Apparatus and method for detecting full-capture radiation events

An apparatus and method for sampling the output signal of a radiation detector and distinguishing full-capture radiation events from Compton scattering events. The output signal of a radiation detector is continuously sampled. The samples are converted to digital values and input to a discriminator where samples that are representative of events are identified. The discriminator transfers only event samples, that is, samples representing full-capture events and Compton events, to a signal processor where the samples are saved in a three-dimensional count matrix with time (from the time of onset of the pulse) on the first axis, sample pulse current amplitude on the second axis, and number of samples on the third axis. The stored data are analyzed to separate the Compton events from full-capture events, and the energy of the full-capture events is determined without having determined the energies of any of the individual radiation detector events.

BACKGROUND OF THE INVENTION 
The present invention relates to identification and quantification of 
radionuclides using a radiation detector. In particular, the present 
invention relates to an apparatus and method for sampling the output 
signals of a radiation detector and distinguishing signals representing 
full-capture events for those representing Compton scattering events. 
2. Discussion of Background 
Conventional radiation spectroscopy techniques are based on the interaction 
of ionizing radiation with the atoms of a suitable detector. As the 
radiated particle loses energy in each interaction, it deposits an excess 
electrical charge in the detector. If all of the charge so deposited were 
collected (as by integration by a capacitor), then the energy of the 
incoming particle can be determined. Therefore, present-day instruments 
attempt to optimize charge collection, i.e. to collect all the excess 
electrical charge. 
The energy of the ionizing radiation particle is a clue to the identity of 
the source of the particle. A given source may produce, through 
radioactive decay, particles having one or more energy levels 
characteristic of that source. To determine the energy spectrum of the 
incoming particles, the energy produced by each interaction--or event--in 
the detector is measured, and the number of events that occur having an 
energy in each energy range are counted and plotted versus energy. FIG. 1 
shows a sample spectrum 10. This two-dimensional method of viewing the 
data is the method used with current instrumentation. 
Because events occur to some extent randomly and several events may occur 
almost simultaneously, collecting, sorting and analyzing the event data 
can pose an electronic obstacle. Many devices and techniques are available 
for obtaining event data from detectors. Data-collection systems are 
typically "event-triggered," that is, the system is enabled when the 
detector output exceeds a predetermined threshold value. Data collection 
continues until the detector output falls below the threshold value, 
whereupon the system is returned to its normal or "non-event" state. 
"Dead-time" limitations are inherent in event-triggered systems: once the 
system is triggered by the start of an event, it cannot collect or process 
subsequent events until the system has returned to its normal or 
"non-event" state. Therefore, event-triggered systems have limited ability 
to distinguish between separate, nearly simultaneous events. When an event 
enables the system, a later event may begin before the first event is 
completed and before the system can return to its normal state. Thus, the 
system will not resolve the signals of the two separate events; the two 
events will be treated as a single, continuous event of extended duration. 
A method and apparatus for reducing dead-time are described in 
commonly-assigned U.S. patent application Ser. No. 08/014,916, filed Feb. 
8, 1993; ("Method and Apparatus For Data Sampling"). In this application, 
the detector output is continuously sampled at a high rate. When no event 
is occurring, the sampled data represent only "non-events" including 
noise. When an event is occurring, the data represent "events," that is, 
the interaction of particles with the detector. The sampled data are 
encoded as binary numbers, or "digitized," and processed to identify those 
samples that are representative of detected events. The use of continual, 
high-speed digital sampling reduces both deadtime and also other problems 
associated with analog data-collection techniques, such as drift. 
But nether the traditional, event-triggered method nor that disclosed in 
application Ser. No. 08/014,916, ("Method and Apparatus For Data 
Sampling"), can distinguish "full-capture" events, where all the energy of 
an incoming particle is deposited in the detector, from "partial-capture" 
or Compton scattering events of the same energy, where only some of the 
particle's energy is deposited in the detector. When integrated in the 
traditional manner or according to the technique described above, a 
Compton event is indistinguishable from a full-capture event of the same 
energy. Thus, Compton scattering events often obscure full-capture events 
of comparable energy, leading to inaccuracies in data analysis and 
evaluation. 
