loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Yuji Iwahori 1 ; Hiroaki Hagi 1 ; Hiroyasu Usami 1 ; Robert J. Woodham 2 ; Aili Wang 3 ; M. K. Bhuyan 4 and Kunio Kasugai 5

Affiliations: 1 Chubu University, Japan ; 2 University of British Columbia, Canada ; 3 Harbin University of Science and Technology, China ; 4 Indian Institute of Technology Guwahati, India ; 5 Aichi Medical University, Japan

Keyword(s): Polyp Detection, Endoscope Image, Likelihood, HOG, Random Forests.

Related Ontology Subjects/Areas/Topics: Applications ; Bioinformatics and Systems Biology ; Computer Vision, Visualization and Computer Graphics ; Image Understanding ; Medical Imaging ; Object Recognition ; Pattern Recognition ; Software Engineering

Abstract: An endoscope is a medical instrument that acquires images inside the human body. This paper proposes a new approach for the automatic detection of polyp regions in an endoscope image by generating a likelihood map with both of edge and color information to obtain high accuracy so that probability becomes high at around polyp candidate region. Next, Histograms of Oriented Gradients (HOG) features are extracted from the detected region and random forests are applied for the classification to judge whether the detected region is polyp region or not. It is shown that the proposed approach has high accuracy for the polyp detection and the usefulness is confirmed through the computer experiments with endoscope images.

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 18.218.61.16

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:
Iwahori, Y.; Hagi, H.; Usami, H.; Woodham, R.; Wang, A.; Bhuyan, M. and Kasugai, K. (2017). Automatic Polyp Detection from Endoscope Image using Likelihood Map based on Edge Information. In Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-222-6; ISSN 2184-4313, SciTePress, pages 402-409. DOI: 10.5220/0006189704020409

@conference{icpram17,
author={Yuji Iwahori. and Hiroaki Hagi. and Hiroyasu Usami. and Robert J. Woodham. and Aili Wang. and M. K. Bhuyan. and Kunio Kasugai.},
title={Automatic Polyp Detection from Endoscope Image using Likelihood Map based on Edge Information},
booktitle={Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2017},
pages={402-409},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006189704020409},
isbn={978-989-758-222-6},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - Automatic Polyp Detection from Endoscope Image using Likelihood Map based on Edge Information
SN - 978-989-758-222-6
IS - 2184-4313
AU - Iwahori, Y.
AU - Hagi, H.
AU - Usami, H.
AU - Woodham, R.
AU - Wang, A.
AU - Bhuyan, M.
AU - Kasugai, K.
PY - 2017
SP - 402
EP - 409
DO - 10.5220/0006189704020409
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