A multiresolution image reconstruction method in X-ray microCT

Costin, Marius; Lazaro-Ponthus, Delphine; Legoupil, Samuel; Duvauchelle, Philippe; Kaftandjian, Valérie

doi:10.1109/nssmic.2009.5401919

Cited by 5 publications

(6 citation statements)

References 25 publications

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“…22,28,29 Such distortion can be reduced by a multitude of interior reconstruction algorithms 22,[29][30][31][32][33][34][35][36][37] -the most common of which are the projection completion techniques based methods. 18,38 For interior micro-CT with detector offset, there are two types of truncation.…”

Section: Discussionmentioning

confidence: 99%

“…Object boundary can be acquired from external physical measurements, a low-resolution global scan, 28 or optical measurements by a time-of-flight camera. 39 Approximately accurate knowledge of the object boundary has been shown to significantly reduce the truncation errors.…”

Section: Discussionmentioning

confidence: 99%

“…The cosine-extrapolation was selected because of its ease of use and computational simplicity. Note that other methods 22,27,28,32 can be used to achieve even higher accuracy in the projection completion.…”

Section: Discussionmentioning

confidence: 99%

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Interior micro‐CT with an offset detector

et al. 2014

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Purpose:The size of field-of-view (FOV) of a microcomputed tomography (CT) system can be increased by offsetting the detector. The increased FOV is beneficial in many applications. All prior investigations, however, have been focused to the case in which the increased FOV after offset-detector acquisition can cover the transaxial extent of an object fully. Here, the authors studied a new problem where the FOV of a micro-CT system, although increased after offset-detector acquisition, still covers an interior region-of-interest (ROI) within the object. Methods: An interior-ROI-oriented micro-CT scan with an offset detector poses a difficult reconstruction problem, which is caused by both detector offset and projection truncation. Using the projection completion techniques, the authors first extended three previous reconstruction methods from offset-detector micro-CT to offset-detector interior micro-CT. The authors then proposed a novel method which combines two of the extended methods using a frequency split technique. The authors tested the four methods with phantom simulations at 9.4%, 18.8%, 28.2%, and 37.6% detector offset. The authors also applied these methods to physical phantom datasets acquired at the same amounts of detector offset from a customized micro-CT system. Results: When the detector offset was small, all reconstruction methods showed good image quality. At large detector offset, the three extended methods gave either visible shading artifacts or high deviation of pixel value, while the authors' proposed method demonstrated no visible artifacts and minimal deviation of pixel value in both the numerical simulations and physical experiments. Conclusions: For an interior micro-CT with an offset detector, the three extended reconstruction methods can perform well at a small detector offset but show strong artifacts at a large detector offset. When the detector offset is large, the authors' proposed reconstruction method can outperform the three extended reconstruction methods by suppressing artifacts and maintaining pixel values.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Interior micro‐CT with an offset detector

et al. 2014

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“…Such research has been commonly named as Wavelet-based local reconstruction, and has been reported to be useful in other application areas such as Nano and Micro Tomography [6], [7]; Terahertz Tomography [8], and Dental Radiology [9].…”

Section: Introductionmentioning

confidence: 99%

Tiled-Block Image Reconstruction by Wavelet- Based, Parallel-Filtered Back-Projection

Escobedo

Ozanyan

2016

IEEE Sensors J.

