State-of-the-art review on deep learning in medical imaging

Area of Science:

• Computer Science, Artificial Intelligence, Medical Imaging

Background:

• Deep learning (DL) mimics human brain neural activity for pattern recognition.
• Advancements in computing power (GPUs) facilitate complex DL models.
• DL is increasingly integrated into various aspects of daily life.

Purpose of the Study:

• To survey current deep learning systems and their applications.
• To focus specifically on the use of deep learning in medical imaging.
• To explain the technological transition from machine learning to deep learning.

Main Methods:

• Review and analysis of existing deep learning systems.
• Focused examination of deep learning applications in medical imaging.
• Explanation of the paradigm shift from machine learning to deep learning.

Main Results:

• Detailed overview of available deep learning technologies.
• Identification of key applications of deep learning within medical imaging.
• Analysis of the complexities and benefits associated with the machine learning to deep learning transition.

Conclusions:

• Deep learning offers significant potential, particularly in medical imaging analysis.
• Understanding the shift to deep learning is crucial for users and developers.
• The technology promises substantial benefits, driving innovation in the field.