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DTSTART:19700308T020000
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BEGIN:VEVENT
DTSTAMP:20260522T150117Z
LOCATION:C2/3/4 Ballroom
DTSTART;TZID=America/Chicago:20181113T083000
DTEND;TZID=America/Chicago:20181113T170000
UID:submissions.supercomputing.org_SC18_sess322_post265@linklings.com
SUMMARY:GPU-Accelerated Interpolation for 3D Image Registration
DESCRIPTION:Naveen Himthani (University of Texas, Institute for Computatio
 nal Engineering and Sciences); Andreas Mang (University of Houston); Amir 
 Gholami (University of California, Berkeley); and George Biros (University
  of Texas, Institute for Computational Engineering and Sciences)\n\nImage 
 registration is a key technology in image computing with numerous applicat
 ions in medical imaging. Our overarching goal is the design of a consisten
 t and unbiased computational framework for the integration of medical imag
 ing data with simulation and optimization to support clinical decision mak
 ing for glioma brain tumor patients. A major issue in 3D image registratio
 n is the time to solution, which poses the demand for effective numerical 
 schemes and the utilization of high performance computing resources.\n\nIn
  this poster, we extend present a GPU-accelerated implementation of the La
 grange interpolation kernel using hardware texture filtering feature of mo
 dern hardware. Ongoing work involves implementing a unified single-GPU cod
 e for 3D image registration along with other computational kernels such as
  FFT. I will present my work by briefly explaining image registration foll
 owed by the explanation of the interpolation algorithm and its features an
 d then demonstrate the results obtained.\n\nRegistration Category: Tech Pr
 ogram Reg Pass, Exhibits Reg Pass\n\n
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