Subject Review: Diagnoses cancer diseases systems for most body's sections using image processing techniques

Dena Nadir George; Haitham Salman Chyad; Raniah Ali Mustafa

doi:10.30574/gjeta.2021.6.3.0031

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Subject Review: Diagnoses cancer diseases systems for most body's sections using image processing techniques

Dena Nadir George, Haitham Salman Chyad and Raniah Ali Mustafa ^*

Mustansiriyah University, College of Education, Department of Computer Science, Baghdad, Iraq.

Research Article

Global Journal of Engineering and Technology Advances, 2021, 06(03), 056-062.

Article DOI: 10.30574/gjeta.2021.6.3.0031

DOI url: https://doi.org/10.30574/gjeta.2021.6.3.0031

Publication history

Received on 22 January 2021; revised on 26 February 2021; accepted on 01 March 2021

Abstract

Medical imaging has become an important part of diagnosing, early detection, and treating cancers. In this paper, a comprehensive survey on various image processing techniques for medical images specifically examined cancer diseases for most body sections. These sections are Bone, Liver, Kidney, Breast, Lung, and Brain. Detection of medical imaging involves different stages such as classification, segmentation, image pre-processing, and feature extraction. With regard to this work, many image processing methods will be studied, over 10 surveys reviewing classification, feature extraction, and segmentation methods utilized image processing for cancer diseases for most body's sections are clearly reviewed.

Keywords

Feed-Forward Back Propagation NN; A gray-level co-occurrence matrix (GLCM); Dense Scale Invariant Feature Transform (DSIFT); Deep convolutional neural network (DCNN).

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How to cite this article

Dena Nadir George, Haitham Salman Chyad and Raniah Ali Mustafa. Subject Review: Diagnoses cancer diseases systems for most body's sections using image processing techniques. Global Journal of Engineering and Technology Advances, 2021, 6(3), 056-062. Article DOI: https://doi.org/10.30574/gjeta.2021.6.3.0031

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