AIMC Topic: Surgery, Computer-Assisted

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Artificial intelligence and mixed reality for dental implant planning: A technical note.

Clinical implant dentistry and related research
AIM: The aim of this work is to present a new protocol for implant surgical planning which involves the combined use of artificial intelligence (AI) and mixed reality (MR).

A Label-Efficient Framework for Automated Sinonasal CT Segmentation in Image-Guided Surgery.

Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
OBJECTIVE: Segmentation, the partitioning of patient imaging into multiple, labeled segments, has several potential clinical benefits but when performed manually is tedious and resource intensive. Automated deep learning (DL)-based segmentation metho...

Novel AI-based automated virtual implant placement: Artificial versus human intelligence.

Journal of dentistry
OBJECTIVES: To assess quality, clinical acceptance, time-efficiency, and consistency of a novel artificial intelligence (AI)-driven tool for automated presurgical implant planning for single tooth replacement, compared to a human intelligence (HI)-ba...

Cutting-edge care: unleashing artificial intelligence's potential in gynecologic surgery.

Current opinion in obstetrics & gynecology
PURPOSE OF REVIEW: Artificial intelligence (AI) is now integrated in our daily life. It has also been incorporated in medicine with algorithms to diagnose, recommend treatment options, and estimate prognosis.

A real-time augmented reality system integrated with artificial intelligence for skin tumor surgery: experimental study and case series.

International journal of surgery (London, England)
BACKGROUND: Skin tumors affect many people worldwide, and surgery is the first treatment choice. Achieving precise preoperative planning and navigation of intraoperative sampling remains a problem and is excessively reliant on the experience of surge...

Surgical optomics: hyperspectral imaging and deep learning towards precision intraoperative automatic tissue recognition-results from the EX-MACHYNA trial.

Surgical endoscopy
BACKGROUND: Hyperspectral imaging (HSI), combined with machine learning, can help to identify characteristic tissue signatures enabling automatic tissue recognition during surgery. This study aims to develop the first HSI-based automatic abdominal ti...

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...

Improving Needle Tip Tracking and Detection in Ultrasound-Based Navigation System Using Deep Learning-Enabled Approach.

IEEE journal of biomedical and health informatics
Ultrasound-guided percutaneous interventions have numerous advantages over traditional techniques. Accurate needle placement in the target anatomy is crucial for successful intervention, and reliable visual information is essential to achieve this. H...

Parameter-efficient framework for surgical action triplet recognition.

International journal of computer assisted radiology and surgery
PURPOSE: Surgical action triplet recognition is a clinically significant yet challenging task. It provides surgeons with detailed information about surgical scenarios, thereby facilitating clinical decision-making. However, the high similarity among ...

One model to use them all: training a segmentation model with complementary datasets.

International journal of computer assisted radiology and surgery
PURPOSE: Understanding surgical scenes is crucial for computer-assisted surgery systems to provide intelligent assistance functionality. One way of achieving this is via scene segmentation using machine learning (ML). However, such ML models require ...