module is adapted to deconvolve the histograms from each detector by applying a Bayesian deconvolution.

A detector system in accordance with claim 1 or claim 2 wherein the deconvolution module is adapted to is adapted to apply a numerical deconvolution that makes use of a response matrix for each detector.

A detector system in accordance with any preceding claim comprising a plurality of radiation detectors having at least two different energy resolutions and/ or of least two different efficiencies.

5. A detector system in accordance with claim 4 comprising at least one detector of a first class having a relatively higher energy resolution and/ or a relatively lower absolute efficiency and at least one detector of a second class having a relatively lower energy resolution and/ or a relatively higher absolute efficiency.

6. A detector system in accordance with claim 5 comprising at least one detector from a first class having a relatively higher energy resolution and a relatively lower absolute efficiency and at least one detector from a second class having a detector with a relatively lower energy resolution and a relatively higher absolute efficiency.

7. A detector system in accordance with claim 6 wherein a detector from a first class comprises a direct-conversion semiconductor detector device.

8. A detector system in accordance with claim 7 wherein the direct-conversion semiconductor detector device comprises crystalline Cdi-(_a+b)Mn_aZnbTe where a and/ or b may be zero.

9. A detector system in accordance with one of claims 5 to 8 wherein a detector from the second class comprises an indirect-conversion scintillator semiconductor detector device.

10. A detector system in accordance with any preceding claim further comprising an identification module to isolate and identify the presence or absence of one or more predetermined characteristic spectral features of at least one particular radioactive isotope and so identify the presence of a contribution from the at least one particular radioactive isotope in the collected data.

11. A detector system in accordance with any preceding claim wherein the processing device comprises a means adapted to perform the steps of:

collecting data from radiation incident at each detector;

producing a spectral histogram for the collected data from each detector; deconvoluting the histograms from each detector by applying a numerical deconvolution to derive a single spectral histogram that representatively combines information from the plurality of detectors.

12. A detector system in accordance with claim 11 wherein the processing device comprises a means adapted to apply a numerical deconvolution that makes use of a response matrix for each detector.

13. A detector system in accordance with claim 11 or 12 wherein the processing device comprises a means adapted to perform the steps of:

collecting data from radiation incident on at least one first detector and at least one second detector, the first and second detectors having different response properties;

producing a spectral histogram for the collected data from each detector; deconvoluting the histograms from each detector by applying a Bayesian deconvolution to derive a single spectral histogram that representatively combines information from the plurality of detectors.

14. A detector system in accordance with claim 13 wherein the processing device comprises a means adapted to perform the step of applying a Bayesian deconvolution by applying the numerical relationship:

where M is the measured spectrum, T is the true spectrum, R is the response matrix that describes the known systematic distortions of the measurement, and N is the noise.

15. A detector system in accordance with any preceding claim further comprising a display to display the derived single histogram.

16. A detector system in accordance with any preceding claim further comprising a peak discriminator to compare the peaks in the derived single histogram with levels that define the statistical significance of their height relative to the continuum background.

17. A detector system in accordance with any preceding claim further comprising a peak integrator adapted to integrate the area of peaks in the derived single histogram and use this as input to a calculation of source activity.

18. A detector system in accordance with any preceding claim further comprising a sample holder to retain a sample for testing in appropriate juxtaposition relative to the plurality of radiation detectors.