From Pixels to Diagnoses: Deep Learning's Impact on Medical Image Processing-A Survey

Authors

  • Maad M. Mijwil Computer Techniques Engineering Department, Baghdad College of Economic Sciences University, Baghdad, Iraq
  • Abdel-Hameed Al-Mistarehi School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA
  • Mostafa Abotaleb Department of System Programming, South Ural State University, Chelyabinsk, Russia
  • El-Sayed M. El-kenawy Departme of Communications and Electronics, Delta Higher Institute of Engineering and Technology, Mansoura, Egypt
  • Abdelhameed Ibrahim Computer Engineering and Control Systems Department, Faculty of Engineering, Mansoura University, Mansoura Egypt
  • Abdelaziz A. Abdelhamid Department of Computer Science, Faculty of Computer and Information Sciences, Ain Shams University, Cairo, Egypt
  • Marwa M. Eid Faculty of Artificial Intelligence, Delta University for Science and Technology, Mansoura, Egypt

DOI:

https://doi.org/10.31185/wjcms.178

Keywords:

Deep Learning, Medical Images, Artificial Intelligence, Predication, X-rays

Abstract

In healthcare, medical image processing is considered one of the most significant procedures used in diagnosing pathological conditions. Magnetic resonance imaging (MRI), computed tomography (CT), ultrasound, and X-ray visualization have been used. Health institutions are seeking to use artificial intelligence techniques to develop medical image processing and reduce the burden on physicians and healthcare workers. Deep learning has occupied an important place in the healthcare field, supporting specialists in analysing and processing medical images. This article will present a comprehensive survey on the significance of deep learning in the areas of segmentation, classification, disease diagnosis, image generation, image transformation, and image enhancement. This survey seeks to provide an overview of the significance of deep learning in the early detection of diseases, studying tumor localization behaviors, predicting malignant diseases, and determining the suitable treatment for a patient. This article concluded that deep learning is of great significance in improving healthcare, enabling healthcare workers to make diagnoses quickly and more accurately, and improving patient outcomes by providing them with appropriate treatment strategies.

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Published

2023-09-30

Issue

Vol. 2 No. 3 (2023)

Section

Computer

License

Copyright (c) 2023 Maad M. Mijwil, Abdel-Hameed Al-Mistarehi, Mostafa Abotaleb, El-Sayed M. El-kenawy, Abdelhameed Ibrahim, Abdelaziz A. Abdelhamid, Marwa M. Eid

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Maad M. Mijwil, “From Pixels to Diagnoses: Deep Learning’s Impact on Medical Image Processing-A Survey”, WJCMS, vol. 2, no. 3, pp. 9–15, Sep. 2023, doi: 10.31185/wjcms.178.