A review of deep learning and Generative Adversarial Networks applications in medical image analysis Article Swipe
D N Sindhura
,
Radhika M. Pai
,
Shyamasunder N Bhat
,
M. M. Manohara Pai
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1007/s00530-024-01349-1
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1007/s00530-024-01349-1
Nowadays, computer-aided decision support systems (CADs) for the analysis of images have been a perennial technique in the medical imaging field. In CADs, deep learning algorithms are widely used to perform tasks like classification, identification of patterns, detection, etc. Deep learning models learn feature representations from images rather than handcrafted features. Hence, deep learning models are quickly becoming the state-of-the-art method to achieve good performances in different computer-aided decision-support systems in medical applications. Similarly, deep learning-based generative models called Generative Adversarial Networks (GANs) have recently been developed as a novel method to produce realistic-looking synthetic data. GANs are used in different domains, including medical imaging generation. The common problems, like class imbalance and a small dataset, in healthcare are well addressed by GANs, and it is a leading area of research. Segmentation, reconstruction, detection, denoising, registration, etc. are the important applications of GANs. So in this work, the successes of deep learning methods in segmentation, classification, cell structure and fracture detection, computer-aided identification, and GANs in synthetic medical image generation, segmentation, reconstruction, detection, denoising, and registration in recent times are reviewed. Lately, the review article concludes by raising research directions for DL models and GANs in medical applications.
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Metadata
- Type
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- Language
- en
- Landing Page
- https://doi.org/10.1007/s00530-024-01349-1
- OA Status
- hybrid
- Cited By
- 12
- References
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- OpenAlex ID
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All OpenAlex metadata
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https://openalex.org/W4399069254Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1007/s00530-024-01349-1Digital Object Identifier
- Title
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A review of deep learning and Generative Adversarial Networks applications in medical image analysisWork title
- Type
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reviewOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-05-28Full publication date if available
- Authors
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D N Sindhura, Radhika M. Pai, Shyamasunder N Bhat, M. M. Manohara PaiList of authors in order
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https://doi.org/10.1007/s00530-024-01349-1Publisher landing page
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YesWhether a free full text is available
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hybridOpen access status per OpenAlex
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https://doi.org/10.1007/s00530-024-01349-1Direct OA link when available
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Adversarial system, Computer science, Generative grammar, Deep learning, Artificial intelligence, Image (mathematics), Generative adversarial network, Machine learning, Computer graphics, Theoretical computer scienceTop concepts (fields/topics) attached by OpenAlex
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12Total citation count in OpenAlex
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2025: 11, 2024: 1Per-year citation counts (last 5 years)
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261Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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