Latest AI and machine learning research in surgery for healthcare professionals.
Object detection shows promise for medical and surgical applications such as cell counting and tool tracking. However, its faces multiple real-world edge deployment challenges including limited high-quality annotated data, data sharing restrictions, and computational constraints. In this work, we introduce UltraFlwr, a framework for federated medical and surgical object detection. By leveraging ...
Computed tomography (CT)-guided needle biopsies are critical for diagnosing a range of conditions, including lung cancer, but present challenges such as limited in-bore space, prolonged procedure times, and radiation exposure. Robotic assistance offers a promising solution by improving needle trajectory accuracy, reducing radiation exposure, and enabling real-time adjustments. In our previous wo...
Person detection methods are used widely in applications including visual surveillance, pedestrian detection, and robotics. However, accurate detect...
Future surgical care demands real-time, integrated data to drive informed decision-making and improve patient outcomes. The pressing need for seamle...
We present PANDORA, a novel diffusion-based policy learning framework designed specifically for dexterous robotic piano performance. Our approach em...
Simulating the complex interactions between soft tissues and rigid anatomy is critical for applications in surgical training, planning, and robotic-...
Drug-resistant focal epilepsy is associated with abnormalities in the brain in both grey matter (GM) and superficial white matter (SWM). However, it...
Performing robotic grasping from a cluttered bin based on human instructions is a challenging task, as it requires understanding both the nuances of...
Surgical domain models improve workflow optimization through automated predictions of each staff member's surgical role. However, mounting evidence ...
Recent advances in deep-learning based methods for image matching have demonstrated their superiority over traditional algorithms, enabling correspo...
BACKGROUND: Artificial intelligence-driven technologies offer transformative potential in plastic surgery, spanning preoperative planning, surgical pr...
Coronary artery disease remains one of the leading causes of mortality globally. Despite advances in revascularization treatments like PCI and CABG,...
The registration between the pre-operative model and the intra-operative surface is crucial in image-guided liver surgery, as it facilitates the eff...
We address key limitations in existing datasets and models for task-oriented hand-object interaction video generation, a critical approach of genera...
Automated surgical workflow analysis is crucial for education, research, and clinical decision-making, but the lack of annotated datasets hinders th...
With the rapid advancement of large language models (LLMs) and vision-language models (VLMs), significant progress has been made in developing open-...
In agricultural automation, inherent occlusion presents a major challenge for robotic harvesting. We propose a novel imitation learning-based viewpo...
We seek to extract a temporally consistent 6D pose trajectory of a manipulated object from an Internet instructional video. This is a challenging se...
Integration of Vision-Language Models (VLMs) in surgical intelligence is hindered by hallucinations, domain knowledge gaps, and limited understandin...
Anticipating and recognizing surgical workflows are critical for intelligent surgical assistance systems. However, existing methods rely on determin...