Reduction of Motion Artifacts in the Recovery of Undersampled DCE MR Images Using Data Binning and L+S Decomposition.

Background. Motion is a major source of blurring and ghosting in recovered MR images. It is more challenging in Dynamic Contrast Enhancement (DCE) MRI because motion effects and rapid intensity changes in contrast agent are difficult to distinguish from each other. Material and Methods. In this stud...

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Publicado en:BioMed Research International pp. 1 - 12
Autores principales: Bilal, Muhammad, Anis, Haris, Khan, Najeeb, Qureshi, Ijaz, Shah, Jawad, Kadir, Kushsairy A.
Formato: algorithm diagnostic images equations & formulas research tables/charts Journal Article
Publicado: Wiley-Blackwell 4/17/2019
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 4/17/2019
      pid: 480
      pub: Wiley-Blackwell
      place: Malden, Massachusetts
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        135926285
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        10.1155/2019/6139785
        135926285
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        atl: Reduction of Motion Artifacts in the Recovery of Undersampled DCE MR Images Using Data Binning and L+S Decomposition.
      aug:
        au:
          Bilal, Muhammad
          Anis, Haris
          Khan, Najeeb
          Qureshi, Ijaz
          Shah, Jawad
          Kadir, Kushsairy A.
        affil: Department of Electrical Engineering Int. Islamic University, Islamabad, Pakistan
      sug:
        subj:
          Artifacts
          Motion Analysis Systems Methods
          Magnetic Resonance Imaging Methods
          Image Processing, Computer Assisted Methods
          Human
          Respiration
          Liver
          Abdomen
          Diagnosis, Digestive System Methods
          Image Enhancement
          Contrast Media
      ab: Background. Motion is a major source of blurring and ghosting in recovered MR images. It is more challenging in Dynamic Contrast Enhancement (DCE) MRI because motion effects and rapid intensity changes in contrast agent are difficult to distinguish from each other. Material and Methods. In this study, we have introduced a new technique to reduce the motion artifacts, based on data binning and low rank plus sparse (L+S) reconstruction method for DCE MRI. For Data binning, radial k-space data is acquired continuously using the golden-angle radial sampling pattern and grouped into various motion states or bins. The respiratory signal for binning is extracted directly from radially acquired k-space data. A compressed sensing- (CS-) based L+S matrix decomposition model is then used to reconstruct motion sorted DCE MR images. Undersampled free breathing 3D liver and abdominal DCE MR data sets are used to validate the proposed technique. Results. The performance of the technique is compared with conventional L+S decomposition qualitatively along with the image sharpness and structural similarity index. Recovered images are visually sharper and have better similarity with reference images. Conclusion. L+S decomposition provides improved MR images with data binning as preprocessing step in free breathing scenario. Data binning resolves the respiratory motion by dividing different respiratory positions in multiple bins. It also differentiates the respiratory motion and contrast agent (CA) variations. MR images recovered for each bin are better as compared to the method without data binning.
      pubtype: Academic Journal
      doctype:
        algorithm
        diagnostic images
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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