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Article
Publication date: 23 March 2012

Gergely Orbán and Gábor Horváth

The purpose of this paper is to show an efficient method for the detection of signs of early lung cancer. Various image processing algorithms are presented for different types of…

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Abstract

Purpose

The purpose of this paper is to show an efficient method for the detection of signs of early lung cancer. Various image processing algorithms are presented for different types of lesions, and a scheme is proposed for the combination of results.

Design/methodology/approach

A computer aided detection (CAD) scheme was developed for detection of lung cancer. It enables different lesion enhancer algorithms, sensitive to specific lesion subtypes, to be used simultaneously. Three image processing algorithms are presented for the detection of small nodules, large ones, and infiltrated areas. The outputs are merged, the false detection rate is reduced with four separated support vector machine (SVM) classifiers. The classifier input comes from a feature selection algorithm selecting from various textural and geometric features. A total of 761 images were used for testing, including the database of the Japanese Society of Radiological Technology (JSRT).

Findings

The fusion of algorithms reduced false positives on average by 0.6 per image, while the sensitivity remained 80 per cent. On the JSRT database the system managed to find 60.2 per cent of lesions at an average of 2.0 false positives per image. The effect of using different result evaluation criteria was tested and a difference as high as 4 percentage points in sensitivity was measured. The system was compared to other published methods.

Originality/value

The study described in the paper proves the usefulness of lesion enhancement decomposition, while proposing a scheme for the fusion of algorithms. Furthermore, a new algorithm is introduced for the detection of infiltrated areas, possible signs of lung cancer, neglected by previous solutions.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 5 no. 1
Type: Research Article
ISSN: 1756-378X

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Expert briefing
Publication date: 3 November 2021

The opposition now has a real chance to unseat Prime Minister Viktor Orban in the 2022 elections for the first time since Fidesz’s 2010 landslide. Vast incumbent advantages and a…

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DOI: 10.1108/OXAN-DB265183

ISSN: 2633-304X

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Executive summary
Publication date: 7 June 2021

HUNGARY: Opposition can use Fudan plan against Orban

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Expert briefing
Publication date: 18 October 2019

Local and municipal election results.

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Expert briefing
Publication date: 6 March 2015

Budapest's balancing between traditional and non-traditional ties.

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Executive summary
Publication date: 9 April 2018

HUNGARY: Latest electoral victory will justify Orban

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DOI: 10.1108/OXAN-ES231976

ISSN: 2633-304X

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Expert briefing
Publication date: 19 February 2024

Orban made the announcement during his annual State of the Nation address. For 18 months, Budapest has delayed ratifying Sweden’s NATO membership, over Stockholm's criticism of…

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Publication date: 4 June 2024

A scandal engulfing the ruling right-wing Fidesz party and the subsequent meteoric rise of Peter Magyar as a key opposition player have marked the run-up to the polls, which until…

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DOI: 10.1108/OXAN-DB287450

ISSN: 2633-304X

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Executive summary
Publication date: 20 December 2024

HUNGARY/POLAND: Ties set to deteriorate further

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DOI: 10.1108/OXAN-ES291817

ISSN: 2633-304X

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Expert briefing
Publication date: 23 June 2021

The electoral success of activists, political entrepreneurs, more liberal-minded or pro-EU politicians in capital cities is not a strong signal that attitudes and voting patterns…

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