Improving Medical Image Quality Using a Super-Resolution Technique with Attention Mechanism
Image quality plays a critical role in medical image analysis, significantly impacting diagnostic outcomes. Sharp and detailed images are essential for accurate diagnoses, but acquiring high-resolution medical images often demands sophisticated and costly equipment. To address this challenge, this s...
Saved in:
| Main Authors: | Dong Yun Lee, Jang Yeop Kim, Soo Young Cho |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-01-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/15/2/867 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Dual branch attention network for image super-resolution
by: Yiwei Hu, et al.
Published: (2025-08-01) -
Super-Resolution Reconstruction Method of Face Image Based on Attention Mechanism
by: Chenglin Yu, et al.
Published: (2025-01-01) -
Feature enhanced cascading attention network for lightweight image super-resolution
by: Feng Huang, et al.
Published: (2025-01-01) -
DPHNet: Dual-Path Hybrid Network for Blurry Face Image Super-Resolution
by: Tailai Qiu, et al.
Published: (2025-01-01) -
Image super-resolution reconstruction network combining asymmetric convolution and feature distillation
by: ZHU Lei, et al.
Published: (2024-04-01)