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ORGANIZER;CN=Michael McDonald:mailto:michael.mcdonald@fsu.edu
DESCRIPTION;LANGUAGE=en-US:"Redistilling GRAPPA: A Bipartite Graph Formulat
 ion for Parallel MRI Reconstruction"\n\nZlatko Sokolikj\n\nPlease feel fre
 e to forward/share this invitation with other groups/disciplines that migh
 t be interested in this talk/topic. All are welcome to attend.\n\nNOTE: In
 -person attendance is requested in our 499 Dirac Science Library (DSL) Sem
 inar Room. Zoom access is intended for external (non-departmental) partici
 pants only.\n\nhttps://fsu.zoom.us/j/94273595552\nMeeting # 942 7359 5552\
 n\n\nWednesday\, Sep 30\, 2026\, Schedule:\n\n  *\n3:00 to 3:30 PM Eastern
  Time (US and Canada)\n     *\n☕ Nespresso & Teatime - 417 DSL Commons\n
 \n  *\n3:30 to 4:30 PM Eastern Time (US and Canada)\n     *\n🕟 Colloqui
 um - 499 DSL Seminar Room\n\n\nAbstract:\nMagnetic resonance imaging (MRI)
  produces high-resolution images of soft tissue without ionizing radiation
 \, but acquisition remains relatively slow because the scanner must sample
  raw spatial-frequency data\, known as k-space\, before reconstructing the
  final image. Parallel MRI accelerates this process by using multiple rece
 iver coils to recover information from undersampled data. GRAPPA is a wide
 ly used k-space parallel imaging method that estimates missing samples thr
 ough interpolation weights learned from a fully sampled autocalibration si
 gnal (ACS) region.\n\nThis talk presents Bipartite-Graph GRAPPA (BG-GRAPPA
 )\, a graph-based view of GRAPPA reconstruction in which acquired multicoi
 l k-space samples are represented as source nodes\, missing samples are re
 presented as target nodes\, and calibrated interpolation weights form the 
 edges between them. This reformulation preserves the scan-specific calibra
 tion structure of classical GRAPPA while making its source-to-target conne
 ctivity explicit.\n\nUsing this graph view\, the talk examines how reconst
 ruction behavior changes across anatomy\, acceleration\, coil relationship
 s\, target classes\, and spatial location in k-space. The results show tha
 t reconstruction difficulty is not uniform: performance varies across k-sp
 ace\, and improvements in magnitude image quality do not always correspond
  to improved complex k-space agreement. By making GRAPPA’s interpolation
  structure visible\, BG-GRAPPA provides a framework for analyzing which co
 nnections matter\, where calibration transfers reliably\, and how more ada
 ptive reconstruction strategies may be designed.\n\nAdditional colloquium 
 details can be found here:\nhttps://www.sc.fsu.edu/news-and-events/colloqu
 ium/colloquium-with-zlatko-sokolikj-2026-09-30<https://nam04.safelinks.pro
 tection.outlook.com/?url=https%3A%2F%2Fwww.sc.fsu.edu%2Fnews-and-events%2F
 colloquium%2Fcolloquium-with-zlatko-sokolikj-2026-09-30&data=05%7C02%7Csc-
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 e available here: https://www.sc.fsu.edu/colloquium<https://nam04.safelink
 s.protection.outlook.com/?url=https%3A%2F%2Fwww.sc.fsu.edu%2Fcolloquium&da
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 0100000001697688C577F1A4CA5BAE9A75603D29C
SUMMARY;LANGUAGE=en-US:Scientific Computing Colloquium with Zlatko Sokolikj
DTSTART;TZID=Eastern Standard Time:20260930T153000
DTEND;TZID=Eastern Standard Time:20260930T162500
CLASS:PUBLIC
PRIORITY:5
DTSTAMP:20260926T172314Z
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