Testing the count rate performance of the scintillation camera by exponential attenuation: Decaying source; Multiple filters

Adams, Ralph; Mena, I.

doi:10.1118/1.596241

Cited by 6 publications

(4 citation statements)

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“…Previous efforts by others [7][8][9][10][11][12][13][14][15][16][17] have modeled the dead time behavior of Anger cameras for radioisotopes with a single energy window at high counting rates. The camera dead time has been shown to be dependent on the scattering condition in the source.…”

Section: Introductionmentioning

confidence: 99%

Deadtime correction for two multihead Anger cameras in dual‐energy‐window‐acquisition mode

et al. 1998

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Two side-by-side energy windows, one at the photopeak and one at lower energy, are sometimes employed in quantitative SPECT studies. We measured the count-rate losses at moderately high activities of 131I for two multihead Anger cameras in such a dual-window-acquisition mode by imaging a decaying source composed of two hot spheres within a warm cylinder successively over a total of 23 days. The window locations were kept fixed and the paralyzable model was assumed. In addition, for the Picker Prism 3000 XP camera, the source was viewed from three different angles separated by 120 degrees and the final results are from an average over these three angles. For the Picker camera, the fits to the data from the individual windows are good (the mean of the squared correlation coefficient equals 0.98) while for the Siemens Multispect camera fits to the data from head 1 and from the lower-energy, monitor window are relatively poor. Therefore, with the Siemens camera the data from the two windows are combined for deadtime computation. Repeated autopeaking might improve the fits. At the maximum count rate, corresponding to a total activity of 740 MBq (20 mCi) in the phantom, the multiplicative deadtime correction factor is considerably larger for the Picker than for the Siemens camera. For the Picker camera, it is 1.11, 1.12, and 1.12 for heads 1-3 with the photopeak window and 1.10 for all heads with the lower-energy monitor window. For the Siemens camera, the combined-window deadtime correction factor is 1.02 for head 1 and 1.03 for head 2. Differences between the deadtime correction factor for focal activity and for the total activity do not support the hypothesis of count misplacement between foci of activity at these count rates. Therefore, the total-image dead time correction is recommended for any and all parts of the image.

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Section: Introductionmentioning

confidence: 99%

Deadtime correction for two multihead Anger cameras in dual‐energy‐window‐acquisition mode

et al. 1998

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“…Too large a learning rate can lead to too slow a fitting rate or too large fluctuations in the loss rate but can jump out of the local optimum. Therefore, this paper uses the exponential decay method [11] to dynamically adjust the learning rate, i.e., first using a larger learning rate to make the loss rate drop significantly and then setting a lower learning rate to enable the model to converge more smoothly.…”

Section: Data Sets and Parameter Settingsmentioning

confidence: 99%

Research on the application of OpenPose in escalator safety systems

Zhao

2022

J. Phys.: Conf. Ser.

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This paper describes the application of the OpenPose based human pose detection model in escalator safety systems. The YOLO target detection is used to obtain the position of the human body in the image, and then the human limb information is extracted by OpenPose, and the human joint connection algorithm connects the identified human limb information to obtain the human pose information in the image. The experimental results show that the algorithm can effectively identify the human body posture and can provide timely alarms for dangerous postures, thus improving the safety of escalator riders.

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“…The relation represented by equation (1) is not a function as it is not one-to-one; however, as long as the activity under the camera is less than 1/ β it remains one-to-one and serves as a function. Neither is equation (1) invertible: in order to obtain the activity from the count rate, an iterative algorithm (Sorenson 1975, 1976, Adams and Mena 1988, Zasadny et al 1993, Delpon et al 2002b) is used, valid for static acquisitions, which is based on Newton’s method where each successive approximation of A is obtained from the formula:

A_{n + 1} = A_{n} - \frac{C_{n} - C_{m}}{C_{n}^{'}},

where C m is the measured count rate and the derivative C′ n of equation (1) may be expressed as

C_{n}^{'} = C_{n} (\frac{1}{A_{n}} - β) .

…”

Section: Theorymentioning

confidence: 99%

“…While many studies exist with different methods for dead-time correction in static acquisitions (Sorenson 1975, 1976, Adams and Mena 1988, Zasadny et al 1993, Delpon et al 2002b, Chiesa et al 2009), the problem of varying activity in the detector field of view during acquisition has not been broached. Since the count rate varies as a function of the activity in the field of view, the correction factor during a whole-body scan will depend on the camera head position relative to the anatomical distribution of radioactivity.…”

Section: Introductionmentioning

confidence: 99%

A gamma camera count rate saturation correction method for whole-body planar imaging

Hobbs¹,

Baechler²,

Senthamizhchelvan³

et al. 2010

Phys. Med. Biol.

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Whole-body (WB) planar imaging has long been one of the staple methods of dosimetry, and its quantification has been formalized by the MIRD Committee in pamphlet no 16. One of the issues not specifically addressed in the formalism occurs when the count rates reaching the detector are sufficiently high to result in camera count saturation. Camera dead-time effects have been extensively studied, but all of the developed correction methods assume static acquisitions. However, during WB planar (sweep) imaging, a variable amount of imaged activity exists in the detector's field of view as a function of time and therefore the camera saturation is time dependent. A new time-dependent algorithm was developed to correct for dead-time effects during WB planar acquisitions that accounts for relative motion between detector heads and imaged object. Static camera dead-time parameters were acquired by imaging decaying activity in a phantom and obtaining a saturation curve. Using these parameters, an iterative algorithm akin to Newton's method was developed, which takes into account the variable count rate seen by the detector as a function of time. The algorithm was tested on simulated data as well as on a whole-body scan of high activity Samarium-153 in an ellipsoid phantom. A complete set of parameters from unsaturated phantom data necessary for count rate to activity conversion was also obtained, including build-up and attenuation coefficients, in order to convert corrected count rate values to activity. The algorithm proved successful in accounting for motion-and time-dependent saturation effects in both the simulated and measured data and converged to any desired degree of precision. The clearance half-life calculated from the ellipsoid phantom data was calculated to be 45.1 h after dead-time correction and 51.4 h with no correction; the physical decay half-life of Samarium-153 is 46.3 h. Accurate WB planar dosimetry of high activities relies on successfully compensating for camera saturation which takes into account the variable activity in the field of view, i.e. time-dependent dead-time effects. The algorithm presented here accomplishes this task.

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Testing the count rate performance of the scintillation camera by exponential attenuation: Decaying source; Multiple filters

Cited by 6 publications

References 0 publications

Deadtime correction for two multihead Anger cameras in dual‐energy‐window‐acquisition mode

Deadtime correction for two multihead Anger cameras in dual‐energy‐window‐acquisition mode

Research on the application of OpenPose in escalator safety systems

A gamma camera count rate saturation correction method for whole-body planar imaging

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