| 词条 | Ilastik |
| 释义 |
| name = ilastik | developer = Christoph Sommer, Christoph Straehle, Thorben Kröger, Bernhard X. Kausler, Ullrich Koethe, Fred A. Hamprecht and others | released = {{Start date and age|2011}} | latest_release_version = 1.1.7 | latest_release_date = {{Start date and age|2015|10|09}} | operating_system = Any (Python based) | genre = Image processing & Computer vision & Machine Learning | license = GPL2 | website = {{URL|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. Featuresilastik 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. Historyilastik was first released in 2011 by scientists at the Heidelberg Collaboratory for Image Processing (HCI), University of Heidelberg. Application
Resourcesilastik project is hosted on GitHub. It is a collaborative project, any contributions such as comments, bug reports, bug fixes or code contributions are welcome. References1. ^{{cite book|last=Sommer|first=C|author2=Straehle C |author3=Koethe U |author4=Hamprecht FA |title=ilastik: Interactive Learning and Segmentation Toolkit|journal=IEEE International Symposium on Biomedical Imaging|year=2011|pages=230–33|doi=10.1109/ISBI.2011.5872394|isbn=978-1-4244-4127-3}} 2. ^{{cite journal|last=Straehl|first=C|author2=Köthe U |author3=Briggman K |author4=Denk W |author5=Hamprecht FA |title=Seeded watershed cut uncertainty estimators for guided interactive segmentation|journal=CVPR|year=2012}} 3. ^{{cite journal|last=Straehle|first=CN|author2=Köthe U |author3=Knott G |author4=Hamprecht FA |title=Carving: scalable interactive segmentation of neural volume electron microscopy images|journal=MICCAI|year=2011|pmid=22003674|volume=14|issue=Pt 1|pages=653–60 |doi=10.1007/978-3-642-23623-5_82}} 4. ^{{cite journal|last=Kreshuk|first=A|author2=Straehle CN |author3=Sommer C |author4=Koethe U |author5=Cantoni M |journal=Automated Detection and Segmentation of Synaptic Contacts in Nearly Isotropic Serial Electron Microscopy Images|year=2011|volume=6|issue=10|doi=10.1371/journal.pone.0024899|pmid=22031814 |title=Automated detection and segmentation of synaptic contacts in nearly isotropic serial electron microscopy images |pmc=3198725 |pages=e24899|display-authors=etal}} External links{{Portal|Free and open-source software}}
4 : Image segmentation|Computer vision software|Data mining and machine learning software|Free software programmed in Python |
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