Technical Note: FreeCT_wFBP: A robust, efficient, open‐source implementation of weighted filtered backprojection for helical, fan‐beam CT

Hoffman, John M.; Young, Stefano; Noo, Frédéric; McNitt-Gray, Michael F.

doi:10.1118/1.4941953

Cited by 31 publications

(43 citation statements)

References 37 publications

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“…for diagram of the workflow). Step (1) was implemented using a modified version of freely available, open‐source weighted filtered backprojection (FBP) for CT, FreeCT_wFBP …”

Section: Methodsmentioning

confidence: 99%

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Low‐dose CT perfusion with projection view sharing

et al. 2017

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Purpose: CT Perfusion (CTP) is a widely used clinical imaging modality. However, CTP typically involves the use of substantial radiation dose (CTDI vol ≥~200 mGy). The purpose of this study is to present a low-dose CTP technique using a projection view-sharing reconstruction algorithm originally developed for dynamic MRI -"K-space Weighted Image Contrast" (KWIC). Methods: The KWIC reconstruction is based on an angle-bisection scheme. In KWIC, a Fourier transform was performed along each projection to form a "k-space"-like CT data space, based on the central-slice theorem. As a projection view-sharing technique, KWIC preserves the spatiotemporal resolution of undersampled CTP data by progressively increasing the number of projection views shared for more distant regions of "k-space". KWIC reconstruction was evaluated on a digital FOR-BILD head phantom with numerically simulated time-varying objects. The numerically simulated scans were undersampled using the angle-bisection scheme to achieve 50%, 25%, and 12.5% of the original dose (288, 144, and 72 projections, respectively). The area-under-the-curve (AUC), time-topeak (TTP), and full width half maximum (FWHM) were measured in KWIC recons and compared to fully sampled filtered back projection (FBP) reconstructions. KWIC reconstruction and dose reduction was also implemented for three clinical CTP cases (45 s, 1156 projections per turn, 1 s/ turn, CTDI vol 217 mGy). Quantitative perfusion metrics were computed and compared between KWIC reconstructed CTP data and those of standard FBP reconstruction. Results: The AUC, TTP, and FWHM in the numerical simzulations were unaffected by the undersampling/dose reduction (down to 12.5% dose) with KWIC reconstruction compared to the fully sampled FBP reconstruction. The normalized root-mean-square-error (NRMSE) of the AUC in the FORBILD head phantom is 0.04, 0.05, and 0.07 for 50%, 25%, and 12.5% KWIC, respectively, as compared to FBP reconstruction. The cerebral blood flow (CBF) and cerebral blood volume had no significant difference between FBP and 50%, 25%, and 12.5% KWIC reconstructions (P > 0.05). Conclusions: This study demonstrates that KWIC preserves perfusion metrics for CTP with substantially reduced dose. Clinical implementation will require further investigation into methods of rapid switching of a CT x-ray source.

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“…for diagram of the workflow). Step (1) was implemented using a modified version of freely available, open‐source weighted filtered backprojection (FBP) for CT, FreeCT_wFBP …”

Section: Methodsmentioning

confidence: 99%

“…To achieve the correct geometry, rebinning algorithms originally developed for helical reconstruction were applied to the projection data, transforming the fan‐beam data into “pseudo‐parallel” data . The rebinning portion of the FreeCT_wFBP reconstruction software was utilized to accomplish this …”

Section: Theorymentioning

confidence: 99%

Low‐dose CT perfusion with projection view sharing

et al. 2017

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“…Reconstruction of the raw data is performed next to create the desired image datasets. In the current pipeline, FreeCT_wFBP is utilized to perform the desired reconstructions, which can include variations of reconstructed slice thickness and reconstruction kernel.…”

