Medical Image Segmentation Techniques
Medical Image Segmentation Techniques is a research topic within Computer Vision and Pattern Recognition. Science Explorer counts 43k research works in it since 1950. 9.9% of them reached the world's top 10% most cited for their field and year.
This cluster of papers covers advances in image segmentation techniques, particularly focusing on medical image analysis, graph cuts, active contours, MRI segmentation, deformable image registration, level set methods, statistical shape models, deep learning, and texture analysis.
- Image Segmentation
- Medical Image Analysis
- Graph Cuts
- Active Contours
- MRI Segmentation
- Deformable Image Registration
- Level Set Methods
- Statistical Shape Models
- Deep Learning
- Texture Analysis
- Research works
- 43k fractional, since 1950
- In the world top 10%
- 4.3k per year above
- Top-10% rate
- 9.9% share of its works in the world top 10%
- Growth, 2018-21 → 2022-25
- +35% the tick is no change
- Largest producer
China
52% of the 10 largest, 2022-now
Discussion
Ask a question or share a note about Medical Image Segmentation Techniques. Keep it to the research: no personal attacks, advertising or links. Any reader can report a post, which collapses it for everyone until it is opened.