Detail publikace

Supervised Segmentation for 3D Slicer

CHALUPA, D.

Originální název

Supervised Segmentation for 3D Slicer

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

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.

Klíčová slova

3D Slicer, C++, extension, machine learning, optimization, segmentation, tomography

Autoři

CHALUPA, D.

Vydáno

27. 4. 2017

ISBN

978-80-214-5496-5

Kniha

Proceedings of the 23rd Conference STUDENT EEICT 2017

Strany od

296

Strany do

298

Strany počet

3

BibTex

@inproceedings{BUT139550,
  author="Daniel {Chalupa}",
  title="Supervised Segmentation for 3D Slicer",
  booktitle="Proceedings of the 23rd Conference STUDENT EEICT 2017",
  year="2017",
  pages="296--298",
  isbn="978-80-214-5496-5"
}