Literature DB >> 23591468

Motion correction for MR cystography by an image processing approach.

Qin Lin1, Zhengrong Liang, Chaijie Duan, Jianhua Ma, Haifang Li, Clement Roque, Jie Yang, Guangxiang Zhang, Hongbing Lu, Xiaohai He.   

Abstract

Magnetic resonance (MR) cystography or MR-based virtual cystoscopy is a promising new technology to evaluate the entire bladder in a fully noninvasive manner. It requires the anatomical bladder images be acquired at high spatial resolution and with adequate signal-to-noise ratio (SNR). This often leads to a long-time scan (>5 min) and results in image artifacts due to involuntary bladder motion and deformation. In this paper, we investigated an image-processing approach to mitigate the problem of motion and deformation. Instead of a traditional single long-time scan, six repeated short-time scans (each of approximately 1 min) were acquired for the purpose of shifting bladder motion from intrascan into interscans. Then, the interscan motions were addressed by registering the short-time scans to a selected reference and finally forming a single average motion-corrected image. To evaluate the presented approach, three types of images were generated: 1) the motion-corrected image by registration and average of the short-time scans; 2) the directly averaged image of the short-time scans (without motion correction); and 3) the single image of the corresponding long-time scan. Six experts were asked to blindly score these images in terms of two important aspects: 1) the definition of the bladder wall and 2) the overall expression on the image quality. Statistical analysis on the scores suggested that the best result in both the aspects is achieved by the presented motion-corrected average. Furthermore, the superiority of the motion-corrected average over the other two is statistically significant by the measure of a linear mixed-effect model with p -values < 0.05. Our findings may facilitate the detection of bladder abnormality in MR cystography by mitigating the motion challenge. The effectiveness of this approach depends on the noise level of acquired short-time scans and the robustness of image registration, and future effort on these two aspects is needed.

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Year:  2013        PMID: 23591468      PMCID: PMC3740055          DOI: 10.1109/TBME.2013.2257769

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  37 in total

1.  Nonrigid registration using free-form deformations: application to breast MR images.

Authors:  D Rueckert; L I Sonoda; C Hayes; D L Hill; M O Leach; D J Hawkes
Journal:  IEEE Trans Med Imaging       Date:  1999-08       Impact factor: 10.048

2.  PET-CT image registration in the chest using free-form deformations.

Authors:  David Mattes; David R Haynor; Hubert Vesselle; Thomas K Lewellen; William Eubank
Journal:  IEEE Trans Med Imaging       Date:  2003-01       Impact factor: 10.048

Review 3.  Mutual-information-based registration of medical images: a survey.

Authors:  Josien P W Pluim; J B Antoine Maintz; Max A Viergever
Journal:  IEEE Trans Med Imaging       Date:  2003-08       Impact factor: 10.048

4.  Measuring signal-to-noise ratios in MR imaging.

Authors:  L Kaufman; D M Kramer; L E Crooks; D A Ortendahl
Journal:  Radiology       Date:  1989-10       Impact factor: 11.105

5.  Bladder tumor detection at virtual cystoscopy.

Authors:  J H Song; I R Francis; J F Platt; R H Cohan; J Mohsin; S J Kielb; M Korobkin; J E Montie
Journal:  Radiology       Date:  2001-01       Impact factor: 11.105

6.  Measurement of signal intensities in the presence of noise in MR images.

Authors:  R M Henkelman
Journal:  Med Phys       Date:  1985 Mar-Apr       Impact factor: 4.071

7.  Characterization of texture features of bladder carcinoma and the bladder wall on MRI: initial experience.

Authors:  Zhengxing Shi; Zengyue Yang; Guopeng Zhang; Guangbin Cui; Xiaoshuang Xiong; Zhengrong Liang; Hongbing Lu
Journal:  Acad Radiol       Date:  2013-08       Impact factor: 3.173

Review 8.  Virtual cystoscopy of the bladder based on CT and MRI data.

Authors:  T M Bernhardt; U Rapp-Bernhardt
Journal:  Abdom Imaging       Date:  2001 May-Jun

9.  Reliability of MR imaging-based virtual cystoscopy in the diagnosis of cancer of the urinary bladder.

Authors:  Markus Lämmle; Ambros Beer; Marcus Settles; Christian Hannig; Hartwig Schwaibold; Carsten Drews
Journal:  AJR Am J Roentgenol       Date:  2002-06       Impact factor: 3.959

10.  Diagnostic potential of virtual cystoscopy of the bladder: MRI vs CT. Preliminary report.

Authors:  T M Bernhardt; H Schmidl; C Philipp; E P Allhoff; U Rapp-Bernhardt
Journal:  Eur Radiol       Date:  2002-06-12       Impact factor: 5.315

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  3 in total

1.  Radiofrequency artefacts in echoplanar imaging induced by two 1.5 T MR scanners in close proximity.

Authors:  X Li; J Cui; S P Christopasak; A Kumar; Z-G Peng
Journal:  Br J Radiol       Date:  2014-04-09       Impact factor: 3.039

2.  α-Information-Based Registration of Dynamic Scans for Magnetic Resonance Cystography.

Authors:  Hao Han; Qin Lin; Lihong Li; Chaijie Duan; Hongbing Lu; Haifang Li; Zengmin Yan; John Fitzgerald; Zhengrong Liang
Journal:  IEEE J Biomed Health Inform       Date:  2015-06-17       Impact factor: 5.772

Review 3.  Recent advances in imaging and understanding interstitial cystitis.

Authors:  Pradeep Tyagi; Chan-Hong Moon; Joseph Janicki; Jonathan Kaufman; Michael Chancellor; Naoki Yoshimura; Christopher Chermansky
Journal:  F1000Res       Date:  2018-11-09
  3 in total

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