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Digital imaging applications and informatics in dermatology.
Felipe Giuste1,2, Juan Carlos Vizcarra1,2, David A Gutman3,4
1Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, Georgia.
Seminars in Cutaneous Medicine and Surgery
|May 4, 2019
Summary
Whole slide imaging (WSI) and dermoscopy are revolutionizing dermatology with digital image analysis. Machine learning algorithms are increasingly used with large dermatology image datasets for computer-assisted clinical decisions.
Area of Science:
- Dermatology
- Medical Imaging
- Computer Science
Background:
- Digital imaging is transforming dermatology, enabling computer-assisted clinical decision-making.
- Whole slide imaging (WSI) and dermoscopy are key digital data sources in dermatology.
- Advancements in image digitization facilitate enhanced diagnostic capabilities.
Purpose of the Study:
- To present the application of whole slide imaging (WSI) and dermoscopy in dermatology.
- To introduce common digital imaging data sources and quantification methods.
- To review the utilization of machine learning in dermatology image analysis.
Main Methods:
- Review of whole slide imaging (WSI) and dermoscopy techniques.
- Introduction to image quantification methods in dermatology.
- Exploration of machine learning approaches for large dermatology image datasets.
Main Results:
- Digitization of dermatological images enhances computer-assisted decision-making.
- Various image quantification methods offer potential applications in dermatology.
- Machine learning leverages large datasets for novel dermatological insights.
Conclusions:
- Whole slide imaging (WSI) and dermoscopy are integral to modern digital dermatology.
- Image quantification and machine learning are powerful tools for dermatological research and practice.
- The integration of these technologies promises to advance clinical decision-making and patient care.
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