A novel non-linear recursive filter design for extracting high rate pulse features in nuclear medicine imaging and spectroscopy

Sajedi, Salar; Asl, Alireza Kamal; Ay, Mohammad Reza; Farahani, Mohammad Hossein Davood Abadi; Rahmim, Arman

doi:10.1016/j.medengphy.2012.08.003

Cited by 12 publications

(4 citation statements)

References 24 publications

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“…4. The accuracy of the deconvolution, which is limited in the presence of noise, can be improved using non-linear corrections [25]. This task is thus suitable for an ANN.…”

Section: Neural Network For Waveform Processingmentioning

confidence: 99%

Smart sensors using artificial intelligence for on-detector electronics and ASICs

Carini¹,

Deptuch²,

Dickinson³

et al. 2022

Preprint

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Cutting edge detectors push sensing technology by further improving spatial and temporal resolution, increasing detector area and volume, and generally reducing backgrounds and noise. This has led to a explosion of more and more data being generated in next-generation experiments. Therefore, the need for nearsensor, at the data source, processing with more powerful algorithms is becoming increasingly important to more efficiently capture the right experimental data, reduce downstream system complexity, and enable faster and lower-power feedback loops. In this paper, we discuss the motivations and potential applications for on-detector AI. Furthermore, the unique requirements of particle physics can uniquely drive the development of novel AI hardware and design tools. We describe existing modern work for particle physics in this area. Finally, we outline a number of areas of opportunity where we can advance machine learning techniques, codesign workflows, and future microelectronics technologies which will accelerate design, performance, and implementations for next generation experiments.

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“…4. The accuracy of the deconvolution, which is limited in the presence of noise, can be improved using non-linear corrections [25]. This task is thus suitable for an ANN.…”

Section: Neural Network For Waveform Processingmentioning

confidence: 99%

Smart sensors using artificial intelligence for on-detector electronics and ASICs

Carini¹,

Deptuch²,

Dickinson³

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…Sajedi S. et al [5] proposed an FPGA-based non-linear recursive filter design for high-rate pulse feature extraction in nuclear medicine imaging and spectroscopy. Real data were obtained directly from the pre-amplifier of the detection system.…”

Section: Related Workmentioning

confidence: 99%

“…A significant source of noise is the detector itself, as it is at the beginning of the amplification chain. Although an important noise reduction can be obtained by cooling the detector [3,4], it is still crucial to perform optimal filtering to improve the signal-to-noise ratio (SNR) for high-resolution spectroscopy [5]. Focusing on the latter strategy, an optimal DPP must also be able to efficiently deal with high pulse rates.…”

Section: Introductionmentioning

confidence: 99%

Data Analysis and Filter Optimization for Pulse-Amplitude Measurement: A Case Study on High-Resolution X-ray Spectroscopy

Mannatunga

Valinoti

Samayoa

et al. 2022

Sensors

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In this study, we present a procedure to optimize a set of finite impulse response filter (FIR) coefficients for digital pulse-amplitude measurement. Such an optimized filter is designed using an adapted digital penalized least mean square (DPLMS) method. The effectiveness of the procedure is demonstrated using a dataset from a case study on high-resolution X-ray spectroscopy based on single-photon detection and energy measurements. The energy resolutions of the Kα and Kβ lines of the Manganese energy spectrum have been improved by approximately 20%, compared to the reference values obtained by fitting individual photon pulses with the corresponding mathematical model.

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“…Achievement of optimum quality images depends upon many factors, e.g. accurate processing of the image raw data [11]. SPECT data processing or reconstruction of images employs the filtration of noisy signals which is one of the main problems that this imaging modality inherits.…”

Section: Introductionmentioning

confidence: 99%

Effect of Cut-Off Frequency of Butterworth Filter on Detectability and Contrast of Hot and Cold Regions in Tc-99m SPECT

Sayed¹,

Nasrudin²

2016

IJMPCERO

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In SPECT, noise is one of the major limitations that degrade image quality. To suppress the noisy signals in an image, digital filters are most commonly applied. However, in SPECT image reconstruction, selection of an appropriate filter and its functions has always remained a difficult task. In this work an attempt was made to investigate the effects of varying cut-off frequencies and in keeping the order of Butterworth filter constant on detectability and contrast of hot and cold regions images. A new insert simulating hot and cold regions which provides similar views in a reconstructed image was placed in the phantom's cylindrical source tank and imaged. Tc-99m radionuclide was distributed uniformly in the phantom. SPECT data were collected in a 20% energy window centered at 140 keV by a Philips ADAC Forte dual head gamma camera mounted with a LEHR collimator. Images were generated by using the filtered backprojection technique. A Butterworth filter of order 5 with cut-off frequencies 0.35 and 0.45 cycles•cm −1 was applied. Images were examined in terms of hot and cold regions, detectability and contrast. Results show that the hot and cold regions' detectability and contrast vary with the change of cut-off frequency. With a 0.45 cycles•cm −1 cut-off frequency, a significant enhancement in contrast of cold regions was achieved as compared to a 0.35 cycles•cm −1 cut-off frequency. Furthermore, the detectability of hot and cold regions improved with the use of a 0.45 cycles•cm −1 cut-off frequency. In conclusion, image quality of hot and cold regions affected in a different way with a change of cut-off frequency. Thus, care should be taken in selecting the filter cut-off frequency prior to reconstruction of images; particularly, when both types of regions are expected in the reconstructed image.

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A novel non-linear recursive filter design for extracting high rate pulse features in nuclear medicine imaging and spectroscopy

Cited by 12 publications

References 24 publications

Smart sensors using artificial intelligence for on-detector electronics and ASICs

Smart sensors using artificial intelligence for on-detector electronics and ASICs

Data Analysis and Filter Optimization for Pulse-Amplitude Measurement: A Case Study on High-Resolution X-ray Spectroscopy

Effect of Cut-Off Frequency of Butterworth Filter on Detectability and Contrast of Hot and Cold Regions in Tc-99m SPECT

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