Literature DB >> 28248652

Simultaneous deblurring and iterative reconstruction of CBCT for image guided brain radiosurgery.

SayedMasoud Hashemi1, William Y Song, Arjun Sahgal, Young Lee, Christopher Huynh, Vladimir Grouza, Håkan Nordström, Markus Eriksson, Antoine Dorenlot, Jean Marie Régis, James G Mainprize, Mark Ruschin.   

Abstract

One of the limiting factors in cone-beam CT (CBCT) image quality is system blur, caused by detector response, x-ray source focal spot size, azimuthal blurring, and reconstruction algorithm. In this work, we develop a novel iterative reconstruction algorithm that improves spatial resolution by explicitly accounting for image unsharpness caused by different factors in the reconstruction formulation. While the model-based iterative reconstruction techniques use prior information about the detector response and x-ray source, our proposed technique uses a simple measurable blurring model. In our reconstruction algorithm, denoted as simultaneous deblurring and iterative reconstruction (SDIR), the blur kernel can be estimated using the modulation transfer function (MTF) slice of the CatPhan phantom or any other MTF phantom, such as wire phantoms. The proposed image reconstruction formulation includes two regularization terms: (1) total variation (TV) and (2) nonlocal regularization, solved with a split Bregman augmented Lagrangian iterative method. The SDIR formulation preserves edges, eases the parameter adjustments to achieve both high spatial resolution and low noise variances, and reduces the staircase effect caused by regular TV-penalized iterative algorithms. The proposed algorithm is optimized for a point-of-care head CBCT unit for image-guided radiosurgery and is tested with CatPhan phantom, an anthropomorphic head phantom, and 6 clinical brain stereotactic radiosurgery cases. Our experiments indicate that SDIR outperforms the conventional filtered back projection and TV penalized simultaneous algebraic reconstruction technique methods (represented by adaptive steepest-descent POCS algorithm, ASD-POCS) in terms of MTF and line pair resolution, and retains the favorable properties of the standard TV-based iterative reconstruction algorithms in improving the contrast and reducing the reconstruction artifacts. It improves the visibility of the high contrast details in bony areas and the brain soft-tissue. For example, the results show the ventricles and some brain folds become visible in SDIR reconstructed images and the contrast of the visible lesions is effectively improved. The line-pair resolution was improved from 12 line-pair/cm in FBP to 14 line-pair/cm in SDIR. Adjusting the parameters of the ASD-POCS to achieve 14 line-pair/cm caused the noise variance to be higher than the SDIR. Using these parameters for ASD-POCS, the MTF of FBP and ASD-POCS were very close and equal to 0.7 mm-1 which was increased to 1.2 mm-1 by SDIR, at half maximum.

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Year:  2017        PMID: 28248652     DOI: 10.1088/1361-6560/aa5ed2

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  5 in total

1.  Accelerated Stimulated Raman Projection Tomography by Sparse Reconstruction From Sparse-View Data.

Authors:  Xueli Chen; Shouping Zhu; Huiyuan Wang; Cuiping Bao; Defu Yang; Chi Zhang; Peng Lin; Ji-Xin Cheng; Yonghua Zhan; Jimin Liang; Jie Tian
Journal:  IEEE Trans Biomed Eng       Date:  2019-08-14       Impact factor: 4.538

2.  Statistical Iterative CBCT Reconstruction Based on Neural Network.

Authors:  Binbin Chen; Kai Xiang; Zaiwen Gong; Jing Wang; Shan Tan
Journal:  IEEE Trans Med Imaging       Date:  2018-06       Impact factor: 10.048

3.  Blind deconvolution in model-based iterative reconstruction for CT using a normalized sparsity measure.

Authors:  Lorenz Hehn; Steven Tilley; Franz Pfeiffer; J Webster Stayman
Journal:  Phys Med Biol       Date:  2019-10-31       Impact factor: 3.609

4.  Low-Dose CBCT Reconstruction Using Hessian Schatten Penalties.

Authors:  Liang Liu; Xinxin Li; Kai Xiang; Jing Wang; Shan Tan
Journal:  IEEE Trans Med Imaging       Date:  2017-12       Impact factor: 10.048

5.  Cone-Beam CT image contrast and attenuation-map linearity improvement (CALI) for brain stereotactic radiosurgery procedures.

Authors:  SayedMasoud Hashemi; Christopher Huynh; Arjun Sahgal; William Y Song; Håkan Nordström; Markus Eriksson; James G Mainprize; Young Lee; Mark Ruschin
Journal:  J Appl Clin Med Phys       Date:  2018-10-19       Impact factor: 2.102

  5 in total

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