Original title: Supervised Segmentation For 3D Slicer
Authors: Chalupa, Daniel
Document type: Papers
Language: eng
Publisher: Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií
Abstract: The purpose of this work is to introduce an extendable framework for training and usage of machine learning algorithms. This framework is bundled in an extension for 3D Slicer that is to be used for medical images segmentation. An example usage of the extension is also provided.
Keywords: 3D Slicer; C++; extension; machine learning; optimization; segmentation; tomography
Host item entry: Proceedings of the 23st Conference STUDENT EEICT 2017, ISBN 978-80-214-5496-5

Institution: Brno University of Technology (web)
Document availability information: Fulltext is available in the Brno University of Technology Digital Library.
Original record: http://hdl.handle.net/11012/187112

Permalink: http://www.nusl.cz/ntk/nusl-414772


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