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This article is part of the supplement: Proceedings of the 10th European Congress on Telepathology and 4th International Congress on Virtual Microscopy

Open Access Proceedings

Distributed computing in image analysis using open source frameworks and application to image sharpness assessment of histological whole slide images

Norman Zerbe12*, Peter Hufnagl12 and Karsten Schlüns1

Author Affiliations

1 Institute of Pathology, Charité – Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany

2 University of Applied Sciences Berlin, Wilhelminenhofstraße 75A, 12459, Berlin, Germany

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Diagnostic Pathology 2011, 6(Suppl 1):S16  doi:10.1186/1746-1596-6-S1-S16

Published: 30 March 2011

Abstract

Background

Automated image analysis on virtual slides is evolving rapidly and will play an important role in the future of digital pathology. Due to the image size, the computational cost of processing whole slide images (WSIs) in full resolution is immense. Moreover, image analysis requires well focused images in high magnification.

Methods

We present a system that merges virtual microscopy techniques, open source image analysis software, and distributed parallel processing. We have integrated the parallel processing framework JPPF, so batch processing can be performed distributed and in parallel. All resulting meta data and image data are collected and merged. As an example the system is applied to the specific task of image sharpness assessment. ImageJ is an open source image editing and processing framework developed at the NIH having a large user community that contributes image processing algorithms wrapped as plug-ins in a wide field of life science applications. We developed an ImageJ plug-in that supports both basic interactive virtual microscope and batch processing functionality. For the application of sharpness inspection we employ an approach with non-overlapping tiles. Compute nodes retrieve image tiles of moderate size from the streaming server and compute the focus measure. Each tile is divided into small sub images to calculate an edge based sharpness criterion which is used for classification. The results are aggregated in a sharpness map.

Results

Based on the system we calculate a sharpness measure and classify virtual slides into one of the following categories - excellent, okay, review and defective. Generating a scaled sharpness map enables the user to evaluate sharpness of WSIs and shows overall quality at a glance thus reducing tedious assessment work.

Conclusions

Using sharpness assessment as an example, the introduced system can be used to process, analyze and parallelize analysis of whole slide images based on open source software.