A Query-by-Example Content-Based Image Retrieval System of Non-melanoma Skin Lesions

Lucia Ballerini; Xiang Li; Robert B. Fisher; Jonathan Rees

doi:10.1007/978-3-642-11769-5_3

A Query-by-Example Content-Based Image Retrieval System of Non-melanoma Skin Lesions

Lucia Ballerini, Xiang Li, Robert B. Fisher, Jonathan Rees

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract / Description of output

This paper proposes a content-based image retrieval system for skin lesion images as a diagnostic aid. The aim is to support decision making by retrieving and displaying relevant past cases visually similar to the one under examination. Skin lesions of five common classes, including two non-melanoma cancer types are used. Colour and texture features are extracted from lesions. Feature selection is achieved by optimising a similarity matching function. Experiments on our database of 208 images are performed and results evaluated.

Original language	English
Title of host publication	MEDICAL CONTENT-BASED RETRIEVAL FOR CLINICAL DECISION SUPPORT
Editors	B Caputo, H Muller, T SyedaMahmood, JS Duncan, F Wang, J KalpathyCramer
Place of Publication	BERLIN
Publisher	Springer
Pages	31-38
Number of pages	8
ISBN (Print)	978-3-642-11768-8
DOIs	https://doi.org/10.1007/978-3-642-11769-5_3
Publication status	Published - 2010
Event	1st MICCAI International Workshop on Medical Content-Based Retrieval for Clinical Decision Support - London Duration: 20 Sept 2009 → …

Conference

Conference	1st MICCAI International Workshop on Medical Content-Based Retrieval for Clinical Decision Support
City	London
Period	20/09/09 → …

Access to Document

10.1007/978-3-642-11769-5_3

Ballerini et al MCBR09
The final publication is available at link.springer.com
Submitted manuscript, 1.19 MB

http://link.springer.com/chapter/10.1007%2F978-3-642-11769-5_3

Cite this

@inproceedings{c8aa3808833c4401a0f9bc09429b14c8,

title = "A Query-by-Example Content-Based Image Retrieval System of Non-melanoma Skin Lesions",

abstract = "This paper proposes a content-based image retrieval system for skin lesion images as a diagnostic aid. The aim is to support decision making by retrieving and displaying relevant past cases visually similar to the one under examination. Skin lesions of five common classes, including two non-melanoma cancer types are used. Colour and texture features are extracted from lesions. Feature selection is achieved by optimising a similarity matching function. Experiments on our database of 208 images are performed and results evaluated.",

author = "Lucia Ballerini and Xiang Li and Fisher, {Robert B.} and Jonathan Rees",

year = "2010",

doi = "10.1007/978-3-642-11769-5_3",

language = "English",

isbn = "978-3-642-11768-8",

pages = "31--38",

editor = "B Caputo and H Muller and T SyedaMahmood and JS Duncan and F Wang and J KalpathyCramer",

booktitle = "MEDICAL CONTENT-BASED RETRIEVAL FOR CLINICAL DECISION SUPPORT",

publisher = "Springer",

address = "United Kingdom",

note = "1st MICCAI International Workshop on Medical Content-Based Retrieval for Clinical Decision Support ; Conference date: 20-09-2009",

}

Ballerini, L, Li, X, Fisher, RB & Rees, J 2010, A Query-by-Example Content-Based Image Retrieval System of Non-melanoma Skin Lesions. in B Caputo, H Muller, T SyedaMahmood, JS Duncan, F Wang & J KalpathyCramer (eds), MEDICAL CONTENT-BASED RETRIEVAL FOR CLINICAL DECISION SUPPORT. Springer, BERLIN, pp. 31-38, 1st MICCAI International Workshop on Medical Content-Based Retrieval for Clinical Decision Support, London, 20/09/09. https://doi.org/10.1007/978-3-642-11769-5_3

A Query-by-Example Content-Based Image Retrieval System of Non-melanoma Skin Lesions. / Ballerini, Lucia; Li, Xiang; Fisher, Robert B. et al.
MEDICAL CONTENT-BASED RETRIEVAL FOR CLINICAL DECISION SUPPORT. ed. / B Caputo; H Muller; T SyedaMahmood; JS Duncan; F Wang; J KalpathyCramer. BERLIN: Springer, 2010. p. 31-38.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - A Query-by-Example Content-Based Image Retrieval System of Non-melanoma Skin Lesions

AU - Ballerini, Lucia

AU - Li, Xiang

AU - Fisher, Robert B.

AU - Rees, Jonathan

PY - 2010

Y1 - 2010

N2 - This paper proposes a content-based image retrieval system for skin lesion images as a diagnostic aid. The aim is to support decision making by retrieving and displaying relevant past cases visually similar to the one under examination. Skin lesions of five common classes, including two non-melanoma cancer types are used. Colour and texture features are extracted from lesions. Feature selection is achieved by optimising a similarity matching function. Experiments on our database of 208 images are performed and results evaluated.

AB - This paper proposes a content-based image retrieval system for skin lesion images as a diagnostic aid. The aim is to support decision making by retrieving and displaying relevant past cases visually similar to the one under examination. Skin lesions of five common classes, including two non-melanoma cancer types are used. Colour and texture features are extracted from lesions. Feature selection is achieved by optimising a similarity matching function. Experiments on our database of 208 images are performed and results evaluated.

U2 - 10.1007/978-3-642-11769-5_3

DO - 10.1007/978-3-642-11769-5_3

M3 - Conference contribution

SN - 978-3-642-11768-8

SP - 31

EP - 38

BT - MEDICAL CONTENT-BASED RETRIEVAL FOR CLINICAL DECISION SUPPORT

A2 - Caputo, B

A2 - Muller, H

A2 - SyedaMahmood, T

A2 - Duncan, JS

A2 - Wang, F

A2 - KalpathyCramer, J

PB - Springer

CY - BERLIN

T2 - 1st MICCAI International Workshop on Medical Content-Based Retrieval for Clinical Decision Support

Y2 - 20 September 2009

ER -

A Query-by-Example Content-Based Image Retrieval System of Non-melanoma Skin Lesions

Abstract / Description of output

Conference

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