Impacts of photon counting detector to cerebral CT angiography maximum intensity projection (MIP) images

Harvey, Evan; Feng, Mang; Ji, Xu; Zhang, Ran; Chen, Guang-Hong; Li, Ké

doi:10.1117/12.2513205

Cited by 1 publication

(1 citation statement)

References 6 publications

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“…Due to the photon energy discriminating, electronic noise rejecting, and direct conversion features of photon counting detectors (PCDs), PCD-based computed tomography (PCD-CT) has the potential of improving the non-spectral imaging performance of conventional CT (da Silva et al 2019, Ferrero et al 2018, Gutjahr et al 2016, Harvey et al 2019, Marcus et al 2018, Pourmorteza et al 2016, Shikhaliev et al 2005, Shikhaliev 2008, Symons et al 2017a, Taguchi and Iwanczyk 2013, Taguchi 2017, Willemink et al 2018, Yu et al 2015, 2016 while providing perfectly registered spectral information for every clinical CT scan (Amato et al 2020, Badea et al 2019, Danielsson et al 2020, Fredette et al 2019, Lee et al 2016, Nakada et al 2015, Persson et al 2014, Roessl and Proksa 2007, Roessl et al 2011, Schmidt 2009, Shikhaliev 2008, Sisniega et al 2015, Symons et al 2017a This work aims at providing a publicly available artifact correction method for researchers and other users of PCD-CT that do not have access to the proprietary algorithms or the capability of upgrading their existing PCD hardware. Except for some low-cost acrylic and aluminum sheets, the proposed method does not require any other dedicated apparatus to work.…”

Section: Introductionmentioning

confidence: 99%

An experimental method to correct low-frequency concentric artifacts in photon counting CT

Feng¹,

Ji²,

Zhang³

et al. 2021

Phys. Med. Biol.

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Large-area photon counting detectors (PCDs) are usually built by tiling multiple semiconductor panels that often have slightly different spectral responses to input x-rays. As a result of this spectral inconsistency, experimental PCD-CT images of large, human-sized objects may show high-frequency ring artifacts and low-frequency band artifacts. Due to the much larger width of the bands compared with the rings, the concentric artifact problem in PCD-CT images of human-sized objects cannot be adequately addressed by conventional CT ring correction methods. This work presents an experimental method to correct the concentric artifacts in PCD-CT. The method is applicable to not only energy-discriminating PCDs with multiple bins but also PCDs with only a single threshold controller. Its principle is similar to the two-step beam hardening correction method, except that the proposed method uses pixel-specific polynomial functions to address the spectral inconsistency problem across the detector plane. The pixel-specific polynomial coefficients were experimentally calibrated using 15 acrylic sheets and 6 aluminum sheets of known thicknesses. The pixel-specific polynomial functions were used to convert the measured PCD-CT projection data to acrylic- and aluminum-equivalent thicknesses that are energy-independent. The proposed method was experimentally evaluated using a human cadaver head and multiple physical phantoms: two of them contain iodine and one phantom contains dual K-edge contrast materials (gadolinium and iodine). The results show that the proposed method can effectively remove the low-frequency concentric artifacts in PCD-CT images while reducing beam hardening artifacts. In contrast, the conventional CT ring correction algorithm did not adequately address the low-frequency band artifacts. Compared with the direct material decomposition-based correction method, the proposed method not only relaxes the requirement of multi-energy bins but also generates images with lower noise and fewer concentric artifacts.

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