Ilastik

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ilastik
Developer(s) Christoph Sommer, Christoph Straehle, Thorben Kröger, Bernhard X. Kausler, Ullrich Koethe, Fred A. Hamprecht and others
Stable release 0.5 / June 29, 2012 (2012-06-29)
Operating system Any (Python based)
Type Image processing & Computer vision & Machine Learning
License BSD
Website http://www.ilastik.org/

ilastik[1] is a user-friendly free open source software for image classification and segmentation. No previous experience in image processing is required to run the software.

Features[edit]

ilastik allows user to annotate an arbitrary number of classes in images with a mouse interface. Using these user annotations and the generic (nonlinear) image features, the user can train a random forest classifier. ilastik has a CellProfiler module to use ilastik classifiers to process images within a CellProfiler framework.

History[edit]

ilastik was first released in 2011 by scientists at the Heidelberg Collaboratory for Image Processing (HCI), University of Heidelberg.

Application[edit]

  • The Interactive Learning and Segmentation Toolkit
  • Carving[2][3]
  • Cell classification and neuron classification[4]
  • Synapse detection

Resources[edit]

ilastik project is hosted on GitHub. It is a collaborative project, any contributions such as comments, bug reports, bug fixes or code contributions are welcome.

References[edit]

  1. ^ Sommer, C; Straehle C; Koethe U; Hamprecht FA (2011). "ilastik: Interactive Learning and Segmentation Toolkit". IEEE International Symposium on Biomedical Imaging: 230–33. doi:10.1109/ISBI.2011.5872394. 
  2. ^ Straehl, C; Köthe U; Briggman K; Denk W; Hamprecht FA (2012). "Seeded watershed cut uncertainty estimators for guided interactive segmentation". CVPR. 
  3. ^ Straehle, CN; Köthe U; Knott G; Hamprecht FA (2011). "Carving: scalable interactive segmentation of neural volume electron microscopy images". MICCAI 14 (Pt 1): 653–60. doi:10.1007/978-3-642-23623-5_82. PMID 22003674. 
  4. ^ Kreshuk, A; Straehle CN; Sommer C; Koethe U; Cantoni M; et al. (2011). Automated Detection and Segmentation of Synaptic Contacts in Nearly Isotropic Serial Electron Microscopy Images 6 (10). doi:10.1371/journal.pone.0024899. PMID 22031814. 

External links[edit]