loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Manuel Möller 1 ; Patrick Ernst 1 ; Andreas Dengel 1 and Daniel Sonntag 2

Affiliations: 1 German Research Center for Artificial Intelligence (DFKI) and University of Kaiserslautern, Germany ; 2 German Research Center for Artificial Intelligence (DFKI), Germany

Keyword(s): Medical imaging, Semantic technologies, Spatial reasoning, Formal ontologies.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; BioInformatics & Pattern Discovery ; Computational Intelligence ; Data Reduction and Quality Assessment ; Evolutionary Computing ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Machine Learning ; Mining Multimedia Data ; Soft Computing ; Symbolic Systems

Abstract: We present an approach to use medical expert knowledge represented in formal ontologies to check the results of automatic medical object recognition algorithms for spatial plausibility. Our system is based on the comprehensive Foundation Model of Anatomy ontology which we extend with spatial relations between a number of anatomical entities. These relations are learned inductively from an annotated corpus of 3D volume data sets. The induction process is split into two parts: First, we generate a quantitative anatomical atlas using fuzzy sets to represent inherent imprecision. From this atlas we abstract onto a purely symbolic level to generate a generic qualitative model of the spatial relations in human anatomy. In our evaluation we describe how this model can be used to check the results of a state-of-the-art medical object recognition system for 3D CT volume data sets for spatial plausibility. Our results show that the combination of medical domain knowledge in formal ontologies a nd sub-symbolic object recognition yields improved overall recognition precision. (More)

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 3.147.205.154

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:
Möller, M.; Ernst, P.; Dengel, A. and Sonntag, D. (2010). AUTOMATIC SPATIAL PLAUSIBILITY CHECKS FOR MEDICAL OBJECT RECOGNITION RESULTS USING A SPATIO-ANATOMICAL ONTOLOGY. In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (IC3K 2010) - KDIR; ISBN 978-989-8425-28-7; ISSN 2184-3228, SciTePress, pages 5-13. DOI: 10.5220/0003058600050013

@conference{kdir10,
author={Manuel Möller. and Patrick Ernst. and Andreas Dengel. and Daniel Sonntag.},
title={AUTOMATIC SPATIAL PLAUSIBILITY CHECKS FOR MEDICAL OBJECT RECOGNITION RESULTS USING A SPATIO-ANATOMICAL ONTOLOGY},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (IC3K 2010) - KDIR},
year={2010},
pages={5-13},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003058600050013},
isbn={978-989-8425-28-7},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (IC3K 2010) - KDIR
TI - AUTOMATIC SPATIAL PLAUSIBILITY CHECKS FOR MEDICAL OBJECT RECOGNITION RESULTS USING A SPATIO-ANATOMICAL ONTOLOGY
SN - 978-989-8425-28-7
IS - 2184-3228
AU - Möller, M.
AU - Ernst, P.
AU - Dengel, A.
AU - Sonntag, D.
PY - 2010
SP - 5
EP - 13
DO - 10.5220/0003058600050013
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