Latest AI and machine learning research in surgery for healthcare professionals.
Background: We evaluate SAM 2 for surgical scene understanding by examining its semantic segmentation capabilities for organs/tissues both in zero-shot scenarios and after fine-tuning. Methods: We utilized five public datasets to evaluate and fine-tune SAM 2 for segmenting anatomical tissues in surgical videos/images. Fine-tuning was applied to the image encoder and mask decoder. We limited trai...
Occlusion-free video generation is challenging due to surgeons' obstructions in the camera field of view. Prior work has addressed this issue by installing multiple cameras on a surgical light, hoping some cameras will observe the surgical field with less occlusion. However, this special camera setup poses a new imaging challenge since camera configurations can change every time surgeons move th...
Liver-vessel segmentation is an essential task in the pre-operative planning of liver resection. State-of-the-art 2D or 3D convolution-based methods...
The integration of artificial intelligence (AI) into surgery raises significant ethical concerns, including the impact on autonomy, human authority an...
One of the primary goals of Human-Robot Interaction (HRI) research is to develop robots that can interpret human behavior and adapt their responses ...
Automated detection and segmentation of surgical devices, such as catheters or wires, in X-ray fluoroscopic images have the potential to enhance ima...
This study investigates a pulsating fluid jet as a novel precise, minimally invasive and cold technique for bone cement removal. We utilize the puls...
Robotic instruction following tasks require seamless integration of visual perception, task planning, target localization, and motion execution. How...
Operating rooms (ORs) are complex, high-stakes environments requiring precise understanding of interactions among medical staff, tools, and equipmen...
Minimally invasive procedures have been advanced rapidly by the robotic laparoscopic surgery. The latter greatly assists surgeons in sophisticated a...
Objective: we propose a procedure for calibrating 4 parameters governing the mechanical boundary conditions (BCs) of a thoracic aorta (TA) model der...
Video object segmentation is an emerging technology that is well-suited for real-time surgical video segmentation, offering valuable clinical assist...
Purpose: This study proposes a novel anatomically-driven dynamic modeling framework for coronary arteries using skeletal skinning weights computatio...
The complementary information found in different modalities of patient data can aid in more accurate modelling of a patient's disease state and a bett...
BACKGROUND: A real-time deep learning system was developed to identify the extrahepatic bile ducts during indocyanine green fluorescence-guided laparo...
Realistic and interactive surgical simulation has the potential to facilitate crucial applications, such as medical professional training and autono...
Robotic manipulation within dynamic environments presents challenges to precise control and adaptability. Traditional fixed-view camera systems face...
Intelligent surgical robots have the potential to revolutionize clinical practice by enabling more precise and automated surgical procedures. Howeve...
Robotic tactile sensors, including vision-based and taxel-based sensors, enable agile manipulation and safe human-robot interaction through force se...
Real-time acquisition of accurate depth of scene is essential for automated robotic minimally invasive surgery, and stereo matching with binocular e...