loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Authors: Maxwell Gomes da Silva 1 ; Bruno Augusto Nassif Travençolo 1 and André Backes 2

Affiliations: 1 School of Computer Science, Federal University of Uberlândia, Uberlândia, Brazil ; 2 Department of Computing, Federal University of São Carlos, São Carlos-SP, Brazil

Keyword(s): Deep Learning, Prostate Cancer, Image Segmentation.

Abstract: Prostate cancer remains one of the most critical health challenges, ranking among the leading causes of cancer-related deaths in men worldwide. This study seeks to automate the identification and classification of cancerous regions in histological images using deep learning, specifically convolutional neural networks (CNNs). Using PANDA dataset and Mask R-CNN, our approach achieved an accuracy of 91.3%. This result highlights the potential of our methodology to enhance early detection, improve patient outcomes, and provide valuable support to pathologists in their diagnostic processes.

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 3.129.217.198

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:
Gomes da Silva, M., Travençolo, B. A. N. and Backes, A. (2025). Deep Learning for Image Analysis and Diagnosis Aid of Prostate Cancer. In Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP; ISBN 978-989-758-728-3; ISSN 2184-4321, SciTePress, pages 699-706. DOI: 10.5220/0013302400003912

@conference{visapp25,
author={Maxwell {Gomes da Silva} and Bruno Augusto Nassif Traven\c{c}olo and André Backes},
title={Deep Learning for Image Analysis and Diagnosis Aid of Prostate Cancer},
booktitle={Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP},
year={2025},
pages={699-706},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013302400003912},
isbn={978-989-758-728-3},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP
TI - Deep Learning for Image Analysis and Diagnosis Aid of Prostate Cancer
SN - 978-989-758-728-3
IS - 2184-4321
AU - Gomes da Silva, M.
AU - Travençolo, B.
AU - Backes, A.
PY - 2025
SP - 699
EP - 706
DO - 10.5220/0013302400003912
PB - SciTePress