SC23 Proceedings

The International Conference for High Performance Computing, Networking, Storage, and Analysis

ACM Student Research Competition Poster Archive

Lossy and Lossless Compression for BioFilm Optical Coherence Tomography (OCT)

Student: Max Faykus (Clemson University)
Supervisor: Jon Calhoun (Clemson University)

Abstract: Optical Coherence Tomography (OCT) can be used as a fast and non-destructive technology for bacterial biofilm imaging. However, OCT generates approximately 100 GB per flow cell, which complicates storage and data sharing. Data reduction can reduce data complications by reducing the overhead and the amount of data transferred. This work leverages the similarities between layers of OCT images to minimize the data in order to improve compression. This paper evaluates the 5 lossless and 2 lossy state-of-the-art compressors to reduce the OCT data. The reduction techniques are evaluated to determine which compressor has the most significant compression ratio while maintaining a strong bandwidth and minimal image distortion. Results show that SZ with frame before pre-processing is able to achieve the highest CR of 204.6x on its higher error bounds. The maximum compression bandwidth SZ on higher error bounds is ~41MB/s, for decompression bandwidth, it is able to outperform ZFP achieving.

ACM-SRC Semi-Finalist: no

Poster: PDF
Poster Summary: PDF

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