A novel algorithm for extracting soft-tissue and bone images measured using a photon-counting type X-ray imaging detector with the help of effective atomic number analysis

Kimoto, Natsumi; Hayashi, Hiroaki; Lee, Cheonghae; Maeda, Tatsuya; Ando, Masahiro; Kanazawa, Yuki; Katsumata, Akitoshi; Yamamoto, S.; Okada, Masahiro

doi:10.1016/j.apradiso.2021.109822

Cited by 14 publications

(16 citation statements)

References 31 publications

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“…Bone mineral density (BMD), which is one of the quantitative information, can be usually measured in the current clinical diagnosis by using dualenergy technique and/or ERPCDs. In the future it is expected that advanced x-ray quantitative diagnoses will be established by using ERPCDs (Hayashi et al 2021, 2021a, 2021b.…”

Section: Introductionmentioning

confidence: 99%

“…In the present study, we evaluated image blurring using an effective atomic number (Z eff ) image as an example. This is because the algorithm to derive several quantitative images that we have proposed calculates an Z eff image as a beginning (Hayashi et al 2021, 2021a, 2021b, so improving the accuracy of the atomic number image will lead to improving the quality of other images. Furthermore, it is expected that the quantitative diagnostic by using Z eff themselves will become widespread in clinical examinations (Al-Buriahi and Tonguc 2020).…”

Section: Introductionmentioning

confidence: 99%

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A blurring correction method suitable to analyze quantitative x-ray images derived from energy-resolving photon counting detector

Kobayashi,

Hayashi,

Nishigami

et al. 2024

Phys. Med. Biol.

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Objective. The purpose of this study is to propose a novel blurring correction method that enables accurate quantitative analysis of the object edge when using energy-resolving photon counting detectors (ERPCDs). Although the ERPCDs have the ability to generate various quantitative analysis techniques, such as the derivations of effective atomic number (Zeff) and bone mineral density (BMD) values, at the object edge in these quantitative images, accurate quantitative information cannot be obtained. This is because image blurring prevents the gathering of accurate primary X-ray attenuation information. Approach. We developed the following procedure for blurring correction. A 5 × 5 pixels masking region was set as the processing area, and the pixels affected by blurring were extracted from the analysis of pixel value distribution. The blurred pixel values were then corrected to the proper values estimated by analyzing minimum and/or maximum values in the set mask area. The suitability of our correction method was verified by a simulation study and an experiment using a prototype ERPCD. Main results. When Zeff image of aluminum objects (Zeff = 13) were analyzed without applying our correction method, regardless of raw data or correction data applying a conventional edge enhancement method, the proper Zeff values could not be derived for the object edge. In contrast, when applying our correction method, 82% of pixels affected by blurring were corrected and the proper Zeff values were calculated for those pixels. As a result of investigating the applicability limits of our method through simulation, it was proven that it works effectively for objects with 4 × 4 pixels or more. Significance. Our method is effective in correcting image blurring when the quantitative image is calculated based on multiple images. It will become an in-demand technology for putting a quantitative diagnosis into actual medical examinations.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A blurring correction method suitable to analyze quantitative x-ray images derived from energy-resolving photon counting detector

Kobayashi,

Hayashi,

Nishigami

et al. 2024

Phys. Med. Biol.

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“…At present, in the study of bone tissue, the emphasis is mainly on the structural analysis of the components of the regeneration using methods such as X-ray examination and survey histological staining (Domenyuk et al, 2018;Kimoto et al, 2021). Such approaches make it possible to assess the qualitative composition of the tissue under study, but do not make it possible to conduct a highly sensitive analysis of individual components of the cellular substance (Eldzharov et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Application of Raman Spectroscopy to Study the Mineralization of Bone Regenerates

Tedeeva¹,

Sataev²,

Batraeva³

et al. 2023

J Biochem Technol

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Assessment of the state of bone tissue during biopsy examination of the material of patients with degenerative or traumatic diseases is a very urgent task of modern medicine. Such an assessment makes it possible to characterize the regenerative processes at the site of the bone defect and to choose the most effective treatment strategies. Currently, in the study of bone tissue, methods of X-ray examination and survey histological staining are used. Such methods do not allow a highly sensitive analysis of individual components of the cellular substance. One approach to solving this problem can be the use of Raman spectroscopy. In contrast to infrared spectroscopy, Raman spectroscopy records in the optical range, which ensures high sensitivity and ease of use. Raman spectroscopy is a non-contact, non-destructive testing method suitable for working with substances in any phase. In this scientific work, a study of the distribution of hydroxyapatite in a section of the regenerative material of the parietal bone of the rat skull is carried out. As a result, it was shown that the Raman spectroscopy method can be used to determine the characteristics of the formation, mineralization, and maturation of bone tissue, to identify loci with maximum and minimum mineralization.

