NCTU-DBLAB at Imageclefmed 2005: Medical image retrieval task

Pei Cheng Cheng; Been Chian Chien; Hao Ren Ke; Wei Pang Yang

NCTU-DBLAB at Imageclefmed 2005: Medical image retrieval task

Pei Cheng Cheng^*, Been Chian Chien, Hao Ren Ke, Wei Pang Yang

^*Corresponding author for this work

Research output: Contribution to journal › Conference article › peer-review

2 Citations (Scopus)

Abstract

In this article, we describe the used technologies and experimental results for the medical retrieval task at ImageCLEF 2005. The topics of competition this year contain both semantic queries and visual queries. The content-based approach containing four image features and the text-based approach using word expansion are developed to accomplish the mission. The experimental results show that the text-based approach has higher precision rate than content-based approach. Further, the results of combining both the content-based and text-based approaches are better than those using only one of the approaches. We summarize that the consideration on the image of visual queries can provide more human semantic perception and improve the efficiency for medical image retrieval.

Original language	English
Journal	CEUR Workshop Proceedings
Volume	1171
Publication status	Published - 2005
Externally published	Yes
Event	2005 Cross Language Evaluation Forum Workshop, CLEF 2005, co-located with the 9th European Conference on Digital Libraries, ECDL 2005 - Wien, Austria Duration: 2005 Sept 21 → 2005 Sept 22

Keywords

Content based image retrieval
Medical Image retrieval

ASJC Scopus subject areas

General Computer Science

Cite this

@article{86a4ff46b7d54c3aaa605465d1345152,

title = "NCTU-DBLAB at Imageclefmed 2005: Medical image retrieval task",

abstract = "In this article, we describe the used technologies and experimental results for the medical retrieval task at ImageCLEF 2005. The topics of competition this year contain both semantic queries and visual queries. The content-based approach containing four image features and the text-based approach using word expansion are developed to accomplish the mission. The experimental results show that the text-based approach has higher precision rate than content-based approach. Further, the results of combining both the content-based and text-based approaches are better than those using only one of the approaches. We summarize that the consideration on the image of visual queries can provide more human semantic perception and improve the efficiency for medical image retrieval.",

keywords = "Content based image retrieval, Medical Image retrieval",

author = "Cheng, {Pei Cheng} and Chien, {Been Chian} and Ke, {Hao Ren} and Yang, {Wei Pang}",

year = "2005",

language = "English",

volume = "1171",

journal = "CEUR Workshop Proceedings",

issn = "1613-0073",

publisher = "CEUR-WS",

note = "2005 Cross Language Evaluation Forum Workshop, CLEF 2005, co-located with the 9th European Conference on Digital Libraries, ECDL 2005 ; Conference date: 21-09-2005 Through 22-09-2005",

}

TY - JOUR

T1 - NCTU-DBLAB at Imageclefmed 2005

T2 - 2005 Cross Language Evaluation Forum Workshop, CLEF 2005, co-located with the 9th European Conference on Digital Libraries, ECDL 2005

AU - Cheng, Pei Cheng

AU - Chien, Been Chian

AU - Ke, Hao Ren

AU - Yang, Wei Pang

PY - 2005

Y1 - 2005

N2 - In this article, we describe the used technologies and experimental results for the medical retrieval task at ImageCLEF 2005. The topics of competition this year contain both semantic queries and visual queries. The content-based approach containing four image features and the text-based approach using word expansion are developed to accomplish the mission. The experimental results show that the text-based approach has higher precision rate than content-based approach. Further, the results of combining both the content-based and text-based approaches are better than those using only one of the approaches. We summarize that the consideration on the image of visual queries can provide more human semantic perception and improve the efficiency for medical image retrieval.

AB - In this article, we describe the used technologies and experimental results for the medical retrieval task at ImageCLEF 2005. The topics of competition this year contain both semantic queries and visual queries. The content-based approach containing four image features and the text-based approach using word expansion are developed to accomplish the mission. The experimental results show that the text-based approach has higher precision rate than content-based approach. Further, the results of combining both the content-based and text-based approaches are better than those using only one of the approaches. We summarize that the consideration on the image of visual queries can provide more human semantic perception and improve the efficiency for medical image retrieval.

KW - Content based image retrieval

KW - Medical Image retrieval

UR - http://www.scopus.com/inward/record.url?scp=84922051890&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84922051890&partnerID=8YFLogxK

M3 - Conference article

AN - SCOPUS:84922051890

SN - 1613-0073

VL - 1171

JO - CEUR Workshop Proceedings

JF - CEUR Workshop Proceedings

Y2 - 21 September 2005 through 22 September 2005

ER -

NCTU-DBLAB at Imageclefmed 2005: Medical image retrieval task

Abstract

Keywords

ASJC Scopus subject areas

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