Parallel Hierarchical Multi-View Feature Fusion Based on Canonical Correlation Analysis for Mammogram Retrieval
Due to the diversity of image sources, content-based multi-source image fusion and retrieval have shown promising capabilities in computer vision tasks, and especially when applied in Computer-Aided Diagnosis (CAD) to automate and improve the accuracy of medical image analysis. The combination of co...
Saved in:
Main Authors: | Marwa Abderrahim, Abir Baâzaoui, Walid Barhoumi |
---|---|
Format: | Article |
Language: | English |
Published: |
World Scientific Publishing
2024-11-01
|
Series: | Vietnam Journal of Computer Science |
Subjects: | |
Online Access: | https://www.worldscientific.com/doi/10.1142/S219688882450012X |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A survey on canonical correlation analysis based multi-view learning
by: Chenfeng GUO, et al.
Published: (2022-03-01) -
Leveraging paired mammogram views with deep learning for comprehensive breast cancer detection
by: Jae Won Seo, et al.
Published: (2025-02-01) -
Diagnostic value of digital breast tomosynthesis in suspicious lesions detected in screening mammogram
by: Waleed Abd El-Fattah Mousa, et al.
Published: (2024-12-01) -
Integrating Historical Learning and Multi-View Attention with Hierarchical Feature Fusion for Robotic Manipulation
by: Gaoxiong Lu, et al.
Published: (2024-11-01) -
Transfer learning for deep neural networks-based classification of breast cancer X-ray images
by: Tuan Linh Le, et al.
Published: (2024-12-01)