ERICA: an energy resolving photon counting readout ASIC for X-ray in-line cameras

X-ray imaging is a widely used imaging modality in the medical diagnostic field due to its availability, low cost, high spatial resolution, and fast image acquisition. X-ray photons in standard X-ray sources are polychromatic. Detectors that allow to extract the "color" information of the individual X-rays can lead to contrast enhancement, improved material identification or reduction of beam hardening artifacts at the system level, if we compare them with the widely spread energy integrating detectors. Today, in the field of computed tomography (CT), prototypes of clinical grade systems based on spectral photon counting detectors are currently available for clinical research from different companies. One of the key system components in that development is the X-ray photon detector. This article reviews the photon detection hardware, from the conversion of X-rays into electrical signals to the pulse processing electronics. A review of available photon counting application specific integrated circuits (ASICs) for spectroscopic X-ray imaging is presented with emphasis on the CT medical imaging application.

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“…An overview is presented in [124]. In [97] a fully digital charge sharing correction algorithm is implemented.…”

Section: Correction Algorithmsmentioning

confidence: 99%

Photon Counting Detectors for X-Ray Imaging With Emphasis on CT

Ballabriga

Alozy

Bandi³

et al. 2021

IEEE Trans. Radiat. Plasma Med. Sci.

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“…Some PCD designs aim at event-based real-time processing that corrects for the charge sharing for each event. [18][19][20][21][22][23][24][25][26][27][28][29][30] The key technology is a sophisticated inter-pixel communication to identify coincident events and correct charge sharing for each event in real time. 18,20,21 An analog version of the scheme functions as follows: when a pixel detects an event, it holds onto the analog signal, communicates with neighboring pixels, and if one or more coincident events are detected by the neighboring pixels, it sums the analog signals from the neighboring pixels, identifies the primary incident pixel, and increments a counter of the incident pixel for an energy window that corresponds to the total (corrected) energy.…”

Section: B1 Pcds With Event-based Real-time Charge Sharing Correcmentioning

confidence: 99%

“…As a consequence, the use of the analog charge sharing correction scheme makes PCDs 10 times slower for some circuitries. 18,22 A digital version of the scheme [24][25][26] functions as follows: when a pixel detects an event, it digitizes the charge (i.e., to a candidate count for a candidate energy window), communicates with neighboring pixels, and if one or more coincident candidate counts are found in the neighboring pixels, it identifies the primary incident pixel and energy window, and increment a counter of the incident pixel for the energy window. The energy window is determined based on the candidate energy windows of the candidate counts in the neighboring pixels.…”

Section: B1 Pcds With Event-based Real-time Charge Sharing Correcmentioning

confidence: 99%

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Multi‐energy inter‐pixel coincidence counters for charge sharing correction and compensation in photon counting detectors

Taguchi

2020

Medical Physics

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Purpose: Smaller pixel sizes of x-ray photon counting detectors (PCDs) are advantageous for count rate capabilities but disadvantageous for charge sharing. With charge sharing, the energy of an x-ray photon may be split and one photon may produce two or more counts at adjacent pixels, both at lower energies than the incident energy. This "double-counting" increases noise variance and degrades the spectral response. Overall, it has a significantly negative impact on the performance of PCD-based computed tomography (CT). Charge sharing is induced by the detection physics and occurs regardless of count rates; thus, it is impossible to avoid. We propose in this paper a method that has a potential to address both noise and bias added by charge sharing. Methods: We propose applying a multi-energy inter-pixel coincidence counter (MEICC) technique, which uses energy-dependent coincidence counters, keeps the book of charge sharing events during data acquisition, and provides the exact number of charge sharing occurrences, which can be used to either correct or compensate for them after the acquisition is completed. MEICC does not interfere with the primary counting process; therefore, PCDs with MEICC will remain as fast as those without MEICC. MEICC can be implemented using current electronics technology because its inter-pixel coincidence counters used to handle digital data are rather simple. We evaluated Cram er-Rao lower bound (CRLB) of PCDs with and without MEICC using a Monte Carlo simulation. Results: When the number of energy windows was four or larger and eight neighboring pixels were used, the CRLBs of 225-µm PCD with MEICC normalized by those of the current PCD with the same number of windows were 0.361-0.383 for water density images of two basis functions, which was only 5.7-16.4% worse than those of a PCD without charge sharing (which were at 0.329-0.358). In contrast, the normalized CRLBs of the PCD with one coincidence counter were 0.466-0.499, which were 37.3-45.6% worse than the PCD without charge sharing. The use of eight neighboring pixels provided~10% better CRLB values than four neighboring pixels for MEICC. With four energy windows, decreasing the number of coincidence counters from 16 to 9 only slightly increased the CRLB from 0.255 to 0.269 (which corresponded to as little as a 5.5% change). The normalized CRLBs of MEICC for K-edge imaging (gold) were 0.295-0.426, while those of the one coincidence counter were 0.926-0.959 and the ideal PCDs were 0.126-0.146. Conclusions:The proposed MEICC provides spectral information that can be used to address charge sharing problems in PCDs and is expected to satisfy the requirements for clinical x-ray CT. MEICC is very effective, especially for K-edge imaging, which requires accurate spectral information.