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“…Among them, the effective atomic number Z eff is a practical and promising property that can be obtained by spectral X‐ray imaging. For example, in the field of medical diagnosis and clinical application, the effective atomic number can help to identify organs and lesions, 2 characterize kidney stone, 3 classify non‐calcified coronary plaques, 4 characterize incidental renal mass, 5 quantitative lung perfusion blood volume, 6 and extract soft‐tissue and bone images 7 …”

Section: Introductionmentioning

confidence: 99%

“…For example, in the field of medical diagnosis and clinical application, the effective atomic number can help to identify organs and lesions, 2 characterize kidney stone, 3 classify non-calcified coronary plaques, 4 characterize incidental renal mass, 5 quantitative lung perfusion blood volume, 6 and extract soft-tissue and bone images. 7 There are many references to Z eff 's calculation method and results. [8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26] Spectral X-ray imaging, especially dual-energy X-ray imaging is an effective tool for quantitative analysis of effective atomic number Z eff due to the abundant information acquired by dual-energy X-ray.…”

Section: Introductionmentioning

confidence: 99%

Technical note: Error analysis of material‐decomposition‐based effective atomic number quantification method

Chen,

Ji,

Wang

et al. 2023

Medical Physics

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BackgroundThe effective atomic number (Zeff) is widely applied to the identification of unknown materials. One method to determine the Zeff is material‐decomposition‐based spectral X‐ray imaging. The method relies on certain approximations of the X‐ray interaction cross‐sections such as empirical model coefficients. The impact of such approximations on the accuracy of Zeff quantification has not been fully investigated.PurposeTo perform an error analysis of the material‐decomposition‐based Zeff quantification method and propose a coefficient calibration‐in‐groups method to improve the modeling accuracy and reduce the Zeff quantification error.MethodsThe model of the material‐decomposition‐based Zeff quantification method relies on the dependence of the interaction cross‐sections (σPE) on the atomic number Z and corresponding coefficient, that is, . In this work, all the data is from the National Institute of Standards and Technology (NIST) website. First, the coefficient m is calibrated through a logarithmic fitting method to quickly determine the m values for any certain energy and Zeff ranges. Then materials including elements and common compounds with Zeff ranging from 6–20 are selected as the objects whose effective atomic numbers are to be quantified. Different combinations of basis materials are applied to decompose the object materials and their quantification errors are analyzed. With the help of error analysis, the object materials are divided into high‐error and low‐error groups based on the decomposition coefficient ratio , which is found to have a strong correlation with error, and their coefficients are calibrated in groups. Finally, the average errors of three m selection strategies: (1) using an empirical m value of 3.94, which is also considered a standard method; (2) using a single m value, which is calibrated through the logarithmic fitting method; (3) using different m values calibrated in groups, are calculated to test the effectiveness of our method.ResultsThe approximation of the X‐ray interaction cross‐section leads to certain errors in Zeff quantification and the error distributions for different basis materials are different. The average errors for most basis material combinations (C(6)/Ca(20), C(6)/Al(13), Al(13)/Ca(20), C(6)/Ne(10), Na(11)/P(15)) are lower than 0.5, maintaining good average accuracy. While the average error for S(16)/Ca(20) is up to 0.8461, leading to more misjudgments on atomic number. Meanwhile, the error distribution regularity can be observed. The Pearson's correlation coefficients of absolute errors and decomposition coefficient ratios are 0.743, 0.8432 and 0.7126 for basis material combinations C(6)/Ca(20), C(6)/Al(13) and Al(13)/Ca(20), indicating a good correlation. The method using either empirical m value of 3.94 or single calibrated m value of 4.619 has relatively high average errors. The proposed method using different m values calibrated in groups has the lowest average errors 0.254, 0.203 and 0.169, which are reduced by 21.6%(0.07), 3.8%(0.008) and 62.9%(0.286) respectively compared with the standard method.ConclusionsThe error analysis demonstrates that the approximation of X‐ray interaction cross‐sections leads to inevitable errors, while also revealing certain error distribution regularity. The coefficient calibrated‐in‐groups method has better modeling accuracy and has effectively reduced the error compared with the standard method using a single empirical m value of 3.94.

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A novel algorithm for extracting soft-tissue and bone images measured using a photon-counting type X-ray imaging detector with the help of effective atomic number analysis

Cited by 14 publications

References 31 publications

A blurring correction method suitable to analyze quantitative x-ray images derived from energy-resolving photon counting detector

A blurring correction method suitable to analyze quantitative x-ray images derived from energy-resolving photon counting detector

Application of Raman Spectroscopy to Study the Mineralization of Bone Regenerates

Technical note: Error analysis of material‐decomposition‐based effective atomic number quantification method

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