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  • Zufiria, BlancaKTH,Skolan för kemi, bioteknologi och hälsa (CBH) (author)

A feature-based convolutional neural network for reconstruction of interventional MRI

  • Article/chapterEnglish2019

Publisher, publication year, extent ...

  • 2019-12-19
  • John Wiley and Sons Ltd,2019
  • printrdacarrier

Numbers

  • LIBRIS-ID:oai:DiVA.org:kth-268438
  • https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-268438URI
  • https://doi.org/10.1002/nbm.4231DOI

Supplementary language notes

  • Language:English
  • Summary in:English

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  • Subject category:ref swepub-contenttype
  • Subject category:art swepub-publicationtype

Notes

  • QC 20200423
  • Real-time interventional MRI (I-MRI) could help to visualize the position of the interventional feature, thus improving patient outcomes in MR-guided neurosurgery. In particular, in deep brain stimulation, real-time visualization of the intervention procedure using I-MRI could improve the accuracy of the electrode placement. However, the requirements of a high undersampling rate and fast reconstruction speed for real-time imaging pose a great challenge for reconstruction of the interventional images. Based on recent advances in deep learning (DL), we proposed a feature-based convolutional neural network (FbCNN) for reconstructing interventional images from golden-angle radially sampled data. The method was composed of two stages: (a) reconstruction of the interventional feature and (b) feature refinement and postprocessing. With only five radially sampled spokes, the interventional feature was reconstructed with a cascade CNN. The final interventional image was constructed with a refined feature and a fully sampled reference image. With a comparison of traditional reconstruction techniques and recent DL-based methods, it was shown that only FbCNN could reconstruct the interventional feature and the final interventional image. With a reconstruction time of ~ 500 ms per frame and an acceleration factor of ~ 80, it was demonstrated that FbCNN had the potential for application in real-time I-MRI.

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  • Qiu, S. (author)
  • Yan, K. (author)
  • Zhao, R. (author)
  • Wang, R. (author)
  • She, H. (author)
  • Zhang, C. (author)
  • Sun, B. (author)
  • Herman, Pawel,1979-KTH,Beräkningsvetenskap och beräkningsteknik (CST)(Swepub:kth)u19pqm1e (author)
  • Du, Y. (author)
  • Feng, Y. (author)
  • KTHSkolan för kemi, bioteknologi och hälsa (CBH) (creator_code:org_t)

Related titles

  • In:NMR in Biomedicine: John Wiley and Sons Ltd0952-34801099-1492

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