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Review

Deep Learning in Selected Cancers’ Image Analysis—A Survey

1
Artificial Intelligence Center, 40782 Addis Ababa, Ethiopia
2
College of Electrical and Mechanical Engineering, Addis Ababa Science and Technology University, 120611 Addis Ababa, Ethiopia
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Department of Electrical and Computer Engineering, Debreberhan University, 445 Debre Berhan, Ethiopia
4
Institute of Neural Information Processing, University of Ulm, 89081 Ulm, Germany
*
Author to whom correspondence should be addressed.
Received: 21 July 2020 / Revised: 19 October 2020 / Accepted: 26 October 2020 / Published: 10 November 2020
(This article belongs to the Special Issue Deep Learning in Medical Image Analysis)
Deep learning algorithms have become the first choice as an approach to medical image analysis, face recognition, and emotion recognition. In this survey, several deep-learning-based approaches applied to breast cancer, cervical cancer, brain tumor, colon and lung cancers are studied and reviewed. Deep learning has been applied in almost all of the imaging modalities used for cervical and breast cancers and MRIs for the brain tumor. The result of the review process indicated that deep learning methods have achieved state-of-the-art in tumor detection, segmentation, feature extraction and classification. As presented in this paper, the deep learning approaches were used in three different modes that include training from scratch, transfer learning through freezing some layers of the deep learning network and modifying the architecture to reduce the number of parameters existing in the network. Moreover, the application of deep learning to imaging devices for the detection of various cancer cases has been studied by researchers affiliated to academic and medical institutes in economically developed countries; while, the study has not had much attention in Africa despite the dramatic soar of cancer risks in the continent. View Full-Text
Keywords: deep learning; medical image analysis; breast cancer; brain tumor; cervical cancer; colon cancer; lung cancer deep learning; medical image analysis; breast cancer; brain tumor; cervical cancer; colon cancer; lung cancer
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MDPI and ACS Style

Debelee, T.G.; Kebede, S.R.; Schwenker, F.; Shewarega, Z.M. Deep Learning in Selected Cancers’ Image Analysis—A Survey. J. Imaging 2020, 6, 121. https://0-doi-org.brum.beds.ac.uk/10.3390/jimaging6110121

AMA Style

Debelee TG, Kebede SR, Schwenker F, Shewarega ZM. Deep Learning in Selected Cancers’ Image Analysis—A Survey. Journal of Imaging. 2020; 6(11):121. https://0-doi-org.brum.beds.ac.uk/10.3390/jimaging6110121

Chicago/Turabian Style

Debelee, Taye G.; Kebede, Samuel R.; Schwenker, Friedhelm; Shewarega, Zemene M. 2020. "Deep Learning in Selected Cancers’ Image Analysis—A Survey" J. Imaging 6, no. 11: 121. https://0-doi-org.brum.beds.ac.uk/10.3390/jimaging6110121

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