Several techniques are available for correcting spatial information in 
radiation imaging systems such as gamma cameras and scintillation cameras. 
Barfod (U.S. Pat. No. 4,899,054) reduces the sensitivity for some 
locations on the detector of a gamma camera system to compensate for 
inherent non-uniformities in the system. Del Medico, et al. (U.S. Pat. No. 
4,316,257) and Knoll, et al. (U.S. Pat. No. 4,212,061) use stored spatial 
distortion correction factors to correct for distortion effects in 
scintillation cameras. These spatial-discrimination techniques are not 
capable of correcting time-based data, including distinguishing Compton 
scattering from other detector events. 
In U.S. Pat. No. 4,258,428, Woronowicz discloses a gamma camera having a 
Compton scattered radiation de-emphasizer. Scintillation events are 
displayed at the (x,y) coordinates of the event on a cathode ray tube 
screen by unblanking the tube with z pulses applied to its control 
electrode. The de-emphasizer sends small z pulses into the part of the 
spectrum where Compton scattering is most prevalent and increasingly 
larger z pulses where Compton scattering is insignificant. The system 
produces only a qualitative display, using predetermined, empirical 
correction factors. But individual Compton events as such are not 
distinguished from full-capture events by his system. Some 
multiple-detector systems use time coincidence to distinguish Compton 
events from full-capture events. However, no presently-available 
single-detector system can distinguish full-capture events from Compton 
scattering events. 
SUMMARY OF THE INVENTION 
According to its major aspects and broadly stated, the present invention is 
an apparatus and method for sampling the output of a radiation detector 
and processing the data to distinguish full-capture radiation events from 
Compton scattering events. The output signal of a radiation detector is 
continuously sampled. The magnitudes of the samples are converted to 
digital values and sent to a discriminator, where samples are identified 
as being representative of detected events (full-capture events and 
Compton events) or non-events (noise). The discriminator transfers only 
event samples to a signal processor where they are stored in a 
three-dimensional matrix with time (measured from the time of onset of 
each event) on the first axis, sample amplitude (representing the 
amplitude of the detector output current at each sampling time) on the 
second axis, and the number of samples on the third axis. The event 
samples are plotted to produce a three-dimensional image or "landscape," 
having well-defined series of peaks that correspond to full-capture events 
and randomly-dispersed peaks that represent Compton events. After the 
Compton events are eliminated, a curve is fitted to the maxima of each set 
of peaks and the area under each curve is determined. For each set of 
peaks, this area is proportional to the energy of the detector events that 
produced the peaks. Thus, the energies of the peaks are determined without 
having determined the energies of any of the individual detector events. 
An important feature of the present invention is the sampling of the 
detector output. The higher the sampling rate, the more representative the 
discrete samples are of the detector output signal. The sampling rate is 
preferably at or above the Nyquist criteria for the event pulses being 
sampled, so the samples are sufficiently representative of the detector 
output to provide the information needed for analysis. Importantly, the 
output is only sampled, however often, but no attempt is made to 
accumulate all the output. 
High speed digitizing or encoding in binary form is another, important 
feature of the present invention. All the samples are converted to digital 
representation immediately by one or more high speed analog-to-digital 
converters. Immediate digitizing makes subsequent processing easier and 
faster, and reduces the number of analog stages which are more prone to 
drift. Conventional systems convert to digital after determining which 
output corresponds to an event. 
Another important feature of the present invention is the selection and 
transfer of event data for analysis. By generating the three dimensional 
plot of current amplitude, time and counts, Compton events can be readily 
distinguished from full-capture events and eliminated, leaving only the 
latter for analysis. 
Other features and advantages of the present invention will be apparent to 
those skilled in the art from a careful reading of the Detailed 
Description of a Preferred Embodiment presented below and accompanied by 
the drawings.

