Spatial features terms for describing lung nodule location in chest X-Ray images

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Spatial features have gained attention in CBIR researches as a mean to represent image properties currently. These features provide fine queries to locate object location as well as its relation with others within an image. In fact, spatial features which is portrayed by spatial features terms (SFT) such as left, right, on and in, have been applied in many research domains to denote image attributes. Although the features play an important role in representing image, yet, many researches still rely on visual features for that matter. This condition is also applied in medical image such as Chest X-ray (CXR) image. There is less effort done to identify the actual SFT that should be used to describe the anomalies like lung nodule in CXR image. To overcome this problem, collection of SFTs for describing CXR image must be identified. Hence, this paper presents the effort in identifying the type of SFT that should be used to describe lung nodule in CXR. In order to identify the term, ten radiologists were asked to describe lung nodules in ten CXR images. As a result, five SFTs that are frequently use to describe the image, i.e. left, right, upper, middle and lower were derived from the descriptions. These SFTs are able to visualize the lung region divisions vertically and horizontally within CXR image.

Original languageEnglish
Title of host publicationFrontiers in Artificial Intelligence and Applications
PublisherIOS Press
Pages608-619
Number of pages12
Volume265
ISBN (Print)9781614994336
DOIs
Publication statusPublished - 2014
Event13th International Conference on New Trends in Intelligent Software Methodology Tools, and Techniques, SoMeT 2014 - Langkawi, Malaysia
Duration: 22 Sep 201424 Sep 2014

Publication series

NameFrontiers in Artificial Intelligence and Applications
Volume265
ISSN (Print)09226389

Other

Other13th International Conference on New Trends in Intelligent Software Methodology Tools, and Techniques, SoMeT 2014
CountryMalaysia
CityLangkawi
Period22/9/1424/9/14

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Keywords

  • CBIR
  • Chest X-ray image
  • Spatial features terms

ASJC Scopus subject areas

  • Artificial Intelligence

Cite this

Saad, M. N., Muda, Z., Sahari @ Ashaari, N., & Abdul Hamid, H. (2014). Spatial features terms for describing lung nodule location in chest X-Ray images. In Frontiers in Artificial Intelligence and Applications (Vol. 265, pp. 608-619). (Frontiers in Artificial Intelligence and Applications; Vol. 265). IOS Press. https://doi.org/10.3233/978-1-61499-434-3-608

Spatial features terms for describing lung nodule location in chest X-Ray images. / Saad, Mohd Nizam; Muda, Zurina; Sahari @ Ashaari, Noraidah; Abdul Hamid, Hamzaini.

Frontiers in Artificial Intelligence and Applications. Vol. 265 IOS Press, 2014. p. 608-619 (Frontiers in Artificial Intelligence and Applications; Vol. 265).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Saad, MN, Muda, Z, Sahari @ Ashaari, N & Abdul Hamid, H 2014, Spatial features terms for describing lung nodule location in chest X-Ray images. in Frontiers in Artificial Intelligence and Applications. vol. 265, Frontiers in Artificial Intelligence and Applications, vol. 265, IOS Press, pp. 608-619, 13th International Conference on New Trends in Intelligent Software Methodology Tools, and Techniques, SoMeT 2014, Langkawi, Malaysia, 22/9/14. https://doi.org/10.3233/978-1-61499-434-3-608
Saad MN, Muda Z, Sahari @ Ashaari N, Abdul Hamid H. Spatial features terms for describing lung nodule location in chest X-Ray images. In Frontiers in Artificial Intelligence and Applications. Vol. 265. IOS Press. 2014. p. 608-619. (Frontiers in Artificial Intelligence and Applications). https://doi.org/10.3233/978-1-61499-434-3-608
Saad, Mohd Nizam ; Muda, Zurina ; Sahari @ Ashaari, Noraidah ; Abdul Hamid, Hamzaini. / Spatial features terms for describing lung nodule location in chest X-Ray images. Frontiers in Artificial Intelligence and Applications. Vol. 265 IOS Press, 2014. pp. 608-619 (Frontiers in Artificial Intelligence and Applications).
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