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

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
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 compet-itive 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 deliver real benefits to patients by improving the diagnosis accuracy while reducing health care cost.
Twórcy
autor
  • Department of Engineering and Mathematics, Sheffield Hallam University, United Kingdom
  • Department of Electronic & Computer Engineering, Ngee Ann Polytechnic, Singapore; Department of Biomedical Engineering, School of Science and Technology, Singapore University of Social Sciences, Singapore; Department of Biomedical Imaging, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
  • Department of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy
autor
  • Department of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy
autor
  • Department of Electronic & Computer Engineering, Ngee Ann Polytechnic, Singapore
autor
  • Department of Biomedical Imaging, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
  • Faculty of Medicine, Department of Radiology, Chiang Mai University, Thailand
autor
  • Department of Biomedical Imaging, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
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Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).
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