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DTSTART;TZID=America/Denver:20231112T165500
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UID:submissions.supercomputing.org_SC23_sess431_ws_drbsd106@linklings.com
SUMMARY:Lossy and Lossless Compression for BioFilm Optical Coherence Tomog
 raphy (OCT)
DESCRIPTION:Max Faykus III, Jon Calhoun, and Melissa Smith (Clemson Univer
 sity)\n\nOptical Coherence Tomography (OCT) is a fast and nondestructive t
 echnology for bacterial biofilm imaging. However, OCT generates approximat
 ely 100 GB per flow cell, complicating storage and data sharing. Data redu
 ction reduces data complications by reducing the overhead and amount of da
 ta transferred. This work leverages similarities between layers of OCT ima
 ges to minimize data in order to improve compression. This paper evaluates
  5 lossless and 2 lossy state-of-the-art compressors as well as 2 pre-proc
 essing techniques to reduce the OCT data. Reduction techniques are evaluat
 ed to determine which compressor has the most significant compression rati
 o while maintaining a strong bandwidth and minimal image distortion. Resul
 ts show SZ with frame before pre-processing is able to achieve the highest
  CR of 204.6× on its higher error bounds. The maximum compression bandwidt
 h SZ on higher error bounds is ∼ 41𝑀𝐵/𝑠, for decompression bandwidth, it i
 s able to outperform ZFP achieving ∼ 67𝑀𝐵/𝑠.\n\nTag: Data Analysis, Visual
 ization, and Storage, Data Compression\n\nRegistration Category: Workshop 
 Reg Pass\n\nSession Chairs: Sheng Di (Argonne National Laboratory (ANL), U
 niversity of Chicago); Dingwen Tao (Institute of Computing Technology, Chi
 nese Academy of Sciences; University of Chinese Academy of Sciences); Ana 
 Gainaru (Oak Ridge National Laboratory (ORNL)); Jieyang Chen (University o
 f Oregon); Shadi Ibrahim (French Institute for Research in Computer Scienc
 e and Automation (INRIA)); and Xin Liang (Oregon State University)\n\n
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