DETAILED DESCRIPTION OF A PREFERRED EMBODIMENT 
The present invention is an apparatus and method for sampling the output of 
a radiation detector and processing the data to distinguish full-capture 
radiation events from, for example, those representing Compton scattering 
events. The output signal of a radiation detector is continuously sampled 
and a digital discriminator identifies those samples that are 
representative of detected events. The discriminator transfers only event 
samples, that is, samples representing full-capture events and Compton 
events, to a signal processor for storage and analysis. The stored data 
are analyzed to separate out the Compton events from full-capture events, 
and the energy of the full-capture events is determined. 
The method is implemented as follows: 
1. The detector output signal is continuously sampled at a high rate, 
preferably at or above the Nyquist criteria for the event pulses being 
sampled. The higher the sampling rate, the more representative the 
discrete samples are of the detector output signal. However, as long as 
the sampling rate meets or exceeds the Nyquist criteria, the samples will 
be sufficiently representative of the detector output to provide the 
information needed for analysis. 
2. The samples are sent to a discriminator, where samples are identified as 
being representative of detected events (full-capture events and Compton 
events) or non-events (noise). The discriminator sorts them and transfers 
only event samples to a signal processor for storage and analysis. 
3. Samples representing a succession of events occurring during operation 
of the detector are stored in a three-dimensional matrix with time 
(measured from the time of onset of each event) on the first axis, sample 
amplitude (representing the amplitude of the detector output current at 
each sampling time) on the second axis, and number of samples on the third 
axis. 
4. The samples are plotted to produce a three-dimensional image or 
"landscape," wherein individual detector events appear as peaks. A 
well-defined set of peaks corresponds to a plurality of full-capture 
events, that is, detector interactions with incoming particles having 
approximately the same energy. The maxima of a series of peaks form a 
"ridge" or "edge" in the three-dimensional image. Each set of peaks 
represents detector interactions with incoming particles of different 
energies. Randomly-dispersed peaks, however, represent Compton events, and 
can be distinguished from full-capture events using image enhancement 
techniques. 
5. A curve is fitted to each ridge and the area under each curve integrated 
to determine the energy of the full-capture events that produced those 
peaks. 
Referring now to FIG. 2, there is shown a schematic view of an apparatus 
according to a preferred embodiment of the present invention. Apparatus 12 
includes a radiation detector 20, such as a sodium iodide and 
photomultiplier tube (Na(I)/PMT) detector, that produces an output current 
pulse in response to a radiation event within the detector. Detector 20 
directly interfaces a non-integrating amplifier 22. Amplifier 22 converts 
a current pulse 24 from detector 20 into a voltage pulse 26 and limits the 
signal to a range of frequencies using a bandwidth filter. 
Output 26 of amplifier 22 is fed to two distinct, electrically parallel 
circuits. The first circuit includes a buffer amplifier 30 and a flash 
analog-to-digital (A/D) converter 32. Buffer amplifier 30 amplifies output 
26 to produce an output signal 34. Amplifier 30 is preferably a fixed gain 
amplifier that provides adequate driving capacity to the input of 
converter 32. Alternatively, amplifier 30 may be a variable gain stage 
controlled by a digital signal processor 80. A/D converter 32 performs two 
functions: it samples output 34 of amplifier 30 (representing output 24 of 
detector 20) at a very high sampling rate, regardless of whether or not an 
event is occurring in detector 20, and converts the samples into 
corresponding digital values. 
The sampling rate employed by A/D converter 32 is chosen based on the 
fundamental frequency and duration of the waveform of the event pulses to 
be detected, the rate at which events are occurring in the detector, the 
period of time over which detector events are to be sampled, the 
particular Compton elimination algorithms being used, and the desired 
overall resolution of apparatus 12. Higher sampling rates produce 
discernible peaks in the output of converter 32 in less time. The sampling 
rate for converter 32 is preferably set high enough so that a sufficiently 
large number of samples per event can be taken to obtaining an accurate 
digital representation of each event. For applications at low to moderate 
count rates (that is, the rate of occurrence of events in detector 20), 
the sampling rate meets the Nyquist frequency criteria for the event 
waveform and preferably exceeds it. At extremely high count rates, 
sampling may be performed below the Nyquist frequency to reduce the 
incoming data rate to digital signal processor 80. 
