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A Review: Image Analysis Techniques to Improve Labeling Accuracy of Medical Image Classification

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Recent Advances on Soft Computing and Data Mining (SCDM 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 700))

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Abstract

Medical images contain the Region of Interest (ROI) from the affected area in human body and provide useful information to support clinical decision-making for diagnostics as well as the treatment planning. Unfortunately, medical image data may contain noise, missing values, inhomogeneous ROI that may give inaccurate diagnostic. Therefore, image analysis techniques are needed to improve the quality of an image. Then, features extraction task will be performed to produce best feature of images which leads to better classification result for accurate diagnostic. Many techniques have been used for image analysis. However, limited review have been done in categorize the list of related techniques for each image analysis task in medical imaging application. Thus, the aims of this paper is to gather and present general overview of image analysis task and their techniques in order to inspire researcher, pathologist or radiologist to adapt it when analyzing different types of medical image. The current study of image analysis task was summarized and discussed in this paper.

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Acknowledgement

This work is supported by UTHM under Short Term Grant Vot U660.

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Authors and Affiliations

  1. Department of Information Technology, Center for Diploma Studies, Universiti Tun Hussein Onn Malaysia, 86400, Parit Raja, Batu Pahat, Johor, Malaysia

    Mazniha Berahim & Shelena Soosay Nathan

  2. Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, 86400, Parit Raja, Batu Pahat, Johor, Malaysia

    Noor Azah Samsudin

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  1. Mazniha Berahim
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  2. Noor Azah Samsudin
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  3. Shelena Soosay Nathan
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Correspondence to Mazniha Berahim .

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Editors and Affiliations

  1. Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, Batu Pahat, Johor, Malaysia

    Rozaida Ghazali

  2. Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, Batu Pahat, Johor, Malaysia

    Mustafa Mat Deris

  3. Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, Batu Pahat, Johor, Malaysia

    Nazri Mohd Nawi

  4. School of Information Technology, Deakin University, Geelong, Victoria, Australia

    Jemal H. Abawajy

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Berahim, M., Samsudin, N.A., Nathan, S.S. (2018). A Review: Image Analysis Techniques to Improve Labeling Accuracy of Medical Image Classification. In: Ghazali, R., Deris, M., Nawi, N., Abawajy, J. (eds) Recent Advances on Soft Computing and Data Mining. SCDM 2018. Advances in Intelligent Systems and Computing, vol 700. Springer, Cham. https://doi.org/10.1007/978-3-319-72550-5_29

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  • DOI: https://doi.org/10.1007/978-3-319-72550-5_29

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