AIMC Topic: Surgical Instruments

Clear Filters Showing 1 to 10 of 105 articles

Enhanced deep learning framework for real-time instrument detection and tracking in laparoscopic surgery using advanced augmentation and tracking techniques.

Surgical endoscopy
BACKGROUND: Accurate tracking and enumeration of surgical instruments are critical for patient safety and operational efficiency in laparoscopic procedures. Advanced tracking systems enhance object detection by maintaining instrument identity despite...

SegMatch: semi-supervised surgical instrument segmentation.

Scientific reports
Surgical instrument segmentation is recognised as a key enabler in providing advanced surgical assistance and improving computer-assisted interventions. In this work, we propose SegMatch, a semi-supervised learning method to reduce the need for expen...

Optimizing intraoperative AI: evaluation of YOLOv8 for real-time recognition of robotic and laparoscopic instruments.

Journal of robotic surgery
The accurate recognition of surgical instruments is essential for the advancement of intraoperative artificial intelligence (AI) systems. In this study, we assessed the YOLOv8 model's efficacy in identifying robotic and laparoscopic instruments in ro...

Multi-axis robotic forceps with decoupled pneumatic actuation and force sensing for cochlear implantation.

Nature communications
Delicate manual microsurgeries rely on sufficient hands-on experience for safe manipulations. Automated surgical devices can enhance the effectiveness, but developing high-resolution, multi-axis force-sensing devices for micro operations remains chal...

SurgiTrack: Fine-grained multi-class multi-tool tracking in surgical videos.

Medical image analysis
Accurate tool tracking is essential for the success of computer-assisted intervention. Previous efforts often modeled tool trajectories rigidly, overlooking the dynamic nature of surgical procedures, especially tracking scenarios like out-of-body and...

Developing an Effective Off-the-job Training Model and an Automated Evaluation System for Thoracoscopic Esophageal Atresia Surgery.

Journal of pediatric surgery
BACKGROUND: Pediatric minimally invasive surgery requires advanced technical skills. Off-the-job training (OJT), especially when using disease-specific models, is an effective method of acquiring surgical skills. To achieve effective OJT, it is neces...

MSDE-Net: A Multi-Scale Dual-Encoding Network for Surgical Instrument Segmentation.

IEEE journal of biomedical and health informatics
Minimally invasive surgery, which relies on surgical robots and microscopes, demands precise image segmentation to ensure safe and efficient procedures. Nevertheless, achieving accurate segmentation of surgical instruments remains challenging due to ...

Reducing annotating load: Active learning with synthetic images in surgical instrument segmentation.

Medical image analysis
Accurate instrument segmentation in the endoscopic vision of minimally invasive surgery is challenging due to complex instruments and environments. Deep learning techniques have shown competitive performance in recent years. However, deep learning us...

Enhancing surgical instrument segmentation: integrating vision transformer insights with adapter.

International journal of computer assisted radiology and surgery
PURPOSE: In surgical image segmentation, a major challenge is the extensive time and resources required to gather large-scale annotated datasets. Given the scarcity of annotated data in this field, our work aims to develop a model that achieves compe...

Surgical phase and instrument recognition: how to identify appropriate dataset splits.

International journal of computer assisted radiology and surgery
PURPOSE: Machine learning approaches can only be reliably evaluated if training, validation, and test data splits are representative and not affected by the absence of classes. Surgical workflow and instrument recognition are two tasks that are compl...