loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: A. A. Saraiva 1 ; 2 ; Luciano Lopes 3 ; Pimentel Pedro 3 ; Jose Vigno Moura Sousa 3 ; N. M. Fonseca Ferreira 4 ; 5 ; J. E. S. Batista Neto 2 ; Salviano Soares 4 and Antonio Valente 6 ; 1

Affiliations: 1 University of Trás-os-Montes and Alto Douro, Vila Real, Portugal ; 2 University of São Paulo, São Carlos, Brazil ; 3 UESPI - University of State Piaui, Piripiri, Brazil ; 4 Coimbra Polytechnic, ISEC, Coimbra, Portugal ; 5 Knowledge Engineering and Decision-Support Research Center (GECAD) of the Institute of Engineering, Polytechnic Institute of Porto, Portugal ; 6 INESC-TEC Technology and Science, Porto, Portugal

Keyword(s): UNet, Segmentation, CT Scanner, Lung Nodes.

Abstract: This paper presents a method capable of detecting and segmenting pulmonary nodules in clinical computed tomography images, using UNet convolutional neural network powered by The Lung Image Database Consortium image collection - LIDC-IDRI, that in the training process was submitted to different training tests, where for each of them, their hyper-parameters were modified so that the results could be collected from different media, getting quite satisfactory results in the segmentation task, highlighting the areas of interest almost perfectly, resulting in 91.61% on the IoU (Intersection over Union) metric.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.141.38.5

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Saraiva, A.; Lopes, L.; Pedro, P.; Sousa, J.; Ferreira, N.; Neto, J.; Soares, S. and Valente, A. (2020). Use of Convolutional Neural Networks for Detection and Segmentation of Pulmonary Nodules in Computed Tomography Images. In Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - BIODEVICES; ISBN 978-989-758-398-8; ISSN 2184-4305, SciTePress, pages 292-297. DOI: 10.5220/0009178902920297

@conference{biodevices20,
author={A. A. Saraiva. and Luciano Lopes. and Pimentel Pedro. and Jose Vigno Moura Sousa. and N. M. Fonseca Ferreira. and J. E. S. Batista Neto. and Salviano Soares. and Antonio Valente.},
title={Use of Convolutional Neural Networks for Detection and Segmentation of Pulmonary Nodules in Computed Tomography Images},
booktitle={Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - BIODEVICES},
year={2020},
pages={292-297},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009178902920297},
isbn={978-989-758-398-8},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - BIODEVICES
TI - Use of Convolutional Neural Networks for Detection and Segmentation of Pulmonary Nodules in Computed Tomography Images
SN - 978-989-758-398-8
IS - 2184-4305
AU - Saraiva, A.
AU - Lopes, L.
AU - Pedro, P.
AU - Sousa, J.
AU - Ferreira, N.
AU - Neto, J.
AU - Soares, S.
AU - Valente, A.
PY - 2020
SP - 292
EP - 297
DO - 10.5220/0009178902920297
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic