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Review
. 2020 Jul 26;10(8):518.
doi: 10.3390/diagnostics10080518.

A Comparative Systematic Literature Review on Knee Bone Reports from MRI, X-rays and CT Scans Using Deep Learning and Machine Learning Methodologies

Hafsa Khalid  1 , Muzammil Hussain  1 , Mohammed A Al Ghamdi  2 , Tayyaba Khalid  3 , Khadija Khalid  4 , Muhammad Adnan Khan  5 , Kalsoom Fatima  1 , Khalid Masood  5 , Sultan H Almotiri  2 , Muhammad Shoaib Farooq  1 , Aqsa Ahmed  6
Affiliations
Review

A Comparative Systematic Literature Review on Knee Bone Reports from MRI, X-rays and CT Scans Using Deep Learning and Machine Learning Methodologies

Hafsa Khalid et al. Diagnostics (Basel). .

Abstract

The purpose of this research was to provide a "systematic literature review" of knee bone reports that are obtained by MRI, CT scans, and X-rays by using deep learning and machine learning techniques by comparing different approaches-to perform a comprehensive study on the deep learning and machine learning methodologies to diagnose knee bone diseases by detecting symptoms from X-ray, CT scan, and MRI images. This study will help those researchers who want to conduct research in the knee bone field. A comparative systematic literature review was conducted for the accomplishment of our work. A total of 32 papers were reviewed in this research. Six papers consist of X-rays of knee bone with deep learning methodologies, five papers cover the MRI of knee bone using deep learning approaches, and another five papers cover CT scans of knee bone with deep learning techniques. Another 16 papers cover the machine learning techniques for evaluating CT scans, X-rays, and MRIs of knee bone. This research compares the deep learning methodologies for CT scan, MRI, and X-ray reports on knee bone, comparing the accuracy of each technique, which can be used for future development. In the future, this research will be enhanced by comparing X-ray, CT-scan, and MRI reports of knee bone with information retrieval and big data techniques. The results show that deep learning techniques are best for X-ray, MRI, and CT scan images of the knee bone to diagnose diseases.

Keywords: computed tomography (CT scan); electromagnetic radiation (X-ray); magnetic resonance imaging (MRI); trabecular bone (TB).

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Structure of human knee.
Figure 2
Figure 2
The systematic literature review process.
Figure 3
Figure 3
Hierarchy of number of Studies for SLR.
Figure 4
Figure 4
Publication by years of Deep Learning papers.
Figure 5
Figure 5
Published years of selected ML papers.
See this image and copyright information in PMC

References

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