Time separation technique: Accurate solution for 4D C‐Arm‐CT perfusion imaging using a temporal decomposition model

Bannasch, Sebastian; Frysch, Robert; Pfeiffer, Tim; Warnecke, Gerald; Rose, Georg

doi:10.1002/mp.12768

Cited by 11 publications

(21 citation statements)

References 23 publications

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“…It uses static reconstructions of FDCT projection data from individual sweeps. The second method, Time Separation Technique is an advanced model-based approach to FDCTP reconstruction, see [17].…”

Section: Time Attenuation Curves Estimation For Fdctp Datamentioning

confidence: 99%

“…For all reconstructions in this paper, an algebraic CT reconstruction technique, namely the CGLS method, implemented in an open source package at https://github.com/kulvait/kct_cbct/ was used, see [31]. Perfusion processing with algebraic reconstruction generates less noisy results compared to analytical reconstruction, see [17].…”

Section: Time Attenuation Curves Estimation For Fdctp Datamentioning

confidence: 99%

“…The straightforward approach violates the model ( 2) when performing reconstructions. Model based approaches, see [12,13,17], assume that TACs can be modeled as a linear combination of a set of K temporal functions. Under this assumption, the model ( 2) can be applied to the resulting data without further approximations.…”

Section: Time Separation Technique and Trigonometric Basismentioning

confidence: 99%

“…However, when compared with CTP, FDCTP suffers from higher noise-level, lower frame rate and slower rotation speed. To overcome these drawbacks, there is an ongoing effort to improve FDCTP processing algorithms, see [12,13,14,15,16,17,18]. Time separation technique (TST) is a promising technique to compensate high level of noise, slow rotation speed and produce highly reliable perfusion maps, see [17].…”

Section: Introductionmentioning

confidence: 99%

“…To overcome these drawbacks, there is an ongoing effort to improve FDCTP processing algorithms, see [12,13,14,15,16,17,18]. Time separation technique (TST) is a promising technique to compensate high level of noise, slow rotation speed and produce highly reliable perfusion maps, see [17]. However, studies on real-world perfusion data using TST are still scarce.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

A novel use of time separation technique to improve flat detector CT perfusion imaging in stroke patients

Kulvait,

Hoelter,

Frysch

et al. 2021

Preprint

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Dynamic perfusion imaging is routinely used in the diagnostic workup of acute ischemic stroke (AIS). At present, perfusion imaging can also be performed within the angio suite using flat detector computed tomography (FDCT). However, higher noise level, slower rotation speed and lower frame rate need to be considered in FDCT perfusion (FDCTP) data processing algorithms. The Time Separation Technique (TST) is a model-based perfusion data reconstruction method developed to solve these problems. In this contribution, we used TST and dimension reduction, where we approximate the time attenuation curves by a linear combination of trigonometric functions.Our goal was to show that TST with this data reduction does not impair clinical perfusion measurements. We performed a realistic simulation of FDCTP acquisition based on CT perfusion (CTP) data. Using these FDCTP data, we showed that TST provides better results than classical straightforward processing. Moreover we found that TST is robust to additional noise. Furthermore, we achieved a total processing time from reconstruction of FDCTP data to generation of perfusion maps of under 5 minutes. Perfusion maps created using TST with a trigonometric basis from FDCTP data show equivalent perfusion deficits as CT perfusion maps. Therefore, this technique can be considered a fast reliable tool for FDCTP imaging in AIS.

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Section: Time Attenuation Curves Estimation For Fdctp Datamentioning

confidence: 99%

Section: Time Attenuation Curves Estimation For Fdctp Datamentioning

confidence: 99%

Section: Time Separation Technique and Trigonometric Basismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A novel use of time separation technique to improve flat detector CT perfusion imaging in stroke patients

Kulvait,

Hoelter,

Frysch

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

A novel use of time separation technique to improve flat detector CT perfusion imaging in stroke patients

et al. 2022

Self Cite

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Background: CT perfusion imaging (CTP) is used in the diagnostic workup of acute ischemic stroke (AIS). CTP may be performed within the angio suite using flat detector CT (FDCT) to help reduce patient management time. Purpose: In order to significantly improve FDCT perfusion (FDCTP) imaging, data-processing algorithms need to be able to compensate for the higher levels of noise, slow rotation speed, and a lower frame rate of current FDCT devices. Methods: We performed a realistic simulation of FDCTP acquisition based on CTP data from seven subjects. We used the time separation technique (TST) as a model-based approach for FDCTP data processing. We propose a novel dimension reduction in which we approximate the time attenuation curves by a linear combination of trigonometric functions. Our goal was to show that the TST can be used even without prior assumptions on the shape of the attenuation profiles. Results:We first demonstrated that a trigonometric basis is suitable for dimension reduction of perfusion data. Using simulated FDCTP data, we have shown that a trigonometric basis in the TST provided better results than the classical straightforward processing even with additional noise. Average correlation coefficients of perfusion maps were improved for cerebral blood flow (CBF), cerebral blood volume, mean transit time (MTT) maps. In a moderate noise scenario, the average Pearson's coefficient for the CBF map was improved using the TST from 0.76 to 0.81. For the MTT map, it was improved from 0.37 to 0.45. Furthermore, we achieved a total processing time from the reconstruction of FDCTP data to the generation of perfusion maps of under 5 min. Conclusions: In our study cohort, perfusion maps created from FDCTP data using the TST with a trigonometric basis showed equivalent perfusion deficits to classic CT perfusion maps. It follows, that this novel FDCTP technique has potential to provide fast and accurate FDCTP imaging for AIS patients.

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Liver segmentation using Turbolift learning for CT and cone-beam C-arm perfusion imaging

Haseljić

Chatterjee

Frysch

et al. 2023

Computers in Biology and Medicine

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Time separation technique: Accurate solution for 4D C‐Arm‐CT perfusion imaging using a temporal decomposition model

Cited by 11 publications

References 23 publications

A novel use of time separation technique to improve flat detector CT perfusion imaging in stroke patients

A novel use of time separation technique to improve flat detector CT perfusion imaging in stroke patients

A novel use of time separation technique to improve flat detector CT perfusion imaging in stroke patients

Liver segmentation using Turbolift learning for CT and cone-beam C-arm perfusion imaging

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