Towards better digital pathology workflows: programming libraries for high-speed sharpness assessment of Whole Slide Images.

Christophe Deroulers,Valérie Perrier,David Ameisen,Luc Legrès,Maxime Battistella,Anne Janin,Fatiha Bouhidel,Jean-Baptiste Yunès,Philippe Bertheau

doi:10.1186/1746-1596-9-s1-s3

Abstract

BackgroundSince microscopic slides can now be automatically digitized and integrated in the clinical workflow, quality assessment of Whole Slide Images (WSI) has become a crucial issue. We present a no-reference quality assessment method that has been thoroughly tested since 2010 and is under implementation in multiple sites, both public university-hospitals and private entities. It is part of the FlexMIm R&D project which aims to improve the global workflow of digital pathology. For these uses, we have developed two programming libraries, in Java and Python, which can be integrated in various types of WSI acquisition systems, viewers and image analysis tools.MethodsDevelopment and testing have been carried out on a MacBook Pro i7 and on a bi-Xeon 2.7GHz server. Libraries implementing the blur assessment method have been developed in Java, Python, PHP5 and MySQL5. For web applications, JavaScript, Ajax, JSON and Sockets were also used, as well as the Google Maps API. Aperio SVS files were converted into the Google Maps format using VIPS and Openslide libraries.ResultsWe designed the Java library as a Service Provider Interface (SPI), extendable by third parties. Analysis is computed in real-time (3 billion pixels per minute). Tests were made on 5000 single images, 200 NDPI WSI, 100 Aperio SVS WSI converted to the Google Maps format.ConclusionsApplications based on our method and libraries can be used upstream, as calibration and quality control tool for the WSI acquisition systems, or as tools to reacquire tiles while the WSI is being scanned. They can also be used downstream to reacquire the complete slides that are below the quality threshold for surgical pathology analysis. WSI may also be displayed in a smarter way by sending and displaying the regions of highest quality before other regions. Such quality assessment scores could be integrated as WSI's metadata shared in clinical, research or teaching contexts, for a more efficient medical informatics workflow.

Highlights

Since microscopic slides can be automatically digitized and integrated in the clinical workflow, quality assessment of Whole Slide Images (WSI) has become a crucial issue
In the following, we use the blur assessment method described in the method section as an example to describe any other quantifiable criterion in an image, to be used a fortiori to assess the quality of WSI
On a collection of 100 WSI, two observers could assess the overall level of quality they observed and they visually verified that the thresholds we set were highly predictive of the global sharpness or blurriness of the WSI

Summary

Introduction

Since microscopic slides can be automatically digitized and integrated in the clinical workflow, quality assessment of Whole Slide Images (WSI) has become a crucial issue. We present a no-reference quality assessment method that has been thoroughly tested since 2010 and is under implementation in multiple sites, both public university-hospitals and private entities It is part of the FlexMIm R&D project which aims to improve the global workflow of digital pathology. Another work [5] assessed the focus sharpness of the tiles of a WSI with the generation of a focus assessment map of the WSI at a given magnification level Both these methods still require a human eye to assess if the WSI must be accepted or discarded after the scan [6].The method we designed to automatically assess the quality of a WSI without any sort of comparison (no-reference assessment) has been patented [7] and thoroughly tested in the last four years. We have developed two programming libraries, in Java and Python, that can be integrated in various types of WSI and image handling applications

Methods

Results

Conclusion