A nominal sampling rate for A/D converter 32 may be determined empirically 
by sampling a pulse (or several pulses) at a very high rate, taking a 
Fourier transform of the data, and finding the highest frequency 
component. The sampling rate is preferably at least approximately twice 
the highest frequency component. Depending on the particular choice of 
detector and the types of events to be detected, the sampling rate of 
converter 32 could range from 10.sup.6 samples/sec to 10.sup.9 
samples/sec. 
A/D converter 32 constantly samples the output of detector 20 and converts 
the samples to a stream of digital values. A/D converter 32 has an output 
36, consisting of a stream of digital values representing the amplitude of 
analog signal 34 at each sampling time. Output 36 contains values 
representing events (Compton events and full-capture events) and 
non-events (noise). Output 36 serves as an input to a two-function 
discriminator 40. 
Since A/D converter 32 is a free-running device operating at a sampling 
rate on the order of 10.sup.6 samples/second or higher, the data stream 
(output 36) must be filtered for real data values (events) and no-data 
values or noise (non-events). The second circuit receiving output 26 of 
amplifier 22 includes a comparator 50, a track and hold (T/H) amplifier 
52, an A/D converter 54, an digital-to-analog (D/A) converter 56, a 
sawtooth generator 58, and a clock 60. Generator 58 produces a sawtooth 
waveform signal 62 having a period 64. Signal 62 is input to T/H amplifier 
52. Clock 60 produces a timing signal 66 having a period 68, serving as an 
input to discriminator 40 and A/D converters 32, 54. Comparator 50 has an 
output signal 74, which serves as an input to T/H amplifier 52. Amplifier 
52 produces an output 76. These components together form a trigger circuit 
whose function is to compare amplified detector output 26 with a threshold 
value 70 provided by digital signal processor 80 and implemented by D/A 
converter 56. 
Threshold 70 is set to a voltage established by output 26 of amplifier 22 
to enable the data collection and analysis portions of apparatus 12. The 
value of threshold 70 therefore depends on the type of data being detected 
and is set according to the particular characteristics of the incoming 
data pulses. Ideally, threshold 70 is low enough to trigger data 
collection at or near the beginning of an event, yet high enough to 
prevent at least some non-event data such as noise from being accepted and 
processed as though it represented events. Comparator 50 generates a 
trigger signal 90 when threshold 70 is exceeded, causing T/H amplifier 52 
to freeze its output 76 at the then-existing voltage value of sawtooth 
waveform 62. Output 76 is then converted by A/D converter 54 to a digital 
value representative of the time between the last main clock edge 
(generated by clock 60) and the time when output 26 of amplifier 22 
exceeded threshold 70. Period 64 of sawtooth waveform 62 and period 68 of 
timing signal 66 are preferably the same, permitting accurate timing 
information to be generated and used as "trigger time." 
When output 26 exceeds threshold 70, trigger signal 90 signals the 
beginning of a possible detector event to group discriminator portion 96 
of discriminator 40. Output 36 of A/D converter 32 (sample amplitude, 
representing the output of detector 20) and output 78 of A/D converter 54 
(sample time, as measured from the trigger time) are separately fed to 
discriminator 40 which is preferably a programmable gate array. 
Discriminator 40 processes the incoming data on a sample-by-sample basis 
to identify event samples and non-event samples (noise). Discriminator 40 
also processes the data substantially as described in commonly-assigned 
patent application Ser. No. 07/014,916, filed Feb. 8, 1993, ("Method and 
Apparatus For Data Sampling"), the disclosure of which is incorporated 
herein by reference. 
Discriminator 40 includes a FIFO (first-in-first-out) memory 
director/controller 92, a word discriminator function 94 and a group 
discriminator function 96, as indicated schematically in FIG. 2. 
