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[Artificial intelligence in image analysis-fundamentals and new developments].

Marc Pouly1, Thomas Koller2, Philippe Gottfrois3

  • 1Informatik, Hochschule Luzern, Suurstoffi 1, 6343, Rotkreuz, Schweiz. marc.pouly@hslu.ch.

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|August 14, 2020
PubMed
Summary

Artificial intelligence (AI) in medical imaging, particularly deep learning, now matches human expert performance. This technology is rapidly advancing, becoming a crucial tool in clinical practice and dermatology.

Keywords:
Computer-assisted image analysisDeep learningDiagnostic imagingImage analysis applicationsVisual features

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Area of Science:

  • Medical image analysis
  • Artificial intelligence in healthcare
  • Computer vision applications

Background:

  • Artificial intelligence (AI) has demonstrated expert-level performance in medical image analysis since 2017.
  • The first medical device approval for a computer vision algorithm in 2018 marked a significant step towards clinical integration.

Purpose of the Study:

  • To review recent advancements in AI for image analysis.
  • Focus on clinical applications, particularly in dermatology.
  • Compare classical machine learning with deep learning approaches.

Main Methods:

  • Review of classical machine learning methods and their limitations (performance, scalability).
  • Exploration of deep learning, including artificial neural networks.
  • Discussion of key deep learning concepts: transfer learning, explainable AI, and generative models.

Main Results:

  • Deep learning models achieve human-expert-level performance across various diagnostic tasks.
  • Models are suitable for industrialization, shifting focus to interpretability and clinical applicability.
  • Generative models open new avenues for AI applications in medical imaging.

Conclusions:

  • Deep learning is the new standard for image analysis, surpassing classical methods.
  • AI offers significant improvements for numerous clinical fields, including dermatology.
  • While challenges remain, AI is becoming an indispensable tool in modern medicine.