Dual-Attention-Based Enhanced Unified Net for Precise GTV Segmentation of Nasopharyngeal Carcinoma in 3D MR Images
Accurate gross tumor volume (GTV) segmentation is essential for effective radiotherapy in nasopharyngeal carcinoma (NPC). However, challenges arise due to the nasopharyngeal region’s complex anatomy and the annotated data scarcity. Our study presents a dual-attention-based enhanced unifie...
Saved in:
Main Authors: | Hassan Ali Khan, Gong Xueqing, Muhammad Shoib Amin, Zeeshan Bin Siddique, Muhammad Ahtsam Naeem |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2025-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/11037670/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Genetic Characterization of the Immortalized Human Nasopharyngeal Carcinoma Cell Line NPC/HK1
by: Anna Makowska, et al.
Published: (2025-02-01) -
Individualization of clinical target volume delineation in eccentric nasopharyngeal carcinoma: a prospective comparative study
by: Yunrui Song, et al.
Published: (2025-08-01) -
Effects of Hybridizing the U-Net Neural Network in Traffic Lane Detection Process
by: Aron Csato, et al.
Published: (2025-07-01) -
A Gravity Data Denoising Method Based on Multi-Scale Attention Mechanism and Physical Constraints Using U-Net
by: Bing Liu, et al.
Published: (2025-07-01) -
Research on Buckwheat Weed Recognition in Multispectral UAV Images Based on MSU-Net
by: Jinlong Wu, et al.
Published: (2025-07-01)