Hybrid transformer and convolution iteratively optimized pyramid network for brain large deformation image registration
Abstract In recent years, the pyramid-based encoder-decoder network architecture has become a popular solution to the problem of large deformation image registration due to its excellent multi-scale deformation field prediction ability. However, there are two main limitations in existing research: o...
Saved in:
| Main Authors: | Xinxin Cui, Yuee Zhou, Caihong Wei, Guodong Suo, Fengqing Jin, Jianlan Yang |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-05-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-00403-w |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
RETRACTED ARTICLE: Attention Pyramid Convolutional Neural Network Optimized with Big Data for Teaching Aerobics
by: Chunmei Chen
Published: (2024-06-01) -
Kronecker convolutional feature pyramid for fault diagnosis in rolling bearings
by: Sadia Batool, et al.
Published: (2025-07-01) -
An UNet3+ Network based on global pyramid aggregation for change detection in optical remote-sensing imagesGosNIIASLEarning, VIsion and Remote sensing laboratory
by: Yanbo Sun, et al.
Published: (2024-12-01) -
Laplacian Pyramid Network With Hybrid Encoder and Edge Guidance for Remote Sensing Change Detection
by: Wenkai Yan, et al.
Published: (2025-01-01) -
A semi-supervised deep neuro-fuzzy iterative learning system for automatic segmentation of hippocampus brain MRI
by: M Nisha, et al.
Published: (2024-12-01)