Cty tam Pee we es

ae ae cee aalee ote ate cee Cad Leodlabibacten

87
:jeal fibers, Univ. of Rochester Institute of Optics Report

NYO-9033 (April 1960), p. 6-46.

post, R. F. Resolving time of scintillation counters, .u-

" feonics 10 (6), 56-58 (June 1952).
rods realig \jurinelli, L. D., Clemente, G. F., Abu-Shumays, I. K., and

c phantos
‘xperimeng

~teingraber, O. J. Localization of radioactivity in vive
-' photon time-of-flight techniques. Argonne National

Laboratory Radiological Physics Division Annual Report,
July 1967-June 1968, ANL-7489, pp. 1-12.
6. Marmelli, L. D., Clemente, G. F., Abu-Shumays, I. K., and
Steingraber, O. J. Localization of scintillations in gamma
ray cameras by time-of-flight techniques: Linear resolutions attainable in long fluorescent rods. Radiology 92,
167 (January 1969).

aable und

MEGULARIZATION UNFOLDING IN LOW ¥-RAY ACTIVITY MEASUREMENTS.
} EVALUATION FOR ONE-DIMENSIONAL SCANNING
; efforts iB G. F. Clemente, L. D. Marinelli, and I. K. Abu-Shumays*
: resolutiog—-ne May
The problem of converting the spatial distribution of the
2m rods oy. ing rate of a scanning 3” Nal crystal to the distribution
vever, thapf : vlioactivity in the object being studied involves solution

more senspt * lredholm equation of the first kind. Precision of the reUEP
a function of the physical parameters used
studied as s,
] it;
tt TeSOlty
slice ismeasurement

te first th

1 a two-d,

STRODUCTION

‘rods thre’ We have reported elsewhere“: » on various methods
stails of for the quantitative determinationof the distribution of

swo-dimenl®” level activity in man. We wish here to study, in
this prota™ -. detail, one such competitive method, the regularigation unfolding method, and specifically, its application
):l representative experimental model to be described

clow. We will analyze the effect of the experimental
araumeters on the accuracy of the regularization unHolding of low activity scanning data. A comparison of
ome of our results with results using the usual iterative

ution, psec

ethod@: © favors the regularization unfolding: ®.

* The unfolding problem can be formulated bythefol-

owing Fredholm equation of the first kind

520

680

g(a’) = gle!) +e’) = f 12) K(ea’)de

90

where f(x) is the unknown distribution of activity, g’(z’)
the hypothetically exact and g(x’) the actual speetrum
or response of the detector, e(2’) the statistical and experimental error superimposed on g(z’), and the kernel
AY +.c') the point response function.
lor simplicity, the present treatment is restricted to

1175

b

one dimension. We start with a known distribution

J(), calibrate (i.e., measure the response kernel by usIng point sourees of knownactivity), measure the spectrum g(x’) corresponding to f(z) and try to reproduce

§ the known distribution f(z) by using the regularization

fUnlolding method.
; The distribution of activity f(z) consisted of a poly-

e's lone catheter 0.034” I.D., 270 cm Jong filled with

'68).

idy of A

——

a

\pplhed Mathematics Division.

radioactive (Cs) microspheres (~0.725 mm in diame-

ter); the source configuration (54 cm long) consisted of
nearly sinusoidal waves of 5-cm amplitude and of vary-

ing frequencies set on a light Lucite bar. The total activity (1.07 + 3% uCi) of the distribution was cali-

brated by proper comparison with the activity (0.127
pCi) of the point source used to obtain the point response function K(z,2’).
Measurements of the spectrum g(x’) were carried out
by taking measurements at various intervals over a
single distribution of activity, using a 3” x 3” Nal erystal with different collimators placed in a low background
lead well. The crystal was restricted to move on a

straight line parallel to the long axis of the distribution

f(z).

This paper considers the influence of the following
parameters on the calculated distribution f(x): A.

previous knowledge of the total radioactivity C which
is the integral of the distribution f(z); B. the full width
at haif maximum (FWHM) of the point response kernel
(equivalent to the resolution radius of the colimator);
C. the experimental and statistical error superimposed
on g(x’); D. the quadrature approximations or, equivalently, the interval h between two consecutive readings
of g(v’); and E. the usefulness of extending the measurements of g(x’) beyond the rangeof the distribution f(z),
and thus increasing the information content of g(z’).

Wewill proceed to describe the method weused to solve
for the distribution f(z). This method has been programmed for the IBM 360 by Mrs. Alice B. Meyer and
one of the authors (IIXA).
MATHEMATICAL OUTLINE OF THE UNFOLDING PROCEDURE

If one eliminates e(x’) from Eq. (1), the result is a

mathematicaily‘‘all-posed problem.”’ The measurement

g(z’) is relatively insensitive to fictitious (positive-negative) distributions f’ for which
f K(a,2') f (x) dx = e(z),

Select target paragraph3