Mosaic-Based Color-Transform Optimization for Lossy and Lossy-to-Lossless Compression of Pathology Whole-Slide Images

Miguel Hernandez-Cabronero, Victor Sanchez, Ian Blanes, Francesc Auli-Llinas, Michael W Marcellin, Joan Serra-Sagrista

Research output: Contribution to journalArticle

4 Scopus citations

Abstract

The use of whole-slide images (WSIs) in pathology entails stringent storage and transmission requirements because of their huge dimensions. Therefore, image compression is an essential tool to enable efficient access to these data. In particular, color transforms are needed to exploit the very high degree of inter-component correlation and obtain competitive compression performance. Even though state-of-the-art color transforms remove some redundancy, they disregard important details of the compression algorithm applied after the transform. Therefore, their coding performance is not optimal.We propose an optimization method called Mosaic Optimization for designing irreversible and reversible color transforms simultaneously optimized for any given WSI and the subsequent compression algorithm. Mosaic Optimization is designed to attain reasonable computational complexity and enable continuous scanner operation. Exhaustive experimental results indicate that, for JPEG 2000 at identical compression ratios, the optimized transforms yield images more similar to the original than other state-of-the-art transforms. Specifically, irreversible optimized transforms outperform the Karhunen-Lo`eve Transform (KLT) in terms of PSNR (up to 1.1 dB), the HDR-VDP-2 visual distortion metric (up to 3.8 dB) and accuracy of computer-aided nuclei detection tasks (F1 score up to 0.04 higher). Additionally, reversible optimized transforms achieve PSNR, HDR-VDP-2 and nuclei detection accuracy gains of up to 0.9 dB, 7.1 dB and 0.025, respectively, when compared to the reversible color transform (RCT) in lossy-to-lossless compression regimes.

Original languageEnglish (US)
JournalIEEE Transactions on Medical Imaging
DOIs
StateAccepted/In press - Jul 3 2018

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Keywords

  • Color-Transform Optimization
  • Compression algorithms
  • Image coding
  • Image color analysis
  • Image Compression
  • Optimization
  • Pathology
  • Transform coding
  • Transforms
  • Whole-Slide Images

ASJC Scopus subject areas

  • Software
  • Radiological and Ultrasound Technology
  • Computer Science Applications
  • Electrical and Electronic Engineering

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