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Abstract-We demonstrate an algorithm, relevant to tomography sensor systems, to obtain images from the parallel reconstruction of essentially localized elements at different scales. This is achieved by combining methodology to reconstruct images from limited and/or truncated data, with the time-frequency capabilities of the Wavelet Transform. Multi-scale, as well as time-frequency, localization properties of the separable twodimensional wavelet transform are exploited as an approach for faster reconstruction. The speed up is realized not only by reducing the computation load on a single processor, but also by achieving the parallel reconstruction of several tiled blocks. With tiled-block image reconstruction by wavelet-based, parallel filtered back-projection we measure more than 36 times gain in speed, compared to standard filtered back-projection.Index Terms-image reconstruction, computed tomography, data processing algorithms, parallel processing, wavelet transform. I. INTRODUCTIONCROSS many applications, it is common to identify the need of information about an object, without altering its physical structure. Fortunately, there are numerous methods allowing radiation, either emitted or transmitted, to be employed to obtain cross-sectional images characterizing the inner structure of an object. The mathematical foundation behind such an approach was developed by Johann Radon in 1917 [1] and several decades later, in 1972, experimentally implemented by Hounsfield [2] resulting in the demonstration of the first Computed Tomography (CT) scanner.The main motivation for this work was the existing body of knowledge and achievements on the reconstruction of reduced-area full-resolution images, originally encouraged by the radiation dose exposure reduction in medical imaging and where the Wavelet Transform (WT), along its different representations, proved to be an effective tool given its timefrequency localization capabilities [4], [5]. Such research has been commonly named as Wavelet-based local reconstruction, and has been reported to be useful in other application areas such as Nano and Micro Tomography [6], [7]; Terahertz Tomography [8], and Dental Radiology [9].Of special interest is the 2D fast wavelet transform (2D FWT), employed in [5] and [10]. In addition to achieving local Manuscript received October 15, 2015. Jorge Guevara Escobedo (jorge.guevaraescobedo@manchester.ac.uk) and Krikor B. Ozanyan (k.ozanyan@manchester.ac.uk) are with the School of Electrical and Electronic Engineering, The University of Manchester, M13 9PL, Manchester, UK. JGE wishes to acknowledge the financial support of Consejo Nacional de Ciencia y Tecnología (CONACyT), Mexico, for a doctoral studentship.reconstruction, it allows projection data to be processed in a multi-resolution scheme. Such a feature proves to be of great benefit, when realizing its similarities with the parallel algorithm proposed in [11]. In that algorithm, a frequential decomposition of projection data is performed with the aim to back-project every componen...

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“…Diagnosis is commonly achieved by intravenous urography (IVU), retrograde pyelography, and CT or MRI scans (Table 1) [7]. Recently novel procedures, such as multi-resolution image reconstruction or X-ray micro-diffraction, play an important role as non-invasive imaging techniques in the diagnosis of UFP [8][9][10]. Final diagnosis of UFP is based on pathologic evidence from endoscopic biopsy specimens.…”

Section: Introductionmentioning

confidence: 99%

Imaging diagnosis and endoscopic treatment for ureteral fibroepithelial polyp prolapsing into the bladder

Zhang

et al. 2013

Journal of X-Ray Science and Technology

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OBJECTIVE: Fibroepithelial polyps of ureter prolapsing into the bladder are a rare urological condition. We report the imaging findings and our experience with endoscopic treatment for ureteral fibroepithelial polyps prolapsing into the bladder. PATIENTS AND RESULTS: Four patients with frank pain and hematuria were enrolled. Intravenous urography and computed tomography revealed a ureteral mass with filling defects in affected ureter and mild hydronephrosis. Endoscopic examination showed ureteral polyps prolapsing in the bladder. The histopathologic diagnosis on 4 cases was benign fibroepithelial polyps of ureter. The largest polyps (from 4-10 cm in length) were successfully resected and vaporized by Holmium: YAG laser. A double-pigtail ureteral stent at 7F was placed and left for 6 weeks after the procedure. Neither recurrence nor ureter stricture was observed after up to 12 years of follow-up. CONCLUSIONS: Ureteral malignancy must be excluded in cases where a ureteral mass is detected. Endoscopic management is recommended to minimize morbidity and complications in treatment of ureteral fibroepithelial polyps that prolapse into the bladder.

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A multiresolution image reconstruction method in X-ray microCT

Cited by 5 publications

References 25 publications

Interior micro‐CT with an offset detector

Interior micro‐CT with an offset detector

Tiled-Block Image Reconstruction by Wavelet- Based, Parallel-Filtered Back-Projection

Imaging diagnosis and endoscopic treatment for ureteral fibroepithelial polyp prolapsing into the bladder

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