Detail publikace

DETECTION OF PATHOLOGICAL VERTEBRAE IN SPINAL CT UTILISED BY MACHINE LEARNING METHODS

TYSHCHENKO, B.

Originální název

DETECTION OF PATHOLOGICAL VERTEBRAE IN SPINAL CT UTILISED BY MACHINE LEARNING METHODS

Anglický název

DETECTION OF PATHOLOGICAL VERTEBRAE IN SPINAL CT UTILISED BY MACHINE LEARNING METHODS

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

čeština

Originální abstrakt

This paper presents a computer aided detection system to identify pathological vertebrae and to classify a type of pathology. Designed classification system is based on using neural network (NN), which performs classification step and on principal component analysis (PCA), which is used to reducing the original number of observation features.

Anglický abstrakt

This paper presents a computer aided detection system to identify pathological vertebrae and to classify a type of pathology. Designed classification system is based on using neural network (NN), which performs classification step and on principal component analysis (PCA), which is used to reducing the original number of observation features.

Klíčová slova

Neural network; Classification; CT; Machine Learning; Pathologies of spine; Principal Component Analysis; Vertebra

Klíčová slova v angličtině

Neural network; Classification; CT; Machine Learning; Pathologies of spine; Principal Component Analysis; Vertebra

Autoři

TYSHCHENKO, B.

Vydáno

25. 4. 2019

Nakladatel

Brno University of Technology

Místo

Brno

ISBN

978-80-214-5735-5

Kniha

Proceedings of the 25th Conference STUDENT EEICT 2019

Číslo edice

první

Strany od

390

Strany do

393

Strany počet

4

URL

http://www.feec.vutbr.cz/conf/EEICT/archiv/sborniky/EEICT_2019_sbornik.pdf

BibTex

@inproceedings{BUT156826,
  author="Bohdan {Tyshchenko}",
  title="DETECTION OF PATHOLOGICAL VERTEBRAE IN SPINAL CT UTILISED BY MACHINE LEARNING METHODS",
  booktitle="Proceedings of the 25th  Conference STUDENT EEICT 2019",
  year="2019",
  number="první",
  pages="390--393",
  publisher="Brno University of Technology",
  address="Brno",
  isbn="978-80-214-5735-5",
  url="http://www.feec.vutbr.cz/conf/EEICT/archiv/sborniky/EEICT_2019_sbornik.pdf"
}