Detail publikačního výsledku

Implementation of a deep learning model for segmentation of multiple myeloma in CT data

GÁLÍK, P.; NOHEL, M.

Originální název

Implementation of a deep learning model for segmentation of multiple myeloma in CT data

Anglický název

Implementation of a deep learning model for segmentation of multiple myeloma in CT data

Druh

Stať ve sborníku v databázi WoS či Scopus

Originální abstrakt

This paper deals with the implementation of a deep learning model for spinal tumor segmentation of multiple myeloma patients in CT data. Deep learning is becoming an important part of developing computer-aided detection and diagnosis systems. In this study, a database of 25 patients who were imaged on spectral CT and for whom different parametric images (conventional CT, virtual monoenergetic images, calcium suppression images) were reconstructed, was used. Three convolutional neural network models based on the nnU-Net framework for lytic lesion segmentation were trained on the selected data. The results were evaluated on a test database and the trained models were compared.

Anglický abstrakt

This paper deals with the implementation of a deep learning model for spinal tumor segmentation of multiple myeloma patients in CT data. Deep learning is becoming an important part of developing computer-aided detection and diagnosis systems. In this study, a database of 25 patients who were imaged on spectral CT and for whom different parametric images (conventional CT, virtual monoenergetic images, calcium suppression images) were reconstructed, was used. Three convolutional neural network models based on the nnU-Net framework for lytic lesion segmentation were trained on the selected data. The results were evaluated on a test database and the trained models were compared.

Klíčová slova

multiple myeloma, computed tomography, deep learning, nnU-Net, segmentation, monoenergetic image, calcium suppress image

Klíčová slova v angličtině

multiple myeloma, computed tomography, deep learning, nnU-Net, segmentation, monoenergetic image, calcium suppress image

Autoři

GÁLÍK, P.; NOHEL, M.

Rok RIV

2025

Vydáno

23.04.2024

Nakladatel

Brno University of Technology, Faculty of Electrical Engineering and Communication

Místo

Brno, Czech Republic

ISBN

978-80-214-6231-1

Kniha

Proceedings I of the 30st Conference STUDENT EEICT 2024: General papers

Edice

1

Strany od

105

Strany do

108

Strany počet

4

URL

https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2024_sbornik_1.pdf

BibTex

@inproceedings{BUT189071,
  author="Pavel {Gálík} and Michal {Nohel}",
  title="Implementation of a deep learning model for segmentation of multiple myeloma in CT data",
  booktitle="Proceedings I of the 30st Conference STUDENT EEICT 2024: General papers",
  year="2024",
  series="1",
  pages="105--108",
  publisher="Brno University of Technology, Faculty of Electrical Engineering and Communication",
  address="Brno, Czech Republic",
  isbn="978-80-214-6231-1",
  url="https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2024_sbornik_1.pdf"
}