Discriminator 40 has an output 98. Output 98 is fed to an array of 
buffers, preferably FIFO buffers 100, 102, then to digital signal 
processor 80. FIFO memory controller 92 communicates with signal processor 
80 via a two-way link 106. Signal processor 80 may be any device that is 
capable of storing and processing the amount of data produced during 
operation of detector 20, such as an AD21020 floating point digital signal 
processor produced by Analog Devices, Inc. of Norwood, Mass. 
As noted above, threshold 70 is preferably set at a level that is low 
enough to trigger collection of substantially all event data. Therefore, 
some of the samples collected by discriminator 40 may represent non-event 
data such as noise spikes. Discriminator 40 processes the samples to 
distinguish event data (full-capture events and Compton events) from 
non-event data. 
Word discriminator 94 compares, in sequence, the amplitude of each sample 
in output 36 to a preselected threshold value V.sub.th. V.sub.th is 
preferably at least approximately equal to threshold 70, but may be set at 
a higher value if desired to filter out at least some non-event data. 
Samples having an amplitude greater than or equal to V.sub.th are 
identified as being "potential event" samples; samples with a lesser 
amplitude are identified as "non-event" samples. The samples continue in 
their original sequence to group discriminator 96. 
Group discriminator 96 receives alternating groups of potential event 
samples, having amplitudes greater than or equal to V.sub.th, and groups 
of non-event samples, having amplitudes less than V.sub.th, arranged 
according to their original sampling sequence. Thus, the non-event samples 
serve as separators between groups of potential event samples. 
The interaction of an incoming radioactive particle with detector 20 is not 
instantaneous, but takes place over a period of time that depends on the 
type of particle and its energy. Noise spikes, in contrast, are typically 
shorter in duration. Thus, detector events generate at least a minimum 
number N.sub.min of contiguous samples, where N.sub.min is selected 
depending on the types of events being detected, their normal duration and 
the sampling rate of A/D converter 30. N.sub.min is preferably set low 
enough to allow collection of substantially all event data, but high 
enough to filter out substantially all non-event data. 
Group discriminator 96 identifies event samples by their belonging to a 
sequence of at least a preselected minimum number N.sub.min of contiguous 
potential event samples. If a group of potential event samples contains at 
least N.sub.min samples, the entire group exits group discriminator 96 
through an output 98. If the group contains fewer than N.sub.min potential 
event samples, the entire group is treated as noise and disregarded. As a 
result, output 98 from discriminator 40 carries a stream of samples 
occurring in sequence and representing only detected events. 
The identified event samples are transferred via output 98 to an empty FIFO 
storage area, one of two or more such devices as indicated by FIFO areas 
100, 102. Each of areas 100, 102 is preferably large enough to 
sequentially store all of the samples representing one event, retaining 
those samples for a period long enough to transfer the samples to signal 
processor 80. Thus, a series of event samples representing an event A is 
stored in area 100. Similarly, a series of event samples representing next 
event B is stored in area 102. A greater number of FIFO storage areas 
could be used as dictated by the actual occurrence rate of events and the 
speed of data processing by discriminator 40 and signal processor 80. With 
this type of storage, identified event sample groups are transferred from 
discriminator 40 into a buffer area (100 or 102) at a preselected rate, 
preferably equal to the sampling rate of A/D converter 32. This permits 
the sampling and discrimination processes of apparatus 12 to function at 
normal operating speed without delay. Event sample groups are then sent to 
signal processor 80 for storage and further analysis. 
FIFO director/controller function 92 insures that all the samples from one 
detector pulse are inserted into the same FIFO memory along with the 
trigger time for that pulse. This is indicated schematically within FIFO 
100 by samples 1 through M of a particular detector output pulse with 
"trigger time M." Similarly, the trigger time and samples of a second 
detector pulse are inserted into a successive FIFO area such as indicated 
by area 102 if signal processor 80 has not completed the process of 
transferring the samples from FIFO 100 to its own memory via output 104 
before a next detector event occurs (indicated by "trigger time N" and 
samples 1 through N in FIFO 102). When its data have been transferred to 
processor 80, any FIFO area is ready for re-use as needed. 