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“…PCDs that handle CS include an event-based real-time CS correction [11][12][13][14][15][16][17][18][19][20][21][22][23][24] or rejection [25][26][27] and a reading-based post-acquisition correction/compensation. [28][29][30][31] The analog version of event-based real-time CS correction 11,15,19 is called analog charge summing scheme (ACS) and the digital version 13,14,19 is called digital count summing scheme (DCS) in this paper.…”

Section: Introductionmentioning

confidence: 99%

Assessment of multi‐energy inter‐pixel coincidence counters for photon‐counting detectors at the presence of charge sharing and pulse pileup: A simulation study

Taguchi

Iwanczyk

2021

Medical Physics

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Purpose Spectral distortion due to charge sharing (CS) and pulse pileup (PP) in photon‐counting detectors (PCDs) degrades the quality of PCD data. We recently proposed multi‐energy inter‐pixel coincidence counters (MEICC) that provided spectral cross‐talk information related to CS. When PP was absent, the normalized Cramér–Rao lower bounds (nCRLBs) of 225‐µm pixel PCDs with MEICC was comparable to those of 450‐µm pixel PCD without MEICC. The aim of this study was to assess the performance of PCDs with MEICC in the presence of both CS and PP using computer simulations. Methods An in‐house Monte Carlo program was modified to incorporate the following four temporal elements: (1) A pulse shape with a pulse duration of 20 ns, (2) delays of up to 10 ns in anode arrival times when photons were incident on pixel boundaries, (3) offsets proportional to a vertical separation between the primary and secondary charge clouds at the rate of ±4 ns per ±100 µm, and (4) a stochastic fluctuation of anode arrival times for all of the charge clouds with a standard deviation of 2 ns. We assessed the performance of five PCDs, (a)–(f), for three spectral tasks, (A)–(C): (a) The conventional PCD, (b) a PCD with MEICC, (c) a PCD with one coincidence counter (1CC), (d) a PCD with a 3 × 3 analog charge summing scheme (ACS), and (e) a PCD with a 3 × 3 digital count summing scheme (DCS); (A) conventional CT imaging with water (i.e., linear attenuation coefficient maps), (B) water–bone material decomposition, and (C) K‐edge imaging with tungsten. The tube current was changed from 1 mA to 1000 mA and the nCRLB was assessed. Results The recorded count rate curves were fitted by the non‐paralyzable detection model with the effective deadtime parameter. The best fit was achieved by 25.8 ns for the conventional PCD, 18.6 ns for MEICC and 1CC, 140.5 ns for ACS, and 209.0 ns for DCS. The nCRLBs were strongly dependent on count rates. MEICC provided the best nCRLBs for all of the imaging tasks over the count rate range investigated except for a few conditions such as K‐edge imaging at 1 mA. PP decreased the merit of MEICC over the conventional PCD in addressing CS. Nonetheless, MEICC consistently provided better nCRLBs than the conventional PCD did. The nCRLBs of MEICC were in the range of 49–58% of those of the conventional PCD for K‐edge imaging, 45–76% for water–bone material decomposition, and 81–88% for the conventional CT imaging (i.e., linear attenuation coefficient maps). ACS provided better nCRLBs than the conventional PCD did only when the effect of PP was minor (e.g., when the counting efficiency of the conventional PCD was higher than 0.95 with the tube current of up to 100 mA). Conclusion Besides a few cases, MEICC provides the best nCRLBs for all of the tasks at all of the count rates. ACS and DCS provide better nCRLBs than the conventional PCD does only when count rates are very low.

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ERICA: an energy resolving photon counting readout ASIC for X-ray in-line cameras

Cited by 6 publications

References 12 publications

Photon Counting Detectors for X-Ray Imaging With Emphasis on CT

Photon Counting Detectors for X-Ray Imaging With Emphasis on CT

Multi‐energy inter‐pixel coincidence counters for charge sharing correction and compensation in photon counting detectors

Assessment of multi‐energy inter‐pixel coincidence counters for photon‐counting detectors at the presence of charge sharing and pulse pileup: A simulation study

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