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SUMMARY:Robust principle component analysis based four-dimensional compute
 d tomography - Zhao\, H (University of California\, Irvine)
DTSTART:20110823T100000Z
DTEND:20110823T104500Z
UID:TALK32464@talks.cam.ac.uk
CONTACT:Mustapha Amrani
DESCRIPTION:We present a new spatiotemporal model for 4D-CT from matrix pe
 rspective\, Robust PCA based 4DCT model. Instead of viewing 4D object as a
  temporal collection of three-dimensional (3D) images and looking for loca
 l coherence in time or space independently\, we explore the maximum tempor
 al coherence of spatial structure among phases. This Robust PCA based 4DCT
  model can be applicable in other imaging problems for motion reduction or
 /and change detection. A dynamic data acquisition procedure\, i.e.\, a tem
 porally spiral scheme\, is proposed that can potentially maintain the simi
 lar reconstruction accuracy while using fewer projections of the data. The
  key point of this dynamic scheme is to reduce the total number of measure
 ments and hence the radiation dose by acquiring complementary data in diff
 erent phases without redundant measurements of the common background struc
 ture.\n
LOCATION:Seminar Room 1\, Newton Institute
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