Latest AI and machine learning research in surgery for healthcare professionals.
The Critical View of Safety (CVS) is crucial for safe laparoscopic cholecystectomy, yet assessing CVS criteria remains a complex and challenging task, even for experts. Traditional models for CVS recognition depend on vision-only models learning with costly, labor-intensive spatial annotations. This study investigates how text can be harnessed as a powerful tool for both training and inference i...
Brain tumor resection is a complex procedure with significant implications for patient survival and quality of life. Predictions of patient outcomes provide clinicians and patients the opportunity to select the most suitable onco-functional balance. In this study, global features derived from structural magnetic resonance imaging in a clinical dataset of 49 pre- and post-surgery patients identif...
Biplanar X-ray imaging is widely used in health screening, postoperative rehabilitation evaluation of orthopedic diseases, and injury surgery due to...
Dexterous robotic hands have been a central focus in robotics research, aiming to replicate the versatility and functionality of the human hand. This ...
Choosing the right fabric is crucial to meet functional and quality requirements in robotic applications for textile manufacturing, apparel producti...
Transcranial magnetic stimulation (TMS) is a non-invasive and safe brain stimulation procedure with growing applications in clinical treatments and ...
Understanding surgical scenes can provide better healthcare quality for patients, especially with the vast amount of video data that is generated du...
Holistic surgical scene segmentation in robot-assisted surgery (RAS) enables surgical residents to identify various anatomical tissues, articulated ...
Brain stroke is one of the leading causes of mortality and long-term disability worldwide, highlighting the need for precise and fast prediction tec...
Gastrointestinal malignancies constitute a leading cause of cancer-related mortality worldwide, with advanced-stage prognosis remaining particularly...
The importance of rapid and accurate histologic analysis of surgical tissue in the operating room has been recognized for over a century. Our standa...
Automated polyp counting in colonoscopy is a crucial step toward automated procedure reporting and quality control, aiming to enhance the cost-effec...
Precise surgical interventions are vital to patient safety, and advanced enhancement algorithms have been developed to assist surgeons in decision-m...
Object-centric slot attention is an emerging paradigm for unsupervised learning of structured, interpretable object-centric representations (slots)....
Ultrasound (US) is a widely used medical imaging modality due to its real-time capabilities, non-invasive nature, and cost-effectiveness. Robotic ul...
Purpose: Neural Radiance Fields (NeRF) offer exceptional capabilities for 3D reconstruction and view synthesis, yet their reliance on extensive mult...
In this study, we developed deep learning-based method to classify the type of surgery performed for epiretinal membrane (ERM) removal, either inter...
Ophthalmic surgical robots offer superior stability and precision by reducing the natural hand tremors of human surgeons, enabling delicate operatio...
Liver landmarks provide crucial anatomical guidance to the surgeon during laparoscopic liver surgery to minimize surgical risk. However, the tubular...
OBJECTIVE: Endoscopic endonasal transsphenoidal surgery (EETS) is a minimally invasive procedure that accesses the sellar and parasellar regions. Vari...