Publication detail

PROSTATIC CELLS CLASSIFICATION USING DEEP LEARNING

MAJERČÍK, J. ŠPAČEK, M.

Original Title

PROSTATIC CELLS CLASSIFICATION USING DEEP LEARNING

Type

conference paper

Language

English

Original Abstract

Human prostate cancer PC-3 cell line is widely used in cancer research. Previously, Zinc-Resistant variant was described characteristically by higher dry cellular mass determined by quantitative phase imaging. This work aims to classify these 2 cell types into corresponding categories using machine learning methods. We have achieved 97.5% accuracy with the correct preprocessing using Res-Net network.

Keywords

cell classification; deep learning; neural network; quantitative phase imaging; microscopy

Authors

MAJERČÍK, J.; ŠPAČEK, M.

Released

1. 6. 2020

Publisher

Brno University of Technology, Faculty of Electrical Engineering and

Location

Brno, Czech Republic

ISBN

978-80-214-5868-0

Book

Proceedings II of the 26th Conference STUDENT EEICT 2020

Edition

1

Pages from

28

Pages to

31

Pages count

4

URL

https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2020_sbornik_2.pdf

BibTex

@inproceedings{BUT177113,
  author="Jakub {Majerčík} and Michal {Špaček}",
  title="PROSTATIC CELLS CLASSIFICATION USING DEEP LEARNING",
  booktitle="Proceedings II of the 26th Conference STUDENT EEICT 2020",
  year="2020",
  series="1",
  pages="28--31",
  publisher="Brno University of Technology, Faculty of Electrical Engineering and",
  address="Brno, Czech Republic",
  isbn="978-80-214-5868-0",
  url="https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2020_sbornik_2.pdf"
}