Comparative assessment of texture features for the identification of cancer in ultrasound images: a review

FAUST, Oliver, ACHARYA, U Rajendra, MEIBURGER, Kristen M, MOLINARI, Filippo, KOH, Joel E W, YEONG, Chai Hong, KONGMEBHOL, Palin and NG, Kwan Hoong (2018). Comparative assessment of texture features for the identification of cancer in ultrasound images: a review. Biocybernetics and Biomedical Engineering, 38 (2), 275-296.

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Link to published version:: https://doi.org/10.1016/j.bbe.2018.01.001

Abstract

In this paper, we review the use of texture features for cancer detection in Ultrasound (US) images of breast, prostate, thyroid, ovaries and liver for Computer-Aided Diagnosis (CAD) systems. This paper shows that texture features are a valuable tool to extract diagnostically relevant information from US images. This information helps practitioners to discriminate normal from abnormal tissues. A drawback of some classes of texture features comes from their sensitivity to both changes in image resolution and grayscale levels. These limitations pose a considerable challenge to CAD systems, because the information content of a specific texture feature depends on the US imaging system and its setup. Our review shows that single classes of texture features are insufficient, if considered alone, to create robust CAD systems, which can help to solve practical problems, such as cancer screening. Therefore, we recommend that the CAD system design involves testing a wide range of texture features along with features obtained with other image processing methods. Having such a competitive testing phase helps the designer to select the best feature combination for a particular problem. This approach will lead to practical US based cancer detection systems which de- liver real benefits to patients by improving the diagnosis accuracy while reducing health care cost.

Item Type: Article
Research Institute, Centre or Group: Materials and Engineering Research Institute > Engineering Research
Departments: Faculty of Science, Technology and Arts > Department of Engineering and Mathematics
Identification Number: https://doi.org/10.1016/j.bbe.2018.01.001
Depositing User: Oliver Faust
Date Deposited: 06 Feb 2018 16:16
Last Modified: 16 Nov 2018 13:58
URI: http://shura.shu.ac.uk/id/eprint/18547

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