In use, radiation detector 20 is placed in an area of interest. Detector 
output 24 is amplified, and amplified signal 26 is sent to buffer 30. A/D 
converter 32 continuously samples analog output 34 of buffer amplifier 30 
at a frequency in the approximate range of 10.sup.6 -10.sup.9 samples/sec. 
Output 36 of converter 32 is in the form of a sequential stream of 
discrete digital values representing the amplitude of analog waveform 34 
at each sampling time. Output 36 enters discriminator 40, where word 
discriminator 94 and group discriminator 96 select for further processing 
those values which are greater than or equal to a predetermined threshold 
value, and which occur in a contiguous sequence of at least a minimum 
number of samples. The groups of digital values emerging from 
discriminator 40 pass to FIFO buffers 100, 102, then to signal processor 
80 for storage and analysis. 
Referring now to FIG. 3, there is shown a graphical view of a series of 
waveform samples obtained with apparatus 12. For clarity, only two 
representative time slices 120, 122 are shown, each containing samples 
124, 126, respectively, taken by A/D converter 32 from many detector 
events. 
When a series of radiation events is captured by radiation detector 20 as 
current pulses, each event being sampled at the same rate, the data 
samples are digitized and saved in signal processor 80 as they are 
received, in a three-dimensional matrix with time (measured from the 
trigger condition of the pulse) on one axis, the amplitude of the pulse 
current on the second axis, and the number of occurrences of 
time-amplitude samples on the third axis. Each point in the time-amplitude 
plane is actually a memory location in processor 80 that is dimensioned to 
handle the anticipated number of samples that may occur. For example, an 
unsigned 16-bit integer would permit as many as 65,535 samples to be 
accumulated in the third dimension of any one matrix element. As more 
events occur in detector 20, the third axis builds as individual 
time-amplitude points recur. 
Radiation events do not occur synchronously in time. Therefore, the data 
points collected on one event pulse will not necessarily coincide with 
those collected for other pulses, even if the pulses have approximately 
the same shape. When the data points from multiple events of the same 
energy are overlaid on one another, the total collection of time-amplitude 
samples in the matrix produces a three-dimensional image or "landscape," 
with peaks corresponding to the individual detector events (FIG. 4). 
During operation of detector 20, full-capture events occur repeatedly at 
specific energies while Compton events occur at random energies. 
Therefore, full-capture events appear in the image as sets of 
well-defined, clustered peaks such as a set 130, consisting of individual 
peaks 130a, 130b, 130c, 130d, and so forth. The balance of the landscape 
contains randomly-dispersed peaks from Compton events, such as peaks 132, 
134, 136. The Compton events can be removed by image enhancement 
techniques, revealing only peaks such as peaks 130 corresponding to 
repeated full-capture events. Peaks 130 have maxima 142a, 142b, and so 
forth, forming a "ridge" or "edge" in the three-dimensional image. A 
dotted line 144 represents the best curve fit along maxima 142. The area 
under curve 144 is proportional to the energy of the individual detector 
events that produced peaks 130. 
Apparatus 10 may be calibrated using standard reference sources. Detector 
20 receives incoming radiation from a standard source having a known 
energy spectrum, and the data are collected and processed as described 
above. The peaks in the three-dimensional image that represent 
full-capture events are identified, and the areas under the peaks are 
computed. These areas are correlated with the known energy spectrum of the 
source to provide calibration data for apparatus 12. 
Curve 144 represents the average energy of a plurality of full-capture 
events represented by individual peaks 130a, 130b, and so forth. 
Therefore, the area under curve 144 provides a more accurate determination 
of the energy than the data from a single pulse interacting with detector 
20. Radiation sources typically produce particles with a spectrum of 
energies, which would be represented in the three-dimensional image by a 
series of different curves such as curve 144. The energy spectrum of the 
incoming particles can be found by computing the area under each such 
curve, without determining the energy of any of the individual detector 
pulses whose digitized samples provided the energy information. This 
method is especially useful for analyzing full-capture events that are 
obscured by higher-energy Compton events. No other single-detector method 
of distinguishing Compton events from full-capture events is known. 
