AbstractsBiology & Animal Science

Integration Platform for Biomedical Image Analysis

by Ville Rantanen




Institution: University of Helsinki
Department: Institute of Biomedicine, Research Programs Unit
Year: 2015
Keywords: biomedicine
Record ID: 1135022
Full text PDF: http://hdl.handle.net/10138/153857


Abstract

Images provide invaluable information to Biomedicine. Especially, microscopy as an information source has been providing knowledge for research and clinical diagnostics. We have moved away from simply looking at the images to quantifiable computerized image analysis. Over the last decades, image analysis developers have prepared algorithms and software to address various scientific enquiries using images. These software are often created for a single purpose. Naturally, not even the most generic software can include all the algorithms ever created. From an image analysis developer point of view, the choice of software creates limitations. It limits the developer to the algorithms included and to the language it was developed in. Even if the software is modular and extendable, a specific language is required and the earlier algorithm implementations would have to be ported. This thesis presents an integration platform for image analysis: Anima. It is capable of using existing software and including them in analysis workflows. Since image analysis is very case specific, custom processing commands are frequently needed. Anima comes with a large number of data and image analysis components developed directly for the platform, as well as components that send custom commands to the integrated software. All of the components can be executed in a single analysis pipeline. Anima itself is built on top of Anduril, another software, inheriting its software architecture. Anduril gives Anima the power of parallel processing and rerun prevention mechanism, speeding up the development cycle of new algorithms. The usability of Anima for method development is shown by implementing new segmentation algorithms and visualization tools. The tools and methods are all suited to large data sets. To display the modularity, the tools are published as separate programs that are then integrated in Anima. The usefulness of the platform is shown by applying it in different biomedical research settings. The settings include different organisms: human, rat and nematode; different sample material: brain tissue, lymphatic nodes and serum; and different medical interests: cerebral ischemia, cancer and allergy. Anima is a versatile open-source image analysis platform, that encourages the use of best practices of programming habits. It makes the development of analysis workflows and individual algorithms more efficient. Kuvantaminen on tärkeä tiedon lähde lääketieteelle. Erityisesti mikroskopia on tärkeä kuvapohjaisen tiedon tuottaja biolääketieteellisessä tutkimuksessa. Tietokoneteknologian ansiosta emme ole enää riippuvaisia ihmissilmistä kuvien tulkitsijana. Viime vuosikymmeninä kuva-analyysien kehittäjät ovat luoneet algoritmeja ja kokonaisia ohjelmistoja kuvien hyödyntämiseksi tieteellisiin tarkoituksiin. Useimmat näistä ohjelmista tehdään yhtä tutkimuskysymystä varten. Edes yleisluontoiset ohjelmistopaketit eivät voi sisältää menetelmiä kaikkiin tarkoituksiin. Kuva-analyysikehittäjälle ohjelman valinta luo myös rajoituksia.…