Continual learning in medical imaging analysis: A comprehensive review of recent advancements and future prospects
Medical imaging analysis has witnessed remarkable advancements even surpassing
human-level performance in recent years, driven by the rapid development of advanced …
human-level performance in recent years, driven by the rapid development of advanced …
Rethinking exemplars for continual semantic segmentation in endoscopy scenes: Entropy-based mini-batch pseudo-replay
Endoscopy is a widely used technique for the early detection of diseases or robotic-assisted
minimally invasive surgery (RMIS). Numerous deep learning (DL)-based research works …
minimally invasive surgery (RMIS). Numerous deep learning (DL)-based research works …
Surgical-VQLA++: Adversarial contrastive learning for calibrated robust visual question-localized answering in robotic surgery
Medical visual question answering (VQA) bridges the gap between visual information and
clinical decision-making, enabling doctors to extract understanding from clinical images and …
clinical decision-making, enabling doctors to extract understanding from clinical images and …
Continual learning in medical image analysis: A survey
In the dynamic realm of practical clinical scenarios, Continual Learning (CL) has gained
increasing interest in medical image analysis due to its potential to address major …
increasing interest in medical image analysis due to its potential to address major …
LLM-assisted multi-teacher continual learning for visual question answering in robotic surgery
Visual question answering (VQA) can be fundamentally crucial for promoting robotic-
assisted surgical education. In practice, the needs of trainees are constantly evolving, such …
assisted surgical education. In practice, the needs of trainees are constantly evolving, such …
OSSAR: Towards Open-Set Surgical Activity Recognition in Robot-assisted Surgery
In the realm of automated robotic surgery and computer-assisted interventions,
understanding robotic surgical activities stands paramount. Existing algorithms dedicated to …
understanding robotic surgical activities stands paramount. Existing algorithms dedicated to …
A survey of medical vision-and-language applications and their techniques
Medical vision-and-language models (MVLMs) have attracted substantial interest due to
their capability to offer a natural language interface for interpreting complex medical data …
their capability to offer a natural language interface for interpreting complex medical data …
Joint Sparse Representations and Coupled Dictionary Learning in Multi-Source Heterogeneous Image Pseudo-color Fusion
Considering that coupled dictionary learning (CDL) method can obtain a reasonable linear
mathematical relationship between resource images, we propose a novel CDL-based …
mathematical relationship between resource images, we propose a novel CDL-based …
Endoood: Uncertainty-aware out-of-distribution detection in capsule endoscopy diagnosis
Wireless capsule endoscopy (WCE) is a non-invasive diagnostic procedure that enables
visualization of the gastrointestinal (GI) tract. Deep learning-based methods have shown …
visualization of the gastrointestinal (GI) tract. Deep learning-based methods have shown …
ORacle: Large Vision-Language Models for Knowledge-Guided Holistic OR Domain Modeling
Every day, countless surgeries are performed worldwide, each within the distinct settings of
operating rooms (ORs) that vary not only in their setups but also in the personnel, tools, and …
operating rooms (ORs) that vary not only in their setups but also in the personnel, tools, and …