KNIME exploration, image analysis point of view

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Introduction

Introduction/potential interest

What is Knime?

From Knime wikipedia article:

The Konstanz Information Miner, is an open source data analytics, reporting and integration platform. KNIME integrates various components for machine learning and data mining through its modular data pipelining concept. A graphical user interface allows assembly of nodes for data preprocessing (ETL: Extraction, Transformation, Loading), for modeling and data analysis and visualization.

What is the interest of Knime for image analysis?

  • Possibility to build Heterogeneous pipeline combining python/R/matlab/ImageJ(Java)
  • Automation of the batch processing and its parallelization
  • Access to reporting and data analyzis function

What is the interest of KNIME for a service?

  • Unify complex pipeline in a single workflow that can be proposed in service portfolio and can be enhanced for more versatility
  • ease reuse of basic pipeline while avoiding to rebuild the infrastructure part of the analysis (reporting, batch processing, experimental condition handling for instance)

One see a view of Knime interface in Figure \ref{fig:GeneralView}