A Systematic Review of Generalization Research in Medical Image Classification
S Matta, M Lamard, P Zhang, AL Guilcher… - arxiv preprint arxiv …, 2024 - arxiv.org
Numerous Deep Learning (DL) classification models have been developed for a large
spectrum of medical image analysis applications, which promises to reshape various facets …
spectrum of medical image analysis applications, which promises to reshape various facets …
[HTML][HTML] A systematic review of generalization research in medical image classification
S Matta, M Lamard, P Zhang, A Le Guilcher… - Computers in biology …, 2024 - Elsevier
Abstract Numerous Deep Learning (DL) classification models have been developed for a
large spectrum of medical image analysis applications, which promises to reshape various …
large spectrum of medical image analysis applications, which promises to reshape various …
Advancing uwf-slo vessel segmentation with source-free active domain adaptation and a novel multi-center dataset
H Wang, X Luo, W Chen, Q Tang, M **n… - … Conference on Medical …, 2024 - Springer
Accurate vessel segmentation in Ultra-Wide-Field Scanning Laser Ophthalmoscopy (UWF-
SLO) images is crucial for diagnosing retinal diseases. Although recent techniques have …
SLO) images is crucial for diagnosing retinal diseases. Although recent techniques have …
Unified bi-encoder bispace-discriminator disentanglement for cross-domain echocardiography segmentation
Disentanglement-based methods effectively facilitate domain-invariant feature learning in
Unsupervised Domain Adaptation (UDA) by leveraging complementary domain-specific …
Unsupervised Domain Adaptation (UDA) by leveraging complementary domain-specific …
Data efficient deep learning for medical image analysis: A survey
The rapid evolution of deep learning has significantly advanced the field of medical image
analysis. However, despite these achievements, the further enhancement of deep learning …
analysis. However, despite these achievements, the further enhancement of deep learning …
AI in radiology: From promise to practice− A guide to effective integration
Abstract While Artificial Intelligence (AI) has the potential to transform the field of diagnostic
radiology, important obstacles still inhibit its integration into clinical environments. Foremost …
radiology, important obstacles still inhibit its integration into clinical environments. Foremost …
CLMS: Bridging domain gaps in medical imaging segmentation with source-free continual learning for robust knowledge transfer and adaptation
W Li, Y Zhang, H Zhou, W Yang, Z **e, Y He - Medical Image Analysis, 2025 - Elsevier
Deep learning shows promise for medical image segmentation but suffers performance
declines when applied to diverse healthcare sites due to data discrepancies among the …
declines when applied to diverse healthcare sites due to data discrepancies among the …
Pseudo-label guided dual classifier domain adversarial network for unsupervised cross-domain fault diagnosis with small samples
Y Sun, H Tao, V Stojanovic - Advanced Engineering Informatics, 2025 - Elsevier
Deep learning has been extensively employed in fault diagnosis applications due to its
capacity to autonomously extract features from voluminous datasets. In practical engineering …
capacity to autonomously extract features from voluminous datasets. In practical engineering …
An In-Depth Analysis of Domain Adaptation in Computer and Robotic Vision
This review article comprehensively delves into the rapidly evolving field of domain
adaptation in computer and robotic vision. It offers a detailed technical analysis of the …
adaptation in computer and robotic vision. It offers a detailed technical analysis of the …
Unsupervised domain adaptation based on feature and edge alignment for femur X-ray image segmentation
The gold standard for diagnosing osteoporosis is bone mineral density (BMD) measurement
by dual-energy X-ray absorptiometry (DXA). However, various factors during the imaging …
by dual-energy X-ray absorptiometry (DXA). However, various factors during the imaging …