Section: Pipeline Design and Implementationmentioning

confidence: 98%

“…Full details can be found on the Github page, however in brief this means that users are free to copy, distribute, and modify the software provided changes are identified and dated in the source code and any modifications are made freely available under the same license. The reconstruction software has also previously been made freely available . At present, the code for the calibrated noise addition and the analysis modules (segmentation, internal data format conversion, etc.)…”

Section: Pipeline Design and Implementationmentioning

confidence: 98%

“…Additionally, they are likely to be tied to proprietary data formats which prevent the possibility of simulation studies, which are often of interest to the reconstruction and quantitative imaging community. In a previous technical note, free, open‐source weighted filtered backprojection reconstruction software for diagnostic CT was released, which allows the offline reconstruction of clinical datasets, effectively enabling researchers to build their own “recon boxes” using a published, clinically similar reconstruction method.…”

Section: Introductionmentioning

confidence: 99%

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Technical Note: Design and implementation of a high‐throughput pipeline for reconstruction and quantitative analysis of CT image data

et al. 2019

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Purpose With recent substantial improvements in modern computing, interest in quantitative imaging with CT has seen a dramatic increase. As a result, the need to both create and analyze large, high‐quality datasets of clinical studies has increased as well. At present, no efficient, widely available method exists to accomplish this. The purpose of this technical note is to describe an open‐source high‐throughput computational pipeline framework for the reconstruction and analysis of diagnostic CT imaging data to conduct large‐scale quantitative imaging studies and to accelerate and improve quantitative imaging research. Methods The pipeline consists of two, primary “blocks”: reconstruction and analysis. Reconstruction is carried out via a graphics processing unit (GPU) queuing framework developed specifically for the pipeline that allows a dataset to be reconstructed using a variety of different parameter configurations such as slice thickness, reconstruction kernel, and simulated acquisition dose. The analysis portion then automatically analyzes the output of the reconstruction using “modules” that can be combined in various ways to conduct different experiments. Acceleration of analysis is achieved using cluster processing. Efficiency and performance of the pipeline are demonstrated using an example 142 subject lung screening cohort reconstructed 36 different ways and analyzed using quantitative emphysema scoring techniques. Results The pipeline reconstructed and analyzed the 5112 reconstructed datasets in approximately 10 days, a roughly 72× speedup over previous efforts using the scanner for reconstructions. Tightly coupled pipeline quality assurance software ensured proper performance of analysis modules with regard to segmentation and emphysema scoring. Conclusions The pipeline greatly reduced the time from experiment conception to quantitative results. The modular design of the pipeline allows the high‐throughput framework to be utilized for other future experiments into different quantitative imaging techniques. Future applications of the pipeline being explored are robustness testing of quantitative imaging metrics, data generation for deep learning, and use as a test platform for image‐processing techniques to improve clinical quantitative imaging.

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Technical Note: FreeCT_ICD: An open‐source implementation of a model‐based iterative reconstruction method using coordinate descent optimization for CT imaging investigations

et al. 2018

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FreeCT_ICD is an open-source implementation of a model-based iterative reconstruction method that extends the capabilities of previously released open-source reconstruction software and provides the ability to perform vendor-independent reconstructions of clinically acquired raw projection data. This implementation represents a reasonable tradeoff between storage and computational requirements and has demonstrated acceptable image quality in both simulated and clinical image datasets.

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Technical Note: FreeCT_wFBP: A robust, efficient, open‐source implementation of weighted filtered backprojection for helical, fan‐beam CT

Abstract: FreeCT_wFBP is a fast, highly configurable reconstruction package for third-generation CT available under the GNU GPL. It shows good performance with both clinical and simulated data.

Cited by 31 publications

References 37 publications

Low‐dose CT perfusion with projection view sharing

Low‐dose CT perfusion with projection view sharing

Technical Note: Design and implementation of a high‐throughput pipeline for reconstruction and quantitative analysis of CT image data

Technical Note: FreeCT_ICD: An open‐source implementation of a model‐based iterative reconstruction method using coordinate descent optimization for CT imaging investigations

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