Enhanced Diagnostic Fidelity in Pathology Whole Slide Image Compression via Deep Learning

Maximilian Fischer, Peter Neher, Peter Schüffler, Shuhan Xiao, Silvia Dias Almeida, Constantin Ulrich, Alexander Muckenhuber, Rickmer Braren, Michael Götz, Jens Kleesiek, Marco Nolden, Klaus Maier-Hein

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Accurate diagnosis of disease often depends on the exhaustive examination of Whole Slide Images (WSI) at microscopic resolution. Efficient handling of these data-intensive images requires lossy compression techniques. This paper investigates the limitations of the widely-used JPEG algorithm, the current clinical standard, and reveals severe image artifacts impacting diagnostic fidelity. To overcome these challenges, we introduce a novel deep-learning (DL)-based compression method tailored for pathology images. By enforcing feature similarity of deep features between the original and compressed images, our approach achieves superior Peak Signal-to-Noise Ratio (PSNR), Multi-Scale Structural Similarity Index (MS-SSIM), and Learned Perceptual Image Patch Similarity (LPIPS) scores compared to JPEG-XL, Webp, and other DL compression methods. Our method increases the PSNR value from 39 (JPEG80) to 41, indicating improved image fidelity and diagnostic accuracy. Our approach can help to drastically reduce storage costs while maintaining large levels of image quality. Our method is online available.

Original languageEnglish
Title of host publicationMachine Learning in Medical Imaging - 14th International Workshop, MLMI 2023, Held in Conjunction with MICCAI 2023, Proceedings
EditorsXiaohuan Cao, Xi Ouyang, Xuanang Xu, Islem Rekik, Zhiming Cui
PublisherSpringer Science and Business Media Deutschland GmbH
Pages427-436
Number of pages10
ISBN (Print)9783031456756
DOIs
StatePublished - 2024
Event14th International Workshop on Machine Learning in Medical Imaging, MLMI 2023 - Vancouver, Canada
Duration: 8 Oct 20238 Oct 2023

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14349 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference14th International Workshop on Machine Learning in Medical Imaging, MLMI 2023
Country/TerritoryCanada
CityVancouver
Period8/10/238/10/23

Keywords

  • Digital Pathology
  • Lossy Image Compression
  • Whole Slide Imaging

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