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A feature-based con...
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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 ...
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2019-12-19
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John Wiley and Sons Ltd,2019
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printrdacarrier
Numbers
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LIBRIS-ID:oai:DiVA.org:kth-268438
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https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-268438URI
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https://doi.org/10.1002/nbm.4231DOI
Supplementary language notes
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Language:English
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Summary in:English
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Subject category:ref swepub-contenttype
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Subject category:art swepub-publicationtype
Notes
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QC 20200423
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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)
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Yan, K.
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Zhao, R.
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Wang, R.
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She, H.
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Zhang, C.
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Sun, B.
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Herman, Pawel,1979-KTH,Beräkningsvetenskap och beräkningsteknik (CST)(Swepub:kth)u19pqm1e
(author)
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Du, Y.
(author)
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Feng, Y.
(author)
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KTHSkolan för kemi, bioteknologi och hälsa (CBH)
(creator_code:org_t)
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In:NMR in Biomedicine: John Wiley and Sons Ltd0952-34801099-1492
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Zufiria, Blanca
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Qiu, S.
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Yan, K.
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Zhao, R.
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Wang, R.
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She, H.
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Zhang, C.
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Sun, B.
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Herman, Pawel, 1 ...
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Du, Y.
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Feng, Y.
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- ENGINEERING AND TECHNOLOGY
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ENGINEERING AND ...
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and Electrical Engin ...
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NMR in Biomedici ...
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Royal Institute of Technology