Distinguishing background data (Compton events and noise) from full-capture 
event data includes these steps: 
1. Background reduction to produce an enhanced image. For example, an 
addressable array of background correction factors may be stored in signal 
processor 80. For any point in the image, the correction factor 
corresponding to that coordinate position is used to generate a corrected 
point. The background-reduced data are plotted to produce an enhanced 
image. 
2. Convolution of the enhanced image to detect ridges formed by 
well-defined sets of peaks. 
3. Quantification of the detected ridges. For each set of peaks, a curve is 
fitted to the ridge formed by the maxima of the peaks. The area under the 
curve is calculated to find the energy of the particular detector events 
that produces those peaks. 
These basic techniques may be combined with data analysis methods in 
numerous ways, including but not limited to the following: 
A. Linear background subtraction and ridge detection convolution. 
1. The three-dimensional image resulting from a series of detector events 
is rendered in either gray-scale or color. 
2. Background reduction is carried out using the linear background 
subtraction technique, wherein a uniform gray-scale or color value is 
subtracted from the samples forming the image. 
3. Two-dimensional convolution is then used to search for "ridges" or 
"edges" in the image formed by the repetitive occurrence of same-energy 
events (represented by peaks 130 in FIG. 4). 
4. For the peaks of interest, the best polynomial curve fit is found for 
the points detected by ridge detection convolution (line 144 in FIG. 4)). 
5. The area under the curve is calculated by integrating the polynomial 
across the period from pulse start to pulse end. 
B. Non-linear spline fitting. Background reduction is carried out using the 
non-linear spline fitting background subtraction technique, wherein a 
non-uniform, but smoothly varying background level is removed from the 
entire image. The resulting image is analyzed as in steps 3-5 of method A. 
C. Contrast enhancement by histogram equalization. The distribution of 
gray-scale or color values is determined for the image as-is. Scaling 
coefficients are determined such that the distribution of gray-scale or 
color values can be equalized across the entire image. The equalized image 
is then the subject of ridge detection and curve fitting as described in 
steps 3-5 of method A. 
D. Partial background reduction. Background reduction is carried out on a 
portion of the image bounded by discernible peak curves as follows: 
1. Discernible peaks are located by linear background subtraction, 
non-linear spline fitting background subtraction, or contrast enhancement 
by histogram equalization. Alternatively, peak curves are located by 
simpler methods such as searching for only the highest numerical values on 
the sample axis, relying on pre-characterized and previously-stored 
Compton distribution images. 
2. The stored Compton image is intensity scaled (either in gray levels or 
color values as appropriate) to the relative magnitude in the third 
dimension (number of samples) of the peak height and then subtracted from 
the acquired image to remove nominal Compton effects from the image. This 
process is repeated for each energy peak curve discerned beginning with 
the highest energy peak curve. 
3. The resulting image is processed by one of methods A-C as described 
above. 
E. Template comparison. The acquired image is compared to a template (or 
convolution of previously stored peak curve templates) to find the points 
of maximum correlation with the template. Regional contrast enhancement of 
the image is carried out at areas showing at least a particular minimum 
level of correlation. Edge detection and further data analysis proceed as 
in steps 3-5 of method A. 
F. Detector-adaptive synthetic template generation. 
1. Readily discernible peaks are located by linear background subtraction, 
non-linear spline fitting background subtraction or contrast enhancement 
by histogram equalization as described above. 
2. A polynomial is fitted to the collection of points representing the 
peak. 
3. The coefficients of the polynomial are scaled to generate templates 
corresponding to the anticipated curves of energies peculiar to selected 
isotopes such that the remaining field of the image can be searched for 
correlation to these known isotopic energies. 
Other combinations of image-enhancement and data analysis techniques may be 
used without departing from the spirit of the present invention. 
It will be apparent to those skilled in the art that many changes and 
substitutions can be made to the preferred embodiment herein described 
without departing from the spirit and scope of the present invention as 
defined by the appended claims.