Deep learning

Combinatorics

Physics

Image segmentation

Pathology

Pattern recognition (psychology)

Segmentation-based object categorization

Mathematics

Pipeline (software)

Scale-space segmentation

Homogeneous

Image (mathematics)

Machine learning

Critical appraisal

Artificial intelligence

Component (thermodynamics)

Programming language

Alternative medicine

Computer science

Computer vision

Medicine

Segmentation

Thermodynamics

Journal of Digital Imaging

Deep learning-based image segmentation is by now firmly established as a robust tool in image segmentation. It has been widely used to separate homogeneous areas as the first and critical component of diagnosis and treatment pipeline. In this article, we present a critical appraisal of popular methods that have employed deep-learning techniques for medical image segmentation. Moreover, we summarize the most common challenges incurred and suggest possible solutions.

Deep Learning Techniques for Medical Image Segmentation: Achievements and Challenges